**Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study**

Syed Mudassar, Mosin S Khan, Nighat P. Khan, Mahboob ul- Hussain and Khurshid I. Andrabi

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57380

## **1. Introduction**

Cancer is not just one disease, but a generic term used to encompass a group of more than two hundred diseases sharing common characteristics. From a clinical point of view, cancer is a large group of diseases, that vary in their age of onset, rate of growth, state of cellular differ‐ entiation, diagnostic detectability, invasiveness, metastatic potential, response to treatment, and prognosis. From a molecular and cell biological point of view, however, cancer may be a relatively small number of diseases caused by similar molecular defects in cell function resulting from common types of alterations to a cell's genes. Ultimately, cancer is a disease of abnormal gene expression. There are a number of mechanisms by which this altered gene expression occurs. These mechanisms may occur via a direct insult to DNA, such as a gene mutation, translocation, amplification, deletion, loss of heterozygosity, or via a mechanism resulting from abnormal gene transcription or translation. The overall result is an imbalance of cell replication and cell death in a tumor cell population that leads to an expansion of tumor tissue. Cancers (carcinomas) are characterized by their unregulated growth and spread of cells to other parts of the body [1,2]. Treatment of an individual diagnosed with cancer is not only dependent upon which type of malignancy (cancer) they have, but also on the extent of its spread, together with its sensitivity to treatment [3].The total care of the patient will involve assessment of their physical, psychological and social needs, so that a complete care package can be developed to support them and their carer(s) throughout the whole of their patient.

© 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **1.1. Colorectal cancer**

Colorectal cancer (CRC), less formally known as bowel cancer, is a cancer characterized by neoplasia in the colon, rectum, or vermiform appendix. CRC is a leading cause of cancer mortality in the Western World. In the United States, CRC is the third most commonly diagnosed cancer in men and women and the second leading cause of cancer-related mortality [4]. Because 5% of persons (1 in 20 persons) will develop colorectal cancer, this disease is an important public health issue.

#### **1.2. Incidence of colorectal cancer**

Globally, cancer of the colon and rectum is the third mostcommon cancer in males and in females with mortality paralleling incidence [5]. An estimated 141,210 cases (71,850 male and 69360 female) of CRC were expected to occur in 2011.An estimated 49, 380 deaths (25,250 male and 24,130 female)of CRC were expected to occur in 2011, accounting for about 9% of all cancer deaths (Table 1). The5-year survival is 90% when CRC is diagnosed at an early stage however, less than 40% cases are diagnosed when the cancer is still localized [6]. The frequency of CRC varies remarkably among different populations. The incidence of colorectal cancer is increas‐ ing in certain countries where risk was historically low (Japan, Puerto Rico). In high-risk countries, trends are gradually increasing (England), stabilizing (New Zealand), or declining (United States) with time. The greatest increases in the incidence of colorectal cancer are in Asia (Japan, Hong Kong, Singapore), Eastern Europe (Hungary, Poland), Israel, and Puerto Rico. In contrast to the recent decrease in rates seen in some western and northern European countries, relatively large increases have been observed in Spain. The decrease in incidence in the United States partially reflects the increase in detection and removal of precancerous lesions; the increase in several Asian and Eastern European countries may reflect changes in the prevalence of obesity and dietary patterns. Age standardized incidence of colorectal cancer around the world is depicted in graph 1.

In India, CRC does not figure amongst the 10 most common malignancies. The age-standar‐ dized rates of CRC in India have been estimated to be 4.2 and 3.2/100,000 for males and females, respectively.

Inter-regional differences in the incidence of CRC, including difference among population groups living in geographic proximity but with different life styles, suggest that environment plays a role in the development of the disease [7]. Change in the location of these tumours is seen with increasing age. The proportion of tumours beyond the reach of sigmoidoscopy increases with age [8]. Sub site distribution also may differ according to ethnicity [9]

Age

Sex

populations among women [10]

Colorectal cancer is most commonly found in those aged 50 years and over.

Men are more likely than women to develop colorectal cancer. The incidence rate of colorectal cancer between 2000 and 2004 was 69.2 per 100,000 population among men and 45.8per 100,000

**Estimated New cases Estimated Deaths** Male Female Male Female Prostate Breast Lung & bronchus Lung & bronchus 240,890 (29%) 230,480 (30%) 85,600 (28%) 71,340 (26%) Lung & bronchus Lung & bronchus Prostate Breast 115,060 (14%) 106,070 (14%) 33,720 (11%) 39,520 (15%) Colon & rectum Colon & rectum Colon & rectum Colon & rectum 71,850 (9%) 69,360 (9%) 25,250 (8%) 24,130 (9%) Urinary bladder Uterine corpus Pancreas Pancreas 52,020 (6%) 46,470 (6%) 19,360 (6%) 18,300 (7%)

40,010 (5%) 36,550 (5%) 13,260 (4%) 15,460 (6%) Kidney & renal pelvis Non-Hodgkin lymphoma Leukemia Non-Hodgkin lymphoma 37,120 (5%) 30,300 (4%) 12,740 (4%) 9,570 (4%)

36,060 (4%) 30,220 (4%) 11,910 (4%) 9,040 (3%) Oral cavity & pharynx Kidney & renal pelvis Urinary bladder Uterine corpus 27,710 (3%) 23,800 (3%) 10,670 (4%) 8,120 (3%)

25,320 (3%) 21,990 (3%) 9,750 (3%) 6,330 (2%)

22,050 (3%) 21,980 (3%) 8,270 (3%) system

All sites All sites All sites All sites 822,300 (100%) 774,370 (100%) 300,430 (100%) 271,520 (100%)

**Table 1.** Leading Sites of New Cancer Cases and Deaths (2011, American Cancer Society, Inc., Surveillance) 2011.

Leukemia Ovary Non-Hodgkin lymphoma Liver & intrahepatic bile duct

Pancreas Pancreas Kidney & renal pelvis Brain & other nervous

Non-Hodgkin lymphoma Melanoma of the skin Esophagus Leukemia

duct Ovary

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

5,670 (2%)

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333

Melanoma of the skin Thyroid Liver & intrahepatic bile

#### **1.3. Risk factors**

Epidemiologic studies have revealed a number of risk factors for colorectal cancer including age, family history of colon cancer or inflammatory bowel disease, smoking, alcohol con‐ sumption, obesity, and diet.


**Table 1.** Leading Sites of New Cancer Cases and Deaths (2011, American Cancer Society, Inc., Surveillance) 2011.

Age

**1.1. Colorectal cancer**

important public health issue.

**1.2. Incidence of colorectal cancer**

332 Colorectal Cancer - Surgery, Diagnostics and Treatment

around the world is depicted in graph 1.

respectively.

**1.3. Risk factors**

sumption, obesity, and diet.

Colorectal cancer (CRC), less formally known as bowel cancer, is a cancer characterized by neoplasia in the colon, rectum, or vermiform appendix. CRC is a leading cause of cancer mortality in the Western World. In the United States, CRC is the third most commonly diagnosed cancer in men and women and the second leading cause of cancer-related mortality [4]. Because 5% of persons (1 in 20 persons) will develop colorectal cancer, this disease is an

Globally, cancer of the colon and rectum is the third mostcommon cancer in males and in females with mortality paralleling incidence [5]. An estimated 141,210 cases (71,850 male and 69360 female) of CRC were expected to occur in 2011.An estimated 49, 380 deaths (25,250 male and 24,130 female)of CRC were expected to occur in 2011, accounting for about 9% of all cancer deaths (Table 1). The5-year survival is 90% when CRC is diagnosed at an early stage however, less than 40% cases are diagnosed when the cancer is still localized [6]. The frequency of CRC varies remarkably among different populations. The incidence of colorectal cancer is increas‐ ing in certain countries where risk was historically low (Japan, Puerto Rico). In high-risk countries, trends are gradually increasing (England), stabilizing (New Zealand), or declining (United States) with time. The greatest increases in the incidence of colorectal cancer are in Asia (Japan, Hong Kong, Singapore), Eastern Europe (Hungary, Poland), Israel, and Puerto Rico. In contrast to the recent decrease in rates seen in some western and northern European countries, relatively large increases have been observed in Spain. The decrease in incidence in the United States partially reflects the increase in detection and removal of precancerous lesions; the increase in several Asian and Eastern European countries may reflect changes in the prevalence of obesity and dietary patterns. Age standardized incidence of colorectal cancer

In India, CRC does not figure amongst the 10 most common malignancies. The age-standar‐ dized rates of CRC in India have been estimated to be 4.2 and 3.2/100,000 for males and females,

Inter-regional differences in the incidence of CRC, including difference among population groups living in geographic proximity but with different life styles, suggest that environment plays a role in the development of the disease [7]. Change in the location of these tumours is seen with increasing age. The proportion of tumours beyond the reach of sigmoidoscopy

Epidemiologic studies have revealed a number of risk factors for colorectal cancer including age, family history of colon cancer or inflammatory bowel disease, smoking, alcohol con‐

increases with age [8]. Sub site distribution also may differ according to ethnicity [9]

Colorectal cancer is most commonly found in those aged 50 years and over.

Sex

Men are more likely than women to develop colorectal cancer. The incidence rate of colorectal cancer between 2000 and 2004 was 69.2 per 100,000 population among men and 45.8per 100,000 populations among women [10]

cancer. A case-control study conducted by Caan *et al* [13] found that men who had a BMI in the highest quintile were almost 2 times as likely to develop colon cancer as men with a BMI

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

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335

Staging describes the extent or spread of the disease at the time of diagnosis. It is essential in determining the choice of therapy and in assessing prognosis. Stage is based on the primary tumour's size and location and whether it has spread to other areas of the body. A number of different staging systems are used to classify tumours. For CRC patients´ pathologic stage represents one of the most important prognostic factors. The Dukes´ system was the classic staging method for CRC, however the tumour, node, metastasis (TNM) staging system is more detailed and is most commonly used today. On occasion, Roman numerals I through IV are used in CRC staging (Table 2). These numerals correspond with Dukes´ classes.TNM staging system is useful for descriptive and statistical analysis of tumour registry data. If cancer cells are present only in the layer of cells where they originated and have not penetrated the basement membrane of the tissue, the stage is in situ; otherwise it is invasive. Stage is catego‐ rized as local if cancer cells are confined to the organ of origin, regional if the cells have spread beyond their original (primary) site to nearby lymph nodes or tissues, and distant if they have

spread from the primary site to distant organs or distant lymph nodes.

**AJCC stage TNM stage TNM stage criteria for colorectal cancer** Stage 0 Tis N0 M0 Tis: Tumour confined to mucosa; cancer-in-situ

Stage I T1 N0 M0 T1: Tumour invades submucosa Stage I T2 N0 M0 T2: Tumour invades muscularispropria

Stage II-A T3 N0 M0 T3: Tumour invades subserosa or beyond (without other

Stage II-B T4 N0 M0 T4: Tumour invades adjacent organs or perforates the

Stage III-A T1-2 N1 M0 N1: Metastasis to 1 to 3 regional lymph nodes. T1 or T2. Stage III-B T3-4 N1 M0 N1: Metastasis to 1 to 3 regional lymph nodes. T3 or T4. Stage III-C any T, N2 M0 N2: Metastasis to 4 or more regional lymph nodes. Any T. Stage IV any T, any N, M1 M1: Distant metastases present. Any T, any N.

Fifteen years ago, Fearon and Vogelstein [14] proposed a genetic model to explain the stepwise formation of CRC from normal colonic tissues. This model states that 1) CRC is the result of changes (mutations) of genes with important functions in regulating cell proliferation or repair

organs involved)

visceral peritoneum

in the lowest quintile.

**1.4. Classification and grade of CRC**

**Table 2.** TNM staging for colorectal cancer

**1.5. Genetics of CRC**

#### **Graph 1** Family History

Graph 1: Age standardized incidence of colorectal cancer/100,000populations around the world (Arshad et al., 2011)

According to the CDC (Centre for Disease Control and Prevention), those who have a family history of colorectal cancer are at higher risk for developing colorectal cancer themselves. In addition to particular genetic pathways that are activated in the development of colon cancer, there are also known genetic mutations that can be inherited and make up approximately10% of all colorectal cancer cases [11]

#### Smoking

Tobacco use does not only put persons at risk for higher rates of lung, mouth, and esophageal cancers, it has also been associated with higher risk for developing colon cancer [11,12]

#### Diet

There have been a number of different dietary factors that have been linked to a higher risk of colorectal cancer including higher levels of red meat consumption, low levels of fruit and vegetable consumption, and diets that are low in fiber.

#### Obesity

Obesity is an important risk factor to consider based on the recent trends in the U.S. A number of studies have shown that being overweight is associated with increased risk of colorectal cancer. A case-control study conducted by Caan *et al* [13] found that men who had a BMI in the highest quintile were almost 2 times as likely to develop colon cancer as men with a BMI in the lowest quintile.

#### **1.4. Classification and grade of CRC**

Staging describes the extent or spread of the disease at the time of diagnosis. It is essential in determining the choice of therapy and in assessing prognosis. Stage is based on the primary tumour's size and location and whether it has spread to other areas of the body. A number of different staging systems are used to classify tumours. For CRC patients´ pathologic stage represents one of the most important prognostic factors. The Dukes´ system was the classic staging method for CRC, however the tumour, node, metastasis (TNM) staging system is more detailed and is most commonly used today. On occasion, Roman numerals I through IV are used in CRC staging (Table 2). These numerals correspond with Dukes´ classes.TNM staging system is useful for descriptive and statistical analysis of tumour registry data. If cancer cells are present only in the layer of cells where they originated and have not penetrated the basement membrane of the tissue, the stage is in situ; otherwise it is invasive. Stage is catego‐ rized as local if cancer cells are confined to the organ of origin, regional if the cells have spread beyond their original (primary) site to nearby lymph nodes or tissues, and distant if they have spread from the primary site to distant organs or distant lymph nodes.


**Table 2.** TNM staging for colorectal cancer

#### **1.5. Genetics of CRC**

Graph 1: Age standardized incidence of colorectal cancer/100,000populations around the

**0 5 10 15 20 25 30 35**

Female Male

According to the CDC (Centre for Disease Control and Prevention), those who have a family history of colorectal cancer are at higher risk for developing colorectal cancer themselves. In addition to particular genetic pathways that are activated in the development of colon cancer, there are also known genetic mutations that can be inherited and make up approximately10%

Tobacco use does not only put persons at risk for higher rates of lung, mouth, and esophageal cancers, it has also been associated with higher risk for developing colon cancer [11,12]

There have been a number of different dietary factors that have been linked to a higher risk of colorectal cancer including higher levels of red meat consumption, low levels of fruit and

Obesity is an important risk factor to consider based on the recent trends in the U.S. A number of studies have shown that being overweight is associated with increased risk of colorectal

world (Arshad et al., 2011)

**Graph 1** Family History

**New Zealand Sweden Los Angles Shanghai Singapore India Kuwait**

334 Colorectal Cancer - Surgery, Diagnostics and Treatment

**U.S. U.S B U.S W France Australia Canada Germany Israel Scotland China**

of all colorectal cancer cases [11]

vegetable consumption, and diets that are low in fiber.

Smoking

Diet

Obesity

Fifteen years ago, Fearon and Vogelstein [14] proposed a genetic model to explain the stepwise formation of CRC from normal colonic tissues. This model states that 1) CRC is the result of changes (mutations) of genes with important functions in regulating cell proliferation or repair of DNA damages, 2) mutations in more than one gene are required, and 3) the sequence of mutations is important in determining the eventual formation of CRC. The model is illustrated in (Figure 1), which also incorporated information from more recent studies.

The other pathway, namely the MSI pathway, begins with the inactivation of one of a group of genes responsible for DNA nucleotide mismatch repair, which leads to extensive mutations in both repetitive and non-repetitive DNA sequences with low frequencies of allelic losses and rare alterations of tumour DNA content [18]. The mechanism of tumorigenesis in highmicrosatellite instability (MSI-H) tumours is thought to involve frame shift mutations of microsatellite repeats within coding regions of the affected target genes, and the inactivation of these target genes is believed to directly contribute to tumour development and progression. Although these two distinct major genetic pathways of genetic instabilities are widely accepted, some tumours reveal different genetic pathways i.e., some tumours show both types of genomic instabilities and some tumours do not show any of these two instabilities. Further evidence for alternative pathways come from studies which show that mutations in *APC, KRAS* as well as *p53* do not occur in all tumours and some tumours may only contain a mutation in one of these genes. Another novel pathway has been described termed the CpG island methylator phenotype (CIMP) [17]. Two groups of tumours were identified. CIMP-positive tumours show a high degree of CpG island methylation in genes such as *p16* and *hMLH1* and are accompanied by mutations in *KRAS* and *TGF RII.* CIMP-negative tumours, which by definition do not contain a high degree of methylation, are characterized by *p53* mutations. CIMP-positive tumours may show a degree of correlation with the MSI pathway. Finally, colorectal cancers, arising from ulcerative colitis, do not develop from adenomas suggesting

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337

that they follow yet another different pathway 9 (Figure 2) [19]

**Figure 2.** Characteristics of the two major pathways in CRC.

The genes involved in the genetic paradigm leading to CRC can be broadly divided into two classes: tumour suppressor genes (TSGs) and oncogenes. TSGs encode proteins that either inhibit cell proliferation or promote apoptosis.

**Figure 1.** Correlation between CRC Progression and the accumulation of genetic alterations according to Fearon & Vogelstein (1990). The genetic alterations frequently found in CIN tumours are depicted in black; genetic alterations more common in MIN tumours are depicted in red.

TSGs are often inactivated in CRC. In contrast, oncogenes are activated versions of protooncogenes, which are often involved promoting cell proliferation or development. Once activated, oncogenes can lead to accelerated cell growth and contribute to tumour formation [15]. It is widely accepted that the molecular genetics of human cancers can be used to categorize colorectal carcinomas into two major types of genomic instabilities, chromosomal instability (CIN) and microsatellite instability (MSI) [16].The majority of colorectal carcinomas are categorized into the CIN pathway, which is characterized by a high frequency of allelic losses, deletions, and/or mutations of tumour suppressor genes such as APC and p53, and abnormal tumour DNA (Figure 2) [16]. Aneuploidy in CIN phenotype tumours had been demonstrated in colorectal cancer cell lines and tumour tissues. Although CIN is a common finding in colorectal carcinomas, the mechanism of CIN has not been clearly elucidated. Defects in DNA replication check point genes and many other genes increase the rate of genome rearrangement and it is suggested to be associated with CIN [17].

The other pathway, namely the MSI pathway, begins with the inactivation of one of a group of genes responsible for DNA nucleotide mismatch repair, which leads to extensive mutations in both repetitive and non-repetitive DNA sequences with low frequencies of allelic losses and rare alterations of tumour DNA content [18]. The mechanism of tumorigenesis in highmicrosatellite instability (MSI-H) tumours is thought to involve frame shift mutations of microsatellite repeats within coding regions of the affected target genes, and the inactivation of these target genes is believed to directly contribute to tumour development and progression. Although these two distinct major genetic pathways of genetic instabilities are widely accepted, some tumours reveal different genetic pathways i.e., some tumours show both types of genomic instabilities and some tumours do not show any of these two instabilities. Further evidence for alternative pathways come from studies which show that mutations in *APC, KRAS* as well as *p53* do not occur in all tumours and some tumours may only contain a mutation in one of these genes. Another novel pathway has been described termed the CpG island methylator phenotype (CIMP) [17]. Two groups of tumours were identified. CIMP-positive tumours show a high degree of CpG island methylation in genes such as *p16* and *hMLH1* and are accompanied by mutations in *KRAS* and *TGF RII.* CIMP-negative tumours, which by definition do not contain a high degree of methylation, are characterized by *p53* mutations. CIMP-positive tumours may show a degree of correlation with the MSI pathway. Finally, colorectal cancers, arising from ulcerative colitis, do not develop from adenomas suggesting that they follow yet another different pathway 9 (Figure 2) [19]

**Figure 2.** Characteristics of the two major pathways in CRC.

of DNA damages, 2) mutations in more than one gene are required, and 3) the sequence of mutations is important in determining the eventual formation of CRC. The model is illustrated

The genes involved in the genetic paradigm leading to CRC can be broadly divided into two classes: tumour suppressor genes (TSGs) and oncogenes. TSGs encode proteins that either

**Figure 1.** Correlation between CRC Progression and the accumulation of genetic alterations according to Fearon & Vogelstein (1990). The genetic alterations frequently found in CIN tumours are depicted in black; genetic alterations

TSGs are often inactivated in CRC. In contrast, oncogenes are activated versions of protooncogenes, which are often involved promoting cell proliferation or development. Once activated, oncogenes can lead to accelerated cell growth and contribute to tumour formation [15]. It is widely accepted that the molecular genetics of human cancers can be used to categorize colorectal carcinomas into two major types of genomic instabilities, chromosomal instability (CIN) and microsatellite instability (MSI) [16].The majority of colorectal carcinomas are categorized into the CIN pathway, which is characterized by a high frequency of allelic losses, deletions, and/or mutations of tumour suppressor genes such as APC and p53, and abnormal tumour DNA (Figure 2) [16]. Aneuploidy in CIN phenotype tumours had been demonstrated in colorectal cancer cell lines and tumour tissues. Although CIN is a common finding in colorectal carcinomas, the mechanism of CIN has not been clearly elucidated. Defects in DNA replication check point genes and many other genes increase the rate of

genome rearrangement and it is suggested to be associated with CIN [17].

in (Figure 1), which also incorporated information from more recent studies.

inhibit cell proliferation or promote apoptosis.

336 Colorectal Cancer - Surgery, Diagnostics and Treatment

more common in MIN tumours are depicted in red.

#### **1.6. Axin**

*Axin1* (also simply called Axin), which encodes isoformaand b, and *Axin2* (also called Axil or Conductin) have 45%identity at the nucleotide level and the proteins they encode appear to be functionally similar. However, whereas *Axin1* is expressed ubiquitously during mouse embryogenesis, *Axin2* is expressed in a restricted pattern [20]. *Axin1* is the constitutively expressed component of the degradation complex and is essential for the maintenance of low Wnt signalling activity in the basal state. In contrast, *Axin2* is upregulated in response to increased β-catenin concentrations and thus serves to limit the duration and intensity of the Wnt signal [21]. *Axin* is downregulated in a Wnt dependent manner and is dephosphorylated after Wnt stimulation, which leads to *Axin1* destabilisation over time. Cells that receive Wnt ligand signals have low concentrations of *Axin*. Biochemical studies show that the intracellular concentrations of *Axin* are approximately 1000 times lower than other destruction complex components, suggesting that *Axin* is the limiting factor in this pathway [22]

#### *1.6.1. Role of Axin in signaling pathways*

*Axin* has emerged as a major scaffold protein for regulating a variety of signaling pathways and biological functions (Figure 3). In Wnt signalling, *Axin* binds to many components in the pathway, including the Wnt co-receptor LRP (low-density lipoprotein-related protein recep‐ tor) [23] Dishevelled or Dvl [24], tumour suppressor adenomatous polyposis coli (APC), GSK-3β, β-catenin [25], Casein kinases [26], protein phosphatase 2A (PP2A) [27], Diversin [28] *Ccd1* [29], and *Axam* [30].Interestingly, *Axin* itself is regulated with its stability being modu‐ lated by Wnt receptors, Dvl [31], and phosphorylation by GSK-3β. Inaddition, *Axin* also interacts with proteins that have no close relevance to Wnt signalling, including MAP kinase kinase (MEKK) [32, 33], I-MFA [34], DCAP [35], SH2/3 adaptor protein Grb4 [36], and Smad3. Interaction of *Axin* with MEKK leads to JNK activation, proceeding through a cascade from Axin, MEKK, and MKK to JNK[37].The most intriguing aspect of JNK activation by Axin is that multiple seemingly concrete structural elements of Axin are required [38]. Axin interacts with Smad3 and affects TGF-β signalling pathway.

#### *1.6.2. Mutation of Axin in colorectal cancers*

Alterations in both *Axin1* and *Axin2* have been detected in several different tumours. Muta‐ tions are found in most *Axin* domains including the APC (RGS) and β-catenin-binding domains. *Axin* sequence variants have also been found in colon, ovarian, endometrioid, adenocarcinoma, and HCC cell lines. Biochemical and functional studies have shown that these mutations interfere with the binding of GSK3 and that they also alter the interaction between *Axin* and two upstream activators of TCF-dependent transcription, Frat1, and DVL. Many components of the Wnt signalling system are mutated in colorectal cancer. Germ line loss of function mutations in the APC gene are associated with an inherited form of colorectal cancer —familial adenomatous polyposis— with 90–95% penetrance. Somatic APC mutations are also found in most sporadic colorectal cancers [39]. Alterations in other components of Wnt

signalling, including β-catenin, TCF, *Axin1*, and *Axin2*, found in colorectal cancer indicate the important role that this pathway plays in the etiology of this disease [40]. Most *Axin1* mutations in colorectal cancer occur between exon 1 and 5, where the APC, GSK3, and β-catenin-binding domains are located. Mutations in *Axin2* have been found in approximately 20% of mismatch repair deficient colorectal tumours [41]. In most cases, one base deletion or insertion occurs in the mononucleotide repeat sequences located in exon 7, leading to a frame shift and premature protein truncation [42]. These mutations lead to elimination of the DIX domain, where DVL binds and negatively regulates *Axin* activity. This domain is also essential for homo-oligome‐ rization of *Axin*. The mutant form of *Axin2* appears to be more stable than the wild-type

tesy. S Salahshor et al. 2004)

**Figure 3.** Regulation of three signalling pathways by Axin (1) Axin in the absence of Wnt ligand stimulates β-catenin degradation by proteosome complex and halts its transcriptional activity (2) The presence of transforming growth fac‐ tor receptor signals Axin and stimulates Smad phosphorylation by TGF-β receptor I & II. The activated Smads then translocate into nucleus and stimulates transcription of downstream target gene. (3) Cells subjected to stress Axin bind to mitogenactivated protein and stimulate stress-activated protein kinase (SAPK/Jun) mediated apoptosis. (cour‐

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**1.6. Axin**

*Axin1* (also simply called Axin), which encodes isoformaand b, and *Axin2* (also called Axil or Conductin) have 45%identity at the nucleotide level and the proteins they encode appear to be functionally similar. However, whereas *Axin1* is expressed ubiquitously during mouse embryogenesis, *Axin2* is expressed in a restricted pattern [20]. *Axin1* is the constitutively expressed component of the degradation complex and is essential for the maintenance of low Wnt signalling activity in the basal state. In contrast, *Axin2* is upregulated in response to increased β-catenin concentrations and thus serves to limit the duration and intensity of the Wnt signal [21]. *Axin* is downregulated in a Wnt dependent manner and is dephosphorylated after Wnt stimulation, which leads to *Axin1* destabilisation over time. Cells that receive Wnt ligand signals have low concentrations of *Axin*. Biochemical studies show that the intracellular concentrations of *Axin* are approximately 1000 times lower than other destruction complex

*Axin* has emerged as a major scaffold protein for regulating a variety of signaling pathways and biological functions (Figure 3). In Wnt signalling, *Axin* binds to many components in the pathway, including the Wnt co-receptor LRP (low-density lipoprotein-related protein recep‐ tor) [23] Dishevelled or Dvl [24], tumour suppressor adenomatous polyposis coli (APC), GSK-3β, β-catenin [25], Casein kinases [26], protein phosphatase 2A (PP2A) [27], Diversin [28] *Ccd1* [29], and *Axam* [30].Interestingly, *Axin* itself is regulated with its stability being modu‐ lated by Wnt receptors, Dvl [31], and phosphorylation by GSK-3β. Inaddition, *Axin* also interacts with proteins that have no close relevance to Wnt signalling, including MAP kinase kinase (MEKK) [32, 33], I-MFA [34], DCAP [35], SH2/3 adaptor protein Grb4 [36], and Smad3. Interaction of *Axin* with MEKK leads to JNK activation, proceeding through a cascade from Axin, MEKK, and MKK to JNK[37].The most intriguing aspect of JNK activation by Axin is that multiple seemingly concrete structural elements of Axin are required [38]. Axin interacts

Alterations in both *Axin1* and *Axin2* have been detected in several different tumours. Muta‐ tions are found in most *Axin* domains including the APC (RGS) and β-catenin-binding domains. *Axin* sequence variants have also been found in colon, ovarian, endometrioid, adenocarcinoma, and HCC cell lines. Biochemical and functional studies have shown that these mutations interfere with the binding of GSK3 and that they also alter the interaction between *Axin* and two upstream activators of TCF-dependent transcription, Frat1, and DVL. Many components of the Wnt signalling system are mutated in colorectal cancer. Germ line loss of function mutations in the APC gene are associated with an inherited form of colorectal cancer —familial adenomatous polyposis— with 90–95% penetrance. Somatic APC mutations are also found in most sporadic colorectal cancers [39]. Alterations in other components of Wnt

components, suggesting that *Axin* is the limiting factor in this pathway [22]

*1.6.1. Role of Axin in signaling pathways*

338 Colorectal Cancer - Surgery, Diagnostics and Treatment

with Smad3 and affects TGF-β signalling pathway.

*1.6.2. Mutation of Axin in colorectal cancers*

**Figure 3.** Regulation of three signalling pathways by Axin (1) Axin in the absence of Wnt ligand stimulates β-catenin degradation by proteosome complex and halts its transcriptional activity (2) The presence of transforming growth fac‐ tor receptor signals Axin and stimulates Smad phosphorylation by TGF-β receptor I & II. The activated Smads then translocate into nucleus and stimulates transcription of downstream target gene. (3) Cells subjected to stress Axin bind to mitogenactivated protein and stimulate stress-activated protein kinase (SAPK/Jun) mediated apoptosis. (cour‐ tesy. S Salahshor et al. 2004)

signalling, including β-catenin, TCF, *Axin1*, and *Axin2*, found in colorectal cancer indicate the important role that this pathway plays in the etiology of this disease [40]. Most *Axin1* mutations in colorectal cancer occur between exon 1 and 5, where the APC, GSK3, and β-catenin-binding domains are located. Mutations in *Axin2* have been found in approximately 20% of mismatch repair deficient colorectal tumours [41]. In most cases, one base deletion or insertion occurs in the mononucleotide repeat sequences located in exon 7, leading to a frame shift and premature protein truncation [42]. These mutations lead to elimination of the DIX domain, where DVL binds and negatively regulates *Axin* activity. This domain is also essential for homo-oligome‐ rization of *Axin*. The mutant form of *Axin2* appears to be more stable than the wild-type protein. Transfection of normal fibroblasts with *Axin2* mutants led to the accumulation of βcatenin in the nuclei. Li-Hua Jin *et al*.2003analysed 54 colorectal tumour tissues for *Axin1* mutation and reported 11% missense mutation suggesting *Axin* mutation may contribute to the onset of colorectal tumourigenesis. Webster *et al* [43] screened *Axin* gene in a range of human tumour cell lines including colon cancer cell lines. They identified two sequence variants carrying a substitution in four colon cancer cell lines. Biochemical and functional studies carried out by them showed that the L 396M change interfered with Axin'sability to bind GSK-3. Interestingly, this mutation and a neighboring L392M change differentially altered Axin'sability to interfere with two upstream activators of TCF dependent transcription factor Frat-1 and Dishevelled. Suraweera *et al* [44] reported heterozygous frame shift mutation and an in frame deletion in exon 7 of *Axin2*. They also reported 8% mutation of *Axin* in colon cancer cell lines. These studies indicates role of *Axin* gene in colorectal carcinogenesis.

allele as only one is detected, hence loss of heterozygosity. Most commonly the deletion of DNA will not be isolated to just this marker but will more than likely also involve the loss of gene surrounding that region. This is important if the surrounding region contains one or more tumour suppressor genes. In fact LOH studies are often used to examine neoplasms to locate frequent chromosomal regions that are lost and hence may harbor putative tumour suppressor genes pivotal in the development of cancer. The greater the degree of LOH, the more geneti‐

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341

Global patterns of LOH can be understood through allele typing of tumours with polymorphic genetic markers. Simple sequence length polymorphisms (SSLPs or microsatellites) are reliable genetic markers for studying LOH. Microsatellites are short repetitive sequences of DNA that are scattered throughout the genome and are stably inherited, unique to each individual and have low inherent mutation rate [49]. Several studies have shown that alterations due to mutations in the simple repeat sequences or microsatellites are a feature in a number of cancers [50].Researchers working on colon cancers found the length of microsatellite DNA in tumour tissue vary from matching normal tissue. This variation in length of microsatellite represents a mutational process of insertion or deletion within tumour DNA [51].Loss of heterozygosity (LOH) i.e., loss of one allele at a constitutional heterozygous locus indicates the probability of

loss of a tumour suppressor gene, which might promote neoplastic progression [52].

India is heavily burdened with CRC. Most of the genes implicated in CRC (like *APC, KRAS, SMAD* etc) have been studied in CRC patients of this population. Results therein have depicted either some semblance or little discrepancies in CRC in comparison to other studies conducted in other ethnic groups. The important genes like *Axin 1*, *Axin 2* and *DCC* have been reported to be involved in etio-pathology of CRC, but their role is yet to be elucidated in CRC patients of North India. Keeping in view of this, we carried out this study with following objectives **•** To analyse the mutations, if any, in the coding exons (1a,1b,1c,2,4,6 and 10) of *Axin*1 gene

**•** To establish the correlation of *Axin1* and *Axin2* gene mutation with clinicopathological

**•** To analyse expression of *Axin* in CRC patients using western blotting technique andto correlate the altered expression of *Axin* with clinico -pathological characteristics of CRC

**•** To analyse Loss of Heterozygosity of *DCC* gene at VNTR and D18S8-M2 markers in CRC

patients and to correlate LOH of *DCC* gene with clinicopathological variables.

cally unstable the tumour type and more aggressive it is likely to be.

**•** To analyse the mutations, if any, in exon 7 of *Axin2* gene.

**•** Polymorphic studies of SNPs at codon 399 of *XRCC1* genes.

The main goals of this work are based on the hypothesis to understand

**2. Aim and objectives**

variables of CRC patients

patients.

#### **1.7. Deleted in colorectal cancers (DCC) gene**

The development of human cancer has been proposed to be a multistep process [45]. Vogelstein et al., 1988 showed that colonic tumorigenesis provides the systematic course to the multistep hypothesis at the molecular level. Several genes have been identified that alter during tumour progression. Frequent and consistent loss of heterozygosity (LOH) of specific chromosomes in human cancers has been associated with the presence of tumour suppressor genes [46]. In particular, the long arm of chromosome 18 has been shown to be lost in about 75% of colonic cancers [47].The tumour-suppressor gene *DCC* (deleted in colorectal carcinoma),located on the long arm of chromosome 18 (Figure 2) encodes a cell surface protein containing homology with N-CAM [14].*DCC* a putative tumour suppressor gene has been mapped on the long arm of 18th chromosome (18q). In normal conditions, *DCC* induced apoptosis limits cellular lifespan in the intestinal crypt and thereby inhibits the initiation of malignant transformation. Transfection of *DCC* cDNA into a human cell line lacking *DCC* expression suppresses tumour growth and results in apoptosis and cell cycle arrest [48].

#### *1.7.1. Loss of heterozygosity of DCC gene*

Human cancers arise by a combination of discrete mutations and chromosomal alterations. Loss of heterozygosity (LOH) of chromosomal regions bearing mutated tumour suppressor genes is a key event in the evolution of epithelial and mesenchymal tumours. The term Loss of heterozygosityv (LOH), refers to a technique widely used in cancer research.LOH relies upon an individual processing two non-identical alleles for specific genetic marker, which can be distinguished from each other. These individuals are referred to as heterozygote with respect to this allele. Distinguishing between alleles can be done by the presence of a restriction site on one allele or through polymorphic microsatellite repeats (also referred to as microsa‐ tellite markers).In the latter the alleles differ from one another based on their size. Using LOH, a comparison is made between the DNA extracted from normal and tumour tissue. If an allele is present in the normal DNA but missing in the tumour than we can suggest that this region of DNA has been lost or deleted through mutation. Therefore the tumour cells have lost an allele as only one is detected, hence loss of heterozygosity. Most commonly the deletion of DNA will not be isolated to just this marker but will more than likely also involve the loss of gene surrounding that region. This is important if the surrounding region contains one or more tumour suppressor genes. In fact LOH studies are often used to examine neoplasms to locate frequent chromosomal regions that are lost and hence may harbor putative tumour suppressor genes pivotal in the development of cancer. The greater the degree of LOH, the more geneti‐ cally unstable the tumour type and more aggressive it is likely to be.

Global patterns of LOH can be understood through allele typing of tumours with polymorphic genetic markers. Simple sequence length polymorphisms (SSLPs or microsatellites) are reliable genetic markers for studying LOH. Microsatellites are short repetitive sequences of DNA that are scattered throughout the genome and are stably inherited, unique to each individual and have low inherent mutation rate [49]. Several studies have shown that alterations due to mutations in the simple repeat sequences or microsatellites are a feature in a number of cancers [50].Researchers working on colon cancers found the length of microsatellite DNA in tumour tissue vary from matching normal tissue. This variation in length of microsatellite represents a mutational process of insertion or deletion within tumour DNA [51].Loss of heterozygosity (LOH) i.e., loss of one allele at a constitutional heterozygous locus indicates the probability of loss of a tumour suppressor gene, which might promote neoplastic progression [52].

## **2. Aim and objectives**

protein. Transfection of normal fibroblasts with *Axin2* mutants led to the accumulation of βcatenin in the nuclei. Li-Hua Jin *et al*.2003analysed 54 colorectal tumour tissues for *Axin1* mutation and reported 11% missense mutation suggesting *Axin* mutation may contribute to the onset of colorectal tumourigenesis. Webster *et al* [43] screened *Axin* gene in a range of human tumour cell lines including colon cancer cell lines. They identified two sequence variants carrying a substitution in four colon cancer cell lines. Biochemical and functional studies carried out by them showed that the L 396M change interfered with Axin'sability to bind GSK-3. Interestingly, this mutation and a neighboring L392M change differentially altered Axin'sability to interfere with two upstream activators of TCF dependent transcription factor Frat-1 and Dishevelled. Suraweera *et al* [44] reported heterozygous frame shift mutation and an in frame deletion in exon 7 of *Axin2*. They also reported 8% mutation of *Axin* in colon cancer cell lines. These studies indicates role of *Axin* gene in colorectal carcinogenesis.

The development of human cancer has been proposed to be a multistep process [45]. Vogelstein et al., 1988 showed that colonic tumorigenesis provides the systematic course to the multistep hypothesis at the molecular level. Several genes have been identified that alter during tumour progression. Frequent and consistent loss of heterozygosity (LOH) of specific chromosomes in human cancers has been associated with the presence of tumour suppressor genes [46]. In particular, the long arm of chromosome 18 has been shown to be lost in about 75% of colonic cancers [47].The tumour-suppressor gene *DCC* (deleted in colorectal carcinoma),located on the long arm of chromosome 18 (Figure 2) encodes a cell surface protein containing homology with N-CAM [14].*DCC* a putative tumour suppressor gene has been mapped on the long arm of 18th chromosome (18q). In normal conditions, *DCC* induced apoptosis limits cellular lifespan in the intestinal crypt and thereby inhibits the initiation of malignant transformation. Transfection of *DCC* cDNA into a human cell line lacking *DCC* expression suppresses tumour

Human cancers arise by a combination of discrete mutations and chromosomal alterations. Loss of heterozygosity (LOH) of chromosomal regions bearing mutated tumour suppressor genes is a key event in the evolution of epithelial and mesenchymal tumours. The term Loss of heterozygosityv (LOH), refers to a technique widely used in cancer research.LOH relies upon an individual processing two non-identical alleles for specific genetic marker, which can be distinguished from each other. These individuals are referred to as heterozygote with respect to this allele. Distinguishing between alleles can be done by the presence of a restriction site on one allele or through polymorphic microsatellite repeats (also referred to as microsa‐ tellite markers).In the latter the alleles differ from one another based on their size. Using LOH, a comparison is made between the DNA extracted from normal and tumour tissue. If an allele is present in the normal DNA but missing in the tumour than we can suggest that this region of DNA has been lost or deleted through mutation. Therefore the tumour cells have lost an

**1.7. Deleted in colorectal cancers (DCC) gene**

340 Colorectal Cancer - Surgery, Diagnostics and Treatment

growth and results in apoptosis and cell cycle arrest [48].

*1.7.1. Loss of heterozygosity of DCC gene*

India is heavily burdened with CRC. Most of the genes implicated in CRC (like *APC, KRAS, SMAD* etc) have been studied in CRC patients of this population. Results therein have depicted either some semblance or little discrepancies in CRC in comparison to other studies conducted in other ethnic groups. The important genes like *Axin 1*, *Axin 2* and *DCC* have been reported to be involved in etio-pathology of CRC, but their role is yet to be elucidated in CRC patients of North India. Keeping in view of this, we carried out this study with following objectives


The main goals of this work are based on the hypothesis to understand


**Clinico-epidemiological Parameters Subgroup**

WD: well differentiated; MD: moderately differentiated, PD: poorly differentiated

Lane M: 100bp DNA ladder; Lane 1: DNA derived from blood of CRC patients; Lane 2: DNA derived from blood of a normal healthy control; Lane 3 and 4: DNA derived from Tumour Tissue; Lane 5, 6 and 7: DNA derived from adjacent

**Figure 4.** Agarose gel electrophoresis of DNA isolated from blood, tumour tissue, and adjacent normal tissue of CRC

**Table 3.** Clinico-epidemiological characteristics of the CRC patients

Grade/Differentiation

Stage

Location

Dwelling

Age

Sex

Smoking status

Normal Tissue

patients.

Cases (n=50)

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WD 33 (66%) MD/PD 17 (34%)

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

I/II 28(56%) III/IV 22(44%)

Colon 29 (58%) Rectum 21 (42%)

Rural 31(62%) Urban 19 (38%)

<50 19 (38%) ≥50 31 (62%)

Male 24 (48%) Female 26 (52%)

Never 21(42%) Ever 29(58%)


## **3. Methodology and results**

#### **3.1. Mutational analysis of** *Axin 1* **and** *Axin 2* **gene**

#### Characteristics of the study subjects

A total of fifty (n=50) tissue samples of colorectal carcinoma and their adjacent normal samples were used for mutational analysis of *Axin1* and *Axin2* gene. Same samples were used for analysis of Axin protein expression. Tumour and adjacent normal tissue samples were collected in the General Surgery Department (SKIMS) after surgical resection. All the resected tissue specimens were histologically confirmed to be colorectal carcinomas by a panel of 2 expert pathologists. Median age at the time of diagnosis was 52 years (range 30-75); and male: female ratio was 1:1. Clinico-pathological characteristics of patients are given in table 3.On the basis of age, the patients were grouped into two categories, less than 50 years (<50) and greater than or equal to 50 years of age (≥50). The number of cases in the age group of ≥50 were 62 % (31/50) and less than <50 years were 38 % (19/50).In this study 29(58%) patients had cancer in the colon while as cancer of rectum accounted for 21(42%) of CRC cases. 33(61%) cases of CRC were well differentiated and 17(34%) were poorly/moderately differentiated. 31(62%) of CRC patients belonged to rural area and 19 (38%) to urban area. Based on the smoking status, 21(42%) patients were non-smokers and 29 (58%) were smokers. Almost all the patients with left colon carcinoma had attended the hospital with a clinical presentation of bleeding per rectum.

#### **3.2. Molecular analysis of** *Axin* **1 and** *Axin 2* **gene**

High molecular weight genomic DNA isolated from the samples (tumour tissues and corre‐ sponding normal tissues) (Figure 4) were subjected to PCR to amplify the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and exon 7 of *Axin2.*The representative gel pictures of each amplified exon of *Axin1* and *Axin2* genes are given in figure 5. PCR products were purified manually and then purified samples were subjected to DNA sequence analysis. To identify the sequence varia‐ tions, the electrophoregram obtained after sequencing of the PCR products were compared manually with the reference sequence of the *Axin1* and *Axin2* gene deposited in the NCBI Gene Bank database (Accession No.NC 000016 & NC 000017).

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study http://dx.doi.org/10.5772/57380


WD: well differentiated; MD: moderately differentiated, PD: poorly differentiated

**Table 3.** Clinico-epidemiological characteristics of the CRC patients

**•** What is the role of *Axin* 1 and *Axin* 2 gene aberrations in CRC?

**•** What is the role of Arg399Gln SNP of *XRCC1* gene in CRC?

**•** What is the role of *DCC* gene aberrations in CRC?

**3.1. Mutational analysis of** *Axin 1* **and** *Axin 2* **gene**

**3.2. Molecular analysis of** *Axin* **1 and** *Axin 2* **gene**

Bank database (Accession No.NC 000016 & NC 000017).

**3. Methodology and results**

342 Colorectal Cancer - Surgery, Diagnostics and Treatment

Characteristics of the study subjects

samples?

rectum.

**•** To understand the pattern of Axin expression in CRC tumours with respect to normal

A total of fifty (n=50) tissue samples of colorectal carcinoma and their adjacent normal samples were used for mutational analysis of *Axin1* and *Axin2* gene. Same samples were used for analysis of Axin protein expression. Tumour and adjacent normal tissue samples were collected in the General Surgery Department (SKIMS) after surgical resection. All the resected tissue specimens were histologically confirmed to be colorectal carcinomas by a panel of 2 expert pathologists. Median age at the time of diagnosis was 52 years (range 30-75); and male: female ratio was 1:1. Clinico-pathological characteristics of patients are given in table 3.On the basis of age, the patients were grouped into two categories, less than 50 years (<50) and greater than or equal to 50 years of age (≥50). The number of cases in the age group of ≥50 were 62 % (31/50) and less than <50 years were 38 % (19/50).In this study 29(58%) patients had cancer in the colon while as cancer of rectum accounted for 21(42%) of CRC cases. 33(61%) cases of CRC were well differentiated and 17(34%) were poorly/moderately differentiated. 31(62%) of CRC patients belonged to rural area and 19 (38%) to urban area. Based on the smoking status, 21(42%) patients were non-smokers and 29 (58%) were smokers. Almost all the patients with left colon carcinoma had attended the hospital with a clinical presentation of bleeding per

High molecular weight genomic DNA isolated from the samples (tumour tissues and corre‐ sponding normal tissues) (Figure 4) were subjected to PCR to amplify the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and exon 7 of *Axin2.*The representative gel pictures of each amplified exon of *Axin1* and *Axin2* genes are given in figure 5. PCR products were purified manually and then purified samples were subjected to DNA sequence analysis. To identify the sequence varia‐ tions, the electrophoregram obtained after sequencing of the PCR products were compared manually with the reference sequence of the *Axin1* and *Axin2* gene deposited in the NCBI Gene

Lane M: 100bp DNA ladder; Lane 1: DNA derived from blood of CRC patients; Lane 2: DNA derived from blood of a normal healthy control; Lane 3 and 4: DNA derived from Tumour Tissue; Lane 5, 6 and 7: DNA derived from adjacent Normal Tissue

**Figure 4.** Agarose gel electrophoresis of DNA isolated from blood, tumour tissue, and adjacent normal tissue of CRC patients.

343

 **A:** *Axin 1*; Exon 1a (311bp) **B:** *Axin 1*; Exon 1b (387 bp)

 **C:** *Axin* 1; Exon 1c (405bp) **D:** *Axin* 1; Exon 2 ( 224bp)

**3.3. Mutational spectrum of** *Axin* **1 and** *Axin* **2 gene**

any clinico-epidemiological characteristics (Table 6 & 7).

**3.4. Analysis of protein expression of Axin**

**3.5. Loss of heterozygosity (LOH) of** *DCC* **gene**

In this study DNA sequencing was used to analyze the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and exon 7 of *Axin2* in a series of 50 CRC patients. No previously reported mutations were detected in any of the analysed exons of *Axin1* and *Axin2* genes in CRC patients except two SNPs mentioned below. However, an interesting finding of this study was that we detected a novel mutation of G>T (GCT>TCT) transversion in exon 7 of *Axin2* gene at codon G695T (p.alanine>serine) which has not been reported before this study [53] This G695T novel mutation was further confirmed by reverse sequence of the same samples. This novel mutation was found at a frequency of 6% (3/50). Among these three patients two were chronic smokers with mean age of fifty seven years. All the three patients had well differentiated adenocarci‐ noma. Clinico-pathological characteristics of patients having novel mutation are given in *Table 4*. In the same exon of *Axin2* gene a single nucleotide polymorphism (SNP) (rs 35415678) of C>T transition was detected in codon L688L (CCT>CTT) at a frequency of 18/50(36%). In exon1c of Axin1 we detected a SNP of T>C transition at codon D726D (GAT>GAC) at a frequency of 31/50 (62.5%) (Table 5.). This SNP is synonymous and does not lead to any change of amino acid (Figures 6, 7 & 8 ). Table 4.3 shows the changes in nucleotides of *Axin1* and *Axin2* genes observed in our study. No significant association of these SNPs was found in this report with

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345

In the present study, 50 colorectal cancer tissues and their adjacent normal samples previously studied for mutation spectrum were analysed for the protein expression of the *Axin*. The clinicopathological characteristics of the studied subjects are given in Table 3. The represen‐ tative picture of the proteins extracted that were run on SDS page is shown in the figure 9. Out of 50 cases of CRC, 26% (13/50) showed reduced expression of *Axin* (Figure 10) and the rest 74% (37/50) of the cases showed normal protein (*Axin*) expression. Among 13 cases of CRC with reduced expression,27% (9/33) were of well differentiated grade and 24% (4/17) of moderately/poorly differentiated grade. Reduced expression of Axin was found to be 25% (7/28) and 27% (6/22) of cases of stage I/II and III/IV respectively. Reduced expression of Axin was found to be in 4/21 (19%) of never smokers and 9/29 (31%) of ever smokers. Reduced expression of Axin in males was observed as 5/24 (21%) and in females as 8/26 (31%). 24% (7/29) of the CRC cases with colon carcinoma and 29% (6/21) cases of rectal carcinoma showed reduced expression of *Axin*. Association of reduced expression of Axin with clinicopatholog‐ ical characteristics is shown in Graph 2. No significant association of reduced expression of

Axin with any of the clinicopathological characteristic was found (p>0.05) (Table 8).

Loss of heterozygosity of *DCC* gene was determined by PCR-LOH assay in eighty samples of colorectal carcinoma and corresponding adjacent normal tissue. Mean age at the time of diagnosis was 52 years (range 30-80) with male: female ratio of 1:1.All the tumour samples included in this study were histopathologically confirmed cases of CRC. Histopathological findings of the CRC cases revealed 51 of 80 (64%) as well differentiated grade and 29 of 80

In this study DNA sequencing was used to analyze the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and

exon 7 of *Axin2* in a series of 50 CRC patients. No previously reported mutations were detected in any of the

**3.3 Mutational spectrum of** *Axin* **1 and** *Axin* **2 gene** 

Lane M Molecular size marker 100bp; Lane 1-5, 6 and 7 Amplified product of DNA.

 *Figure 5: PCR amplification of different exons of Axin1 and Axin2 genes Lane M Molecular size marker 100bp Lane 1-5, 6 and 7 Amplified product of DNA.*  **Figure 5.** PCR amplification of different exons of Axin1 and Axin2 genes

#### **3.3. Mutational spectrum of** *Axin* **1 and** *Axin* **2 gene**

 **M 1 2 3 4 5 6 M 1 2 3 4 5** 

344 Colorectal Cancer - Surgery, Diagnostics and Treatment

 **A:** *Axin 1*; Exon 1a (311bp) **B:** *Axin 1*; Exon 1b (387 bp)

 **M 1 2 3 4 5 6 M 1 2 3 4 5 6 7** 

 **C:** *Axin* 1; Exon 1c (405bp) **D:** *Axin* 1; Exon 2 ( 224bp)

 **E:** *Axin1*; Exon 4 (253 bp) **F:** *Axin1*; Exon 6 (256 bp)

 **G:** *Axin 1*;Exon 10 (260 bp) **H:** *Axin 2*; Exon 7 (320bp)

In this study DNA sequencing was used to analyze the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and

exon 7 of *Axin2* in a series of 50 CRC patients. No previously reported mutations were detected in any of the

 *Figure 5: PCR amplification of different exons of Axin1 and Axin2 genes* 

**Figure 5.** PCR amplification of different exons of Axin1 and Axin2 genes

Lane M Molecular size marker 100bp; Lane 1-5, 6 and 7 Amplified product of DNA.

 *Lane M Molecular size marker 100bp Lane 1-5, 6 and 7 Amplified product of DNA.* 

**3.3 Mutational spectrum of** *Axin* **1 and** *Axin* **2 gene** 

 **M 1 2 3 4 5 6 M 1 2 3 4 5 6** 

 **M 1 2 3 4 5 6 M 1 2 3 4 5 6** 

In this study DNA sequencing was used to analyze the exon 1a, 1b, 1c, 2, 4, 6 and 10 of *Axin1* and exon 7 of *Axin2* in a series of 50 CRC patients. No previously reported mutations were detected in any of the analysed exons of *Axin1* and *Axin2* genes in CRC patients except two SNPs mentioned below. However, an interesting finding of this study was that we detected a novel mutation of G>T (GCT>TCT) transversion in exon 7 of *Axin2* gene at codon G695T (p.alanine>serine) which has not been reported before this study [53] This G695T novel mutation was further confirmed by reverse sequence of the same samples. This novel mutation was found at a frequency of 6% (3/50). Among these three patients two were chronic smokers with mean age of fifty seven years. All the three patients had well differentiated adenocarci‐ noma. Clinico-pathological characteristics of patients having novel mutation are given in *Table 4*. In the same exon of *Axin2* gene a single nucleotide polymorphism (SNP) (rs 35415678) of C>T transition was detected in codon L688L (CCT>CTT) at a frequency of 18/50(36%). In exon1c of Axin1 we detected a SNP of T>C transition at codon D726D (GAT>GAC) at a frequency of 31/50 (62.5%) (Table 5.). This SNP is synonymous and does not lead to any change of amino acid (Figures 6, 7 & 8 ). Table 4.3 shows the changes in nucleotides of *Axin1* and *Axin2* genes observed in our study. No significant association of these SNPs was found in this report with any clinico-epidemiological characteristics (Table 6 & 7).

#### **3.4. Analysis of protein expression of Axin**

In the present study, 50 colorectal cancer tissues and their adjacent normal samples previously studied for mutation spectrum were analysed for the protein expression of the *Axin*. The clinicopathological characteristics of the studied subjects are given in Table 3. The represen‐ tative picture of the proteins extracted that were run on SDS page is shown in the figure 9. Out of 50 cases of CRC, 26% (13/50) showed reduced expression of *Axin* (Figure 10) and the rest 74% (37/50) of the cases showed normal protein (*Axin*) expression. Among 13 cases of CRC with reduced expression,27% (9/33) were of well differentiated grade and 24% (4/17) of moderately/poorly differentiated grade. Reduced expression of Axin was found to be 25% (7/28) and 27% (6/22) of cases of stage I/II and III/IV respectively. Reduced expression of Axin was found to be in 4/21 (19%) of never smokers and 9/29 (31%) of ever smokers. Reduced expression of Axin in males was observed as 5/24 (21%) and in females as 8/26 (31%). 24% (7/29) of the CRC cases with colon carcinoma and 29% (6/21) cases of rectal carcinoma showed reduced expression of *Axin*. Association of reduced expression of Axin with clinicopatholog‐ ical characteristics is shown in Graph 2. No significant association of reduced expression of Axin with any of the clinicopathological characteristic was found (p>0.05) (Table 8).

#### **3.5. Loss of heterozygosity (LOH) of** *DCC* **gene**

Loss of heterozygosity of *DCC* gene was determined by PCR-LOH assay in eighty samples of colorectal carcinoma and corresponding adjacent normal tissue. Mean age at the time of diagnosis was 52 years (range 30-80) with male: female ratio of 1:1.All the tumour samples included in this study were histopathologically confirmed cases of CRC. Histopathological findings of the CRC cases revealed 51 of 80 (64%) as well differentiated grade and 29 of 80 (36%) as moderately/poorly differentiated grade. In order to analyse LOH of *DCC* gene at two markers both the markers were amplified the amplified PCR products for D18S8-M2 (396bp) was digested by *Msp*I restriction enzyme and analyzed on 8% polyacrylamide gel whereas amplified product of VNTR region was directly run on 8% PAGE (Figure 12) and photograph‐ ed under ultraviolet light.


Abbrevations: S.code=sample code;S.Status=Smaoking status; C.smoker=chronic smoker;

N.smoker=non-smoker HP G = Histopathological grade;WD=well differentiated; A.A change=Amino acid change;

N.N change =nucleotide change C.Change=codon change; A. Colon= ascending colon.

**Table 4.** Clinico-epidemiological characteristics of the patients with novel mutation in Axin 2 gene


(Transcript ID of Axin1 gene ENSG00000103126, NCBI Reference Sequence NC\_000016.9) (Transcript ID of Axin2 gene ENSG00000168646, NCBI Reference Sequence: NC\_000017.10)

> in size from 150 to 210bp (Figure 12) depending on insertion or deletion. LOH at both D18S8- M2 and VNTR markers was observed as 39% (20/51) in samples with well differentiated grade and 86% (25/29) in moderately/poorly differentiated samples. 47 of 80 (59%) cases of CRC were of stage I-II and 33 of 80 (41%) of stage III-IV. LOH was found 47% (22/47) and 70% (23/33) at both the markers in stage I-II and III-IV respectively. The overall combined frequency of LOH at two markers (D18S8-M2 and VNTR) in CRC cases was reported to be 56.25 % (45/80) (Table 10; see Graph 3 also). LOH of DCC was found to be highly frequent in patients with higher stage/grade of CRC and this association was found to be significant (p<0.05). However no association of LOH was observed with any of the etiological parameter as depicted in Table 9.

**Variables**

*Age Group*

*Gender*

*Smoking*

*Residence*

*Tumor site*

*Grade*

**Cases (n=50)** **Wild allele 19(38%)**

WD 33(66%) 13(39%) 20(61%) Reference

MD/PD 17(34%) 06(35%) 11(65%) 1.2(0.3-4.7)

<50 19(38%) 08(42%) 11(58%) Reference

≥50 31(62%) 11(35%) 20(65%) 1.3(0.4-4.1)

Male 24(48%) 10(42%) 14(58%) Reference

Female 26(52%) 09(35%) 17(65%) 1.3(0.4-4.1)

Never 21(42%) 09(43%) 12(57%) Reference

Ever 29(58%) 10(34%) 19(66%) 1.4(0.4-4.0)

Rural 31(62%) 12(39%) 19(61%) Reference

Urban 19 (38%) 10(53%) 09(47%) 0.5(0.09-2.9)

Colon 29(58%) 10(34%) 19(66%) Reference

Rectum 21 (42%) 09(43%) 12(57%) 0.7(0.2-2.2)

WD=Well Differentiated; MD= Moderately differentiated

**Table 6.** Single nucleotide changes in Axin1 & Axin2 genes in CRC patients.

**Variant allele**

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

**31(62%) OR(95%CI)** *P-Value*

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0.77

347

0.63

0.63

0.62

0.33

0.54

**Table 5.** Single nucleotide changes in Axin1 & Axin2 genes in CRC patients.

In this study only informative cases were included (cases in which normal samples were heterozygous at M2-D18S8 marker), whereas uninformative cases (cases in which normal sample showed no heterozygosity) (Figure 11) were excluded from the study. Digested product of D18S8-M2 region yielded products of size 396, 257 and 139bp. LOH was considered positive for samples with absence of 396 bp bands and presence of 257 and139 bp (Figure 11). PCR product of VNTR when run directly on 8% PAGE generated a spectrum of alleles ranging


**Table 6.** Single nucleotide changes in Axin1 & Axin2 genes in CRC patients.

(36%) as moderately/poorly differentiated grade. In order to analyse LOH of *DCC* gene at two markers both the markers were amplified the amplified PCR products for D18S8-M2 (396bp) was digested by *Msp*I restriction enzyme and analyzed on 8% polyacrylamide gel whereas amplified product of VNTR region was directly run on 8% PAGE (Figure 12) and photograph‐

**Status Dwelling Location HPG C.change A.Achange**

**N. change**

> 2397 G→T

> 2397 G→T

> 2397 G→T

Alanine →serine

Alanine →serine

Alanine →serine

ed under ultraviolet light.

346 Colorectal Cancer - Surgery, Diagnostics and Treatment

**S.**

CRC 29 50 Male C.smoker Urban A. Colon WD GCT→TCT

CRC 32 65 Male C.smoker Urban Rectum WD GCT→TCT

CRC 38 57 Female N.smoker Rural Colon WD GCT→TCT

Abbrevations: S.code=sample code;S.Status=Smaoking status; C.smoker=chronic smoker;

N.N change =nucleotide change C.Change=codon change; A. Colon= ascending colon.

**Table 4.** Clinico-epidemiological characteristics of the patients with novel mutation in Axin 2 gene

**Gene/Exon Nucleotide change Codon change Amino Acid change Frequency**

GAT→GAC Exon 1c 1134 T→C Asp→ Asp 31/50(62.5%)

CCT→CTT Exon 7 2376 C→T Leu→ Leu 18/50(36%)

ENSG00000168646, NCBI Reference Sequence: NC\_000017.10)

**Table 5.** Single nucleotide changes in Axin1 & Axin2 genes in CRC patients.

(Transcript ID of Axin1 gene ENSG00000103126, NCBI Reference Sequence NC\_000016.9) (Transcript ID of Axin2 gene

In this study only informative cases were included (cases in which normal samples were heterozygous at M2-D18S8 marker), whereas uninformative cases (cases in which normal sample showed no heterozygosity) (Figure 11) were excluded from the study. Digested product of D18S8-M2 region yielded products of size 396, 257 and 139bp. LOH was considered positive for samples with absence of 396 bp bands and presence of 257 and139 bp (Figure 11). PCR product of VNTR when run directly on 8% PAGE generated a spectrum of alleles ranging

N.smoker=non-smoker HP G = Histopathological grade;WD=well differentiated; A.A change=Amino acid change;

**S. code Age Gender**

*Axin1*

*Axin2*

in size from 150 to 210bp (Figure 12) depending on insertion or deletion. LOH at both D18S8- M2 and VNTR markers was observed as 39% (20/51) in samples with well differentiated grade and 86% (25/29) in moderately/poorly differentiated samples. 47 of 80 (59%) cases of CRC were of stage I-II and 33 of 80 (41%) of stage III-IV. LOH was found 47% (22/47) and 70% (23/33) at both the markers in stage I-II and III-IV respectively. The overall combined frequency of LOH at two markers (D18S8-M2 and VNTR) in CRC cases was reported to be 56.25 % (45/80) (Table 10; see Graph 3 also). LOH of DCC was found to be highly frequent in patients with higher stage/grade of CRC and this association was found to be significant (p<0.05). However no association of LOH was observed with any of the etiological parameter as depicted in Table 9.


**Figure 7.** Partial nucleotide sequences in Exon 7 of the normal (left) and mutants in exon 7 of the Axin2 gene codon

**N (%)**

*Age* Reference 0.3

*Sex* Reference 0.4

*Dwelling* Reference 0.2

*Smoking* Reference 0.3

*Grade* Reference 0.77

*Stage* Reference 0.8

*Location* Reference 0.7

χ<sup>2</sup> was used to calculate the p-value of the variables. \*P-Value <0.05 was considered statistically significant

**Table 8.** Association of Clinic pathological characteristics with reduced expression of Axin

**Reduced expression**

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

(n=50) 37(74%) 13(26%) - -

**OR(95%CI) P-Value**

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349

1.9(0.57-7)

1.68(1.0-2.3)

0.39(0.09-1.6)

1.9(0.57-7.2)

0.8(0.2-3.0)

1.1(0.3-3.8)

1.25(0.35-4.3)

(CCT→CTT). Red arrow points toward base change in mutants with respect to normal sequence.

**Normal expression**

**N (%)**

Overall results Case

*<50* 19(38%) 15(79%) 4(21%)

*>50* 31(62%) 22(71%) 9(29%)

*Male* 24(48%) 19(79%) 5(21%)

*Female* 26(52%) 18(69%) 8(31%)

*Rural* 31(62%) 21(68%) 10(32%)

*Urban* 19(38%) 16(84%) 03(16%)

*Never* 21(42%) 17(81%) 4(19%)

*Ever* 29(58%) 20(69%) 9(31%)

*WD* 33(66%) 24(73%) 9(27%)

*MD/PD* 17(34%) 13(76%) 4(24%)

*I/II* 28(56%) 21(75%) 7(25%)

*III/IV* 22(44%) 16(73%) 6(27%)

*Colon* 29(58%) 22(76%) 7(24%)

*Rectum* 21(42%) 15(71%) 6(29%)

Clinico pathological variables

**Table 7.** Clinico-epidemiological Characteristics of the CRC Patients with single nucleotide polymorphism at codon 688 CCT>CTT Axin2 gene.

**Figure 6.** Partial nucleotide sequences in Exon 7 of normal (left) and of the mutants in (right) of the Axin 2 gene co‐ don (GCT>TCT) Partial reverse sequence of the same mutation (below). Arrow points toward base change in mutants with respect to normal sequence.

**Variables Cases (n=50) Wild allele**

348 Colorectal Cancer - Surgery, Diagnostics and Treatment

*Grade*

*AgeGroup*

*Gender*

*Smoking*

*Residence*

*Tumorsite*

688 CCT>CTT Axin2 gene.

with respect to normal sequence.

**32(64%)**

WD 33(66%) 19(58%) 14(42%) Reference

MD/PD 17(34%) 13(76%) 04(24%) 0.4(0.2-1.5)

<50 19(38%) 13(68%) 06(32%) Reference

≥50 31 (62%) 19(61%) 12(39%) 1.3(0.4-4.8)

Male 24(48%) 16(67%) 08(33%) Reference

Never 21(42%) 13(62%) 08(38%) Reference

Rural 31(62%) 20(65%) 11(35%) Reference

Urban 19 (38%) 12(63%) 07(37%) 1(0.3-3.2)

Colon 29(58%) 18(62%) 11(38%) Reference

Rectum 21 (42%) 14(67%) 07(33%) 0.8(0.24-3.0)

**Table 7.** Clinico-epidemiological Characteristics of the CRC Patients with single nucleotide polymorphism at codon

**Figure 6.** Partial nucleotide sequences in Exon 7 of normal (left) and of the mutants in (right) of the Axin 2 gene co‐ don (GCT>TCT) Partial reverse sequence of the same mutation (below). Arrow points toward base change in mutants

Ever 29(58%) 19(66%) 10(34%) 0.8(0.24-2.6)

Female 26 (52%) 16(62%) 10(38%) 1.3(0.3-4.2 )

**Variant allele**

**18(36%) OR(95%CI)** *<sup>P</sup>***-value**

0.19

0.10

0.7

0.79

0.9

0.7

**Figure 7.** Partial nucleotide sequences in Exon 7 of the normal (left) and mutants in exon 7 of the Axin2 gene codon (CCT→CTT). Red arrow points toward base change in mutants with respect to normal sequence.


χ<sup>2</sup> was used to calculate the p-value of the variables. \*P-Value <0.05 was considered statistically significant

**Table 8.** Association of Clinic pathological characteristics with reduced expression of Axin

**Variables Cases n=80 LOH–ve [%] LOH+ve [%] P-value**

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

0.00019\*

351

http://dx.doi.org/10.5772/57380

0.044\*

0.12

0.393

0.8412

0.323

0.21

Well differentiated 51(64%) 31(61%) 20 (39%)

Mod/Poorly differentiated 29(36%) 4(14%) 25 (86%)

Stages I-II 47(59%) 25(53%) 22(47%)

Stages III-IV 33(41%) 10(30%) 23(70%)

Colon 42(52.5%) 15 (36%) 27 (64%)

Rectum 38(47.5%) 20 (53%) 18 (47%)

Rural 46(57.5%) 22 (48%) 24 (52%)

Urban 34(42.5%) 13 (38%) 21 (62%)

<50 33(41.25%) 14 (42%) 19 (58%)

≥50 47(58.75%) 21 (45%) 26 (55%)

Male 43(53.75%) 21(49%) 22(51%)

Female 37(46.25%) 14(38%) 23(62%)

D18S8M2 61(76%) 19(24%)

VNTR 54(67.50%) 26(32.50%)

**Table 10.** Percentage of Cases with and without Loss of Heterozygosity at two different markers

**Table 9.** Relation of clinico-pathological variables with LOH of DCC gene

χ2 was used to calculate the P-value of the variables

χ2 was used to calculate the p-value of the variables. \*p-Value<0.05 was considered statistically significant

**Markers(n=80) LOH-ve LOH+ve p-value**

*Grade(differentiation)*

*Clinical staging*

*Location*

*Dwelling*

*Age*

*Sex*

**Figure 8.** Partial nucleotide sequences in Exon1c of the normal (left) and mutants in exon 1c of the Axin1 gene codon (GAT →GAC).Arrow points toward base change in mutants with respect to normal sequence.

**Figure 9.** Representative gel picture of 10% SDS-PAGE. In each case 25 µl of the crude protein extract from tumor as well as normal tissue was loaded.

Lanes N: Protein extracted from Normal tissues; Lanes T: Protein extracted from Tumour tissue; Membrane was pro‐ bed with a polyclonal antibody specific for Axin

**Figure 10.** Western blot analysis of Axin protein in colorectal tumour and adjacent normal tissues. Figure A-D Repre‐ sentative immunoblot showing the expression of Axin in Colorectal carcinoma as compared to their adjacent normals. Extract from samples was separately run for β-actin protein expression as loading control.


χ2 was used to calculate the p-value of the variables. \*p-Value<0.05 was considered statistically significant

**Table 9.** Relation of clinico-pathological variables with LOH of DCC gene

**Figure 8.** Partial nucleotide sequences in Exon1c of the normal (left) and mutants in exon 1c of the Axin1 gene codon

**Figure 9.** Representative gel picture of 10% SDS-PAGE. In each case 25 µl of the crude protein extract from tumor as

Lanes N: Protein extracted from Normal tissues; Lanes T: Protein extracted from Tumour tissue; Membrane was pro‐

**Figure 10.** Western blot analysis of Axin protein in colorectal tumour and adjacent normal tissues. Figure A-D Repre‐ sentative immunoblot showing the expression of Axin in Colorectal carcinoma as compared to their adjacent normals.

Extract from samples was separately run for β-actin protein expression as loading control.

(GAT →GAC).Arrow points toward base change in mutants with respect to normal sequence.

well as normal tissue was loaded.

350 Colorectal Cancer - Surgery, Diagnostics and Treatment

bed with a polyclonal antibody specific for Axin


**Table 10.** Percentage of Cases with and without Loss of Heterozygosity at two different markers

**Figure 12.** LOH of DCC gene at VNTR region. Lane M: 100bp DNA ladder, N: normal DNA, T: tumor DNA. Strong allelic imbalance is seen in tumor showing range of bands (150-200bp) not in adjacent normal tissues, with dominance of

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353

**Graph 3.** Frequency of distribution of LOH at two markers D18S8-M2 & VNTR of DCC gene

ing trend and sites among the top ten common cancers [56]

Colorectal cancer (CRC) is a leading cause of death in the western world. [54]. The frequency of CRC varies remarkably among different populations. In India, CRC does not figure amongst the 10 most common malignancies [55]. In Kashmir incidence of cancer is showing an increas‐

the larger 200-base pair allele.

**4. Summary and conclusion**

**Graph 2.** Association of reduced expression of Axin with clinic-pathological characteristics

Lane M: 100bp DNA ladder,N=Normal; T=tumour. Normal samples showed three bands (band size 396,257 &139). LOH+ve Informative cases. LOH -ve samples showed no loss of heterozygosity.

**Figure 11.** (a): LOH of DCC gene at D18S8-M2 region, (b): Uninformative cases (UI) were excluded from the study.

**Figure 12.** LOH of DCC gene at VNTR region. Lane M: 100bp DNA ladder, N: normal DNA, T: tumor DNA. Strong allelic imbalance is seen in tumor showing range of bands (150-200bp) not in adjacent normal tissues, with dominance of the larger 200-base pair allele.

**Graph 3.** Frequency of distribution of LOH at two markers D18S8-M2 & VNTR of DCC gene

### **4. Summary and conclusion**

**Graph 2.** Association of reduced expression of Axin with clinic-pathological characteristics

352 Colorectal Cancer - Surgery, Diagnostics and Treatment

Lane M: 100bp DNA ladder,N=Normal; T=tumour. Normal samples showed three bands (band size 396,257 &139).

**Figure 11.** (a): LOH of DCC gene at D18S8-M2 region, (b): Uninformative cases (UI) were excluded from the study.

LOH+ve Informative cases. LOH -ve samples showed no loss of heterozygosity.

Colorectal cancer (CRC) is a leading cause of death in the western world. [54]. The frequency of CRC varies remarkably among different populations. In India, CRC does not figure amongst the 10 most common malignancies [55]. In Kashmir incidence of cancer is showing an increas‐ ing trend and sites among the top ten common cancers [56]

Multiple factors contribute to the development of CRC, dietary and life style factors on one hand and genetic factors on the other [57]. Colon cancer is a common disease in both men and women. Because 5% of persons (1 in 20 persons) will develop colorectal cancer, this disease is an important public health issue. Colon cancer is usually observed in one of three specific patterns: sporadic, inherited or familial. Sporadic disease, with no familial or inherited predisposition, accounts for approximately 70% of colorectal cancer in the population. Sporadic colon cancer is common in persons older than 50 years of age, probably as a result of dietary and environmental factors as well as normal aging. Fewer than 10% of patients have an inherited predisposition to colon cancer. The inherited syndromes include those in which colonic polyps are a major manifestation of disease and those in which they are not. The polyposis syndromes are subdivided into familial adenomatous polyposis and the hamar‐ tomatous polyposis syndromes. The non-polyposis predominant syndromes include heredi‐ tary non-polyposis colorectal cancer (HNPCC) (Lynch syndrome I) and the cancer family syndrome (Lynch syndrome II). Although uncommon, these syndromes provide insight into the biology of all types of colorectal cancer. The third and least understood pattern of colon cancer development is known as familial colon cancer. In affected families, colon cancer develops too frequently to be considered sporadic colon cancer but not in a pattern consistent with an inherited syndrome. Up to 25% of all cases of colon cancer may fall into this category. CRC is more common in North America, parts of Europe, Australia, New Zeeland and Japan than in eastern Asia and Africa [58] This together with the fact that populations migrating from a low-incidence to a high-incidence geographical area show a similar incidence as those living in the high-incidence area, points towards life style and dietary habits being causative [59] The exact causes are still controversial but epidemiological studies indicate that diets that include low fruit, vegetable or fiber intake, high red meat or saturated fat consumption increase the risk of developing CRC. Exposure to caffeine, cigarette smoke and alcohol has also been suggested to increase risk. Diets high in calcium, folate and regular physical activity are associated with a reduced risk of developing CRC [60]

**•** The frequency of this novel mutation was found to be 6 % (3/50).

acid

istic with the development of CRC.

same studied for mutational analysis.

the reduced expression of Axin.

development of CRC.

controls with P<0.05

of CRC.

for controls.

found.

**•** 26% (13/50) CRC patients showed reduced expression of Axin.

**•** LOH of *DCC* gene at D18S8M2 marker was found to be 23.75 % (19/80).

**•** LOH of *DCC* gene at VNTR marker was found to be 32.50 % (26/80).

samples with respect to adjacent normal samples.

**•** This novel mutation leads to the change of amino acid alanine to serine.

**•** A SNP (rs 35415678) of C>T was found in exon 7 of *Axin2* gene at a frequency of 32% (18/50).This SNP was found at codon L688L resulting in the change of codon CCT>CTT. However this SNP was synonymous and hence does not lead to the change of amino acid.

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

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355

**•** A SNP (rs 1805105) of T>C was found in exon 1c of *Axin1* gene at a frequency of 62.5% (31/50).This SNP was found at codon D726D leading to the change of codon GAT>GAC. This SNP was also found to be synonymous and hence does not lead to the change of amino

**•** We did not find any significant association of any of the clinical epidemiological character‐

**•** Protein expression of *Axin* gene in fifty tumour specimens with respect to their adjacent normal samples was studied. The samples which were studied for protein expression were

**•** No association was found with any of the clinico-pathological characteristic of CRC with

**•** LOH of *DCC* gene at D18S8-M2 and VNTR marker was studied in eighty CRC tumour

**•** Aggregate percentage of loss of heterozygosity of *DCC* gene was found to be 55.25%.

**•** We found a significant association of LOH of *DCC* gene with higher stage and grade (P<0.05)

**•** No significant association of any other clinical pathological parameter was found with the

**•** Arg/Arg (GG) and Arg/Gln (GA) were found to be significantly associated with higher risk

**•** The frequency of the *XRCC1* allele Gln/Gln was found to be 6(5%) for cases & 34(23.3%) for

**•** The frequency of the *XRCC1* allele Arg/Gln was found to be 80(66.7%) for cases & 62(42.5%)

**•** No significant association of Arg399Gln SNP with any clinico-pathological parameters was

**•** No other sequence variation in any other analysed exons of *Axin* gene was found

According to the model developed by Vogelstein and coworkers, colorectal neoplasia evolves through a series of genetic alterations that includes the activation of oncogenes by mutation and the inactivation of tumor suppressor genes by mutation, loss of gene, or methylation [61]. As per their multistage model of colorectal carcinogenesis alteration of genes like Axin, APC, β-Catenin, Smads, TGF-β, B-Raf are early events whereas alteration of p53,DCC are late events in the development of CRC. In our population genes like APC, β-catenin and Smads have been previously studied in relation to the development of colorectal cancer. As per one of the study carried out on Kashmiri population by Sameer et al., 2010 the mutational aberrations of APC and β-catenin were reported to be low in CRC cases in Kashmiri populations however, frequency of the epigenetic silencing of the APC gene was reported to be high. SMAD4 gene aberrations were reported to be the common event in CRC development [62].

We studied genetic alterations of *Axin* 1, *Axin* 2 and *DCC* genes in CRC patients of Kashmiri population. Following are the major findings of our study

**•** In the present study we studied fifty CRC and adjacent normal samples, we found a novel mutation in exon 7 of *Axin2* gene at codon 695.This G>T transversion leads to the change of codon GCT>TCT.

**•** The frequency of this novel mutation was found to be 6 % (3/50).

Multiple factors contribute to the development of CRC, dietary and life style factors on one hand and genetic factors on the other [57]. Colon cancer is a common disease in both men and women. Because 5% of persons (1 in 20 persons) will develop colorectal cancer, this disease is an important public health issue. Colon cancer is usually observed in one of three specific patterns: sporadic, inherited or familial. Sporadic disease, with no familial or inherited predisposition, accounts for approximately 70% of colorectal cancer in the population. Sporadic colon cancer is common in persons older than 50 years of age, probably as a result of dietary and environmental factors as well as normal aging. Fewer than 10% of patients have an inherited predisposition to colon cancer. The inherited syndromes include those in which colonic polyps are a major manifestation of disease and those in which they are not. The polyposis syndromes are subdivided into familial adenomatous polyposis and the hamar‐ tomatous polyposis syndromes. The non-polyposis predominant syndromes include heredi‐ tary non-polyposis colorectal cancer (HNPCC) (Lynch syndrome I) and the cancer family syndrome (Lynch syndrome II). Although uncommon, these syndromes provide insight into the biology of all types of colorectal cancer. The third and least understood pattern of colon cancer development is known as familial colon cancer. In affected families, colon cancer develops too frequently to be considered sporadic colon cancer but not in a pattern consistent with an inherited syndrome. Up to 25% of all cases of colon cancer may fall into this category. CRC is more common in North America, parts of Europe, Australia, New Zeeland and Japan than in eastern Asia and Africa [58] This together with the fact that populations migrating from a low-incidence to a high-incidence geographical area show a similar incidence as those living in the high-incidence area, points towards life style and dietary habits being causative [59] The exact causes are still controversial but epidemiological studies indicate that diets that include low fruit, vegetable or fiber intake, high red meat or saturated fat consumption increase the risk of developing CRC. Exposure to caffeine, cigarette smoke and alcohol has also been suggested to increase risk. Diets high in calcium, folate and regular physical activity are

According to the model developed by Vogelstein and coworkers, colorectal neoplasia evolves through a series of genetic alterations that includes the activation of oncogenes by mutation and the inactivation of tumor suppressor genes by mutation, loss of gene, or methylation [61]. As per their multistage model of colorectal carcinogenesis alteration of genes like Axin, APC, β-Catenin, Smads, TGF-β, B-Raf are early events whereas alteration of p53,DCC are late events in the development of CRC. In our population genes like APC, β-catenin and Smads have been previously studied in relation to the development of colorectal cancer. As per one of the study carried out on Kashmiri population by Sameer et al., 2010 the mutational aberrations of APC and β-catenin were reported to be low in CRC cases in Kashmiri populations however, frequency of the epigenetic silencing of the APC gene was reported to be high. SMAD4 gene

We studied genetic alterations of *Axin* 1, *Axin* 2 and *DCC* genes in CRC patients of Kashmiri

**•** In the present study we studied fifty CRC and adjacent normal samples, we found a novel mutation in exon 7 of *Axin2* gene at codon 695.This G>T transversion leads to the change of

aberrations were reported to be the common event in CRC development [62].

associated with a reduced risk of developing CRC [60]

354 Colorectal Cancer - Surgery, Diagnostics and Treatment

population. Following are the major findings of our study

codon GCT>TCT.


**•** We found a protective role of Gln/Gln allele against the risk of development of CRC in Kashmiri population.

[3] Gabriel, J. Cancer: Health promotion, early detection and staging. In: Oncology Nurs‐

Possible Role of Proto-Oncogenes in Colorectal Cancer — A Population Based Study

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[4] American Cancer Society. Cancer Facts & Figures;2005. http://www.cancer.org/

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In conclusion, our study demonstrates significant role of *Axin* in the development of colorectal cancer. Eventhough we did not find any of the reported mutation in *Axin1* gene but we found reduced expression of *Axin1* in majority of CRC cases which clearly suggests its possible role in the development of CRC. Thus, our study points to the fact those other possible genetic alterations other than mutation could be responsible for malfunctioning of *Axin1* gene which may be responsible for the development of CRC. In *Axin*2 gene the novel mutation was found at low frequency of 6% leading to the change of amino acid from alanine to serine. The codon at which this novel mutation was found lies in the region capable of binding to various proteins and thus may somehow render *Axin* incapable of binding various other proteins involved in different pathways. This may lead to the derangement of Wnt, TGF-β, and Jun/SAPK path‐ ways. Aberration in specific binding of these signaling molecules to *Axin* due to the mutation G695T found in our study perhaps may aid in the deregulation of pathways and hence may lead to colorectal carcinogenesis.

Our study also supports the multistep model of colorectal carcinogenesis in which alteration of DCC gene has been reported to be the late event in the development of CRC as observed in our report. In this study we found that LOH has a frequency of 56% in patients with CRC and is highly frequent in patients with higher stage/grade in CRC suggesting that LOH of DCC gene may be one of the genetic events involved in the development of colorectal cancer in Kashmiri population.

## **Author details**

Syed Mudassar1 , Mosin S Khan1 , Nighat P. Khan1 , Mahboob ul- Hussain2 and Khurshid I. Andrabi2\*

\*Address all correspondence to: andrabik@uok.edu.in

1 Department of Clinical Biochemistry, Sher-I-Kashmir Institute of Medical Sciences, Srina‐ gar, India

2 Department of Biotechnology, University of Kashmir, Srinagar, India

### **References**


[3] Gabriel, J. Cancer: Health promotion, early detection and staging. In: Oncology Nurs‐ ing in Practice Whurr Publishers, London; 2001

**•** We found a protective role of Gln/Gln allele against the risk of development of CRC in

In conclusion, our study demonstrates significant role of *Axin* in the development of colorectal cancer. Eventhough we did not find any of the reported mutation in *Axin1* gene but we found reduced expression of *Axin1* in majority of CRC cases which clearly suggests its possible role in the development of CRC. Thus, our study points to the fact those other possible genetic alterations other than mutation could be responsible for malfunctioning of *Axin1* gene which may be responsible for the development of CRC. In *Axin*2 gene the novel mutation was found at low frequency of 6% leading to the change of amino acid from alanine to serine. The codon at which this novel mutation was found lies in the region capable of binding to various proteins and thus may somehow render *Axin* incapable of binding various other proteins involved in different pathways. This may lead to the derangement of Wnt, TGF-β, and Jun/SAPK path‐ ways. Aberration in specific binding of these signaling molecules to *Axin* due to the mutation G695T found in our study perhaps may aid in the deregulation of pathways and hence may

Our study also supports the multistep model of colorectal carcinogenesis in which alteration of DCC gene has been reported to be the late event in the development of CRC as observed in our report. In this study we found that LOH has a frequency of 56% in patients with CRC and is highly frequent in patients with higher stage/grade in CRC suggesting that LOH of DCC gene may be one of the genetic events involved in the development of colorectal cancer in

, Nighat P. Khan1

2 Department of Biotechnology, University of Kashmir, Srinagar, India

edn, Jones and Bartlett Publishers, Boston, MA; 2005

1 Department of Clinical Biochemistry, Sher-I-Kashmir Institute of Medical Sciences, Srina‐

[1] Corner, J. What is cancer? In: Cancer Nursing Care in Context, Blackwell Publishing,

[2] Yarbro,C., Frogge,M. and Goodman,M. Cancer Nursing:Principles and Practice, 6th

, Mahboob ul- Hussain2

and

Kashmiri population.

356 Colorectal Cancer - Surgery, Diagnostics and Treatment

lead to colorectal carcinogenesis.

, Mosin S Khan1

\*Address all correspondence to: andrabik@uok.edu.in

Kashmiri population.

**Author details**

Syed Mudassar1

gar, India

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Oxford; 2011

Khurshid I. Andrabi2\*


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**Chapter 15**

**Prospects of 'Omics Based Molecular Approaches in**

**Developing World: A Case Study in Cape Town, South**

The emergence of the field of genomics, proteomics and more recently lipidomics in science has advanced diagnostic and therapeutic medicine in no small measure. These fields typically deal with the documentation of the identity, abundance and localization of DNA, RNA, protein and lipid biomolecules in a given cell, tissue or organism. An in-depth knowledge of the biologic and physiologic localization, chemistry, and methodology for isolation of these essential biomolecules is key to a successful analysis and interpretation of information

The recent rapid development of these fields can be accounted for by the concurrent develop‐ ment of new state of the art, high throughput technologies such as real time qualitative polymerase chain reaction (RTqPCR), microarrays, flow cytometry, mass spectrometry and sequencing. These high throughput technologies have found extensive utility in diverse areas of human biology, particularly following the completion of the human genome project (HGP) in 2003. This project, which successfully documented the full complement of genes present physiologically within the human cell, gave a scientific platform to newer experimental

Clinical application of 'Omics based approaches have gained popularity and are believed to be the future of medicine because of its inherent ability to determine disease-associated changes in the human genome, transcriptome, proteome, lipidome and metabolome. Docu‐

> © 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Colorectal Cancer Diagnosis and Treatment in the**

**Africa**

Henry Adeola, Ryan William Goosen, Paul Goldberg and Jonathan Blackburn

http://dx.doi.org/10.5772/57485

retrieved in the 'omics field.

initiatives thereafter.

**1. Introduction**

Additional information is available at the end of the chapter

**Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and Treatment in the Developing World: A Case Study in Cape Town, South Africa**

Henry Adeola, Ryan William Goosen, Paul Goldberg and Jonathan Blackburn

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57485

**1. Introduction**

The emergence of the field of genomics, proteomics and more recently lipidomics in science has advanced diagnostic and therapeutic medicine in no small measure. These fields typically deal with the documentation of the identity, abundance and localization of DNA, RNA, protein and lipid biomolecules in a given cell, tissue or organism. An in-depth knowledge of the biologic and physiologic localization, chemistry, and methodology for isolation of these essential biomolecules is key to a successful analysis and interpretation of information retrieved in the 'omics field.

The recent rapid development of these fields can be accounted for by the concurrent develop‐ ment of new state of the art, high throughput technologies such as real time qualitative polymerase chain reaction (RTqPCR), microarrays, flow cytometry, mass spectrometry and sequencing. These high throughput technologies have found extensive utility in diverse areas of human biology, particularly following the completion of the human genome project (HGP) in 2003. This project, which successfully documented the full complement of genes present physiologically within the human cell, gave a scientific platform to newer experimental initiatives thereafter.

Clinical application of 'Omics based approaches have gained popularity and are believed to be the future of medicine because of its inherent ability to determine disease-associated changes in the human genome, transcriptome, proteome, lipidome and metabolome. Docu‐

© 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

mentation of these changes in principle enables the identification of disease-associated biomarkers for use in diagnostic tests, as well as with identifying molecular mechanisms of disease.

Whilst research and health institutions in the developed world are replete with ongoing studies and discoveries of candidate disease biomarkers, significant attendant challenges are associ‐ ated with 'omics based studies in a developing world setting, *inter alia*: infrastructure, human capacity and funding. Here we provide a synoptic overview of the prospects, challenges and benefits of 'omics based approaches in the diagnosis and treatment of CRC in a developing

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

http://dx.doi.org/10.5772/57485

365

The intricacies of CRC are due in part to its multiple implicated aetiologies and the heteroge‐ neity of the tumour. Important aetiologic considerations include; location (right sided or left sided, surface or cryptic, colonic or rectal), whether sporadic or hereditary, de novo or sequel to adenomatous polyp; intra-tumour heterogeneity (ITH) also plays an important role in the accuracy of histopathologic and molecular diagnosis. The classical theory of 'field cancerisa‐ tion' [6] presupposes that cancer develops from multifocal areas of precancerous changes; this concept is supported by latter studies which demonstrated that true cancer boundaries often exceed the physically discernible margin taken out at surgery, with histological analyses showing that these multiple abnormal tissues constituting premalignant cancer cell field changes persist and surround the tumor and may form multiple independent lesions that sometimes coalesce. The implications of such findings are profound when differentiating the cancer field recurrence from second primary tumours [6-8]. Subsequently, others have considered the concept of 'sequential carcinogenesis' which suggests that cancers develop as a progression from patchy premalignant lesions which later show evidence of mild, then moderate and then severe epithelial dysplasia. [7] These dysplastic lesions eventually progress to carcinoma-in-situ (high grade intraepithelial neoplasm), then to microinvasive carcinoma

The literature is replete with the extensive application of the field concept of Slaughter in surgical management of head and neck cancers and is gradually becoming a major consider‐ ation in the management of cancer of other organs such as the stomach, skin, cervix, lungs, vulva, bladder, colon, breast, and ovaries. [9, 10] In addition, molecular investigations have been used to assess correlation between phenotypic stages of cancer progression and expres‐ sion of cancer specific genes and mutations; these studies have demonstrated significant correlations between both [7, [11], implying that molecular markers have the potential to significantly enhance the precise diagnosis, staging and treatment monitoring of cancers.

The possibility of a physically normal tissue adjacent to the tumour area and expressing cancer specific genetic profiles has spurred interest in the origin of molecular level heterogeneity and histologic variability in the immediate field surrounding the cancer area. Some researchers have suggested that the heterogeneity in cancer growth follows a Darwinian evolutionary theory of natural selection [12], whilst others have concluded that there are two plausible origins of diversity in tumour cells expansion, described by the 'clonal evolution' theory and the 'cancer stem cell' theory. [13-15] The clonal evolution theory (cancer monoclonality)

world, using our Cape Town experience as a case example.

**2. Diagnostic inaccuracies in colorectal cancer**

and advanced invasive carcinoma.

Establishment of the HGP was then followed by the initiation of the Cancer Genome Atlas project to create a repertoire of genomic profiles for 20 different types of cancers. This project is designed to evaluate, across-the-board, the molecular and genomic depiction of different cancer types and to delineate the networks and maps for disease pathogenesis; the first results to be published from this project were for human glioblastomas [1], followed by ovarian carcinomas. [2]

Most recently, human colon and rectal cancers have been added to the Cancer Genome Atlas Project [3], the aim being to evaluate somatic modifications in such carcinomas using genome level methodologies to assess variation in DNA copy number, methylation patterns, micro‐ RNA expression, exon utilization; and acquired mutations: To date, genetic mutations have been found in 29 genes and amplifications of ERBB2 and IGF2 have also been observed. This large scale identification of novel genetic changes in human colorectal cancer (CRC) may in due course enable the identification of underlying molecular mechanisms of cancer develop‐ ment and new therapeutic targets, as well as the development of diagnostic and/or predictive tests for CRC.

Current knowledge of cancer cell biology shows that the complex carcinogenesis process is made up of several intricate molecular pathways and that different cancer cells express a heterogeneous array of signals. Hence individualized administration of beneficial treatment regimens to patients, rather than a 'one-size-fits-all' approach, is becoming more acceptable as a generic principle to strive towards, not least since it would be similar to the use of specific antibiotics based on microscopic culture and drug sensitivity testing instead of using a broad spectrum/empirical antibiotic approach.

According to the GLOBOCAN cancer fact sheet of the International Agency for Research on Cancer (IARC), over 12 new cancer cases and 7 million cancer deaths are reported worldwide annually. Colorectal cancer is the third most common cancer in males (663,000 new cases representing 10.0% of the total cancer cases) and the second most common cancer in females (571,000 new cases representing 9.4% of the total cancer cases). [4] Roughly 600,000 cases of colorectal cancer deaths are expected annually, accounting for almost a tenth of all cancer deaths, making it the fourth leading cause of cancer death worldwide. In trend, mortality rates are higher in males than in females except in the Caribbean regions.

Over half of the global CRC burden is occurs in developed countries and its incidence is known to be lowest in third world countries. The lowest incidence is reported in Africa; however in South Africa the incidence of CRC more closely resembles that of developed countries. Even though the mortality and incidence figures are poorly reported and cannot be harmonized reliably, reports from the currently defunct National Cancer Registry of South Africa revealed that in 1999 CRC was the sixth commonest cancer in the general population, accounting for about 2,367 cases of the total 26,606 new cancer cases reported. [5]

Whilst research and health institutions in the developed world are replete with ongoing studies and discoveries of candidate disease biomarkers, significant attendant challenges are associ‐ ated with 'omics based studies in a developing world setting, *inter alia*: infrastructure, human capacity and funding. Here we provide a synoptic overview of the prospects, challenges and benefits of 'omics based approaches in the diagnosis and treatment of CRC in a developing world, using our Cape Town experience as a case example.

## **2. Diagnostic inaccuracies in colorectal cancer**

mentation of these changes in principle enables the identification of disease-associated biomarkers for use in diagnostic tests, as well as with identifying molecular mechanisms of

Establishment of the HGP was then followed by the initiation of the Cancer Genome Atlas project to create a repertoire of genomic profiles for 20 different types of cancers. This project is designed to evaluate, across-the-board, the molecular and genomic depiction of different cancer types and to delineate the networks and maps for disease pathogenesis; the first results to be published from this project were for human glioblastomas [1], followed by ovarian

Most recently, human colon and rectal cancers have been added to the Cancer Genome Atlas Project [3], the aim being to evaluate somatic modifications in such carcinomas using genome level methodologies to assess variation in DNA copy number, methylation patterns, micro‐ RNA expression, exon utilization; and acquired mutations: To date, genetic mutations have been found in 29 genes and amplifications of ERBB2 and IGF2 have also been observed. This large scale identification of novel genetic changes in human colorectal cancer (CRC) may in due course enable the identification of underlying molecular mechanisms of cancer develop‐ ment and new therapeutic targets, as well as the development of diagnostic and/or predictive

Current knowledge of cancer cell biology shows that the complex carcinogenesis process is made up of several intricate molecular pathways and that different cancer cells express a heterogeneous array of signals. Hence individualized administration of beneficial treatment regimens to patients, rather than a 'one-size-fits-all' approach, is becoming more acceptable as a generic principle to strive towards, not least since it would be similar to the use of specific antibiotics based on microscopic culture and drug sensitivity testing instead of using a broad

According to the GLOBOCAN cancer fact sheet of the International Agency for Research on Cancer (IARC), over 12 new cancer cases and 7 million cancer deaths are reported worldwide annually. Colorectal cancer is the third most common cancer in males (663,000 new cases representing 10.0% of the total cancer cases) and the second most common cancer in females (571,000 new cases representing 9.4% of the total cancer cases). [4] Roughly 600,000 cases of colorectal cancer deaths are expected annually, accounting for almost a tenth of all cancer deaths, making it the fourth leading cause of cancer death worldwide. In trend, mortality rates

Over half of the global CRC burden is occurs in developed countries and its incidence is known to be lowest in third world countries. The lowest incidence is reported in Africa; however in South Africa the incidence of CRC more closely resembles that of developed countries. Even though the mortality and incidence figures are poorly reported and cannot be harmonized reliably, reports from the currently defunct National Cancer Registry of South Africa revealed that in 1999 CRC was the sixth commonest cancer in the general population, accounting for

are higher in males than in females except in the Caribbean regions.

about 2,367 cases of the total 26,606 new cancer cases reported. [5]

disease.

364 Colorectal Cancer - Surgery, Diagnostics and Treatment

carcinomas. [2]

tests for CRC.

spectrum/empirical antibiotic approach.

The intricacies of CRC are due in part to its multiple implicated aetiologies and the heteroge‐ neity of the tumour. Important aetiologic considerations include; location (right sided or left sided, surface or cryptic, colonic or rectal), whether sporadic or hereditary, de novo or sequel to adenomatous polyp; intra-tumour heterogeneity (ITH) also plays an important role in the accuracy of histopathologic and molecular diagnosis. The classical theory of 'field cancerisa‐ tion' [6] presupposes that cancer develops from multifocal areas of precancerous changes; this concept is supported by latter studies which demonstrated that true cancer boundaries often exceed the physically discernible margin taken out at surgery, with histological analyses showing that these multiple abnormal tissues constituting premalignant cancer cell field changes persist and surround the tumor and may form multiple independent lesions that sometimes coalesce. The implications of such findings are profound when differentiating the cancer field recurrence from second primary tumours [6-8]. Subsequently, others have considered the concept of 'sequential carcinogenesis' which suggests that cancers develop as a progression from patchy premalignant lesions which later show evidence of mild, then moderate and then severe epithelial dysplasia. [7] These dysplastic lesions eventually progress to carcinoma-in-situ (high grade intraepithelial neoplasm), then to microinvasive carcinoma and advanced invasive carcinoma.

The literature is replete with the extensive application of the field concept of Slaughter in surgical management of head and neck cancers and is gradually becoming a major consider‐ ation in the management of cancer of other organs such as the stomach, skin, cervix, lungs, vulva, bladder, colon, breast, and ovaries. [9, 10] In addition, molecular investigations have been used to assess correlation between phenotypic stages of cancer progression and expres‐ sion of cancer specific genes and mutations; these studies have demonstrated significant correlations between both [7, [11], implying that molecular markers have the potential to significantly enhance the precise diagnosis, staging and treatment monitoring of cancers.

The possibility of a physically normal tissue adjacent to the tumour area and expressing cancer specific genetic profiles has spurred interest in the origin of molecular level heterogeneity and histologic variability in the immediate field surrounding the cancer area. Some researchers have suggested that the heterogeneity in cancer growth follows a Darwinian evolutionary theory of natural selection [12], whilst others have concluded that there are two plausible origins of diversity in tumour cells expansion, described by the 'clonal evolution' theory and the 'cancer stem cell' theory. [13-15] The clonal evolution theory (cancer monoclonality) presupposes that tumour cells result from a solitary clone of mitotically unstable cell that differentiate into different offspring lineage clones that have developed additional unique genetic damage down the lineage. [13] By contrast, the cancer stem cell theory (cancer polyclonality) is premised on the possibility of cancer developing from multiple cancer stem cells that proliferate concurrently and drive the expansion of the tumour. Both theories have therapeutic implications in that only a fraction of the tumour bulk drives its expansion, hence targeted molecular therapies at these 'driver cells' could in principle be established for cancer treatment.

in their scope to identify such clinically relevant aberrant changes in tissue that appears morphologically normal; interestingly, these molecular observations are entirely consistent with Slaughter's 'field cancerisation' theory. [6] However, whether or not such a field has a gradually tapering aberrant effect as function of distance from the tumour remains incom‐ pletely answered. For instance, it has been found that there was no significant correlation between the degree of aberrant gene expression perturbation and distance from a polyp or tumour. [20] Irrespective, of the specific characteristics of any field effect, it is interesting to note that supporting evidence of aberrant perturbations in histologically normal colorectal mucosa appeared five decades after Slaughter's original hypothesis as a direct result of modern

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

http://dx.doi.org/10.5772/57485

367

In a study of normal colonic mucosa from individuals with a family history of sporadic cancer conducted by Hao et al [21], it was found that there was a significant difference in the expres‐ sion of several genes in these individuals' normal mucosa relative to the same tissue from healthy controls. In particular, the gene expression levels of PPAR-gamma, SAA1, and IL-8 were found to be significantly different in the morphologically normal rectosigmoid tissue samples in the individuals with a family history of CRC. Furthermore, a follow-up study in individuals with adenomatous polyps with or without familial history of colorectal carcinoma again found that there was a difference between gene expression in normal rectosigmoid mucosa from these individuals and healthy controls, regardless of the presence of a familial

Polley et al [19] observed significantly different proteomic signatures in morphologically normal mucosa from patients with colorectal neoplasia compared to the same tissue from healthy subjects. It therefore appears that a larger than anticipated field of tissue in the colorectum may be affected by the presence of a neoplastic lesion, implying in turn that the method used to determine clear margins estimated during surgical resection may need the support of molecular assays in the future. However, whether or not the molecularly perturbed

In addition to genomic and proteomic perturbations, epigenetic changes have also been reported in CRC tissues, one example being the hypomethylation of L1 promoter sequences in colorectal tumours and in adjacent normal tissue of 6 out of 19 cancer patients, but not in colonic mucosa of 14 healthy individuals. Furthermore, genomic CpG methylation appeared to be lower in normal colorectal tissue from diseased patients, compared to healthy subjects, and significantly lower in patients with hypomethylation of the L1 promoter sequences. [23]

The above examples at the genomic, proteomic and epigenetic level provide substantial evidence of molecular aberrations in morphologically normal tissue sample adjacent to a tumour. These changes might be subtle and may not effect a microscopically visible phenotype, but could well represent significant perturbations that impart normal tissue samples with precancerous characteristics. It is therefore important that such findings are considered when assessing individual biopsies by histopathology since these samples may in fact have under‐ lying molecular signals of disease that, if interpreted correctly, could provide insight into the

normal mucosa will progress to disease remains to be determined.

genomic, epigenomic, and proteomic research.

history of cancer. [22]

disease.

Phylogenetic evidence suggests that well-characterized subpopulations of tumour cells, including annotations of genetic mutations, have been derived from sequential genetic events [16] and mathematical models have been described to account for this, but to date have mostly provided a one-dimensional insight into the complexities of ITH. [17, 18] The mechanistic development of cancer is a multi- dimensional event and multiple factors have been estab‐ lished to govern its progression such as: the shape of the organ in which it occurs; blood supply; surgical interference; the consistency of the surface on which it occurs; tumour microenviron‐ ment; and the genetic nature of the cell. Clearly ITH is a reality that affects tumour diagnosis, classification, prognosis, and treatment; and requires further understanding.

#### **2.1. Reliability of histopathology reports**

*Introduction:* Histopathology is the science of utilising classical histological techniques to assess micro- and macroscopic evidence of potential disease. Classical histology routinely utilises microscopic observation of micrometer cross-sections of tissue, differential staining techni‐ ques, as well as immunohistochemical assays, to assess the tissue specimen in question. The visual evidence provided by each technique, or combination thereof, allows a pathologist to identify potential evidence of pathology, thereby providing a pathological diagnosis for a given specimen.

Classical histological techniques are inherently limited in their scope for the detection of pathology as they rely on a microscopically visible presentation of clear or strong evidence of pathology, e.g. in the case of advanced disease. Furthermore, any aberrant change at the submicroscopic level, i.e. the molecular level, needs to have translated into morphological change at the subcellular and/or overall cellular morphological level, or to have produced a variation in the abundance of a particular protein, or set of proteins, that is detectable through immu‐ nohistochemistry.

*Evidence of molecular changes that are not yet detectable at the histological level:* In molecular studies of tumour biopsies and adjacent "paired" normal samples, researchers often seek to identify molecular signatures that can distinguish tumour samples compared to histologically normal samples obtained from anatomical sites distal to the primary lesion. However, recent studies have investigated the possibility of significant molecular differences between histologically normal colorectal tissue from patients with polyps, or colorectal carcinoma, versus the same tissue from healthy individuals [19], suggesting that significant aberrant molecular changes occur in apparently normal colorectal tissue, despite being apparently distinctly located from the original lesion. In turn, this suggests that classic histopathological techniques are limited in their scope to identify such clinically relevant aberrant changes in tissue that appears morphologically normal; interestingly, these molecular observations are entirely consistent with Slaughter's 'field cancerisation' theory. [6] However, whether or not such a field has a gradually tapering aberrant effect as function of distance from the tumour remains incom‐ pletely answered. For instance, it has been found that there was no significant correlation between the degree of aberrant gene expression perturbation and distance from a polyp or tumour. [20] Irrespective, of the specific characteristics of any field effect, it is interesting to note that supporting evidence of aberrant perturbations in histologically normal colorectal mucosa appeared five decades after Slaughter's original hypothesis as a direct result of modern genomic, epigenomic, and proteomic research.

presupposes that tumour cells result from a solitary clone of mitotically unstable cell that differentiate into different offspring lineage clones that have developed additional unique genetic damage down the lineage. [13] By contrast, the cancer stem cell theory (cancer polyclonality) is premised on the possibility of cancer developing from multiple cancer stem cells that proliferate concurrently and drive the expansion of the tumour. Both theories have therapeutic implications in that only a fraction of the tumour bulk drives its expansion, hence targeted molecular therapies at these 'driver cells' could in principle be established for cancer

Phylogenetic evidence suggests that well-characterized subpopulations of tumour cells, including annotations of genetic mutations, have been derived from sequential genetic events [16] and mathematical models have been described to account for this, but to date have mostly provided a one-dimensional insight into the complexities of ITH. [17, 18] The mechanistic development of cancer is a multi- dimensional event and multiple factors have been estab‐ lished to govern its progression such as: the shape of the organ in which it occurs; blood supply; surgical interference; the consistency of the surface on which it occurs; tumour microenviron‐ ment; and the genetic nature of the cell. Clearly ITH is a reality that affects tumour diagnosis,

*Introduction:* Histopathology is the science of utilising classical histological techniques to assess micro- and macroscopic evidence of potential disease. Classical histology routinely utilises microscopic observation of micrometer cross-sections of tissue, differential staining techni‐ ques, as well as immunohistochemical assays, to assess the tissue specimen in question. The visual evidence provided by each technique, or combination thereof, allows a pathologist to identify potential evidence of pathology, thereby providing a pathological diagnosis for a

Classical histological techniques are inherently limited in their scope for the detection of pathology as they rely on a microscopically visible presentation of clear or strong evidence of pathology, e.g. in the case of advanced disease. Furthermore, any aberrant change at the submicroscopic level, i.e. the molecular level, needs to have translated into morphological change at the subcellular and/or overall cellular morphological level, or to have produced a variation in the abundance of a particular protein, or set of proteins, that is detectable through immu‐

*Evidence of molecular changes that are not yet detectable at the histological level:* In molecular studies of tumour biopsies and adjacent "paired" normal samples, researchers often seek to identify molecular signatures that can distinguish tumour samples compared to histologically normal samples obtained from anatomical sites distal to the primary lesion. However, recent studies have investigated the possibility of significant molecular differences between histologically normal colorectal tissue from patients with polyps, or colorectal carcinoma, versus the same tissue from healthy individuals [19], suggesting that significant aberrant molecular changes occur in apparently normal colorectal tissue, despite being apparently distinctly located from the original lesion. In turn, this suggests that classic histopathological techniques are limited

classification, prognosis, and treatment; and requires further understanding.

**2.1. Reliability of histopathology reports**

366 Colorectal Cancer - Surgery, Diagnostics and Treatment

treatment.

given specimen.

nohistochemistry.

In a study of normal colonic mucosa from individuals with a family history of sporadic cancer conducted by Hao et al [21], it was found that there was a significant difference in the expres‐ sion of several genes in these individuals' normal mucosa relative to the same tissue from healthy controls. In particular, the gene expression levels of PPAR-gamma, SAA1, and IL-8 were found to be significantly different in the morphologically normal rectosigmoid tissue samples in the individuals with a family history of CRC. Furthermore, a follow-up study in individuals with adenomatous polyps with or without familial history of colorectal carcinoma again found that there was a difference between gene expression in normal rectosigmoid mucosa from these individuals and healthy controls, regardless of the presence of a familial history of cancer. [22]

Polley et al [19] observed significantly different proteomic signatures in morphologically normal mucosa from patients with colorectal neoplasia compared to the same tissue from healthy subjects. It therefore appears that a larger than anticipated field of tissue in the colorectum may be affected by the presence of a neoplastic lesion, implying in turn that the method used to determine clear margins estimated during surgical resection may need the support of molecular assays in the future. However, whether or not the molecularly perturbed normal mucosa will progress to disease remains to be determined.

In addition to genomic and proteomic perturbations, epigenetic changes have also been reported in CRC tissues, one example being the hypomethylation of L1 promoter sequences in colorectal tumours and in adjacent normal tissue of 6 out of 19 cancer patients, but not in colonic mucosa of 14 healthy individuals. Furthermore, genomic CpG methylation appeared to be lower in normal colorectal tissue from diseased patients, compared to healthy subjects, and significantly lower in patients with hypomethylation of the L1 promoter sequences. [23]

The above examples at the genomic, proteomic and epigenetic level provide substantial evidence of molecular aberrations in morphologically normal tissue sample adjacent to a tumour. These changes might be subtle and may not effect a microscopically visible phenotype, but could well represent significant perturbations that impart normal tissue samples with precancerous characteristics. It is therefore important that such findings are considered when assessing individual biopsies by histopathology since these samples may in fact have under‐ lying molecular signals of disease that, if interpreted correctly, could provide insight into the disease.

*Molecular Intratumour heterogeneity due to branched evolutionary clonal expansion:* Intratumour heterogeneity in terms of cellular morphology and types of cells, is a well-established obser‐ vation in anatomical pathology. However, it is only recently that a further layer of complexity has been introduced through the discovery of an added layer of heterogeneity at the genomic and epigenomic level. This molecular heterogeneity further complicates biopsy selection and subsequent histopathological assessment because a specific lineage of clones, with a distinct genomic profile, may occur in physical clusters on a given tumour and thus be physically separated from other clonal populations. Therefore, each biopsy taken may present a uniform or slightly variable morphological appearance but might be distinct at the molecular level with unique functional potential and characteristics. This has fundamental ramifications when it comes to assessing the severity of disease and the prognosis, as well as deciding the appropriate course of treatment. Furthermore, intra-tumour heterogeneity governs how each unique tumour lineage evolves and adapts to therapeutic interventions and should therefore ideally be understood when developing new chemo- and biological treatments.

can be identified. This enhanced approach should facilitate the development of novel treatment regimens that efficaciously target all heterogeneous subpopulations for a given tumour and, in doing so, potentially also thwart aberrant histologically normal tissue from progressing to

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

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369

The possibility that distinct subpopulation of cells and/ or genetic signals exist in different areas of a particular biopsy specimen poses a major challenge in implementing personalized therapy. [25] 'Omics based research can in principle generate a more robust predictor of therapeutic benefits, but this often involve an extensive sample collection for discovery and validation, adequate funding and availability of appropriate manpower: an example of one such initiative is the 'Personalized RNA Interference to Enhance the Delivery of Individualized Cytotoxic and Targeted Therapeutics' (PREDICT) consortium [26] that aims to identify reliable

The earliest classification system for CRC by Dukes [27], modified by Astler [28], considered the staging of CRC severity to be based on its depth of invasion. More recently, a standardized widely accepted staging system of the American Joint Committee on Cancer (AJCC) also known as the TNM system which incorporated the tumour size, nodal involvement and presence of distant metastasis was introduced [29]: These three classifications are largely based on morphologic evidence and can be subject to inaccuracies. To minimize errors in diagnosis, these phenotypically driven systems of staging colorectal tumour could now in principle be

Newer and often more reliable molecular based assessment of tumour staging and prognosis are beginning to emerge for CRC based on new molecular cancer knowledge and 'omics based techniques and complement existing orthodox morphology based methods. One of such molecular classification is based on CpG island methylator phenotype (CIMP), as well as microsatellite instability (MSI), and is scored as type 1-5 based on different combinations of these molecular features. [11] Chromosomal instability (CIN) has also been identified as an important global molecular classifiers of CRC. [30] In addition, KRAS mutations have emerged as the most common prognostic biomarker of CRC for anti-EGFR therapy patients and many more candidate markers for prediction of therapeutic outcomes in colorectal cancer are being discovered now using 'omics based techniques, including loss of PTEN signals, PI3KCA

Identification of cancer specific genes, proteins, lipids and metabolites is increasingly regarded as a promising route to early diagnosis, treatment and monitoring of disease progress. For instance, the following genes have been recognized as associated with the risk of developing colorectal cancer; TP53, MLH1, MSH2, MSH6, MYH, EPCAM, KIT, BLM, SMAD4, PGDFRA, BMPR1A, APC, AXIN2, and STK11. *Vogelstein et al* [32] In a recent meta-analysis of 25 different genetic expression studies of colorectal cancer, a statistically significant down-regulation of carbonic anhydrase II (CAII) and CEACAM1 was observed, while there was up-regulation of TGFβ1, IFITM1, SPARC, GDF15 and MYC genes. [33] Based on these molecular patterns, a novel staging and classification system that is devoid of errors can now potentially be evolved.

usefully complemented with a validated molecular diagnostic method.

a malignant lesion.

biomarkers of different cancer types.

**2.2. Tumour classification and staging**

mutation and BRAF gene mutation. [31]

In a landmark study by Gerlinger et al [14], multiple spatially separated biopsy samples obtained from primary renal carcinomas and associated metastatic sites showed evidence of branched evolutionally growth by unique clonal population lineages. Furthermore, the majority of all somatic mutations (63 – 69%) were not found to be present across all tumour biopsies. One clinically relevant consequence of these findings was the identification of both good and poor prognostic signatures in different biopsies of the same tumour. This study highlights the inherent complexity of utilising a single biopsy for biomarker development, prognostic or predictive measures based on molecular markers to guide treatment regimen. It is clear that future biopsy collection - for the purpose of treatment planning or for biomarker research - should ensure collection and molecular assessment of multiple biopsies from physically separate sites on the same tumour.

A recent study by Kreso et al [24] has provided supporting evidence, in the context of colorectal carcinoma, that the distinct genetic profile of each intratumoural clonal subpopulation has implications in growth potential and chemotherapy tolerance and therefore has an impact on treatment outcomes. This appears to be due to Darwinian style natural selection, with certain subpopulations becoming more dominant by leveraging their intrinsic tolerance to selective pressure such as chemotherapeutic intervention. These findings highlight the fact that different tumour subpopulations have distinct proliferative potentials and chemotherapy tolerance mechanisms; as such, treatment regimens in the future my need to target each type of cellular population individually in order to prevent disease recurrence.

*Future directions for modern pathological assessments of cancer tissue samples:* Given the recent developments in the field of intratumour heterogeneity, and the evidence of significant molecular aberrations in histologically normal mucosa, it is clear that classical histopatholog‐ ical techniques are limited in their ability to assess the underlying clinically relevant hetero‐ geneity in tumour and normal tissue samples, suggesting that modern, validated, cost-effective molecular assays should be integrated into histopathological assessments. Amongst others, this would ensure that clinically relevant phenotypic or functional characteristics - whether dormant or active - which may directly govern a tumours response to therapeutic intervention can be identified. This enhanced approach should facilitate the development of novel treatment regimens that efficaciously target all heterogeneous subpopulations for a given tumour and, in doing so, potentially also thwart aberrant histologically normal tissue from progressing to a malignant lesion.

The possibility that distinct subpopulation of cells and/ or genetic signals exist in different areas of a particular biopsy specimen poses a major challenge in implementing personalized therapy. [25] 'Omics based research can in principle generate a more robust predictor of therapeutic benefits, but this often involve an extensive sample collection for discovery and validation, adequate funding and availability of appropriate manpower: an example of one such initiative is the 'Personalized RNA Interference to Enhance the Delivery of Individualized Cytotoxic and Targeted Therapeutics' (PREDICT) consortium [26] that aims to identify reliable biomarkers of different cancer types.

#### **2.2. Tumour classification and staging**

*Molecular Intratumour heterogeneity due to branched evolutionary clonal expansion:* Intratumour heterogeneity in terms of cellular morphology and types of cells, is a well-established obser‐ vation in anatomical pathology. However, it is only recently that a further layer of complexity has been introduced through the discovery of an added layer of heterogeneity at the genomic and epigenomic level. This molecular heterogeneity further complicates biopsy selection and subsequent histopathological assessment because a specific lineage of clones, with a distinct genomic profile, may occur in physical clusters on a given tumour and thus be physically separated from other clonal populations. Therefore, each biopsy taken may present a uniform or slightly variable morphological appearance but might be distinct at the molecular level with unique functional potential and characteristics. This has fundamental ramifications when it comes to assessing the severity of disease and the prognosis, as well as deciding the appropriate course of treatment. Furthermore, intra-tumour heterogeneity governs how each unique tumour lineage evolves and adapts to therapeutic interventions and should therefore ideally

In a landmark study by Gerlinger et al [14], multiple spatially separated biopsy samples obtained from primary renal carcinomas and associated metastatic sites showed evidence of branched evolutionally growth by unique clonal population lineages. Furthermore, the majority of all somatic mutations (63 – 69%) were not found to be present across all tumour biopsies. One clinically relevant consequence of these findings was the identification of both good and poor prognostic signatures in different biopsies of the same tumour. This study highlights the inherent complexity of utilising a single biopsy for biomarker development, prognostic or predictive measures based on molecular markers to guide treatment regimen. It is clear that future biopsy collection - for the purpose of treatment planning or for biomarker research - should ensure collection and molecular assessment of multiple biopsies from

A recent study by Kreso et al [24] has provided supporting evidence, in the context of colorectal carcinoma, that the distinct genetic profile of each intratumoural clonal subpopulation has implications in growth potential and chemotherapy tolerance and therefore has an impact on treatment outcomes. This appears to be due to Darwinian style natural selection, with certain subpopulations becoming more dominant by leveraging their intrinsic tolerance to selective pressure such as chemotherapeutic intervention. These findings highlight the fact that different tumour subpopulations have distinct proliferative potentials and chemotherapy tolerance mechanisms; as such, treatment regimens in the future my need to target each type of cellular

*Future directions for modern pathological assessments of cancer tissue samples:* Given the recent developments in the field of intratumour heterogeneity, and the evidence of significant molecular aberrations in histologically normal mucosa, it is clear that classical histopatholog‐ ical techniques are limited in their ability to assess the underlying clinically relevant hetero‐ geneity in tumour and normal tissue samples, suggesting that modern, validated, cost-effective molecular assays should be integrated into histopathological assessments. Amongst others, this would ensure that clinically relevant phenotypic or functional characteristics - whether dormant or active - which may directly govern a tumours response to therapeutic intervention

be understood when developing new chemo- and biological treatments.

physically separate sites on the same tumour.

368 Colorectal Cancer - Surgery, Diagnostics and Treatment

population individually in order to prevent disease recurrence.

The earliest classification system for CRC by Dukes [27], modified by Astler [28], considered the staging of CRC severity to be based on its depth of invasion. More recently, a standardized widely accepted staging system of the American Joint Committee on Cancer (AJCC) also known as the TNM system which incorporated the tumour size, nodal involvement and presence of distant metastasis was introduced [29]: These three classifications are largely based on morphologic evidence and can be subject to inaccuracies. To minimize errors in diagnosis, these phenotypically driven systems of staging colorectal tumour could now in principle be usefully complemented with a validated molecular diagnostic method.

Newer and often more reliable molecular based assessment of tumour staging and prognosis are beginning to emerge for CRC based on new molecular cancer knowledge and 'omics based techniques and complement existing orthodox morphology based methods. One of such molecular classification is based on CpG island methylator phenotype (CIMP), as well as microsatellite instability (MSI), and is scored as type 1-5 based on different combinations of these molecular features. [11] Chromosomal instability (CIN) has also been identified as an important global molecular classifiers of CRC. [30] In addition, KRAS mutations have emerged as the most common prognostic biomarker of CRC for anti-EGFR therapy patients and many more candidate markers for prediction of therapeutic outcomes in colorectal cancer are being discovered now using 'omics based techniques, including loss of PTEN signals, PI3KCA mutation and BRAF gene mutation. [31]

Identification of cancer specific genes, proteins, lipids and metabolites is increasingly regarded as a promising route to early diagnosis, treatment and monitoring of disease progress. For instance, the following genes have been recognized as associated with the risk of developing colorectal cancer; TP53, MLH1, MSH2, MSH6, MYH, EPCAM, KIT, BLM, SMAD4, PGDFRA, BMPR1A, APC, AXIN2, and STK11. *Vogelstein et al* [32] In a recent meta-analysis of 25 different genetic expression studies of colorectal cancer, a statistically significant down-regulation of carbonic anhydrase II (CAII) and CEACAM1 was observed, while there was up-regulation of TGFβ1, IFITM1, SPARC, GDF15 and MYC genes. [33] Based on these molecular patterns, a novel staging and classification system that is devoid of errors can now potentially be evolved.

#### **2.3. Role of surgical pathology**

The rationale behind the histopathologic use of slide sections from biopsy samples has been to evaluate for diagnostic purposes a representative microcosm of disease from a routine‐ ly processed, waxed, and miniaturized specimen blocks. However this has sometimes led to mis- or under- diagnosis of tumour depending on the exact site from which the biopsy was taken from. In principle, the goal of surgical resection is to take adequate 'tumourfree' margin; however achievement of this goal in practice is at best an estimated blind procedure, since cancer specific molecular alterations in the 'apparently' tumour free regions are largely unknown. This makes it difficult to readily determine the adequacy of a surgically resected margin. Not least, pathologists have had to take multiple biopsies from different sites in a resected tumour mass, trying to maximize the chances of locating the accurate tumour areas. This blind sampling procedure is a major potential source of diagnostic inaccuracies in practice and it is therefore important to detect colorectal cancer early to improve the chances of getting an adequate 'tumour free' surgical margin. Prompt surgical intervention, coupled with accurate determination of the most beneficial adju‐ vant therapy for the specific patient, appears to hold the key. Surgical pathology - which is the interface between surgery and pathologic specimen processing - is thus a vital control point for the eradication of diagnostic inaccuracies. Given the current molecular eviden‐ ces on intratumour and interbiopsy heterogeneity, an exclusive morphology based sampling technique is a potential minefield for diagnostic errors, even with the best mastery.

**2.4. Patient evaluation and therapeutic loopholes**

biomarkers.

regimen. [31]

Biomarker discovery research will in principle enable accurate stratification of patients into appropriate risk categories. The orthodox clinical approach of prescribing a common thera‐ peutic cancer regimen to all colorectal cancer patients is fast becoming a subject of evidencebased debates. Certain differences exist between patients who come from demographically, geographically and genetically divergent backgrounds. Such inter-patient variability may also present significant differences in tumour phenotype, behavior and natural histories across a population, an important observation that is referred to as single nucleotide polymorphism (SNP) noise. [39] Patient stratification based on these natural clusters can enable meaningful biomarker discovery using 'omics based techniques. For instance, in a culturally heterogene‐ ous South African population composed of Caucasians, Indigenous African, Indian, and Mixed Ancestries, the *a priori* expectation is that different racial groups may express different biomarkers of disease. In the same light, candidate biomarkers discovered from studies on developed world patient cohorts may not necessarily be effective for the management of colorectal cancer in a developing world situation due to differing ethnicities, which has clear implications for the planning and execution of 'omics based discovery and validation of

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

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371

In principle, it is possible to predict response to specific targeted therapies (e.g. Herceptin) using 'omics based approaches, with patients who would not respond to specific targeted therapies being identified at the outset and given alternative therapies. Patient dependent source of variation for biomarker discovery includes individual genetic make-up, metabolism, stage of disease, health, immunocompetence, nutritional factors, and environmental factors. Careful patient selection to eliminate confounders must be carried out prior to experiments

Genetic profiling of patients for KRAS mutation, BRAF genes, Microsatellite instability (MSI) and CpG island methylator phenotypes (CIMP) is now being increasingly carried out for colorectal cancer patients in the developed world and this has contributed significantly to treatment planning. Patients that exhibit MSI have been found to possess better overall survival than those with chromosomal instability and are less affected by p53 mutations [40], whilst CRC with p53 +, MSI + profiles are usually more aggressive than those with p53-, MSI + profiles. [41] Biomarkers such as telomerase and survivin have been used to assess the long term risk of CRC development [42] whilst morphologic biomarkers in patients include neoplastic colorectal polyposis and the presence of aberrant cryptic foci (AFC); the presence of adenomas with Intraepithelial Neoplasm in the colorectal region can also be used in surveillance as surrogate endpoint biomarkers. [43] Paradoxically, most anti-cancer agents do not have wellestablished single predictors of individualized response, however with the advances in 'omics based approaches it should be possible to provide such molecular predictors. For example, MSI has been documented to be an effective predictor of response to fluoropyrimidine therapy, whilst ERCC1 was found to be beneficial in patients using platinum containing anticancer

and biomarkers must be validated in a standardized acceptable manner.

'Omics based techniques relevant to colorectal cancer management

A delicate balance needs to be achieved during sampling of surgical specimens for the assessment of tumour heterogeneity. The most prominent, average pattern of expression is most likely to be identified during sampling of a large tumour biopsy sample, but this approach risks masking the less prominent but potentially equally important information about sub-populations of tumour cells in the biopsy sample. By contrast, signal-to-noise ratios have to be carefully balanced when analysing smaller biopsy samples since this approach presents a smaller sampling frame within which it may be impractical to identify all possible biomarker signals a tumour could express. [34] Surgeons and pathologists also need to bear in mind the downstream requirements and applications of 'omics based research when surgical biopsy samples are taken, especially since mining the molecular archives of formalin fixed paraffin embedded (FFPE) specimens through genomics, proteomics and lipidomics research is beginning to gain traction now. However, factors such as age of tissue, condition of storage, tissue sample size, fixation time, pH influen‐ ces and buffers are known to influence the outcome of 'omics based analyses on surgical specimens. [35] In particular, RNA degrades rapidly at room temperature, whilst formal‐ in damages nucleic acids within the specimen by forming sclerotic crosslinks of DNA and RNA *via* methylol adducts and methylene bridges. [35] Thus, immediate snap freezing of fresh sections in liquid nitrogen or dry ice is good practice, whilst use of newer alcoholbased kits [36], or of phosphate buffered formalin [37, 38], provide useful alternatives to standard formalin for rapid fixation of surgical specimens prior transport to the lab.

#### **2.4. Patient evaluation and therapeutic loopholes**

**2.3. Role of surgical pathology**

370 Colorectal Cancer - Surgery, Diagnostics and Treatment

The rationale behind the histopathologic use of slide sections from biopsy samples has been to evaluate for diagnostic purposes a representative microcosm of disease from a routine‐ ly processed, waxed, and miniaturized specimen blocks. However this has sometimes led to mis- or under- diagnosis of tumour depending on the exact site from which the biopsy was taken from. In principle, the goal of surgical resection is to take adequate 'tumourfree' margin; however achievement of this goal in practice is at best an estimated blind procedure, since cancer specific molecular alterations in the 'apparently' tumour free regions are largely unknown. This makes it difficult to readily determine the adequacy of a surgically resected margin. Not least, pathologists have had to take multiple biopsies from different sites in a resected tumour mass, trying to maximize the chances of locating the accurate tumour areas. This blind sampling procedure is a major potential source of diagnostic inaccuracies in practice and it is therefore important to detect colorectal cancer early to improve the chances of getting an adequate 'tumour free' surgical margin. Prompt surgical intervention, coupled with accurate determination of the most beneficial adju‐ vant therapy for the specific patient, appears to hold the key. Surgical pathology - which is the interface between surgery and pathologic specimen processing - is thus a vital control point for the eradication of diagnostic inaccuracies. Given the current molecular eviden‐ ces on intratumour and interbiopsy heterogeneity, an exclusive morphology based sampling

technique is a potential minefield for diagnostic errors, even with the best mastery.

A delicate balance needs to be achieved during sampling of surgical specimens for the assessment of tumour heterogeneity. The most prominent, average pattern of expression is most likely to be identified during sampling of a large tumour biopsy sample, but this approach risks masking the less prominent but potentially equally important information about sub-populations of tumour cells in the biopsy sample. By contrast, signal-to-noise ratios have to be carefully balanced when analysing smaller biopsy samples since this approach presents a smaller sampling frame within which it may be impractical to identify all possible biomarker signals a tumour could express. [34] Surgeons and pathologists also need to bear in mind the downstream requirements and applications of 'omics based research when surgical biopsy samples are taken, especially since mining the molecular archives of formalin fixed paraffin embedded (FFPE) specimens through genomics, proteomics and lipidomics research is beginning to gain traction now. However, factors such as age of tissue, condition of storage, tissue sample size, fixation time, pH influen‐ ces and buffers are known to influence the outcome of 'omics based analyses on surgical specimens. [35] In particular, RNA degrades rapidly at room temperature, whilst formal‐ in damages nucleic acids within the specimen by forming sclerotic crosslinks of DNA and RNA *via* methylol adducts and methylene bridges. [35] Thus, immediate snap freezing of fresh sections in liquid nitrogen or dry ice is good practice, whilst use of newer alcoholbased kits [36], or of phosphate buffered formalin [37, 38], provide useful alternatives to standard formalin for rapid fixation of surgical specimens prior transport to the lab.

Biomarker discovery research will in principle enable accurate stratification of patients into appropriate risk categories. The orthodox clinical approach of prescribing a common thera‐ peutic cancer regimen to all colorectal cancer patients is fast becoming a subject of evidencebased debates. Certain differences exist between patients who come from demographically, geographically and genetically divergent backgrounds. Such inter-patient variability may also present significant differences in tumour phenotype, behavior and natural histories across a population, an important observation that is referred to as single nucleotide polymorphism (SNP) noise. [39] Patient stratification based on these natural clusters can enable meaningful biomarker discovery using 'omics based techniques. For instance, in a culturally heterogene‐ ous South African population composed of Caucasians, Indigenous African, Indian, and Mixed Ancestries, the *a priori* expectation is that different racial groups may express different biomarkers of disease. In the same light, candidate biomarkers discovered from studies on developed world patient cohorts may not necessarily be effective for the management of colorectal cancer in a developing world situation due to differing ethnicities, which has clear implications for the planning and execution of 'omics based discovery and validation of biomarkers.

In principle, it is possible to predict response to specific targeted therapies (e.g. Herceptin) using 'omics based approaches, with patients who would not respond to specific targeted therapies being identified at the outset and given alternative therapies. Patient dependent source of variation for biomarker discovery includes individual genetic make-up, metabolism, stage of disease, health, immunocompetence, nutritional factors, and environmental factors. Careful patient selection to eliminate confounders must be carried out prior to experiments and biomarkers must be validated in a standardized acceptable manner.

Genetic profiling of patients for KRAS mutation, BRAF genes, Microsatellite instability (MSI) and CpG island methylator phenotypes (CIMP) is now being increasingly carried out for colorectal cancer patients in the developed world and this has contributed significantly to treatment planning. Patients that exhibit MSI have been found to possess better overall survival than those with chromosomal instability and are less affected by p53 mutations [40], whilst CRC with p53 +, MSI + profiles are usually more aggressive than those with p53-, MSI + profiles. [41] Biomarkers such as telomerase and survivin have been used to assess the long term risk of CRC development [42] whilst morphologic biomarkers in patients include neoplastic colorectal polyposis and the presence of aberrant cryptic foci (AFC); the presence of adenomas with Intraepithelial Neoplasm in the colorectal region can also be used in surveillance as surrogate endpoint biomarkers. [43] Paradoxically, most anti-cancer agents do not have wellestablished single predictors of individualized response, however with the advances in 'omics based approaches it should be possible to provide such molecular predictors. For example, MSI has been documented to be an effective predictor of response to fluoropyrimidine therapy, whilst ERCC1 was found to be beneficial in patients using platinum containing anticancer regimen. [31]

'Omics based techniques relevant to colorectal cancer management

The management of CRC has to date been based on fairly invasive techniques for diagnosis and treatment. In contrast, 'omics based techniques in most instances are non- or minimally invasive, thereby improving patient compliance, eliminating surgical morbidities and ultimately reducing the burden of disease through early diagnosis and effective treatment monitoring. The potential utility of increasingly common-place 'omics based techniques in the diagnosis, surveillance, treatment, and prevention of colorectal cancer is thus discussed below.

assays, gene expression microarrays and, more recently, 'next generation sequencing' based methods have provided the necessary platforms to investigate putative prognostic and predictive genetic markers. These platforms, combined with known clinical outcomes, enable panels of genes to be significantly correlated with prognosis, or the outcome of treatment with various chemotherapeutic agents. However, genetic association studies require large datasets in order to identify putative prognostic and predictive markers with significance worthy of clinical utility. As such, there are to date a limited number of landmark publications that present such multi-gene panel lists associated with prognosis and treatment outcome predic‐

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A study by O'Connell et al [48] involved the combined analyses of four independent studies of colorectal cancer patients. Samples were obtained from 1851 CRC patients in the United States, with stage II or III disease, who participated in the National Surgical Adjuvant Breast and Bowel Project (C-01/C-02 and Cleveland Clinic (CC); C04; C-06) and 1136 candidate genes (761 genes assessed in C-01/C-02; 375 genes in CC/C-06) were evaluated. The aim of the study was to establish a panel of markers that could be associated with the risk of disease recurrence and that could determine the likelihood of patients benefitting from adjuvant 5-fluorouracil/ leucovorin adjuvant therapy. The analyses resulted in the identification of 48 genes signifi‐ cantly associated with the risk of disease recurrence and 66 genes significantly associated with 5-FU/LV benefit (with four genes in common between the two sets). For practical reasons a gene panel of 7 genes predictive of disease recurrence, 6 predicted of 5-FU/LV benefit, and 5 reference genes were selected. The clinical utility of this predictive panel was then independ‐ ently evaluated in the Quick and Simple and Reliable (QUASAR) study. [49] The aforemen‐ tioned study validated the use of this gene panel, and it's consequent recurrence score, as an independent predictor of the risk of recurrent disease in stage II colon cancer patients who had undergone surgery. This gene panel was then commercialized by Genomic Health by the

production of a multi-gene panel called the Oncotype DX® Colon Cancer Assay.

for the utility of molecular approaches over purely clinical markers.

In separate work, Salazar et al [50] described a gene expression signature - named ColoPrint in early 2011 that allowed for improved prediction of prognosis in TNM stage II and III colorectal cancer. The gene signature consists of 18 genes that were identified from analysis of 188 frozen tumour samples (TNM stage I-IV; 78.7% not treated with adjuvant chemotherapy), and a cross-validated on 206 independent tumour samples (TNM stage I-III; 60.7% not treated with adjuvant chemotherapy) originating from three sites in the Netherlands. This panel showed better predictive accuracy, in comparison to the American Society of Clinical Oncology criteria for assessing the risk of cancer recurrence without prescreening for microsatellite instability (MSI), with a hazard ratio of 2.69 (95% CI, 1.41 to 5.13; P = 0.003) for patients with stage II disease. Results such as these are encouraging, and provide strong supporting evidence

In a related study, a panel of 13 genes - referred to as ColoGuideEx - was reported by Ågesen *et al* [51] to be significantly associated with predicting prognosis for stage II colorectal cancer patients. This study was conducted on an initial dataset obtained from 207 colorectal samples originating from three independent Norwegian patient series, and validated on a 108-sample gene expression dataset originating from the USA and Australia. The independent prognostic

tion in TNM stage II and III colon and rectal cancers.

#### **2.5. Genomics and epigenomics**

*Introduction:* In genomic investigations, high-throughput technologies such as microarray platforms or DNA/ RNA sequencing are now commonplace. These technologies are now routinely applied to large sample collections, with complete clinical annotations, and aim to produce profound insights into disease at the resolution of single nucleotide polymorphisms, gene expression, and the status of epigenetic regulatory mechanisms such as hypo- and hypermethylation.

Extensive bioinformatic analysis of these high-throughput, multi-level, datasets has provided in-depth insights into the mechanisms of disease and treatment resistance. These findings have been translated into biomedical research aimed at addressing the significant challenge in treating cancer of the colorectum. While it is well established that cure rate for treating TNM stage I colorectal cancer is over 90%, the clinical management of stage II CRC is more compli‐ cated. [44, 45] Furthermore, improved chemo- or biological treatment regimens are needed to address the high rates of recurrent disease observed with stage II and III CRC disease, as well as for TNM stage IV disease which is generally considered incurable at present. [46, 47]

The overall disease-free survival statistics for TNM stage II disease, treated with surgery alone, are as high as 75%. [44] However, certain sub-populations of patients experience a worse prognosis and have clinical outcomes more similar to TNM stage III disease. Therefore, much focus has been on finding genetic markers to guide treatment regimen selection in stage II and III disease, the goal being to improve overall efficacy, decrease treatment failures, reduce the incidence of recurrent disease, whilst at the same time lowering the cost of treatment by limiting costly chemotherapeutics to those patients with predicted benefit.

High-throughput genomic studies today provide a comprehensive means to analyse amongst others the expression level of every individual gene, as well as to assess chromosomal segment copy number- and DNA methylation pattern variations and to determine single nucleotide polymorphism and mutation frequencies, all in a genome-wide manner. Biomarker research can thereafter be carried out to identify and validate distinct signatures derived from inte‐ grated value measurements associated with each gene, as a prelude to translating such findings into a clinical setting, as either biomarkers or novel therapeutic targets.

## **3. Transcriptomics**

The field of transcriptomic research, within the context of prognosis and treatment outcome prediction, has seen much attention in recent years. High-volume real-time gene expression assays, gene expression microarrays and, more recently, 'next generation sequencing' based methods have provided the necessary platforms to investigate putative prognostic and predictive genetic markers. These platforms, combined with known clinical outcomes, enable panels of genes to be significantly correlated with prognosis, or the outcome of treatment with various chemotherapeutic agents. However, genetic association studies require large datasets in order to identify putative prognostic and predictive markers with significance worthy of clinical utility. As such, there are to date a limited number of landmark publications that present such multi-gene panel lists associated with prognosis and treatment outcome predic‐ tion in TNM stage II and III colon and rectal cancers.

The management of CRC has to date been based on fairly invasive techniques for diagnosis and treatment. In contrast, 'omics based techniques in most instances are non- or minimally invasive, thereby improving patient compliance, eliminating surgical morbidities and ultimately reducing the burden of disease through early diagnosis and effective treatment monitoring. The potential utility of increasingly common-place 'omics based techniques in the diagnosis, surveillance, treatment, and prevention of colorectal cancer is thus discussed below.

*Introduction:* In genomic investigations, high-throughput technologies such as microarray platforms or DNA/ RNA sequencing are now commonplace. These technologies are now routinely applied to large sample collections, with complete clinical annotations, and aim to produce profound insights into disease at the resolution of single nucleotide polymorphisms, gene expression, and the status of epigenetic regulatory mechanisms such as hypo- and

Extensive bioinformatic analysis of these high-throughput, multi-level, datasets has provided in-depth insights into the mechanisms of disease and treatment resistance. These findings have been translated into biomedical research aimed at addressing the significant challenge in treating cancer of the colorectum. While it is well established that cure rate for treating TNM stage I colorectal cancer is over 90%, the clinical management of stage II CRC is more compli‐ cated. [44, 45] Furthermore, improved chemo- or biological treatment regimens are needed to address the high rates of recurrent disease observed with stage II and III CRC disease, as well as for TNM stage IV disease which is generally considered incurable at present. [46, 47]

The overall disease-free survival statistics for TNM stage II disease, treated with surgery alone, are as high as 75%. [44] However, certain sub-populations of patients experience a worse prognosis and have clinical outcomes more similar to TNM stage III disease. Therefore, much focus has been on finding genetic markers to guide treatment regimen selection in stage II and III disease, the goal being to improve overall efficacy, decrease treatment failures, reduce the incidence of recurrent disease, whilst at the same time lowering the cost of treatment by

High-throughput genomic studies today provide a comprehensive means to analyse amongst others the expression level of every individual gene, as well as to assess chromosomal segment copy number- and DNA methylation pattern variations and to determine single nucleotide polymorphism and mutation frequencies, all in a genome-wide manner. Biomarker research can thereafter be carried out to identify and validate distinct signatures derived from inte‐ grated value measurements associated with each gene, as a prelude to translating such findings

The field of transcriptomic research, within the context of prognosis and treatment outcome prediction, has seen much attention in recent years. High-volume real-time gene expression

limiting costly chemotherapeutics to those patients with predicted benefit.

into a clinical setting, as either biomarkers or novel therapeutic targets.

**2.5. Genomics and epigenomics**

372 Colorectal Cancer - Surgery, Diagnostics and Treatment

hypermethylation.

**3. Transcriptomics**

A study by O'Connell et al [48] involved the combined analyses of four independent studies of colorectal cancer patients. Samples were obtained from 1851 CRC patients in the United States, with stage II or III disease, who participated in the National Surgical Adjuvant Breast and Bowel Project (C-01/C-02 and Cleveland Clinic (CC); C04; C-06) and 1136 candidate genes (761 genes assessed in C-01/C-02; 375 genes in CC/C-06) were evaluated. The aim of the study was to establish a panel of markers that could be associated with the risk of disease recurrence and that could determine the likelihood of patients benefitting from adjuvant 5-fluorouracil/ leucovorin adjuvant therapy. The analyses resulted in the identification of 48 genes signifi‐ cantly associated with the risk of disease recurrence and 66 genes significantly associated with 5-FU/LV benefit (with four genes in common between the two sets). For practical reasons a gene panel of 7 genes predictive of disease recurrence, 6 predicted of 5-FU/LV benefit, and 5 reference genes were selected. The clinical utility of this predictive panel was then independ‐ ently evaluated in the Quick and Simple and Reliable (QUASAR) study. [49] The aforemen‐ tioned study validated the use of this gene panel, and it's consequent recurrence score, as an independent predictor of the risk of recurrent disease in stage II colon cancer patients who had undergone surgery. This gene panel was then commercialized by Genomic Health by the production of a multi-gene panel called the Oncotype DX® Colon Cancer Assay.

In separate work, Salazar et al [50] described a gene expression signature - named ColoPrint in early 2011 that allowed for improved prediction of prognosis in TNM stage II and III colorectal cancer. The gene signature consists of 18 genes that were identified from analysis of 188 frozen tumour samples (TNM stage I-IV; 78.7% not treated with adjuvant chemotherapy), and a cross-validated on 206 independent tumour samples (TNM stage I-III; 60.7% not treated with adjuvant chemotherapy) originating from three sites in the Netherlands. This panel showed better predictive accuracy, in comparison to the American Society of Clinical Oncology criteria for assessing the risk of cancer recurrence without prescreening for microsatellite instability (MSI), with a hazard ratio of 2.69 (95% CI, 1.41 to 5.13; P = 0.003) for patients with stage II disease. Results such as these are encouraging, and provide strong supporting evidence for the utility of molecular approaches over purely clinical markers.

In a related study, a panel of 13 genes - referred to as ColoGuideEx - was reported by Ågesen *et al* [51] to be significantly associated with predicting prognosis for stage II colorectal cancer patients. This study was conducted on an initial dataset obtained from 207 colorectal samples originating from three independent Norwegian patient series, and validated on a 108-sample gene expression dataset originating from the USA and Australia. The independent prognostic value of the panel of genes was confirmed by multivariate Cox regression analyses (p≤0.004), which included various clinicopathological variables and all three-sample series.

INHBA [TGF-ß family] O'Connell et al (2010); (2) *Axon guidance* (n=3 genes; EPHA7 from Ågesen et al (2012), EFNB2 from O'Connell et al (2010), and SEMA3A from Ågesen et al (2012); (3) *Pathways in Cancer* (n=3 genes; LAMA3 from Salazar et al (2011), AXIN2 from O'Connell et al (2010), RUNX1 from O'Connell et al (2010)); (4) *p53 signaling pathway – target genes* (n=2 genes; SESN1 from Ågesen et al (2012), and GADD45B from O'Connell et al (2010)). These KEGG pathway association mappings were adapted from outputs generated by GeneCodis. [52-54] In a novel study that utilised eight published prognostic and predictive gene expression signatures, Shi et al [55] combined the datasets and integrated them with publically available protein-protein interaction network data in order to identify candidate molecular markers associated directly with the recurrent colorectal cancer phenotype. As a result, they were able to not only infer pathophysiological mechanisms underpinning the recurrent disease pheno‐ type, but also used the augmented and cross-study integrated signature to identify both a prognostic signature and a multi-gene signature to predict treatment outcome. The resultant gene signature consists of 487 genes and is referred to as the NEM signature (as it integrates

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375

It is clear therefore that gene expression panels are developing to the point where they are close to translation into a clinical setting and adoption into routine clinical practice. It remains to be seen though how many of the published gene panels will make it into the clinic after appropriate validation studies have been carried out to assess performance across larger and more ethnically diverse patient populations. In this context, it is important to note that such signatures might yet be inherently compromised by the likely existence of multiple, possibly opposing, signatures in the same tissue sample (*vide supra*). Therefore, testing of multiple biopsies from the same tumour may be necessary in order to generate a holistic prognosis and to provide guidance on treatment strategy. Furthermore, in developing nations where the incidence of colorectal cancer is not yet decreasing and cases consistently present at more advanced stages of disease, it remains to be seen whether the cost of such diagnostic or prognostic panels will be affordable in the public sector where there is the most need and where

*Single nucleotide polymorphisms:* Colorectal cancer has classically been treated by 5-fluorouracil (Capecitabine; Xeloda®; Hoffmann-La Roche Inc.), combined with either Oxaliplatin (Eloxa‐ tin®; Sanofi-Synthélabo Inc.) or Irinotecan (Camptosar® or CPT-11; Pfizer Pharmaceuticals Inc.). Over the past decade these regimens have been augmented by the addition of biological therapeutic agents, such as the monoclonal antibodies Cetuximab (Erbitux®; ImClone Systems Inc.), Panitumumab (Vectibix®; Amgen Inc.), and Bevacizumab (Avastin®; Genentech Inc). Each drug has a different mechanism of action and a unique set of molecular targets, as well as distinct sets of enzymes responsible for its metabolism; furthermore, particularly in the case of biological agents, specific enzymes that are functionally important to the pathways targeted by the biologic are major determinants of response. It is well-established that polymorphic variations in enzymes involved in drug metabolism can alter drug availability, thereby causing a variation in clinical response, by altering the rate and specificity of drug metabolism. Such variant drug metabolizing enzymes are generally encoded by single nucleotide polymor‐ phisms (SNPs) that result in changes in the amino acid composition of the relevant gene

information from Network, Expression, and Mutation datasets).

the greatest diversity exists.


**Table 1.** A list of multi-gene panels that are significantly associated with disease recurrence, or benefit from adjuvant 5-fluorouracil (5-FU) and leucovorin (LV) chemotherapy, as published in three independent studies.

Table 1 illustrates the various gene panels from the four studies described above and it is noteworthy that there are no genes in common between these gene panels. Furthermore, the biological relevance the genes utilised in each panel has yet to be fully explained and may represent an opportunity to identify pathologically associated genes and pathways when molecular enrichment analyses are applied across multiple gene panel studies in the context of prognostic and predictive biomarkers used in recurrent colorectal cancer. For example, there are genes across the lists in Table 1 that share a relationship by virtue of their KEGG pathway associations: (1) *Cytokine-cytokine receptor interaction* (n=6 genes; CXCL10 and CXCL13 [Che‐ mokines; CXC subfamily] from Ågesen et al (2012), LIF [gpl30 shared] from Salazar et al (2011), IL2RA and IL2RB [IL2RG shared] from the Hematopoietins from Salazar et al (2011), and INHBA [TGF-ß family] O'Connell et al (2010); (2) *Axon guidance* (n=3 genes; EPHA7 from Ågesen et al (2012), EFNB2 from O'Connell et al (2010), and SEMA3A from Ågesen et al (2012); (3) *Pathways in Cancer* (n=3 genes; LAMA3 from Salazar et al (2011), AXIN2 from O'Connell et al (2010), RUNX1 from O'Connell et al (2010)); (4) *p53 signaling pathway – target genes* (n=2 genes; SESN1 from Ågesen et al (2012), and GADD45B from O'Connell et al (2010)). These KEGG pathway association mappings were adapted from outputs generated by GeneCodis. [52-54]

value of the panel of genes was confirmed by multivariate Cox regression analyses (p≤0.004),

**5FU benefit Disease recurrence Disease recurrence Disease recurrence** ATP5E ATP5E CA4388O2 AZGP1 AXIN2 BGN CTSC BNIP3 BIK C-MYC CYFIP2 CXCL10 EFNB2 FAP EDEM1 CXCL13 GPX1 GADD45B HSD3B1 DSC3 HSPE1 GPX1 IL2RA ENPP3 MAD2L1 INHBA IL2RB EPHA7 PGK1 Ki-67 LAMA3 KLK6 RUNX1 MYBL2 LIF MMP3 UBB PGK1 MCTP1 PIGR VDAC2 UBB PIM3 SEMA3A

**Salazar et al (2011) ColoPrint®**

VDAC2 PLIN3 SESN1

PYROX D1 SLC6A11 THNSL2 ZBED4 ZNF697

**Table 1.** A list of multi-gene panels that are significantly associated with disease recurrence, or benefit from adjuvant

Table 1 illustrates the various gene panels from the four studies described above and it is noteworthy that there are no genes in common between these gene panels. Furthermore, the biological relevance the genes utilised in each panel has yet to be fully explained and may represent an opportunity to identify pathologically associated genes and pathways when molecular enrichment analyses are applied across multiple gene panel studies in the context of prognostic and predictive biomarkers used in recurrent colorectal cancer. For example, there are genes across the lists in Table 1 that share a relationship by virtue of their KEGG pathway associations: (1) *Cytokine-cytokine receptor interaction* (n=6 genes; CXCL10 and CXCL13 [Che‐ mokines; CXC subfamily] from Ågesen et al (2012), LIF [gpl30 shared] from Salazar et al (2011), IL2RA and IL2RB [IL2RG shared] from the Hematopoietins from Salazar et al (2011), and

5-fluorouracil (5-FU) and leucovorin (LV) chemotherapy, as published in three independent studies.

PPARA TUBA1B

**Ågesen et al (2012) ColoGuideEx**

which included various clinicopathological variables and all three-sample series.

**Oncotype DX® Colon Assay**

**O'Connell et al (2010) O'Connell et al (2010)**

374 Colorectal Cancer - Surgery, Diagnostics and Treatment

In a novel study that utilised eight published prognostic and predictive gene expression signatures, Shi et al [55] combined the datasets and integrated them with publically available protein-protein interaction network data in order to identify candidate molecular markers associated directly with the recurrent colorectal cancer phenotype. As a result, they were able to not only infer pathophysiological mechanisms underpinning the recurrent disease pheno‐ type, but also used the augmented and cross-study integrated signature to identify both a prognostic signature and a multi-gene signature to predict treatment outcome. The resultant gene signature consists of 487 genes and is referred to as the NEM signature (as it integrates information from Network, Expression, and Mutation datasets).

It is clear therefore that gene expression panels are developing to the point where they are close to translation into a clinical setting and adoption into routine clinical practice. It remains to be seen though how many of the published gene panels will make it into the clinic after appropriate validation studies have been carried out to assess performance across larger and more ethnically diverse patient populations. In this context, it is important to note that such signatures might yet be inherently compromised by the likely existence of multiple, possibly opposing, signatures in the same tissue sample (*vide supra*). Therefore, testing of multiple biopsies from the same tumour may be necessary in order to generate a holistic prognosis and to provide guidance on treatment strategy. Furthermore, in developing nations where the incidence of colorectal cancer is not yet decreasing and cases consistently present at more advanced stages of disease, it remains to be seen whether the cost of such diagnostic or prognostic panels will be affordable in the public sector where there is the most need and where the greatest diversity exists.

*Single nucleotide polymorphisms:* Colorectal cancer has classically been treated by 5-fluorouracil (Capecitabine; Xeloda®; Hoffmann-La Roche Inc.), combined with either Oxaliplatin (Eloxa‐ tin®; Sanofi-Synthélabo Inc.) or Irinotecan (Camptosar® or CPT-11; Pfizer Pharmaceuticals Inc.). Over the past decade these regimens have been augmented by the addition of biological therapeutic agents, such as the monoclonal antibodies Cetuximab (Erbitux®; ImClone Systems Inc.), Panitumumab (Vectibix®; Amgen Inc.), and Bevacizumab (Avastin®; Genentech Inc).

Each drug has a different mechanism of action and a unique set of molecular targets, as well as distinct sets of enzymes responsible for its metabolism; furthermore, particularly in the case of biological agents, specific enzymes that are functionally important to the pathways targeted by the biologic are major determinants of response. It is well-established that polymorphic variations in enzymes involved in drug metabolism can alter drug availability, thereby causing a variation in clinical response, by altering the rate and specificity of drug metabolism. Such variant drug metabolizing enzymes are generally encoded by single nucleotide polymor‐ phisms (SNPs) that result in changes in the amino acid composition of the relevant gene product (i.e. protein), resulting in altered enzymatic activity. As such, the biomedical com‐ munity has utilised an arsenal of molecular techniques, including high-throughput genomic platforms, to identify such SNPs and to quantify their frequency in populations in order to correlate with treatment outcomes and thereby to identify biomarkers that are predictive of therapeutic response.

This compound has been extensively utilised in combination with 5-FU and Leucovorin, a regimen referred to as FOLFOX and commonly prescribed for treatment of advanced colorectal

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

There are two groups of genes that are primarily responsible for altered response to Oxalipla‐ tin, namely genes involved in DNA repair and in glutathione conjugation reactions. In the former group, a polymorphism in the X-ray repair cross-complementing group 1 enzyme (XRCC1) - which is part of the base excision repair system - has been associated with variable initiation of DNA repair. [57] In addition, a polymorphism in a component of the ubiquitous nucleotide excision repair pathway - the excision repair cross complementing group 2 (ERCC2) gene - has been significantly associated with a clinical response to platinum-based chemo‐ therapy. [57] However, there are no known polymorphisms in the DNA mismatch repair pathway associated with variation in treatment response with Oxaliplatin. In the second group, it has been reported that platinum compounds are inactivated by glutathione conju‐ gation and therefore the enzymes responsible for catalyzing this reaction have been investi‐ gated. In particular, SNPs in several glutathione-S-transferase (GST) genes have been

> **Associated treatment outcome**

GSTP1 613G Decreased activity Increased response Bandrés et al (2007) GSTT1 Deletion Decreased activity Increased response Bandrés et al (2007) GSTM1 Deletion Decreased activity Increased response Bandrés et al (2007) XRCC1 388Gln Decreased activity Increased response Bandrés et al (2007) ERCC2 751Gln Decreased activity Increased response Bandrés et al (2007)

**Table 3.** A list of single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported by

It is noteworthy that in a recent study by Fernandez-Rozadilla et al [63], seven SNPs (rs16857540, rs2465403, rs10876844, rs10784749, rs17626122, rs7325568, rs4243761) were found to be significantly associated with adverse drug reactions in the context of singular 5-FU or FOLFOX treatment. Given the relatively large sample size of 221 CRC patients and a validation set of 791 patients, these results hold strong statistical significance and provide potential predictive capacity for toxicity response on an individual patient basis if validated through a

*Irinotecan (CPT-11):* Irinotecan is a camptothecin analogue with well-established anti-neoplasia activity exerted though stabilization of the ordinarily transient DNA topoisomerase I-DNA complex, thus preventing the repair of temporary single stranded breaks during DNA replication and leading to cell death. [64] There are two primary pathways that have been implicated in variable response to Irinotecan treatment: drug transport into the extracellular

Bandrés et al (2007), when using a chemotherapeutic regimen that includes Oxaliplatin.

**Reference**

http://dx.doi.org/10.5772/57485

377

implicated in conferring resistance to Oxaliplatin. [57]

**Gene SNP Molecular effect**

larger cohort.

cancer.

This area of research has been comprehensively reviewed recently by Asghar et al [56], Bandrés et al [57], Benheim et al [58], Coate et al [59], De Roock et al [60], and Ross et al [61] and forms the basis of the rich pharmacogenetic resource, PharmGKB® (http://www.pharmgkb.org) which documents each therapeutic agent together with an aggregated list of SNPs reported in the literature to be associated with treatment outcome.

## **4. Pharmacogenomics**

#### **4.1. Markers of treatment outcomes when treated with classical chemotherapeutics**

*5-Fluorouracil:* 5-Fluorouracil (5-FU) was introduced more than 50 years ago by Heidelberger et al [62] and is the foundational cytotoxic agent used in the treatment of colorectal neoplasia. 5-FU can be administered in three different physical forms: either through an intravenous solution, or as an oral compound (Capecitabine, and Tegafur). The metabolism of either of these compounds results in the formation of fluoronucleotides. A subset of these molecules, fluorouridine triphosphate (FUTP) and fluorodeoxyuridine monophosphate (FdUMP) are misincorporation into DNA and RNA during their *in vivo* biosynthesis. In addition, FdUMP inhibits thymidylate, synthase thereby resulting in a nucleotide imbalance due to a depleted intracellular reserve of thymidine for DNA synthesis. The enzymes responsible for producing the active metabolites have been studied for polymorphic variation and analysed for their correlation to treatment response (as seen in Table 2).


**Table 2.** A list of single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported by Bandrés et al (2007), when using a 5-fluorouracil-based regimen.

Oxaliplatin: Oxaliplatin is a platinum analog that results in inter- and intra-molecular DNA cross-links, resulting in the inhibition of DNA synthesis, transcription and repair processes. This compound has been extensively utilised in combination with 5-FU and Leucovorin, a regimen referred to as FOLFOX and commonly prescribed for treatment of advanced colorectal cancer.

product (i.e. protein), resulting in altered enzymatic activity. As such, the biomedical com‐ munity has utilised an arsenal of molecular techniques, including high-throughput genomic platforms, to identify such SNPs and to quantify their frequency in populations in order to correlate with treatment outcomes and thereby to identify biomarkers that are predictive of

This area of research has been comprehensively reviewed recently by Asghar et al [56], Bandrés et al [57], Benheim et al [58], Coate et al [59], De Roock et al [60], and Ross et al [61] and forms the basis of the rich pharmacogenetic resource, PharmGKB® (http://www.pharmgkb.org) which documents each therapeutic agent together with an aggregated list of SNPs reported in

**4.1. Markers of treatment outcomes when treated with classical chemotherapeutics**

*5-Fluorouracil:* 5-Fluorouracil (5-FU) was introduced more than 50 years ago by Heidelberger et al [62] and is the foundational cytotoxic agent used in the treatment of colorectal neoplasia. 5-FU can be administered in three different physical forms: either through an intravenous solution, or as an oral compound (Capecitabine, and Tegafur). The metabolism of either of these compounds results in the formation of fluoronucleotides. A subset of these molecules, fluorouridine triphosphate (FUTP) and fluorodeoxyuridine monophosphate (FdUMP) are misincorporation into DNA and RNA during their *in vivo* biosynthesis. In addition, FdUMP inhibits thymidylate, synthase thereby resulting in a nucleotide imbalance due to a depleted intracellular reserve of thymidine for DNA synthesis. The enzymes responsible for producing the active metabolites have been studied for polymorphic variation and analysed for their

TP Increased expression Increased response Bandrés et al (2007) TS TSER2R Decreased expression Increased response Bandrés et al (2007)

**Table 2.** A list of single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported by

Oxaliplatin: Oxaliplatin is a platinum analog that results in inter- and intra-molecular DNA cross-links, resulting in the inhibition of DNA synthesis, transcription and repair processes.

**Associated treatment outcome**

**Reference**

Increased toxicity Bandrés et al (2007)

Increased response Bandrés et al (2007)

therapeutic response.

376 Colorectal Cancer - Surgery, Diagnostics and Treatment

**4. Pharmacogenomics**

the literature to be associated with treatment outcome.

correlation to treatment response (as seen in Table 2).

DPD DYPD\*2A Decreased activity Increased response

CH2FH4

**Gene SNP Molecular effect**

MTHFR 677T Increased production of

Bandrés et al (2007), when using a 5-fluorouracil-based regimen.

There are two groups of genes that are primarily responsible for altered response to Oxalipla‐ tin, namely genes involved in DNA repair and in glutathione conjugation reactions. In the former group, a polymorphism in the X-ray repair cross-complementing group 1 enzyme (XRCC1) - which is part of the base excision repair system - has been associated with variable initiation of DNA repair. [57] In addition, a polymorphism in a component of the ubiquitous nucleotide excision repair pathway - the excision repair cross complementing group 2 (ERCC2) gene - has been significantly associated with a clinical response to platinum-based chemo‐ therapy. [57] However, there are no known polymorphisms in the DNA mismatch repair pathway associated with variation in treatment response with Oxaliplatin. In the second group, it has been reported that platinum compounds are inactivated by glutathione conju‐ gation and therefore the enzymes responsible for catalyzing this reaction have been investi‐ gated. In particular, SNPs in several glutathione-S-transferase (GST) genes have been implicated in conferring resistance to Oxaliplatin. [57]


**Table 3.** A list of single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported by Bandrés et al (2007), when using a chemotherapeutic regimen that includes Oxaliplatin.

It is noteworthy that in a recent study by Fernandez-Rozadilla et al [63], seven SNPs (rs16857540, rs2465403, rs10876844, rs10784749, rs17626122, rs7325568, rs4243761) were found to be significantly associated with adverse drug reactions in the context of singular 5-FU or FOLFOX treatment. Given the relatively large sample size of 221 CRC patients and a validation set of 791 patients, these results hold strong statistical significance and provide potential predictive capacity for toxicity response on an individual patient basis if validated through a larger cohort.

*Irinotecan (CPT-11):* Irinotecan is a camptothecin analogue with well-established anti-neoplasia activity exerted though stabilization of the ordinarily transient DNA topoisomerase I-DNA complex, thus preventing the repair of temporary single stranded breaks during DNA replication and leading to cell death. [64] There are two primary pathways that have been implicated in variable response to Irinotecan treatment: drug transport into the extracellular environment, and metabolism of Irinotecan into its active (SN-38 and SN-38G) and inactive metabolites.

and aggressiveness in most malignancies [67]; mAbs have thus been designed to target VEGF, thereby reducing the amount of free VEGF, reducing VEGF receptor activation, and ultimately reducing angiogenesis. [68] A recombinant humanized IgG1 monoclonal antibody, Bevacizu‐ mab, that specifically targets VEGF is currently indicated as part of combination therapy in metastatic colorectal cancer; however, a biomarker that is predictive of response to anti-VEGF

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379

*Epidermal growth factor receptor as a target:* Another fundamental hallmark of the cancer phenotype is the ability for tumours to alter their response to growth factors through differ‐ ential gene expression of growth factor receptors. This too presents the opportunity interrupt aberrant growth mechanisms. In colorectal cancer, it has been shown that there is an abnormal activation of epidermal growth factor receptor (EGFR). [69] As such, a humanized monoclonal antibody, Cetuximab, targeted at the extracellular domain of EGFR has been evaluated in clinical trials. This mAb blocks specific EGF-mediated signal transduction events [70], thereby inhibiting cellular proliferation and inducing apoptosis. [71] Treatment with Cetuximab also leads to increased responses to classic chemotherapeutic agents and radiotherapy, as well as inhibiting cellular proliferation, angiogenesis and metastasis. [72] Another recombinant human IgG2 monoclonal antibody, Panitumumab, which also targets EGFR is currently indicated in metastatic colorectal carcinoma where there has been resistance to fluoropyrimi‐

To date there have been a small but useful number of genes harboring mutations that provide insight into the outcome of anti-EGFR therapy. For example, the mutational status of the Kirsten-ras (KRAS) gene is currently being used in predicting treatment benefit in the context of anti-EGFR therapy for patients with metastatic disease. Other common genes with muta‐ tions relevant to anti-EGFR mAb therapy include BRAF and PIK3CA, as well as loss of

*Conclusion:* It is clear that SNP biomarkers associated with treatment outcome are generally found in genes with specific characteristics of cancer pathophysiology, or with drug metabo‐ lism and transport, and numerous low-throughput, focused, yet fruitful studies have resulted in clinically translatable SNP biomarkers being identified. This contrasts with the highthroughput transcriptomic approach to identification of biomarker gene panels that is typically initially blind to the functional significance of each individual gene. As such, these simple SNP markers present a cost-effective option to predicting the efficacy of a specific therapeutic agent, or combination thereof, prior to prescription, enabling design of individualized therapy that

Molecular studies of cancer have revealed the presence of not only of genetic mutations, copy number alterations, altered gene expression, but also of aberrant epigenetic changes. Intense investigation in recent years has shown that epigenetic regulation of gene expression plays a crucial role in embryonic development, imprinting, and tissue differentiation. [73] Therefore,

therapy is yet to be discovered.

expression of PTEN.

dine, Oxaliplatin, and Irinotecan containing regimens.

will result in increased efficacy and improved treatment outcomes.

**5. Epigenomics and epigenetics**

Hydrolysis of Irinotecan by carboxylesterases: CES1 and CES2 results in the production of its active metabolite, SN-38. This metabolite then undergoes detoxification via the process of glucuronidation, catalyzed by uridine diphosphate-glucurono-syltransferase 1A (UGT1A), to produce a metabolite called SN-38G which then interacts directly with the DNA topoisomerase I enzyme. However, Irinotecan can also be oxidized by members of the Cytochrome P450 3A subfamily (CYP3A) to produce inactivate metabolites. Each of these metabolites is transported out of the cell by the adenosine-triphosphate (ATP) binding cassette (ABC) transporter transmembrane proteins. As such, polymorphic variation in these enzymes has been associ‐ ated with altered metabolism, transport and therapeutic efficacy of this drug and its metabo‐ lites. A selection of these SNPs is detailed in the Table 4.


**Table 4.** A list of the single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported by Bandrés et al (2007), when using a chemotherapeutic regimen that includes Irinotecan (CPT-11).

*Markers of treatment outcomes when treated with biological agents*: In recent years there has been an emergence of a new class of antibody-based therapeutics that directly and specifically target molecules belonging to processes fundamental to cancer pathophysiology. Comprehensive reviews of the hallmarks of the cancer phenotype have been updated recently by Hanahan and Weinberg [65, 66]; in addition, comprehensive reviews of biomarkers associated with mono‐ clonal antibody therapies that are currently in being used in the treatment of this disease have also been published recently. [56, 60]

*Vascular endothelial growth factor as a target:* It is well understood that tumours have angiogenic potential, i.e. they possess the ability to induce the production of new blood vessels, and thereby increase their supply of oxygen and nutrients; this characteristic provides an oppor‐ tunity for therapeutic intervention, targeting the vascular endothelial growth factor (VEGF) and associated VEGF receptors (VEGFR-1, -2, and -3). In particular, overexpression of VEGF has been associated with vascularity, endothelial cell migration and invasion, poor prognosis and aggressiveness in most malignancies [67]; mAbs have thus been designed to target VEGF, thereby reducing the amount of free VEGF, reducing VEGF receptor activation, and ultimately reducing angiogenesis. [68] A recombinant humanized IgG1 monoclonal antibody, Bevacizu‐ mab, that specifically targets VEGF is currently indicated as part of combination therapy in metastatic colorectal cancer; however, a biomarker that is predictive of response to anti-VEGF therapy is yet to be discovered.

*Epidermal growth factor receptor as a target:* Another fundamental hallmark of the cancer phenotype is the ability for tumours to alter their response to growth factors through differ‐ ential gene expression of growth factor receptors. This too presents the opportunity interrupt aberrant growth mechanisms. In colorectal cancer, it has been shown that there is an abnormal activation of epidermal growth factor receptor (EGFR). [69] As such, a humanized monoclonal antibody, Cetuximab, targeted at the extracellular domain of EGFR has been evaluated in clinical trials. This mAb blocks specific EGF-mediated signal transduction events [70], thereby inhibiting cellular proliferation and inducing apoptosis. [71] Treatment with Cetuximab also leads to increased responses to classic chemotherapeutic agents and radiotherapy, as well as inhibiting cellular proliferation, angiogenesis and metastasis. [72] Another recombinant human IgG2 monoclonal antibody, Panitumumab, which also targets EGFR is currently indicated in metastatic colorectal carcinoma where there has been resistance to fluoropyrimi‐ dine, Oxaliplatin, and Irinotecan containing regimens.

To date there have been a small but useful number of genes harboring mutations that provide insight into the outcome of anti-EGFR therapy. For example, the mutational status of the Kirsten-ras (KRAS) gene is currently being used in predicting treatment benefit in the context of anti-EGFR therapy for patients with metastatic disease. Other common genes with muta‐ tions relevant to anti-EGFR mAb therapy include BRAF and PIK3CA, as well as loss of expression of PTEN.

*Conclusion:* It is clear that SNP biomarkers associated with treatment outcome are generally found in genes with specific characteristics of cancer pathophysiology, or with drug metabo‐ lism and transport, and numerous low-throughput, focused, yet fruitful studies have resulted in clinically translatable SNP biomarkers being identified. This contrasts with the highthroughput transcriptomic approach to identification of biomarker gene panels that is typically initially blind to the functional significance of each individual gene. As such, these simple SNP markers present a cost-effective option to predicting the efficacy of a specific therapeutic agent, or combination thereof, prior to prescription, enabling design of individualized therapy that will result in increased efficacy and improved treatment outcomes.

## **5. Epigenomics and epigenetics**

environment, and metabolism of Irinotecan into its active (SN-38 and SN-38G) and inactive

Hydrolysis of Irinotecan by carboxylesterases: CES1 and CES2 results in the production of its active metabolite, SN-38. This metabolite then undergoes detoxification via the process of glucuronidation, catalyzed by uridine diphosphate-glucurono-syltransferase 1A (UGT1A), to produce a metabolite called SN-38G which then interacts directly with the DNA topoisomerase I enzyme. However, Irinotecan can also be oxidized by members of the Cytochrome P450 3A subfamily (CYP3A) to produce inactivate metabolites. Each of these metabolites is transported out of the cell by the adenosine-triphosphate (ATP) binding cassette (ABC) transporter transmembrane proteins. As such, polymorphic variation in these enzymes has been associ‐ ated with altered metabolism, transport and therapeutic efficacy of this drug and its metabo‐

CES2 IVS10-88 Decreased expression Decreased response Bandrés et al (2007) CYP3A ? Decreased activity Decreased response Bandrés et al (2007)

ABCC2 3792T Increased response Bandrés et al (2007) ABCG2 421A Decreased activity Increased response Bandrés et al (2007)

**Table 4.** A list of the single nucleotide polymorphism (SNP) markers associated with treatment outcome, as reported

*Markers of treatment outcomes when treated with biological agents*: In recent years there has been an emergence of a new class of antibody-based therapeutics that directly and specifically target molecules belonging to processes fundamental to cancer pathophysiology. Comprehensive reviews of the hallmarks of the cancer phenotype have been updated recently by Hanahan and Weinberg [65, 66]; in addition, comprehensive reviews of biomarkers associated with mono‐ clonal antibody therapies that are currently in being used in the treatment of this disease have

*Vascular endothelial growth factor as a target:* It is well understood that tumours have angiogenic potential, i.e. they possess the ability to induce the production of new blood vessels, and thereby increase their supply of oxygen and nutrients; this characteristic provides an oppor‐ tunity for therapeutic intervention, targeting the vascular endothelial growth factor (VEGF) and associated VEGF receptors (VEGFR-1, -2, and -3). In particular, overexpression of VEGF has been associated with vascularity, endothelial cell migration and invasion, poor prognosis

by Bandrés et al (2007), when using a chemotherapeutic regimen that includes Irinotecan (CPT-11).

**Associated treatment outcome**

**Reference**

Increased toxicity Bandrés et al (2007)

Increased toxicity Bandrés et al (2007)

Increased toxicity Bandrés et al (2007)

lites. A selection of these SNPs is detailed in the Table 4.

UGT1A1 UGT1A1\*28 Decreased activity Increased response

ABCB1 1236C"/>T Decreased activity Increased response

ABCB1 3435C"/>T Decreased activity Increased response

**Gene SNP Molecular effect**

378 Colorectal Cancer - Surgery, Diagnostics and Treatment

also been published recently. [56, 60]

metabolites.

Molecular studies of cancer have revealed the presence of not only of genetic mutations, copy number alterations, altered gene expression, but also of aberrant epigenetic changes. Intense investigation in recent years has shown that epigenetic regulation of gene expression plays a crucial role in embryonic development, imprinting, and tissue differentiation. [73] Therefore, deregulation of such a fundamental mechanism might offer insight into the driving molecular mechanisms associated with the development, and regulation, of a carcinoma phenotype, particularly in cases where other genomic perspectives have not yet provided an answer.

EGFR mAb-mediated therapy in patients with KRAS wild-type tumours and metastatic disease. [60, 86, 87] As such, classifying a patient's tumour as having the CIMP phenotype could be used in the future to guide the selection of biological therapeutics to ensure that the

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

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381

The current lack of a standardized panel of genes from which to assess the status of genomic methylation highlights the fact that this is an emerging field of study. As such, the translation of these panels into the clinic as diagnostic or prognostic biomarkers is still premature. However, as the field progresses and more literature-based evidence is published in support and validation of a particular panel, the full potential of such epigenomic biomarkers may

While the field is currently in its infancy, there are a number of encouraging studies that represent good examples of novel discoveries of methylation markers that have highly significant associations. For example, Wang et al [88] examined the methylation status of five tumour suppressor genes in eighty-five paired colorectal tumours and normal mucosa samples from Chinese patients and showed that the methylation status of two genes, CDH13 and FLBN3, were significantly associated with stage of disease and prognosis. In particular, CDH13 was significantly associated with poor differentiation (p=0.019) and had a relatively strong association with advanced stage of disease (p=0.084). In a similar fashion, FLBN3 was signif‐ icantly associated with advanced disease (p=0.027) and with the presence of lymph node metastasis (p=0.029). Furthermore, CDH13 and/or FLBN3 methylation status was found to be predictive of a poor overall survival (p=0.001) and conversely the presence of methylated

In a clinical setting, samples that are obtained in a non- or minimally invasive manner are preferred and there have been a number of studies based on stool and blood plasma samples to assess aberrant methylation patterns. One example is the clinically validated methylation status of the Vimentin gene (*VIM*) - which has been found in the majority of colorectal tumours (53 – 84%; Lao et al 2011) – with assays conducted on stool samples, thus providing a noninvasive mechanism for early detection of colorectal cancer. This assay is currently commer‐ cially available in the United States as the ColoGuard assay (LabCorp), and reports a sensitivity of 83% and a specificity of 82%. [89, 90] Outside of the United States, in Europe and the Middle East there is now an additional non-invasive test for early detection of colorectal cancer by assessing the methylation status of *SEPT9*. This assay is currently commercially available as

The field of epigenomics, and epigenetics, applied to colorectal cancer is providing valuable insights into underlying mechanisms of this disease and seems to be a promising avenue of research. It is clear that assessing the status of DNA methylation alone holds prognostic and predictive value, and as such we would expect this field to gain much momentum towards translating these findings into a routine clinical setting. As this field of study can be conducted on a broad spectrum of sample types, along with commercially available kits to assess methylation, this field is likely to see an increased number of significant findings in the near future. However, as in the case of gene expression-based biomarkers, each epigenetic finding will need to be assessed in patients of diverse ethnicities. A recent study by Nieminen et al [91]

most efficacious treatment regimen is utilised.

ultimately be translated into patient benefit.

hMHL1 indicated a better chance of survival (p=0.046).

Epi *pro*Colon (Epigenomics AG).

In cancer studies, the field of epigenomics has encompassed investigations into aberrant DNA methylation, post-translational modification of histones that affects chromatin structure, altered expression of microRNAs and non-coding RNAs, and nucleosome positioning. [73-75] For complete reviews of this specific topic see Ballestar et al [76], Hatziapostolou et al [77], Khare et al [74], Lao et al [75], Liu et al [78], Sawan et al [79], Sharma et al [73], Ting et al [80], and van Engeland et al [81].

DNA methylation studies have focused particularly on the methylation patterns of cytosine and guanine (CpG)-rich DNA sequences. In particular, regions of the genome that have a higher than expected number of CpG nucleotides compared to the rest of the genome – socalled "CpG islands" – are of particular interest because they have been shown to overlap the promoter regions of 60-70% of genes. [75] An extension of this concept has been the discovery of CpG sites outside of promoter regions, referred to as "CpG Island shores", that are within two kilobases of the 5' end of a CpG island. [75] Methylation of CpG islands is largely associated with transcriptional repression [75, 82] and, in general, CpG islands are protected from aberrant methylation but in cancer this does not appear to be the case. Since methylation changes can significantly alter gene expression profiles and thereby deregulate important biological pathways, a sound understanding of which genes and which associated pathways are affected in which individual patients might in the future be applied in the clinic to guide the selection of appropriate treatment regimens.

The first report of epigenetic alterations in tumours of the colon revealed an extensive loss of 5'-methylcytosine when compared to normal colon tissue. [83] However, it is only recently that this area of research has gained increased attention. Today, high-throughput methylationspecific microarray and sequencing technologies, together with a well-established array of commercially available methylation assay kits, have facilitated large-scale epigenomic investigations and contributed to an increased understanding of the methylome on a multigene scale.

Arguably the most important epigenetic finding to date, in the context of colorectal cancer, has been the identification of a unique molecular subtype characterized by a high frequency of gene methylation. Colorectal tumours of this variety are now referred to as having the CpG island Methylator Phenotype (CIMP). The exact panel for diagnosing CIMP varies from study to study, but the panel of genes proposed by Weisenberger et al [84] has been commonly used, i.e. *NEUROG1, SOCS1, RUNX3, IGF2,* and *CACNA1G.* In general, if a panel has more than 60% of its genes methylated, then is considered to be CIMP positive. Despite, the lack of a stand‐ ardized CIMP diagnostic panel, this type of tumour is reported to be predominantly associated with right-sided colon cancer, and tends to be more common in woman. [84, 85]

Diagnosing CIMP tumours is clinically relevant because approximately 20% of colorectal tumours have this phenotype and generally share a high frequency of the BRAF c.1799T>A (p. V600E) mutation [75] that has been reported to negatively impact treatment outcomes in antiEGFR mAb-mediated therapy in patients with KRAS wild-type tumours and metastatic disease. [60, 86, 87] As such, classifying a patient's tumour as having the CIMP phenotype could be used in the future to guide the selection of biological therapeutics to ensure that the most efficacious treatment regimen is utilised.

deregulation of such a fundamental mechanism might offer insight into the driving molecular mechanisms associated with the development, and regulation, of a carcinoma phenotype, particularly in cases where other genomic perspectives have not yet provided an answer.

In cancer studies, the field of epigenomics has encompassed investigations into aberrant DNA methylation, post-translational modification of histones that affects chromatin structure, altered expression of microRNAs and non-coding RNAs, and nucleosome positioning. [73-75] For complete reviews of this specific topic see Ballestar et al [76], Hatziapostolou et al [77], Khare et al [74], Lao et al [75], Liu et al [78], Sawan et al [79], Sharma et al [73], Ting et al [80],

DNA methylation studies have focused particularly on the methylation patterns of cytosine and guanine (CpG)-rich DNA sequences. In particular, regions of the genome that have a higher than expected number of CpG nucleotides compared to the rest of the genome – socalled "CpG islands" – are of particular interest because they have been shown to overlap the promoter regions of 60-70% of genes. [75] An extension of this concept has been the discovery of CpG sites outside of promoter regions, referred to as "CpG Island shores", that are within two kilobases of the 5' end of a CpG island. [75] Methylation of CpG islands is largely associated with transcriptional repression [75, 82] and, in general, CpG islands are protected from aberrant methylation but in cancer this does not appear to be the case. Since methylation changes can significantly alter gene expression profiles and thereby deregulate important biological pathways, a sound understanding of which genes and which associated pathways are affected in which individual patients might in the future be applied in the clinic to guide

The first report of epigenetic alterations in tumours of the colon revealed an extensive loss of 5'-methylcytosine when compared to normal colon tissue. [83] However, it is only recently that this area of research has gained increased attention. Today, high-throughput methylationspecific microarray and sequencing technologies, together with a well-established array of commercially available methylation assay kits, have facilitated large-scale epigenomic investigations and contributed to an increased understanding of the methylome on a multi-

Arguably the most important epigenetic finding to date, in the context of colorectal cancer, has been the identification of a unique molecular subtype characterized by a high frequency of gene methylation. Colorectal tumours of this variety are now referred to as having the CpG island Methylator Phenotype (CIMP). The exact panel for diagnosing CIMP varies from study to study, but the panel of genes proposed by Weisenberger et al [84] has been commonly used, i.e. *NEUROG1, SOCS1, RUNX3, IGF2,* and *CACNA1G.* In general, if a panel has more than 60% of its genes methylated, then is considered to be CIMP positive. Despite, the lack of a stand‐ ardized CIMP diagnostic panel, this type of tumour is reported to be predominantly associated

Diagnosing CIMP tumours is clinically relevant because approximately 20% of colorectal tumours have this phenotype and generally share a high frequency of the BRAF c.1799T>A (p. V600E) mutation [75] that has been reported to negatively impact treatment outcomes in anti-

with right-sided colon cancer, and tends to be more common in woman. [84, 85]

and van Engeland et al [81].

380 Colorectal Cancer - Surgery, Diagnostics and Treatment

gene scale.

the selection of appropriate treatment regimens.

The current lack of a standardized panel of genes from which to assess the status of genomic methylation highlights the fact that this is an emerging field of study. As such, the translation of these panels into the clinic as diagnostic or prognostic biomarkers is still premature. However, as the field progresses and more literature-based evidence is published in support and validation of a particular panel, the full potential of such epigenomic biomarkers may ultimately be translated into patient benefit.

While the field is currently in its infancy, there are a number of encouraging studies that represent good examples of novel discoveries of methylation markers that have highly significant associations. For example, Wang et al [88] examined the methylation status of five tumour suppressor genes in eighty-five paired colorectal tumours and normal mucosa samples from Chinese patients and showed that the methylation status of two genes, CDH13 and FLBN3, were significantly associated with stage of disease and prognosis. In particular, CDH13 was significantly associated with poor differentiation (p=0.019) and had a relatively strong association with advanced stage of disease (p=0.084). In a similar fashion, FLBN3 was signif‐ icantly associated with advanced disease (p=0.027) and with the presence of lymph node metastasis (p=0.029). Furthermore, CDH13 and/or FLBN3 methylation status was found to be predictive of a poor overall survival (p=0.001) and conversely the presence of methylated hMHL1 indicated a better chance of survival (p=0.046).

In a clinical setting, samples that are obtained in a non- or minimally invasive manner are preferred and there have been a number of studies based on stool and blood plasma samples to assess aberrant methylation patterns. One example is the clinically validated methylation status of the Vimentin gene (*VIM*) - which has been found in the majority of colorectal tumours (53 – 84%; Lao et al 2011) – with assays conducted on stool samples, thus providing a noninvasive mechanism for early detection of colorectal cancer. This assay is currently commer‐ cially available in the United States as the ColoGuard assay (LabCorp), and reports a sensitivity of 83% and a specificity of 82%. [89, 90] Outside of the United States, in Europe and the Middle East there is now an additional non-invasive test for early detection of colorectal cancer by assessing the methylation status of *SEPT9*. This assay is currently commercially available as Epi *pro*Colon (Epigenomics AG).

The field of epigenomics, and epigenetics, applied to colorectal cancer is providing valuable insights into underlying mechanisms of this disease and seems to be a promising avenue of research. It is clear that assessing the status of DNA methylation alone holds prognostic and predictive value, and as such we would expect this field to gain much momentum towards translating these findings into a routine clinical setting. As this field of study can be conducted on a broad spectrum of sample types, along with commercially available kits to assess methylation, this field is likely to see an increased number of significant findings in the near future. However, as in the case of gene expression-based biomarkers, each epigenetic finding will need to be assessed in patients of diverse ethnicities. A recent study by Nieminen et al [91] highlighted this in observing that colorectal carcinomas in an Egyptian cohort had a signifi‐ cantly higher state of methylation, in microsatellite stable tumours, compared with sporadic colorectal cancers in a Finnish cohort.

immunocapture-mass spectrometry - has also yielded candidate biomarkers in CRC, including antibodies against inosine monophosphate dehydrogenase II [101], MUC-5A, MUC-1,

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

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383

Lipidomics is a novel 'omics field which deals with complex large scale analysis of the full complement of various classes of lipids and lipid networks expressed by a cell, tissue or organism (the 'lipidome') and involves the high throughput systems-level identification and quantification of lipid metabolic pathways that may be involved in disease using chromato‐ graphic methods coupled to mass spectrometry. Generally, lipids are hydrophobic molecules that are involved in energy storage, structural components of a cell, cell signaling, endocrine actions, signal transduction, membrane trafficking, and morphogenesis. Structurally, lipids can be classified as: fatty acids; glycerolipids; glycerophospholipids; sphingolipids; sterol lipids; prenol lipids; saccharolipids; and polyketides. These 8 classes of lipids can also be

Whilst there is currently a paucity of clinically validated lipidomics biomarkers for colorectal cancer, the prospects of this field to complement proteomics and genomics in a combined 'systems biology' approach for disease detection, monitoring and treatment is worth consid‐ eration since over the past two decades, numerous publications have described the perturba‐ tion of lipid metabolism and signaling in colorectal carcinogenesis. [107-110] Lipidomics analysis of primary and metastatic colorectal cancer cell lines (SW480 and SW620) identified 600 and 694 lipids respectively in 'shotgun' study [111]; increased level of triglyceride lipid and plasmacholine were observed, while a decrease in the level of C-16 containing sphingo‐ myelin, ceramide lipid and plasmenylethanolamine were observed in the metastatic CRC cell line compared to the primary isogenic CRC cell line, implying that lipidomic biomarkers of

Empirically, polyunsaturated fatty acids have been known to be more beneficial in the prevention of colorectal diseases compared to saturated long-chain types, but the pathways related to this were largely unclear. The emergence of lipidomics techniques however has revealed that metabolic control of long chain fatty acids is an important factor in development of CRC, with short chain fatty acids from the gut microflora/ microbiome being described as

Elevated level of lysophosphatidic acid - a phosphoglyceride - has been described as a prospective cancer biomarker of ovarian tumours [113-115] but, paradoxically, a marked decrease in the serum level of lysophosphatidylcholine has been reported in CRC. [116] Similarly, elevated profiles of phosphatidylcholine and choline kinase activity have been demonstrated it colon cancers [117] and a high ratio of phosphatidylcholine to phosphatidy‐ lethanolamine has been used to differential metastatic colon cancers from localized ones. [118] Elevated levels of sphingomyelin have also been reported to characterize human colon cancer, based on nuclear magnetic resonance (NMR) studies [119], whilst cancer cell motility was shown to be down-regulated by the interaction between CD9 and sialoglycosphingolipid GM3 using CRC cell lines [120] and ceramides have been found to induce apoptosis in CRC cell lines

MAPKAPK3, AVCR2B, HlpA, RpL7/L12, and nucleobindin- 1. [102-106]

**5.2. Lipidomics**

further subdivided into several subclasses.

metastatic CRC disease might be plausible.

onco-preventive. [112]

#### **5.1. Proteomics**

The field of proteomics deals with identification of the total complement of peptides and proteins expressed in a cell, tissue or an organism and is in principle more directly related to phenotypic changes associated with disease pathogenesis. Proteomic studies are able to define: the functional state of protein activities; protein-ligand interactions; protein-protein interac‐ tions; and a host of dynamic post-translational modifications such as glycosylation, phos‐ phorylation, ubiquitinylation, SUMOylation, proteolytic cleavage, lipoylation and acetylation of proteins. The proteome of a cell may vary from one time point to another and in different states of health and disease so proteomics techniques have been employed to identify cancer specific proteomes as a means to identify candidate biomarkers of early disease. A huge amount of data is generated from single proteomic experiments and these are typically analyzed to understand the mechanistic pathways of pathologic events in protein networks using various databases, workflows and algorithms. For proteomics analysis, complex mixtures of proteins derived from a given biological sample are typically rendered into a set of peptides via proteolysis, most commonly using the enzyme trypsin; direct liquid chroma‐ tography-tandem mass spectrometry (LC-MS/MS) based methods are then typically employed to separate, quantify and identify thousands of individual tryptic peptides in a sample [92-94], from which the identity and quantity of the parent proteins in the original biological sample can be inferred. For example, one notable recent study identified and quantified >7,000 unique proteins from FFPE tissue blocks from individual colorectal cancer patients [95], amply demonstrating the potential of the technology.

Common sources of current proteomics biomarkers for CRC include stool, blood, biopsy and urine samples. A common fecal proteomics biomarker in use today is hemoglobin [96], while carcinoembryonic antigen (CEA) is a common blood-based biomarker currently in use. [97] Tissue inhibitor of metalloproteinase 1 (TIMP-1) has also been used and has been found useful in the early detection of cancer although, paradoxically, other studies using multivariate analysis have described TIMP-1 as independent of the stage of cancer. [98] Proteasome activator complex subunit-3 (PSME-3), nicotinamide N-methyltransferase (NNMT), collapsin response mediator protein-2 (CRMP-2), MIF, M2-PK, M-CSF, HNP 1-3, CCSA-2, CCSA-3, CCSA-4, laminin, MMP-9, MMP-7, and a host of other serum proteomics biomarkers are being developed and optimized for clinical use. For example, surface enhanced laser desorptionionisation (SELDI) mass spectrometry was used to analyze the serum of 62 CRC patients compared to 31 controls, and four proteomic markers were found in detectable levels in the serum of CRC patients: apolipoprotein C1, alpha-1-antitrypsin, C3a-desArg and transferrin. [99] A separate study carried out at the Mayo Clinic revealed elevated levels of 5 serum biomarkers in CRC: DcR3, TRAIL-2, spondin-1, MIC 1 and Reg IV [100]; usefully, this '5 biomarker panel' has been reported to exceed the performance of CEA both in specificity and sensitivity. Immunoproteomics - involving techniques such as immunoblotting, ELISA and immunocapture-mass spectrometry - has also yielded candidate biomarkers in CRC, including antibodies against inosine monophosphate dehydrogenase II [101], MUC-5A, MUC-1, MAPKAPK3, AVCR2B, HlpA, RpL7/L12, and nucleobindin- 1. [102-106]

#### **5.2. Lipidomics**

highlighted this in observing that colorectal carcinomas in an Egyptian cohort had a signifi‐ cantly higher state of methylation, in microsatellite stable tumours, compared with sporadic

The field of proteomics deals with identification of the total complement of peptides and proteins expressed in a cell, tissue or an organism and is in principle more directly related to phenotypic changes associated with disease pathogenesis. Proteomic studies are able to define: the functional state of protein activities; protein-ligand interactions; protein-protein interac‐ tions; and a host of dynamic post-translational modifications such as glycosylation, phos‐ phorylation, ubiquitinylation, SUMOylation, proteolytic cleavage, lipoylation and acetylation of proteins. The proteome of a cell may vary from one time point to another and in different states of health and disease so proteomics techniques have been employed to identify cancer specific proteomes as a means to identify candidate biomarkers of early disease. A huge amount of data is generated from single proteomic experiments and these are typically analyzed to understand the mechanistic pathways of pathologic events in protein networks using various databases, workflows and algorithms. For proteomics analysis, complex mixtures of proteins derived from a given biological sample are typically rendered into a set of peptides via proteolysis, most commonly using the enzyme trypsin; direct liquid chroma‐ tography-tandem mass spectrometry (LC-MS/MS) based methods are then typically employed to separate, quantify and identify thousands of individual tryptic peptides in a sample [92-94], from which the identity and quantity of the parent proteins in the original biological sample can be inferred. For example, one notable recent study identified and quantified >7,000 unique proteins from FFPE tissue blocks from individual colorectal cancer patients [95], amply

Common sources of current proteomics biomarkers for CRC include stool, blood, biopsy and urine samples. A common fecal proteomics biomarker in use today is hemoglobin [96], while carcinoembryonic antigen (CEA) is a common blood-based biomarker currently in use. [97] Tissue inhibitor of metalloproteinase 1 (TIMP-1) has also been used and has been found useful in the early detection of cancer although, paradoxically, other studies using multivariate analysis have described TIMP-1 as independent of the stage of cancer. [98] Proteasome activator complex subunit-3 (PSME-3), nicotinamide N-methyltransferase (NNMT), collapsin response mediator protein-2 (CRMP-2), MIF, M2-PK, M-CSF, HNP 1-3, CCSA-2, CCSA-3, CCSA-4, laminin, MMP-9, MMP-7, and a host of other serum proteomics biomarkers are being developed and optimized for clinical use. For example, surface enhanced laser desorptionionisation (SELDI) mass spectrometry was used to analyze the serum of 62 CRC patients compared to 31 controls, and four proteomic markers were found in detectable levels in the serum of CRC patients: apolipoprotein C1, alpha-1-antitrypsin, C3a-desArg and transferrin. [99] A separate study carried out at the Mayo Clinic revealed elevated levels of 5 serum biomarkers in CRC: DcR3, TRAIL-2, spondin-1, MIC 1 and Reg IV [100]; usefully, this '5 biomarker panel' has been reported to exceed the performance of CEA both in specificity and sensitivity. Immunoproteomics - involving techniques such as immunoblotting, ELISA and

colorectal cancers in a Finnish cohort.

382 Colorectal Cancer - Surgery, Diagnostics and Treatment

demonstrating the potential of the technology.

**5.1. Proteomics**

Lipidomics is a novel 'omics field which deals with complex large scale analysis of the full complement of various classes of lipids and lipid networks expressed by a cell, tissue or organism (the 'lipidome') and involves the high throughput systems-level identification and quantification of lipid metabolic pathways that may be involved in disease using chromato‐ graphic methods coupled to mass spectrometry. Generally, lipids are hydrophobic molecules that are involved in energy storage, structural components of a cell, cell signaling, endocrine actions, signal transduction, membrane trafficking, and morphogenesis. Structurally, lipids can be classified as: fatty acids; glycerolipids; glycerophospholipids; sphingolipids; sterol lipids; prenol lipids; saccharolipids; and polyketides. These 8 classes of lipids can also be further subdivided into several subclasses.

Whilst there is currently a paucity of clinically validated lipidomics biomarkers for colorectal cancer, the prospects of this field to complement proteomics and genomics in a combined 'systems biology' approach for disease detection, monitoring and treatment is worth consid‐ eration since over the past two decades, numerous publications have described the perturba‐ tion of lipid metabolism and signaling in colorectal carcinogenesis. [107-110] Lipidomics analysis of primary and metastatic colorectal cancer cell lines (SW480 and SW620) identified 600 and 694 lipids respectively in 'shotgun' study [111]; increased level of triglyceride lipid and plasmacholine were observed, while a decrease in the level of C-16 containing sphingo‐ myelin, ceramide lipid and plasmenylethanolamine were observed in the metastatic CRC cell line compared to the primary isogenic CRC cell line, implying that lipidomic biomarkers of metastatic CRC disease might be plausible.

Empirically, polyunsaturated fatty acids have been known to be more beneficial in the prevention of colorectal diseases compared to saturated long-chain types, but the pathways related to this were largely unclear. The emergence of lipidomics techniques however has revealed that metabolic control of long chain fatty acids is an important factor in development of CRC, with short chain fatty acids from the gut microflora/ microbiome being described as onco-preventive. [112]

Elevated level of lysophosphatidic acid - a phosphoglyceride - has been described as a prospective cancer biomarker of ovarian tumours [113-115] but, paradoxically, a marked decrease in the serum level of lysophosphatidylcholine has been reported in CRC. [116] Similarly, elevated profiles of phosphatidylcholine and choline kinase activity have been demonstrated it colon cancers [117] and a high ratio of phosphatidylcholine to phosphatidy‐ lethanolamine has been used to differential metastatic colon cancers from localized ones. [118] Elevated levels of sphingomyelin have also been reported to characterize human colon cancer, based on nuclear magnetic resonance (NMR) studies [119], whilst cancer cell motility was shown to be down-regulated by the interaction between CD9 and sialoglycosphingolipid GM3 using CRC cell lines [120] and ceramides have been found to induce apoptosis in CRC cell lines (HT-29, LOVO, and HCT-116). [121-123] Urinary phospholipids analysis using nanoflow LC-ESI MS/MS has been previously used for the analysis of breast [124, 125]) and prostate cancer [124], but there is a dearth of literature on the application of this method to colorectal cancer. Interestingly though, urinary levels of metabolites of prostaglandin E2 have been used as a biomarker for colorectal cancer risk evaluation. [126, 127] Overall, these observations of disease-associated variation in colorectal cancer lipid profiles provide a sound precedent for the future development of reliable lipidomics biomarkers.

of medical imaging, they are limited to information at the gross anatomical and physiological levels respectively. Recent years have however seen the emergence of molecular imaging and

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In previous sections we have discussed how a range of different 'omics technologies have facilitated an in-depth view of the pathophysiology and molecular pathology of cancer. These insights provide candidate biomarkers based on the identification of differentially expressed genes and proteins between tumours and normal tissue. These biomarkers have either been associated with prognosis, stage of disease, molecular subtypes, predictors of treatment outcome, and markers of discriminating carcinoma from benign lesions at the molecular level.

In this light, molecular imaging is then the science of utilising the ever-increasing knowledge of cancer molecular pathology to: identify the appropriate molecular targets; design molecular constructs to selectively and specifically interact with them; and produce a visual signal that is measurable through an imaging technology. In order for this methodology to succeed at the molecular level, the target should be available for interaction and should be unique enough to ensure selective and specific interactions. Furthermore, once a signal has been generated from the appropriate interaction, it is important that a suitably sensitive imagining technology exists

In the context of colorectal cancer, plasma-membrane associated proteins are generally considered good candidate targets since they are reasonably accessible and a subset of them play vital roles in signal transduction. In a similar fashion, aberrantly expressed or deregulated intracellular and secreted enzymes represent potentially useful targets for molecular imaging, based on their ability to catalyse formation of spectroscopically-measurable products. Both of these types of targets are accessible through the extensive vascularisation of the colorectum, but more importantly these targets can be accessed via the luminal surface through topical

Molecular imaging provides tremendous opportunities to enhance the early detection of CRC, as well as potentially aiding the demarcation of clear margins during surgical resection, as

By way of illustration of the potential of molecular imaging methods, colorectal cancers have been found to naturally emit a red fluorescent signal due to the accumulation of protopor‐ phyrin IX (PpIX) in primary colorectal tumours and associated metastases located in lymph nodes. [137] These authors postulated that endogenous PpIX accumulates as a result of aberrant metabolic changes in the CRC cells; Kemmner et al [138] subsequently provided supporting evidence for this hypothesis by showing that there is a significant down-regulation of ferrochelatase (FECH) mRNA expression in gastric, colon, and rectal carcinomas, leading to accumulation of PpIX. In an effort to utilise this information Moesta et al [137] found that metastatically involved lymph nodes could be identified compared to all other palpable nodes; in the context of previously untreated patients (n=24), this observation had a sensitivity of 62% and a specificity of 78% (p < 0.0001). However, in a neoadjuvant setting there was a reduction in PpIX fluorescence in primary tumours, and a drastic reduction of fluorescent signal in metastases that resulted in not being able to discriminate between lymph nodes containing

reviewed recently by Abdullah [134], Seaman et al [135] and Akin et al [136].

its addition to the repertoire of techniques to visualise disease.

in order to visualise, and quantify, signal emission.

application of an appropriately designed molecular construct.

#### **5.3. Metabolomics**

The relatively new field of 'omics techniques that investigates the presence and abundance of low molecular weight metabolites in cells and body fluids is known as 'metabolomics'. This new branch in the 'omics world has emerged to address molecular biologic problems that have hitherto not been amenable to genomics or proteomics approaches. Common specimens compatible with metabolomics experiments include urine, serum and tissue. As is the case for genomics, proteomics and lipidomics, the 'metabolome' changes depending on physiologic and pathologic states of an individual and identification of unique metabolites provides potentially useful insight into pathogenetic mechanism of disease.

A number of analytical techniques have been used for metabolomics research, including: gas chromatography mass spectrometry (GC-MS); liquid chromatography mass spectrometry (LC-MS); capillary electrophoresis mass spectrometry (CE-MS); matrix assisted laser desorp‐ tion-ionization mass spectrometry (MALDI-MS); and nuclear magnetic resonance (NMR). [128] By way of example, metabolomics studies on CRC patient serum samples, using a combination of proton-NMR and GC-MS techniques, was used to differentiate locoregional CRC from metastatic types as well as to identify CRC that metastasized to the liver. [129] Separately, in a review of eight metabolomics studies on CRC for diagnostic accuracy and distinguishing metabolites, twelve metabolites were found to be elevated. [130] In a further study using GC-MS, 34 endogenous metabolites were found significantly elevated in CRC compared with health individual, whilst the serum 3-hydroxybutyric acid level was noted to be reduced. [131] A predictive model developed in yet another study comprised of 2-hydrox‐ ybutyrate, kynurenine, cystamine and aspartic acid and was found to have specificity, sensitivity and accuracy as high as 85%, 85%, and 85% respectively. [128] Finally, Cheng et al [132] found evidence of dysregulation of several metabolic pathways through urine analysis of colorectal cancer patients, whilst Qui et al [133] also observed evidence of similar pertur‐ bations in tricarboxylic acid (TCA) and tryptophan metabolic pathways. With a solid founda‐ tion, a panel of metabolite markers may ultimately be developed for metabolomic profiling of colorectal patients as a means to improve diagnosis.

#### **5.4. Molecular Imaging**

Visualisation of precursor lesions and of malignant tissue is a major aspect of diagnosis and monitoring of therapeutic interventions in oncology. Classically this has been carried out using anatomical and functional technologies, such as Ultrasound (US), Computerised Tomography (CT), and Magnetic Resonance Imaging (MRI). While these approaches have been the mainstay of medical imaging, they are limited to information at the gross anatomical and physiological levels respectively. Recent years have however seen the emergence of molecular imaging and its addition to the repertoire of techniques to visualise disease.

(HT-29, LOVO, and HCT-116). [121-123] Urinary phospholipids analysis using nanoflow LC-ESI MS/MS has been previously used for the analysis of breast [124, 125]) and prostate cancer [124], but there is a dearth of literature on the application of this method to colorectal cancer. Interestingly though, urinary levels of metabolites of prostaglandin E2 have been used as a biomarker for colorectal cancer risk evaluation. [126, 127] Overall, these observations of disease-associated variation in colorectal cancer lipid profiles provide a sound precedent for

The relatively new field of 'omics techniques that investigates the presence and abundance of low molecular weight metabolites in cells and body fluids is known as 'metabolomics'. This new branch in the 'omics world has emerged to address molecular biologic problems that have hitherto not been amenable to genomics or proteomics approaches. Common specimens compatible with metabolomics experiments include urine, serum and tissue. As is the case for genomics, proteomics and lipidomics, the 'metabolome' changes depending on physiologic and pathologic states of an individual and identification of unique metabolites provides

A number of analytical techniques have been used for metabolomics research, including: gas chromatography mass spectrometry (GC-MS); liquid chromatography mass spectrometry (LC-MS); capillary electrophoresis mass spectrometry (CE-MS); matrix assisted laser desorp‐ tion-ionization mass spectrometry (MALDI-MS); and nuclear magnetic resonance (NMR). [128] By way of example, metabolomics studies on CRC patient serum samples, using a combination of proton-NMR and GC-MS techniques, was used to differentiate locoregional CRC from metastatic types as well as to identify CRC that metastasized to the liver. [129] Separately, in a review of eight metabolomics studies on CRC for diagnostic accuracy and distinguishing metabolites, twelve metabolites were found to be elevated. [130] In a further study using GC-MS, 34 endogenous metabolites were found significantly elevated in CRC compared with health individual, whilst the serum 3-hydroxybutyric acid level was noted to be reduced. [131] A predictive model developed in yet another study comprised of 2-hydrox‐ ybutyrate, kynurenine, cystamine and aspartic acid and was found to have specificity, sensitivity and accuracy as high as 85%, 85%, and 85% respectively. [128] Finally, Cheng et al [132] found evidence of dysregulation of several metabolic pathways through urine analysis of colorectal cancer patients, whilst Qui et al [133] also observed evidence of similar pertur‐ bations in tricarboxylic acid (TCA) and tryptophan metabolic pathways. With a solid founda‐ tion, a panel of metabolite markers may ultimately be developed for metabolomic profiling of

Visualisation of precursor lesions and of malignant tissue is a major aspect of diagnosis and monitoring of therapeutic interventions in oncology. Classically this has been carried out using anatomical and functional technologies, such as Ultrasound (US), Computerised Tomography (CT), and Magnetic Resonance Imaging (MRI). While these approaches have been the mainstay

the future development of reliable lipidomics biomarkers.

384 Colorectal Cancer - Surgery, Diagnostics and Treatment

potentially useful insight into pathogenetic mechanism of disease.

colorectal patients as a means to improve diagnosis.

**5.4. Molecular Imaging**

**5.3. Metabolomics**

In previous sections we have discussed how a range of different 'omics technologies have facilitated an in-depth view of the pathophysiology and molecular pathology of cancer. These insights provide candidate biomarkers based on the identification of differentially expressed genes and proteins between tumours and normal tissue. These biomarkers have either been associated with prognosis, stage of disease, molecular subtypes, predictors of treatment outcome, and markers of discriminating carcinoma from benign lesions at the molecular level.

In this light, molecular imaging is then the science of utilising the ever-increasing knowledge of cancer molecular pathology to: identify the appropriate molecular targets; design molecular constructs to selectively and specifically interact with them; and produce a visual signal that is measurable through an imaging technology. In order for this methodology to succeed at the molecular level, the target should be available for interaction and should be unique enough to ensure selective and specific interactions. Furthermore, once a signal has been generated from the appropriate interaction, it is important that a suitably sensitive imagining technology exists in order to visualise, and quantify, signal emission.

In the context of colorectal cancer, plasma-membrane associated proteins are generally considered good candidate targets since they are reasonably accessible and a subset of them play vital roles in signal transduction. In a similar fashion, aberrantly expressed or deregulated intracellular and secreted enzymes represent potentially useful targets for molecular imaging, based on their ability to catalyse formation of spectroscopically-measurable products. Both of these types of targets are accessible through the extensive vascularisation of the colorectum, but more importantly these targets can be accessed via the luminal surface through topical application of an appropriately designed molecular construct.

Molecular imaging provides tremendous opportunities to enhance the early detection of CRC, as well as potentially aiding the demarcation of clear margins during surgical resection, as reviewed recently by Abdullah [134], Seaman et al [135] and Akin et al [136].

By way of illustration of the potential of molecular imaging methods, colorectal cancers have been found to naturally emit a red fluorescent signal due to the accumulation of protopor‐ phyrin IX (PpIX) in primary colorectal tumours and associated metastases located in lymph nodes. [137] These authors postulated that endogenous PpIX accumulates as a result of aberrant metabolic changes in the CRC cells; Kemmner et al [138] subsequently provided supporting evidence for this hypothesis by showing that there is a significant down-regulation of ferrochelatase (FECH) mRNA expression in gastric, colon, and rectal carcinomas, leading to accumulation of PpIX. In an effort to utilise this information Moesta et al [137] found that metastatically involved lymph nodes could be identified compared to all other palpable nodes; in the context of previously untreated patients (n=24), this observation had a sensitivity of 62% and a specificity of 78% (p < 0.0001). However, in a neoadjuvant setting there was a reduction in PpIX fluorescence in primary tumours, and a drastic reduction of fluorescent signal in metastases that resulted in not being able to discriminate between lymph nodes containing metastatic cells. In a follow-up study by Wan et al [139], conducted in xenografted nude mice, a novel siRNA-mediated knockdown of FECH was used to enhance the accumulation of PpIX, thereby increasing the endogenous fluorescence in tumour cells. While these results still need to be developed further, and tested in a clinical trial, they do hold promise for increasing the accuracy of early detection of primary and metastatic lesions and monitoring therapeutic response based on the size of the visualised tumour.

derivatized and stabilized with Raman active particles and silica respectively for used in generating composite organic and inorganic nanoparticles (COINs) for potential improvement of biopsy diagnosis. [143] Simultaneous Multiple Aptamers and RGD Targeting (SMART) cancer probes have also been used to detect multiple cancer biomarker signals using currently available imaging techniques. [144] Superconducting quantum interference device (SQUID) sensors and magnetic relaxometry - which are both nanotechnology based techniques - have been reported to be more accurate in the diagnosis of breast cancer than mammography and MRI respectively. KRAS mutant alleles have been detected in gastrointestinal malignancies, including colorectal carcinoma, using nanofluidic digital PCR which showed a better per‐ formance in detection of mutation KRAS in colorectal adenomas compared to conventional PCR. [145] Nanoparticles have been coupled with short cancer specific oligonucleotides (aptamers) for targeted binding to prostate specific membrane antigen positive cells in prostate cancer cell lines. [146] Finally, serum detection of colorectal cancer has been achieved with gold nanoparticles using SERS spectroscopy in a study which exemplified the use of this approach as a viable, minimally invasive screening method for colorectal cancer. [147]

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

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387

Nanotechnology also has significant potential in the development of targeted therapeutics for cancer, with many studies currently at experimental- and a few at clinical validation stages. Different types of nanostructures, including mesoporous silica nanoshells, dendrimers, supramagnetic iron cores, nanosuspensions, gold nanoparticles, nanolipogels, nanoemul‐ sions, carbon nanotubes, titanium oxide nanoparticles, liposomes, polymeric miscelles, and other lipid based nanoparticles have been used as drug delivery vehicles and facilitators of targeted cancer therapies. [148-155] Although most of the cancer nanodiagnostic and nano‐ therapy studies are still in their infancy, it seems clear that nanotechnology will play an

important role in colorectal cancer diagnostics and therapeutics in the future.

**Town**

**6. Prospects of 'Omics based molecular approaches in colorectal cancer diagnosis and treatment in a developing country: A case study in Cape**

Groote Schuur Hospital, situated in Cape Town, South Africa, is a quaternary hospital where the many colorectal cancer patients from the Western Province region are treated by combi‐ nations of radiotherapy, colonic resection and standard chemotherapeutic regimens. However, there are two complicating factors involved in treating these patients with the greatest efficacy: (1) the relatively high cost of utilising platinum- or modern monoclonal antibody-based regimens; and (2) the fact that the majority of patients present with advanced stages of disease, typically between TNM stage II and III. As mentioned earlier, these stages of disease have relatively high recurrence rates and as such timely diagnosis and efficacious treatment

schedules are needed to reduce disease recurrence and improve patient prognoses.

To illustrate this point, consider the cost of the standard chemotherapeutic regimen of 5 fluorouracil (5-FU) alone versus Oxaliplatin: One cycle of Oxaliplatin costs approximately ZAR 5,000.00 (~USD 560), while one cycle of 5-FU is drastically less at a cost of ZAR 200 (~USD 22).

In different work, differential gene expression profiling, confirmed by immunohistochemistry, demonstrated that matrix-metalloproteases (MMPs) are differentially expressed in the context of colorectal adenocarcinoma by macrophage subpopulations and, at times, by the tumours themselves. MMPs are a family of zinc-dependent endopeptidases with multiple human peptidase members. For example, MMP-9 is able to degrade specific components of the extracellular matrix, including type IV collagen, after activation of the secreted zymogen [140] and as a direct consequence, malignant cells are thereby able to become mobile and achieve metastatic potential.

Of particular interest to surgical resection was the finding that colorectal adenocarcinomas express MMP-9 *via* a distinct macrophage subpopulation found at the edge of primary tumours and local lymph node metastases. [140] Fudala et al [141] have subsequently designed a dual fluorophore beacon molecule that is specifically cleaved by MMP-9, resulting in the emission of a specific fluorescent signal, suggesting that if a suitably non-invasive and anti-immuno‐ genic method is developed to administer the beacon molecule to an anatomical structure under investigation, then accurate measurement of the tumour edge may be possible during surgical resection procedures.

As can be seen from the above examples, molecular imaging holds considerable promise for application in CRC. As this field becomes more developed and is validated through clinical trials, it should provide improved visualisation ability coupled with the ability to quantify specific molecules, enabling novel insights into diagnosis, prognosis, treatment response monitoring, and underlying tumour physiology and molecular pathology in CRC.

#### **5.5. Cancer nanotechnology**

Nanotechnology as a division of engineering concerned with the manipulation of atomic and subatomic molecules has recently found its place in the detection, staging, imaging, and management of human cancers. Various physical, chemical and biologic principles have been applied to improve the diagnosis and treatment using elements and molecules in the Nanorange (~10-9). [142]

For diagnosis of CRC, nanoparticles have been used to enhance the precision and reliability of colonoscopy and other conventional diagnostic methods, largely resulting in earlier detection and obviating variables such as operator skills and speed of examination. Quantum dots (QD) and surface-enhanced Raman scattering (SERS) are two important nano- method‐ ologies used to improve tissue based diagnosis of cancer, avoiding the cumbersome protocols and lower reliability of multiplexed tissue staining. Both methods have the ability to detect multiple biomolecular signals in a single cancer cell. Gold and silver particles have been derivatized and stabilized with Raman active particles and silica respectively for used in generating composite organic and inorganic nanoparticles (COINs) for potential improvement of biopsy diagnosis. [143] Simultaneous Multiple Aptamers and RGD Targeting (SMART) cancer probes have also been used to detect multiple cancer biomarker signals using currently available imaging techniques. [144] Superconducting quantum interference device (SQUID) sensors and magnetic relaxometry - which are both nanotechnology based techniques - have been reported to be more accurate in the diagnosis of breast cancer than mammography and MRI respectively. KRAS mutant alleles have been detected in gastrointestinal malignancies, including colorectal carcinoma, using nanofluidic digital PCR which showed a better per‐ formance in detection of mutation KRAS in colorectal adenomas compared to conventional PCR. [145] Nanoparticles have been coupled with short cancer specific oligonucleotides (aptamers) for targeted binding to prostate specific membrane antigen positive cells in prostate cancer cell lines. [146] Finally, serum detection of colorectal cancer has been achieved with gold nanoparticles using SERS spectroscopy in a study which exemplified the use of this approach as a viable, minimally invasive screening method for colorectal cancer. [147]

metastatic cells. In a follow-up study by Wan et al [139], conducted in xenografted nude mice, a novel siRNA-mediated knockdown of FECH was used to enhance the accumulation of PpIX, thereby increasing the endogenous fluorescence in tumour cells. While these results still need to be developed further, and tested in a clinical trial, they do hold promise for increasing the accuracy of early detection of primary and metastatic lesions and monitoring therapeutic

In different work, differential gene expression profiling, confirmed by immunohistochemistry, demonstrated that matrix-metalloproteases (MMPs) are differentially expressed in the context of colorectal adenocarcinoma by macrophage subpopulations and, at times, by the tumours themselves. MMPs are a family of zinc-dependent endopeptidases with multiple human peptidase members. For example, MMP-9 is able to degrade specific components of the extracellular matrix, including type IV collagen, after activation of the secreted zymogen [140] and as a direct consequence, malignant cells are thereby able to become mobile and achieve

Of particular interest to surgical resection was the finding that colorectal adenocarcinomas express MMP-9 *via* a distinct macrophage subpopulation found at the edge of primary tumours and local lymph node metastases. [140] Fudala et al [141] have subsequently designed a dual fluorophore beacon molecule that is specifically cleaved by MMP-9, resulting in the emission of a specific fluorescent signal, suggesting that if a suitably non-invasive and anti-immuno‐ genic method is developed to administer the beacon molecule to an anatomical structure under investigation, then accurate measurement of the tumour edge may be possible during surgical

As can be seen from the above examples, molecular imaging holds considerable promise for application in CRC. As this field becomes more developed and is validated through clinical trials, it should provide improved visualisation ability coupled with the ability to quantify specific molecules, enabling novel insights into diagnosis, prognosis, treatment response

Nanotechnology as a division of engineering concerned with the manipulation of atomic and subatomic molecules has recently found its place in the detection, staging, imaging, and management of human cancers. Various physical, chemical and biologic principles have been applied to improve the diagnosis and treatment using elements and molecules in the Nano-

For diagnosis of CRC, nanoparticles have been used to enhance the precision and reliability of colonoscopy and other conventional diagnostic methods, largely resulting in earlier detection and obviating variables such as operator skills and speed of examination. Quantum dots (QD) and surface-enhanced Raman scattering (SERS) are two important nano- method‐ ologies used to improve tissue based diagnosis of cancer, avoiding the cumbersome protocols and lower reliability of multiplexed tissue staining. Both methods have the ability to detect multiple biomolecular signals in a single cancer cell. Gold and silver particles have been

monitoring, and underlying tumour physiology and molecular pathology in CRC.

response based on the size of the visualised tumour.

386 Colorectal Cancer - Surgery, Diagnostics and Treatment

metastatic potential.

resection procedures.

**5.5. Cancer nanotechnology**

range (~10-9). [142]

Nanotechnology also has significant potential in the development of targeted therapeutics for cancer, with many studies currently at experimental- and a few at clinical validation stages. Different types of nanostructures, including mesoporous silica nanoshells, dendrimers, supramagnetic iron cores, nanosuspensions, gold nanoparticles, nanolipogels, nanoemul‐ sions, carbon nanotubes, titanium oxide nanoparticles, liposomes, polymeric miscelles, and other lipid based nanoparticles have been used as drug delivery vehicles and facilitators of targeted cancer therapies. [148-155] Although most of the cancer nanodiagnostic and nano‐ therapy studies are still in their infancy, it seems clear that nanotechnology will play an important role in colorectal cancer diagnostics and therapeutics in the future.

## **6. Prospects of 'Omics based molecular approaches in colorectal cancer diagnosis and treatment in a developing country: A case study in Cape Town**

Groote Schuur Hospital, situated in Cape Town, South Africa, is a quaternary hospital where the many colorectal cancer patients from the Western Province region are treated by combi‐ nations of radiotherapy, colonic resection and standard chemotherapeutic regimens. However, there are two complicating factors involved in treating these patients with the greatest efficacy: (1) the relatively high cost of utilising platinum- or modern monoclonal antibody-based regimens; and (2) the fact that the majority of patients present with advanced stages of disease, typically between TNM stage II and III. As mentioned earlier, these stages of disease have relatively high recurrence rates and as such timely diagnosis and efficacious treatment schedules are needed to reduce disease recurrence and improve patient prognoses.

To illustrate this point, consider the cost of the standard chemotherapeutic regimen of 5 fluorouracil (5-FU) alone versus Oxaliplatin: One cycle of Oxaliplatin costs approximately ZAR 5,000.00 (~USD 560), while one cycle of 5-FU is drastically less at a cost of ZAR 200 (~USD 22). The response rate obtained with 5-FU alone can be improved by utilising Leucovorin (LV) in a combination therapy approach. However, it has been observed that the further addition of Oxaliplatin or Irinotecan can improve the stage II/III CRC response rates drastically to around 40 – 50%. [156, 157] The relatively recent appearance of monoclonal antibody based therapies has also offered significant gains in treatment response rates.

an indication of whether or not the comparatively expensive anti-epidermal growth factor

Prospects of 'Omics Based Molecular Approaches in Colorectal Cancer Diagnosis and...

http://dx.doi.org/10.5772/57485

389

As discussed above, a number of gene expression panels could also be used to predict patient prognosis and the associated likelihood of disease recurrence, with results being used to design a personalised treatment regimen in which the aggressiveness of the treatment schedule correlates with the severity of disease, the most likely prognosis and the likelihood of recur‐ rence. In this context, Genomic Health's Onco*type* DX® Colon Cancer Assay costs ~USD 3,200 [45], which translates to approximately ZAR 28,560 in South Africa; this assay could provide a very useful clinical metric of the likelihood of recurrence, particularly in complicated TNM stage II cases and stage III cases where recurrence rates are still unfavorably high, but in reality such a test is beyond the financial means available for treatment of CRC disease at a public facility in South Africa today, not least since its cost dwarfs even that of Oxaliplatin-based treatments. The prospects for wide uptake of the Onco*type* DX® Colon Cancer Assay in South

As the complexities of biopsy heterogeneity are addressed by the biomedical community, it is thus clear that local validation studies of simple and cost-effective, assays will be necessary to ensure that the prognostic and treatment outcome biomarkers reported in the literature apply to the diverse ethnicities in South Africa. Given the financial constraints imposed by the government funded healthcare system, it appears that relatively inexpensive techniques such as PCR based SNP assays would be well-suited to the public sector since, despite being a simple, low cost assay, the results could have a profound impact on treatment outcomes for the patients afflicted with this disease. Importantly, if utilised correctly such a molecular diagnostics strategy could actually result in significant cost savings mid-term for the hospitals

'Omics based techniques represent novel, scientifically sound approaches to the diagnostic and therapeutic aspects of managing colorectal cancer patients, but there remain very signif‐ icant challenges regarding their uptake and wide utilisation in developing world healthcare settings, primarily due to financial considerations. None-the-less, surgeons, clinicians, basic medical researchers and all other healthcare workers at the cutting edge of colorectal cancer management need to remain abreast of the prospects and potential effectiveness of integrating molecular approaches in to colorectal cancer management. The old paradigm where patients had no active choice or participation in their disease management, with treatment choices being exclusively the decision of the clinician, is under threat today since many patients now have access to information about emerging therapeutic options *via* the internet. It is therefore important that surgeons and clinicians, in spite of their invariably tight schedules, consider some form of participation in basic medical research in order to contribute clinical perspectives as well as to improve their understanding of molecular approaches to diagnosis and treatment.

administering care by avoiding the complexities of treatment failures.

receptor mAb therapy should be prescribed.

Africa therefore seem remote.

**7. Conclusion**

South Africa is a developing nation with a limited budget for treating non-communicable diseases such as cancer, not least because a large proportion of the country's healthcare budget is understandably spent on addressing the concurrent HIV/AIDS and TB epidemics (see for example the Lancet series on "Health in South Africa" published in 2009, with particular emphasis on the following publications: Abdool et al [158]; Chopra et al [159]; Coovadia et al [160]; and Mayosi et al [161]). Considering these financial constraints, two possible situations can be envisaged in which a patient treated in the public sector (i.e. subject to government healthcare budgets) could access platinum-based regimens and/or modern biological thera‐ peutic agents:

The first opportunity for a patient to access medication with greater efficacy would be through participation in clinical trials conducted by pharmaceutical companies either wanting to assess their treatment in ethnically diverse cohorts (which could be required by local regulatory authorities) or to explore a new disease indication for an existing therapeutic agent. The second opportunity might be one afforded by the use of 'omics approaches, leveraging biomarker panels to provide predictive indications of whether or not a patient might benefit from a particular chemo- or biological therapeutic agent. Furthermore, given the heterogeneity of tumours and the unique molecular subtypes of colorectal cancer, it would be instructive to assess the relative likelihood of recurrent disease. Such a measurement could be used to motivate the aggressiveness of the treatment regimen prescribed.

In terms of possible cost effective benefits from the addition of platinum-based drugs to the standard regimen of 5-FU and LV, a trial conducted in the United Kingdom found that the relative levels of topoisomerase-1 (Topo1), assessed by routine immunohistochemistry, could be used to identify patient subpopulations who could potentially benefit from the addition of Oxaliplatin to their 5-FU/LV regimen [162]. Furthermore, Paré and colleagues [163] reported that a particular polymorphism in the excision repair cross-complementing 1 *ERCC1* gene (codon 118) can predict response and overall survival in patients treated with an Oxaliplatin/ 5-FU/LV regimen. Provided that these markers are further validated in a clinical setting, it then stands to reason that a simple immunohistochemical or real-time polymerase chain reaction assay could therefore be routinely requested to determine likely response to Oxaliplatin and therefore to motivate additional expenditure on an Oxaliplatin-supplemented regimen. This type of personalised approach has the obvious advantage of improving treatment efficacy, and reducing the risk of disease recurrence with a concomitant cost saving for the hospital authority from not having to conduct lengthy additional treatments, after possible first round treatment failure.

Similarly, assessment of the common SNPs that are predictive of benefit from the limited array of biological agents (e.g. the mutational status of the KRAS and BRAF genes) could provide an indication of whether or not the comparatively expensive anti-epidermal growth factor receptor mAb therapy should be prescribed.

As discussed above, a number of gene expression panels could also be used to predict patient prognosis and the associated likelihood of disease recurrence, with results being used to design a personalised treatment regimen in which the aggressiveness of the treatment schedule correlates with the severity of disease, the most likely prognosis and the likelihood of recur‐ rence. In this context, Genomic Health's Onco*type* DX® Colon Cancer Assay costs ~USD 3,200 [45], which translates to approximately ZAR 28,560 in South Africa; this assay could provide a very useful clinical metric of the likelihood of recurrence, particularly in complicated TNM stage II cases and stage III cases where recurrence rates are still unfavorably high, but in reality such a test is beyond the financial means available for treatment of CRC disease at a public facility in South Africa today, not least since its cost dwarfs even that of Oxaliplatin-based treatments. The prospects for wide uptake of the Onco*type* DX® Colon Cancer Assay in South Africa therefore seem remote.

As the complexities of biopsy heterogeneity are addressed by the biomedical community, it is thus clear that local validation studies of simple and cost-effective, assays will be necessary to ensure that the prognostic and treatment outcome biomarkers reported in the literature apply to the diverse ethnicities in South Africa. Given the financial constraints imposed by the government funded healthcare system, it appears that relatively inexpensive techniques such as PCR based SNP assays would be well-suited to the public sector since, despite being a simple, low cost assay, the results could have a profound impact on treatment outcomes for the patients afflicted with this disease. Importantly, if utilised correctly such a molecular diagnostics strategy could actually result in significant cost savings mid-term for the hospitals administering care by avoiding the complexities of treatment failures.

#### **7. Conclusion**

The response rate obtained with 5-FU alone can be improved by utilising Leucovorin (LV) in a combination therapy approach. However, it has been observed that the further addition of Oxaliplatin or Irinotecan can improve the stage II/III CRC response rates drastically to around 40 – 50%. [156, 157] The relatively recent appearance of monoclonal antibody based therapies

South Africa is a developing nation with a limited budget for treating non-communicable diseases such as cancer, not least because a large proportion of the country's healthcare budget is understandably spent on addressing the concurrent HIV/AIDS and TB epidemics (see for example the Lancet series on "Health in South Africa" published in 2009, with particular emphasis on the following publications: Abdool et al [158]; Chopra et al [159]; Coovadia et al [160]; and Mayosi et al [161]). Considering these financial constraints, two possible situations can be envisaged in which a patient treated in the public sector (i.e. subject to government healthcare budgets) could access platinum-based regimens and/or modern biological thera‐

The first opportunity for a patient to access medication with greater efficacy would be through participation in clinical trials conducted by pharmaceutical companies either wanting to assess their treatment in ethnically diverse cohorts (which could be required by local regulatory authorities) or to explore a new disease indication for an existing therapeutic agent. The second opportunity might be one afforded by the use of 'omics approaches, leveraging biomarker panels to provide predictive indications of whether or not a patient might benefit from a particular chemo- or biological therapeutic agent. Furthermore, given the heterogeneity of tumours and the unique molecular subtypes of colorectal cancer, it would be instructive to assess the relative likelihood of recurrent disease. Such a measurement could be used to

In terms of possible cost effective benefits from the addition of platinum-based drugs to the standard regimen of 5-FU and LV, a trial conducted in the United Kingdom found that the relative levels of topoisomerase-1 (Topo1), assessed by routine immunohistochemistry, could be used to identify patient subpopulations who could potentially benefit from the addition of Oxaliplatin to their 5-FU/LV regimen [162]. Furthermore, Paré and colleagues [163] reported that a particular polymorphism in the excision repair cross-complementing 1 *ERCC1* gene (codon 118) can predict response and overall survival in patients treated with an Oxaliplatin/ 5-FU/LV regimen. Provided that these markers are further validated in a clinical setting, it then stands to reason that a simple immunohistochemical or real-time polymerase chain reaction assay could therefore be routinely requested to determine likely response to Oxaliplatin and therefore to motivate additional expenditure on an Oxaliplatin-supplemented regimen. This type of personalised approach has the obvious advantage of improving treatment efficacy, and reducing the risk of disease recurrence with a concomitant cost saving for the hospital authority from not having to conduct lengthy additional treatments, after possible first round treatment

Similarly, assessment of the common SNPs that are predictive of benefit from the limited array of biological agents (e.g. the mutational status of the KRAS and BRAF genes) could provide

has also offered significant gains in treatment response rates.

388 Colorectal Cancer - Surgery, Diagnostics and Treatment

motivate the aggressiveness of the treatment regimen prescribed.

peutic agents:

failure.

'Omics based techniques represent novel, scientifically sound approaches to the diagnostic and therapeutic aspects of managing colorectal cancer patients, but there remain very signif‐ icant challenges regarding their uptake and wide utilisation in developing world healthcare settings, primarily due to financial considerations. None-the-less, surgeons, clinicians, basic medical researchers and all other healthcare workers at the cutting edge of colorectal cancer management need to remain abreast of the prospects and potential effectiveness of integrating molecular approaches in to colorectal cancer management. The old paradigm where patients had no active choice or participation in their disease management, with treatment choices being exclusively the decision of the clinician, is under threat today since many patients now have access to information about emerging therapeutic options *via* the internet. It is therefore important that surgeons and clinicians, in spite of their invariably tight schedules, consider some form of participation in basic medical research in order to contribute clinical perspectives as well as to improve their understanding of molecular approaches to diagnosis and treatment.

## **Acknowledgements**

HA thanks the ICGEB for a PhD scholarship; RWG thanks the National Research Foundation (NRF), South Africa, for a PhD scholarship; JB thanks the NRF for a Research Chair.

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## **Author details**

Henry Adeola1,2, Ryan William Goosen1 , Paul Goldberg1,3 and Jonathan Blackburn1

1 Institute of Infectious Disease & Molecular Medicine, Department of Clinical Laboratory Science, Faculty of Health Sciences, University of Cape Town, South Africa

2 International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa

3 Surgical Gastroenterology Unit, Department of Surgery, Groote Schuur Hospital, Cape Town, South Africa

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[161] Mayosi BM, Flisher AJ, Lalloo UG et al. The burden of non-communicable diseases in South Africa. Lancet 2009; 374(9693): 934-47. doi: 10.1016/S0140-6736(09)61087-4 [162] Braun MS, Richman SD, Quirke P, Daly C, Adlard JW, Elliott F, Barrett JH, Selby P, Meade AM, Stephens RJ, Parmar MKB, Seymour MT. Predictive Biomarkers of Che‐ motherapy Efficacy in Colorectal Cancer: Results From the UK MRC FOCUS Trial.

[163] Paré L, Marcuello E, Altés A, del Río E, Sedano L, Salazar J, Cortés A, Barnadas A, Baiget M. Pharmacogenetic prediction of clinical outcome in advanced colorectal cancer patients receiving oxaliplatin/5-fluorouracil as first-line chemotherapy. Br J

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**Chapter 16**

*COL11A1* **— Genetic Biomarker**

**for Early Diagnosis of Colorectal**

Andra Iulia Suceveanu, Laura Mazilu and

Additional information is available at the end of the chapter

Colorectal cancer (CRC) is the third most frequently diagnosed cancer in both men and women and the second leading cause of cancer death after lung cancer. Even though CRC is considered to be 90% curable if detected in early stage, the majority of patients are diagnosed with

Screening tests applied according to well known strategies make the early diagnosis of CRC possible and there is is strong evidence evidence that screening lowers mortality and incidence rates of cancer, if recommended at proper time in people at risk [2]. Still, the existing tests practiced on a large scale in CRC screening do not fully accomplish the goal of best specificity and sensitivity or either an optimal cost/efficiency ratio. A more effective screening test may

Extensive research over the past two decades provided large information about genetic aberrations underlying CRC and revealed complex and heterogeneous mechanisms in the occurrence of the disease [3, 4]. Genetic changes occurred in normal colonic epithelium cells promoting the neoplastic transformation into benign adenomas and subsequently malignant adenocarcinomas were the essence for understanding the disease behavior and related clinical outcome, and created a perspective for future improvements in diagnosis, treatment and

> © 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Targeted in Stool Samples**

**Cancer in Patients at Risk**

Adrian-Paul Suceveanu

http://dx.doi.org/10.5772/57327

advanced stages, III or IV [1].

significantly decrease disease burden.

**1. Introduction**

survival rates.

**Chapter 16**

*COL11A1* **— Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk**

Andra Iulia Suceveanu, Laura Mazilu and Adrian-Paul Suceveanu

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57327

**1. Introduction**

Colorectal cancer (CRC) is the third most frequently diagnosed cancer in both men and women and the second leading cause of cancer death after lung cancer. Even though CRC is considered to be 90% curable if detected in early stage, the majority of patients are diagnosed with advanced stages, III or IV [1].

Screening tests applied according to well known strategies make the early diagnosis of CRC possible and there is is strong evidence evidence that screening lowers mortality and incidence rates of cancer, if recommended at proper time in people at risk [2]. Still, the existing tests practiced on a large scale in CRC screening do not fully accomplish the goal of best specificity and sensitivity or either an optimal cost/efficiency ratio. A more effective screening test may significantly decrease disease burden.

Extensive research over the past two decades provided large information about genetic aberrations underlying CRC and revealed complex and heterogeneous mechanisms in the occurrence of the disease [3, 4]. Genetic changes occurred in normal colonic epithelium cells promoting the neoplastic transformation into benign adenomas and subsequently malignant adenocarcinomas were the essence for understanding the disease behavior and related clinical outcome, and created a perspective for future improvements in diagnosis, treatment and survival rates.

© 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **2. Colorectal cancer genesis — Gene mutations and underlying stool testing**

demonstrated that some polymorphysms of *COL11A1* are associated with different types of

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

http://dx.doi.org/10.5772/57327

405

This study was designed to analyze *COL11A1* gene mutations identified in the DNA of exfoliated epithelial cells of the colon in the stool of the patients diagnosed with CRC through screening and to demonstrate the perfect similarity between the detected mutations in tumor samples and in exfoliated stool cells, in order to prove the reliability of the method as a

We selected 250 patients diagnosed in the Endoscopy Department of Emergency Hospital of Constanta with adenomatous polyps and CRC using colonoscopy and biopsy and confirmed by histopathological exam, during screening programme or admitted and investigated for intestinal disturbances such as chronic diarrhea or recent exacerbated constipation, stool

We collected samples biopsied from tumors during colonoscopy and stool sample from each

The colonoscopist documented the presence, size, location and extension of colonic tumors. Biopsy or surgical resection samples were examined histopathologically and genetically.

Subjects were instructed prior stool collection. No dietary or medication modifications were required. Until shipping samples to genetic lab, these were disposed in a coded container into a refrigerator, between 0 and 4°C. Specimens were required to arrive within 3 days after

The minimum quantity of stool sample required was 30 g. Samples were stored at –80°C until

The *COL11A1* gene, examined in the present study, produces a component of the colagen type XI, named pro-alpha1 chain, an important factor for connective tissue structure and resistance.

bleeding or association of the above symptoms in their recent history.

Colonoscopy and biopsies were performed with Olympus Exera equipment.

DNA was extracted from biopsy and feaces samples for mutation analysis:

Primers for PCR amplification were provided by TIB MOLBIOL, Germany.

**•** from stool, with QIAmp stool extraction kit (QIGene, Germany); **•** from biopsy sample, with IQ-DNA Extraction Kit (Promega USA).

The bowel preparation was done according to guidelines and its quality was noted.

adenocarcinoma [19].

diagnostic tool for early CRC diagnosis.

**4. Patients and method**

**3. AIM**

patient.

collection.

genetic analysis.

A cancer cell develops through a collection of gene mutations. Mutations left uncorrected by cell cycle regulation before division are fixed in that cell and in its future progenitors. A cell undergoes full carcinogenic transformation once a sufficient number of genes are mutated and the cell can no longer respond to the external signals that act as brakes on cell growth. Comparing with breast cancer, in which a single gene is required for disease initiation, in CRC there are 7 to 10 genes responsible for neoplastic transformation and thereforee, the geneticbased screening for CRC is a more laborious task than screening breast cancer [5].

Although a smaller subgroup can arise as a result of inherited mutations or previous inflam‐ matory bowel disease (Crohn's disease or ulcerative colitis), the great majority of CRC arise sporadically. This means that mutated genes are present only in precancerous and cancerous lesions in the colon and rectum, and are not present in all cells of the body. Therefore, CRC cannot be detected by a blood test, as breast cancer does [6].

Over the time, mutations of three different classes of genes have been described in colon cancer etiology: oncogenes, suppressor genes, and mismatch repair genes [7]. Knowledge of many of the specific mutations responsible for colon carcinogenesis allowed understanding the phenotypic manifestations and provided a large field for genetic testing from stool cell's DNA [8]. Although genetic testing is possible and available, it is not yet clear what battery of genetic tests are more accurate to use as an alternative diagnostic tool instead present widely accepted stool test.

Until now, the genetic changes targeted in the stool cell's DNA involved in the development of some colorectal cancers included: activating mutations of the K-RAS oncogene, inactivating mutations of the adenomatous polyposis cancer (*APC*) and *TP53* tumor suppressor genes [9] and germline or somatic mutations of mismatch repair genes (*MMR*) [10, 11].

A much less studied biomarker targeted in stool samples for early diagnosis of CRC in patients at risk is *COL11A1* gene, mutations of which have been first described in Marshall's syndrome and Stickler's syndrome [12]. The normal function of this gene is the production of collagen type XI, which participate to build the structure and the resistance of conjunctive tissues. Beside its main role in the assembly, organization and development of cartilage, *COL11A1* was found to be expressed at low level in a wide variety of normal adult human tissues, including lung, parotid gland and colorectal cells.

Few studies have found overexpression of the *COL11A1* gene in various types of cancers, such as non-small cell lung cancer (NSCLC), ovarian, oral cavity and colorectal cancers. In partic‐ ular, overexpression of the *COL11A1* gene was found to be correlated with invasive and metastatic potential of these cancers [13-16].

This gene is located on chromosome 1, arm p, site 21, between the 103.055.015 and 103.286.072 pair of bases, and is composed of 231 kbase. It contains 68 exons, not yet wholly sequenced [17]. A major contribution to the *COL11A1* gene sequencing knowleddgee, especially with the purpose of detecting mutations, is *Annune S* research and results [18]. Recent extented studies demonstrated that some polymorphysms of *COL11A1* are associated with different types of adenocarcinoma [19].

## **3. AIM**

**2. Colorectal cancer genesis — Gene mutations and underlying stool testing**

A cancer cell develops through a collection of gene mutations. Mutations left uncorrected by cell cycle regulation before division are fixed in that cell and in its future progenitors. A cell undergoes full carcinogenic transformation once a sufficient number of genes are mutated and the cell can no longer respond to the external signals that act as brakes on cell growth. Comparing with breast cancer, in which a single gene is required for disease initiation, in CRC there are 7 to 10 genes responsible for neoplastic transformation and thereforee, the genetic-

Although a smaller subgroup can arise as a result of inherited mutations or previous inflam‐ matory bowel disease (Crohn's disease or ulcerative colitis), the great majority of CRC arise sporadically. This means that mutated genes are present only in precancerous and cancerous lesions in the colon and rectum, and are not present in all cells of the body. Therefore, CRC

Over the time, mutations of three different classes of genes have been described in colon cancer etiology: oncogenes, suppressor genes, and mismatch repair genes [7]. Knowledge of many of the specific mutations responsible for colon carcinogenesis allowed understanding the phenotypic manifestations and provided a large field for genetic testing from stool cell's DNA [8]. Although genetic testing is possible and available, it is not yet clear what battery of genetic tests are more accurate to use as an alternative diagnostic tool instead present widely accepted

Until now, the genetic changes targeted in the stool cell's DNA involved in the development of some colorectal cancers included: activating mutations of the K-RAS oncogene, inactivating mutations of the adenomatous polyposis cancer (*APC*) and *TP53* tumor suppressor genes [9]

A much less studied biomarker targeted in stool samples for early diagnosis of CRC in patients at risk is *COL11A1* gene, mutations of which have been first described in Marshall's syndrome and Stickler's syndrome [12]. The normal function of this gene is the production of collagen type XI, which participate to build the structure and the resistance of conjunctive tissues. Beside its main role in the assembly, organization and development of cartilage, *COL11A1* was found to be expressed at low level in a wide variety of normal adult human tissues, including lung,

Few studies have found overexpression of the *COL11A1* gene in various types of cancers, such as non-small cell lung cancer (NSCLC), ovarian, oral cavity and colorectal cancers. In partic‐ ular, overexpression of the *COL11A1* gene was found to be correlated with invasive and

This gene is located on chromosome 1, arm p, site 21, between the 103.055.015 and 103.286.072 pair of bases, and is composed of 231 kbase. It contains 68 exons, not yet wholly sequenced [17]. A major contribution to the *COL11A1* gene sequencing knowleddgee, especially with the purpose of detecting mutations, is *Annune S* research and results [18]. Recent extented studies

and germline or somatic mutations of mismatch repair genes (*MMR*) [10, 11].

based screening for CRC is a more laborious task than screening breast cancer [5].

cannot be detected by a blood test, as breast cancer does [6].

404 Colorectal Cancer - Surgery, Diagnostics and Treatment

stool test.

parotid gland and colorectal cells.

metastatic potential of these cancers [13-16].

This study was designed to analyze *COL11A1* gene mutations identified in the DNA of exfoliated epithelial cells of the colon in the stool of the patients diagnosed with CRC through screening and to demonstrate the perfect similarity between the detected mutations in tumor samples and in exfoliated stool cells, in order to prove the reliability of the method as a diagnostic tool for early CRC diagnosis.

## **4. Patients and method**

We selected 250 patients diagnosed in the Endoscopy Department of Emergency Hospital of Constanta with adenomatous polyps and CRC using colonoscopy and biopsy and confirmed by histopathological exam, during screening programme or admitted and investigated for intestinal disturbances such as chronic diarrhea or recent exacerbated constipation, stool bleeding or association of the above symptoms in their recent history.

We collected samples biopsied from tumors during colonoscopy and stool sample from each patient.

Colonoscopy and biopsies were performed with Olympus Exera equipment.

The bowel preparation was done according to guidelines and its quality was noted.

The colonoscopist documented the presence, size, location and extension of colonic tumors.

Biopsy or surgical resection samples were examined histopathologically and genetically.

Subjects were instructed prior stool collection. No dietary or medication modifications were required. Until shipping samples to genetic lab, these were disposed in a coded container into a refrigerator, between 0 and 4°C. Specimens were required to arrive within 3 days after collection.

The minimum quantity of stool sample required was 30 g. Samples were stored at –80°C until genetic analysis.

DNA was extracted from biopsy and feaces samples for mutation analysis:


Primers for PCR amplification were provided by TIB MOLBIOL, Germany.

The *COL11A1* gene, examined in the present study, produces a component of the colagen type XI, named pro-alpha1 chain, an important factor for connective tissue structure and resistance. The method used for *COL11A1* mutations was polyacrylamide gel electrophoresis method for the heteroduplex analysis (HA).

strands. For optimal view of amplification products, we used 6% polyacrylamide gel, con‐ taining 0.5 μg ethidium bromide, migrated 6 V/cm. The gel is observed and photographed on

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

http://dx.doi.org/10.5772/57327

407

In the latter stages of a PCR amplification the polymerase is limiting, so that during the final annealing and synthesis steps, a proportion of the single stranded products spontaneously reanneals without primer extension. When amplifying from individuals heterozygous for any sequence difference, the single strands do not necessarily rehybridize exactly with the complementary strand. They can alternatively form a DNA hybrid (heteroduplex) consisting of a sense strand with one sequence variant and an antisense strand with another variant.

As a consequence, the heteroduplex DNA has a region of at least one base pair mismatch. The region of mismatch can elicit a mobility shift by altering the conformation adopted by the heteroduplex DNA, probably by causing it to bend at the location of the mismatch. The mobility shifts are usually small but can be visualized after prolonged electrophoresis on native

**Figure 1.** Denaturation and renaturation of normal and mutated DNA fragments in order to generate four types of fragments: two heteroduplex and two homoduplex. Fragments were migrated parallel on denaturating gradient gel. "Melting" heteroduplex are modified in the sense that they denaturate at a lower concentration of denaturant, allow‐

UV transilluminator.

polyacrylamide gels.

ing their visualization.

Investigation of *COL11A1* gene is made sequentially by setting fragments to be analyzed. To do this, fragments that usually carry most mutations are identified. Each fragment of *COL11A1* gene that is proposed for investigation is amplified by PCR. For this, primers flanking each particular fragment are used.

PCR conditions are dependent on the characteristics of each pair of primers. Each program contains a PCR initial denaturing step, lasting for 3 minutes at 94°C, followed by 30-35 reaction cycles (depending on the length of the fragment of interest and the size and composition of the primers), each cycle comprising: denaturation, alignment, elongation (conditions are established for each pair of primers used), and the final elongation step, lasting for 5 minutes at 72°C. Obtained amplicons are subjected to additional steps of forced denaturation-renatu‐ ration (to encourage heteroduplex formation), and then migrated in a 6% polyacrylamide gel.

The heteroduplex is represented by a fragment of double-stranded DNA in which the two strands do not express perfect complementarity. When DNA is denatured, the two strands are separated. Through renaturation, complementary chains come together to form a homodu‐ plex. If there is a mutation in one of the two strands, heteroduplex is formed (figure 1).

Heteroduplex analysis was imagined by *Ziemmermann et al* in 1993 [20] and has been used to enhance the sensitivity of denaturing gradient gel electrophoresis (DGGE) in the detection of point mutation [21-23]. DNA fragments for HA can be visualized via a variety of methods including bromide staining, labelling with radioisotopes and silver staining. The mutations detection rate of HA under ideal conditions is near 90%.

Heteroduplex differ from homoduplex by electrophoretic migration speed in polyacrylamide gel. Mutational alteration of a single base pair is sufficient to produce changes in mobility. Electrophoretic mobility of heteroduplex is lower than that of homoduplex, and it can be detected as a slower migrating band. This method can detect insertions, deletions and substitutions of even a single base pair in fragment lengths smaller than 200 bp.

The working protocol for this technique is very simple and quick and consists of a denatura‐ tion-renaturation step for which we set the following conditions: 94°C – 1 minute, 72°C – 1 minute, 65°C – 1 minute, 40°C – 1 minute and thermal shock at 4°C. Each stage is covered by one cycle. The existence of deletion mutations will result in the formation of four bands, two heteroduplex and two homoduplex (heterozygous condition) (Figure 1).

Migration occurs differently based on molecular weight. Samples from patients and healthy individuals (control samples) are migrated in the same gel, in order to analyze the difference in migration. If the investigated individual is a normal homozygous or a homozygous for analyzed mutation, a single band will be displayed in each case. The difference between these conditions is based on different migration and reported to the molecular weight marker used. If there is a substitution mutation, two bands are visualized on polyacrylamide gel: a band representing heteroduplex and a band representing homoduplex. In this case, the difference in migration is explained on the basis of different chemical composition of the four DNA strands. For optimal view of amplification products, we used 6% polyacrylamide gel, con‐ taining 0.5 μg ethidium bromide, migrated 6 V/cm. The gel is observed and photographed on UV transilluminator.

The method used for *COL11A1* mutations was polyacrylamide gel electrophoresis method for

Investigation of *COL11A1* gene is made sequentially by setting fragments to be analyzed. To do this, fragments that usually carry most mutations are identified. Each fragment of *COL11A1* gene that is proposed for investigation is amplified by PCR. For this, primers flanking each

PCR conditions are dependent on the characteristics of each pair of primers. Each program contains a PCR initial denaturing step, lasting for 3 minutes at 94°C, followed by 30-35 reaction cycles (depending on the length of the fragment of interest and the size and composition of the primers), each cycle comprising: denaturation, alignment, elongation (conditions are established for each pair of primers used), and the final elongation step, lasting for 5 minutes at 72°C. Obtained amplicons are subjected to additional steps of forced denaturation-renatu‐ ration (to encourage heteroduplex formation), and then migrated in a 6% polyacrylamide gel.

The heteroduplex is represented by a fragment of double-stranded DNA in which the two strands do not express perfect complementarity. When DNA is denatured, the two strands are separated. Through renaturation, complementary chains come together to form a homodu‐ plex. If there is a mutation in one of the two strands, heteroduplex is formed (figure 1).

Heteroduplex analysis was imagined by *Ziemmermann et al* in 1993 [20] and has been used to enhance the sensitivity of denaturing gradient gel electrophoresis (DGGE) in the detection of point mutation [21-23]. DNA fragments for HA can be visualized via a variety of methods including bromide staining, labelling with radioisotopes and silver staining. The mutations

Heteroduplex differ from homoduplex by electrophoretic migration speed in polyacrylamide gel. Mutational alteration of a single base pair is sufficient to produce changes in mobility. Electrophoretic mobility of heteroduplex is lower than that of homoduplex, and it can be detected as a slower migrating band. This method can detect insertions, deletions and

The working protocol for this technique is very simple and quick and consists of a denatura‐ tion-renaturation step for which we set the following conditions: 94°C – 1 minute, 72°C – 1 minute, 65°C – 1 minute, 40°C – 1 minute and thermal shock at 4°C. Each stage is covered by one cycle. The existence of deletion mutations will result in the formation of four bands, two

Migration occurs differently based on molecular weight. Samples from patients and healthy individuals (control samples) are migrated in the same gel, in order to analyze the difference in migration. If the investigated individual is a normal homozygous or a homozygous for analyzed mutation, a single band will be displayed in each case. The difference between these conditions is based on different migration and reported to the molecular weight marker used. If there is a substitution mutation, two bands are visualized on polyacrylamide gel: a band representing heteroduplex and a band representing homoduplex. In this case, the difference in migration is explained on the basis of different chemical composition of the four DNA

substitutions of even a single base pair in fragment lengths smaller than 200 bp.

heteroduplex and two homoduplex (heterozygous condition) (Figure 1).

detection rate of HA under ideal conditions is near 90%.

the heteroduplex analysis (HA).

406 Colorectal Cancer - Surgery, Diagnostics and Treatment

particular fragment are used.

In the latter stages of a PCR amplification the polymerase is limiting, so that during the final annealing and synthesis steps, a proportion of the single stranded products spontaneously reanneals without primer extension. When amplifying from individuals heterozygous for any sequence difference, the single strands do not necessarily rehybridize exactly with the complementary strand. They can alternatively form a DNA hybrid (heteroduplex) consisting of a sense strand with one sequence variant and an antisense strand with another variant.

As a consequence, the heteroduplex DNA has a region of at least one base pair mismatch. The region of mismatch can elicit a mobility shift by altering the conformation adopted by the heteroduplex DNA, probably by causing it to bend at the location of the mismatch. The mobility shifts are usually small but can be visualized after prolonged electrophoresis on native polyacrylamide gels.

**Figure 1.** Denaturation and renaturation of normal and mutated DNA fragments in order to generate four types of fragments: two heteroduplex and two homoduplex. Fragments were migrated parallel on denaturating gradient gel. "Melting" heteroduplex are modified in the sense that they denaturate at a lower concentration of denaturant, allow‐ ing their visualization.


**11.** Added 200 μl of ethanol to lysate and vortex.

then with 500 μl of Buffer AW2 at 10,000 x g for 1 minute.

**7. DNA tissue extraction from colorectal biopsy**

minute.

is the source of DNA.

**•** Resin-capture DNA;

**•** Magnetic resin-washing;

**•** Elution of DNA from the resin.

**12.** Content was applyed in a column of centrifugation and centrifuged at 10,000 x g for 1

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

http://dx.doi.org/10.5772/57327

409

**13.** The column was washed once with 500 μl of Buffer AW1 at 10,000 x g for 1 minute and

**14.** DNA was eluted from the column at 10,000 x g, 1 minute, with 100 μl heated buffer AE.

DNA extraction from biological product was performed with DNA kit IQTM System, manu‐ factured by Promega, USA. DNA IQTM System is a kit that uses a new DNA extraction principle based on the use of paramagnetic resin. In addition, the kit contains a number of denaturating agents ("lysis buffer") which are designed to disintegrate biological product that

For some biological products (hair, tissue) which are resistant to this type of disintegration, an additional pretreatment with proteinase K is used, an enzyme that produces sample lysis.

A considerable advantage of this kit is that it provides an optimal quantity of DNA extraction

Used magnetic resin binds only a limited amount of DNA even if it is in excess. Finally, DNA is eluted from the resin with 100 μl of eluent solution yielding a final concentration of 1 ng/μl.

**2.** We added 50-100 μl of incubation buffer solution/freshly prepared proteinase K and incubated at 56°C for 2 hours. Usually all tissue is digested after 2 hours, and if it doesn't

**3.** We removed the source sample incubation and added 2 volumes of lysis buffer.

for PCR reaction, respectively 100 ng/μl, regardless of used biological product.

Thus, it is no longer necessary to quantify the amount of extracted DNA.

In principle extraction kit use the following steps:

**8. Purification of DNA from a tissue sample**

**1.** We place about 1 mg of tissue in a 1.5 ml tube.

occur, incubation is extended.

**•** Extraction of the sample and its lysis;


### **5. DNA extraction from proposed samples**

DNA extraction from stool has been made by a specific kit for stool extraction [24, 25]. DNA tissue extraction from the colorectal biopsy has been performed using DNA IQ (TM) System kit [26]. DNA IQ (TM) System kit uses the principle of DNA extraction based on a paramagnetic resine. In addition, the kit contains a series of denaturating agents ("lysis buffer"), having the role of disintegrating the biologic product that is the DNA source.

An important advantage of this kit is that it provides extraction of an optimal DNA quantity for PCR reaction (100 ng/μl).

## **6. DNA extraction from stool**

DNA extraction from stool was performed with a kit designed for extraction from faeces (QIAGEN GmbH, Hilden Germany). The technique included the following steps:


**11.** Added 200 μl of ethanol to lysate and vortex.

**1.** Detection of *COL11A1* gene mutations included the following steps:

**3.** Amplification of the interested gene amplicons through PCR reaction;

biopsy and exfoliated cells from feces;

408 Colorectal Cancer - Surgery, Diagnostics and Treatment

**5. DNA extraction from proposed samples**

**2.** 1.6 ml of this lysate was transferred to a new tube.

**4.** Centrifuged at maximum speed for 1 minute.

**3.** Suspension was boiled for 5 minutes.

**7.** Centrifuged the tube for 3 minutes.

**9.** Added 200 μl of Buffer AL and vortex.

**10.** Incubated at 70°C for 10 minutes.

role of disintegrating the biologic product that is the DNA source.

staining;

staining.

for PCR reaction (100 ng/μl).

**6. DNA extraction from stool**

**2.** Genomic DNA extraction from the analyzed samples: tumor tissue obtained through

**4.** Amplification check up through electrophoresis in agarosis gel and bromide ethidium

**5.** Mutations identification through DGGE technique and silver or ethidium bromide

DNA extraction from stool has been made by a specific kit for stool extraction [24, 25]. DNA tissue extraction from the colorectal biopsy has been performed using DNA IQ (TM) System kit [26]. DNA IQ (TM) System kit uses the principle of DNA extraction based on a paramagnetic resine. In addition, the kit contains a series of denaturating agents ("lysis buffer"), having the

An important advantage of this kit is that it provides extraction of an optimal DNA quantity

DNA extraction from stool was performed with a kit designed for extraction from faeces

(QIAGEN GmbH, Hilden Germany). The technique included the following steps:

**1.** 200 mg of faeces were suspended in 2 ml of ASL buffer by vortexing for 1 minute.

**5.** Transfered 1.2 ml of supernatant into a new tube containing an InhibitEX tablet. **6.** Vortexed the tube for 1 minute and incubated for 1 minute at room temperature.

**8.** Transfered 200 μl of supernatant into a new tube containing 15 μl of proteinase K.


## **7. DNA tissue extraction from colorectal biopsy**

DNA extraction from biological product was performed with DNA kit IQTM System, manu‐ factured by Promega, USA. DNA IQTM System is a kit that uses a new DNA extraction principle based on the use of paramagnetic resin. In addition, the kit contains a number of denaturating agents ("lysis buffer") which are designed to disintegrate biological product that is the source of DNA.

For some biological products (hair, tissue) which are resistant to this type of disintegration, an additional pretreatment with proteinase K is used, an enzyme that produces sample lysis.

A considerable advantage of this kit is that it provides an optimal quantity of DNA extraction for PCR reaction, respectively 100 ng/μl, regardless of used biological product.

Used magnetic resin binds only a limited amount of DNA even if it is in excess. Finally, DNA is eluted from the resin with 100 μl of eluent solution yielding a final concentration of 1 ng/μl. Thus, it is no longer necessary to quantify the amount of extracted DNA.

In principle extraction kit use the following steps:


## **8. Purification of DNA from a tissue sample**


**4.** We added 7 μl of magnetic resin. The sample was vortex 3 seconds and left at room temperature for 5 minutes.

For the DNA typing in our cases, we used a number of 9 STR loci. Determination of the 9 loci can be made by using kits of molecular biology, forming GenePrintSTR Systems of Multiplex

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**10. Amplification of the interested gene amplicons through PCR reaction**

Primers the analysis of all the 68 exons of *COL11A1* gene are not yet available. We managed to obtain sequence for primers of two groups of amplicons containing amplified segments in

PCR reactions were done simultaneously for each of the two groups above. We used PCR amplification kit manufactured by Promega (USA) called "PCR Core System". It was designed

to enhance any type of amplicon, by usind standard type Taq polymerase.

exons where most frequently mutations in various cancers were found.

type.

Amplification groups are:

**◦** Amplicon 38; **◦** Amplicon 41; **◦** Amplicon 16.

**◦** Amplicon 54; **◦** Amplicon 55; **◦** Amplicon 56; **◦** Amplicon 57.

Materials required:

**•** microcentrifuge;

**•** Mineral Oil;

**•** Ice.

**•** Taq DNA polymerase; **•** Nucleases-free water;

**•** 0.2 ml Amplification tubes; **•** 1.5 ml microcentrifuge tubes;

**•** Anti-aerosol pipette tips;

**•** Thermal cicler for 0.2 ml tubes;

**•** Group 1:

**•** Group 2:


## **9. Validation of human origin of DNA extracted from stool by STR loci typing**

The analysis of the nuclear DNA extracted from stools is a recent new method for CRC diagnostics.

In the preliminary phase of our study, we comparatively analyzed the DNA extracted from the biopsy samples of the patients with the DNA extracted from the stool samples of the same patients. This comparative analysis was performed by investigating a number of 9 human STR loci, frequently used in the DNA typing techniques of forensic medicine.

The STR type loci ("short tandem repeat" or "microsatellite repeats") contain 4 bases of segments that repeat 5-50 folds, depending on the loci. These STR are of a very small size (100-400 bases) and are very useful for the degraded DNA analysis. These repetitive sequences are largely spread in the human genome, being a rich source of polymorphic markers that may be detected through PCR.

For the DNA typing in our cases, we used a number of 9 STR loci. Determination of the 9 loci can be made by using kits of molecular biology, forming GenePrintSTR Systems of Multiplex type.

## **10. Amplification of the interested gene amplicons through PCR reaction**

Primers the analysis of all the 68 exons of *COL11A1* gene are not yet available. We managed to obtain sequence for primers of two groups of amplicons containing amplified segments in exons where most frequently mutations in various cancers were found.

Amplification groups are:

**•** Group 1:

**4.** We added 7 μl of magnetic resin. The sample was vortex 3 seconds and left at room

**5.** Then the simple was vortex for 2 seconds and left the tube on the magnetic stand.

**6.** Carefully we aspirated all the solution without disturbing the resin at the bottom of the

**7.** We add 100 μl of prepared lysis buffer. We removed the tube from the magnetic stand

**9.** Added 100 μl of Wash Buffer preparation. We removed the tube from the magnetic stand

**13.** We added 25-100 μl of elution buffer, depending on the amount of biological material

**15.** Removed the tube from the heating device, vortexed 2 seconds and immediately puted

**14.** Then we closed the lid and vortexed 2 seconds. We incubated at 65°C for 5 minutes.

**16.** Finally, we aspirated DNA containing solution and left the tube in conservation.

**9. Validation of human origin of DNA extracted from stool by STR loci**

The analysis of the nuclear DNA extracted from stools is a recent new method for CRC

In the preliminary phase of our study, we comparatively analyzed the DNA extracted from the biopsy samples of the patients with the DNA extracted from the stool samples of the same patients. This comparative analysis was performed by investigating a number of 9 human STR

The STR type loci ("short tandem repeat" or "microsatellite repeats") contain 4 bases of segments that repeat 5-50 folds, depending on the loci. These STR are of a very small size (100-400 bases) and are very useful for the degraded DNA analysis. These repetitive sequences are largely spread in the human genome, being a rich source of polymorphic markers that may

loci, frequently used in the DNA typing techniques of forensic medicine.

**12.** Tubes were allowed in the magnetic stand with the lid open for 5 minutes to dry.

**8.** Placed the tube again on the magnetic stand and vacuum lysis buffer.

**10.** We replaced the tube in the magnetic stand and aspirated the solution.

**11.** We repeated steps 9 and 10, 2 times to make a total of three washes.

temperature for 5 minutes.

410 Colorectal Cancer - Surgery, Diagnostics and Treatment

Separation occured instantly.

and vortex 2 seconds.

and vortex 2 seconds.

the tube on the magnetic stand.

tube.

used.

**typing**

diagnostics.

be detected through PCR.

	- **◦** Amplicon 54;
	- **◦** Amplicon 55;
	- **◦** Amplicon 56;
	- **◦** Amplicon 57.

PCR reactions were done simultaneously for each of the two groups above. We used PCR amplification kit manufactured by Promega (USA) called "PCR Core System". It was designed to enhance any type of amplicon, by usind standard type Taq polymerase.

Materials required:


## **11. Thermal cycling protocol**

Manufacturing company recommends several types of thermal cycling protocols and the choice depends on the thermo-cicler and optimized version that has been established. We have optimized the following protocol – protocol *COL11A1*:

**PCR Master Mix Component Volume per sample (μl)**

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**1.** In order from above table lay the final volume of each reagent in a sterile tube. Shake

**3.** Pipette 2.5 μl of each DNA sample to respective tubes containing 22.5 μl of PCR Master

**4.** Pipette 2.5 μl (5 ng) of K562 DNA (diluted to 2 ng/μl) in a reaction tube containing 22.5

**5.** Pipette 2.5 μl of sterile distilled water (instead of DNA) in a reaction tube containing 22.5

For this complex electrophoresis technique, we used a device type "DCode Universal Mutation

Protocol consists of a denaturation-renaturation step of PCR sample obtained from normal witness mixed with PCR sample from analyzed patient was established under the following

**2.** Add 22.5 μl of PCR Master Mix to each reaction tube and place tubes on ice.

MgCl2 25 mM sol. 1.5 10X Buffer Taq DNA Polymerase 2.5 PCR Nucleotide mix, 10 mM 0.5 "Primer Upstream", 15 μM 1.65 "Primer "Downstream", 15 μM 1.65 Taq DNA Polymerase (at 5 u/μl) 0.12 Distilled water without nucleases 17.08 Total volume 22.5

**Table 1.** Preparation of PCR Master Mix.

Mix.

conditions:

**•** 94°C – 1 minute; **•** 72°C – 1 minute;

gently (not vortex) and place the tube on ice.

μl of PCR Master Mix, which is a positive control.

μl of PCR Master Mix, which is a negative control. **6.** Add 1 drop of mineral oil to each tube. Close the tubes.

**9.** After amplification, the tubes must be kept at –20°C.

Detection System" manufactured by Bio-Rad (Germany).

**12.2. Formation reaction of heteroduplex**

**7.** Centrifuge tubes to bring the contents to the bottom of the tube.

**8.** Assemble the tubes in thermal triggers cicler and start amplification.

**12.1. Electrophoresis of amplified samples for evidence heteroduplex**


Repeated successive steps 1, 2 and 3, in 5 cycles.


Repeated successive steps 4, 5 and 6, in 5 cycles.


## **12. Amplification setting**

To prevent contamination it is strongly recommended the use of gloves and anti-aerosol pipette tips. Maneuvers that must be cosidered are as follows:



**Table 1.** Preparation of PCR Master Mix.

**11. Thermal cycling protocol**

412 Colorectal Cancer - Surgery, Diagnostics and Treatment

**•** Step 1: 94°C, 1 minute;

**•** Step 2: 52°C, 1 minute;

**•** Step 3: 72°C, 1 minute;

**•** Step 4: 94°C, 1 minute;

**•** Step 5: 50°C, 1 minute;

**•** Step 6: 72°C, 1 minute;

**•** Step 7: 94°C, 1 minute;

**•** Step 8: 48°C, 1 minute;

**•** Step 9: 72°C, 1 minute;

**•** Step 11 (rest): 4°C.

final volume.

**•** Step 10: 72°C, 3 minutes;

**12. Amplification setting**

optimized the following protocol – protocol *COL11A1*:

Repeated successive steps 1, 2 and 3, in 5 cycles.

Repeated successive steps 4, 5 and 6, in 5 cycles.

Manufacturing company recommends several types of thermal cycling protocols and the choice depends on the thermo-cicler and optimized version that has been established. We have

To prevent contamination it is strongly recommended the use of gloves and anti-aerosol

**3.** Determine the number of reactions to be performed. This number must include the positive and negative control reaction, respectively. Add to this number another 1-2

**4.** Prepare the amplification (PCR Master Mix) solution, according to the table below (table 1). Multiply the volume per sample (μl) with the total number of reactions, to obtain the

pipette tips. Maneuvers that must be cosidered are as follows:

**2.** Mark each 0.2 ml amplification tube and place it in the stand.

reactions in addition, to compensate for pipetting errors.

**1.** Defrost kit components and pairs of primers and then put them on ice.


#### **12.1. Electrophoresis of amplified samples for evidence heteroduplex**

For this complex electrophoresis technique, we used a device type "DCode Universal Mutation Detection System" manufactured by Bio-Rad (Germany).

#### **12.2. Formation reaction of heteroduplex**

Protocol consists of a denaturation-renaturation step of PCR sample obtained from normal witness mixed with PCR sample from analyzed patient was established under the following conditions:


Heteroduplex are generated by adding to the same PCR reaction the mold of mutant and normal DNA, or by PCR product mixing, denaturation and ultimately their renaturation. A heteroduplex contains a mismatch base in the double chain, causing a distortion in its confor‐ mation; bands containing heteroduplex always migrates more slowly compared to bands containing homoduplex.

We added water to 40 ml. Pour gel immediately after adding TEMED and ammonium

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**1.** It is important that PCR is optimized to decrease the formation of artifact products that may interfere with test itself. PCR products should be assessed for purity by agarose gel

**2.** On gel we applied 180-300 ng of amplified DNA per well. On each gel and for each

amplicon there were joined migration of the sample and normal DNA.

**3.** At each sample, we added a volume of 2X sample application solution.

electrophoresis before being used for electrophoresis.

persulphate.

**•** 50X TAE buffer:

**◦** Tris base 242.0 g;

**◦** water dist. 1 ml;

**•** Staining solution DCode;

**◦** xylene cyanol 0,05 g; **◦** 1X TAE buffer 10 ml;

**◦** bromophenol blue 0.05 g;

**•** Solution for implementing samples: **◦** bromophenol blue 0.25 ml 2%;

**◦** xylene cyanol 0.25ml 2%;

**•** 1.25 X TAE buffer migration: **◦** 50X TAE buffer 175 ml;

**◦** glycerol 7.0 ml;

**◦** water dist. 2.5 ml;

**◦** water dist. 6825 ml.

**13. Sample preparation**

**◦** glacial acetic acid 57.1 ml;

**◦** water dist. ad. 1000 ml. **•** Ammonium persulfate 10%:

**◦** 0.5M EDTA, pH 8.0, 100 ml;

**◦** ammonium persulfate 0.1 g;

#### **12.3. Preparation of reagents**

Acrylamide concentration used generally depends on the sample to be analyzed, and we used a 40% stock solution containing acrylamide and bis-acrylamide.


In the table below (table 2) we present the concentration of acrylamide/bis used to separate different DNA molecules:


**Table 2.** Concentration of acrylamide/bis used to separate DNA molecules.

We worked with a solution of acrylamide/bis 6%, given the length of amplified fragments.


We added water to 40 ml. Pour gel immediately after adding TEMED and ammonium persulphate.

**•** 50X TAE buffer:

**•** 65°C – 1 minute;

414 Colorectal Cancer - Surgery, Diagnostics and Treatment

**•** 40°C – 1 minute;

**•** heat shock at 4°C.

containing homoduplex.

**•** Acrylamide – 38.9 g;

**•** Bis-acrylamide – 1.07 g;

**•** Water dist. – ad. 100 ml.

different DNA molecules:

**•** Acrylamide/Bis 40% 6.0 ml;

**•** Ammonium persulfate 10% 400.0 μl;

**•** 50X TAE buffer 1 ml;

**•** Total volume 40 ml.

**•** Urea 14.4 g;

**•** TEMED 40 μl;

**12.3. Preparation of reagents**

**•** Acrylamide/Bis – 40% (37.5:1);

Heteroduplex are generated by adding to the same PCR reaction the mold of mutant and normal DNA, or by PCR product mixing, denaturation and ultimately their renaturation. A heteroduplex contains a mismatch base in the double chain, causing a distortion in its confor‐ mation; bands containing heteroduplex always migrates more slowly compared to bands

Acrylamide concentration used generally depends on the sample to be analyzed, and we used

In the table below (table 2) we present the concentration of acrylamide/bis used to separate

**Gel concentration Separation of base pairs** 6% 300-1000 bp 8% 200-400 bp 10% 100-300 bp

We worked with a solution of acrylamide/bis 6%, given the length of amplified fragments.

a 40% stock solution containing acrylamide and bis-acrylamide.

**Table 2.** Concentration of acrylamide/bis used to separate DNA molecules.

**•** Acrylamide/Bis solutions, 6% (1.25 x TAE, 6M urea);

	- **◦** ammonium persulfate 0.1 g;
	- **◦** water dist. 1 ml;
	- **◦** bromophenol blue 0.05 g;
	- **◦** xylene cyanol 0,05 g;
	- **◦** 1X TAE buffer 10 ml;
	- **◦** bromophenol blue 0.25 ml 2%;
	- **◦** xylene cyanol 0.25ml 2%;
	- **◦** glycerol 7.0 ml;
	- **◦** water dist. 2.5 ml;
	- **◦** 50X TAE buffer 175 ml;
	- **◦** water dist. 6825 ml.

## **13. Sample preparation**


#### **13.1. Preheating migration buffer**


**4.** Poured the gel solution into the sandwich until comb teeth were covered. Then pressed

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**5.** We allowed the gel to polymerize for 60 minutes. After polymerization we carefully

**2.** After the temperature was reached by the migration buffer (60°C) we disconnected

**3.** Removed the temperature module from the electrophoresis tank. Gel fitting with gel electrophoresis was introduced into the tank and the temperature module was placed

**4.** Filled the volume of migration buffer until the level mark on the camera, and added also

**5.** Before applying the samples we left the machine running again to reach a migration

**6.** Applied the samples after each well was previously rinsed with buffer. Sample application

**7.** Samples prepared as described above were applyed by automated pipetting carefully so

**8.** Closed the device and connected to the source. Migration was 5 hours at a voltage of 5 V/

Electrophoresis was performed after the gel is removed from the tank, and glass plates carefully unfold. The gel sticks to the glass plate. Staining can be done by two procedures: simple procedure with Ethidium Bromide and fluorescence examination or staining procedure

Protocol described below is an adaptation of that offered by the company with the Promega

was made through a specially designed device that is provided.

the comb in its correct position. Solution was added to the filling.

**1.** Electrophoresis tank must contain 7 liters of buffer migration.

removed the comb.

again into position.

temperature of 60°C.

Argent. We opted for the second.

kit "DNA Silver Staining System".

**•** 20 G Silver Nitrate (10 x 2g);

**•** 60 Ml Formaldehyde, 37% (20 x 3 ml);

**•** 10 Ml Sodium thiosulfate, 10 mg/ml (10 x 1 ml);

cm.

**13.5. Gel staining**

**•** 500μl Bind silane;

temperature maintenance system.

into the anode upper chamber.

that they do not spread outside the wells.

A kit contains the following ingredients required for 10 stains:

**13.4. Migrating samples**

#### **13.2. Assemble gel sandwich**

Casting procedure is extremely laborious and is was done by strict electrophoresis guidelines provided by equipment manufacturer. A system of 16x16cm plates was used and the prepared gel was "sandwich" type.


#### **13.3. Casting the gel**


#### **13.4. Migrating samples**

**13.1. Preheating migration buffer**

416 Colorectal Cancer - Surgery, Diagnostics and Treatment

**13.2. Assemble gel sandwich**

gel was "sandwich" type.

edge.

**13.3. Casting the gel**

performed.

by inversion.

comb teeth.

**1.** Electrophoresis tank was filled with a quantity of 7 L of 1X TAE buffer.

have set the spacers on the short edges of this plate.

**4.** We tightened the clamps so that the glass plates were well fixed.

plates alignment plate which serves to align the spacers.

so that the arrows were facing upwards.

**2.** We placed the temperature control module above the electrophoresis tank.

wereneeded. If the buffer is preheated in the oven, this time can be reduced.

**3.** Then we adjusted the temperature to 60°C. To achieve this temperature 1-1.5 hours

Casting procedure is extremely laborious and is was done by strict electrophoresis guidelines provided by equipment manufacturer. A system of 16x16cm plates was used and the prepared

**1.** "Sandwich" gel is mounted on a clean surface. We have placed large plate first, then we

**2.** Lower plate was disposed over the large plate so the bottom was flush with large plate

**3.** We loosen the black screw of the two sandwich cutters. We placed plates in these pliers

**5.** Sandwich assembly was inserted into the alignment (without clips into place) so short board was facing forward. We loosen the clips and clamps easily inserted between the

**6.** We aligned the plates and spacers by moving laterally and obliquely claws. We must ensure that the spacers are perfectly parallel and the lower edge of the two plates was perfectly aligned. We tightened the screw clamps for immobilizing overall assembly. **7.** We removed the plate alignment between glass plates. Then we removed the sandwich from the stand and check the lower edges of the plates and spacers are aligned perfectly.

**1.** We placed the gray foam in the space provided for pouring the gel. Pins of the base were completely relaxed. Placed plates mounted on the lower plate to the front pad. After it was placed correctly by turning the cam, pressing the lower edge of the foam boards was

**2.** In a 50 ml tube we puted the required amount of gel solution. Ammonium persulfate and TEMED were added to a final concentration of 0.09% (v/v). Stopped the tube and mixed

**3.** We inserted the comb into sandwich and positioned it so that it was slightly bent (angle) to the edge boards. This prevented the formation of air bubbles between the gel and the


#### **13.5. Gel staining**

Electrophoresis was performed after the gel is removed from the tank, and glass plates carefully unfold. The gel sticks to the glass plate. Staining can be done by two procedures: simple procedure with Ethidium Bromide and fluorescence examination or staining procedure Argent. We opted for the second.

Protocol described below is an adaptation of that offered by the company with the Promega kit "DNA Silver Staining System".

A kit contains the following ingredients required for 10 stains:


**•** 600 G Sodium Carbonate (10 x 60g).

#### **13.6. Materials required**

	- **◦** 200 ml glacial acetic acid;
	- **◦** 1800 ml distilled water;
	- **◦** silver nitrate (AgNO3) 2 g;
	- **◦** 3 ml 37% formaldehyde;
	- **◦** 2000 ml distilled water;
	- **◦** 3 ml 37% formaldehyde;
	- **◦** Sodium thiosulfate 10 mg/ml, (Na2S2O3 x 5H2O) 400 μl ;
	- **◦** 2000 ml distilled water;
	- **◦** sodium carbonate (Na2CO3) 60 g.

We prepared the solution just in time to use it, cooled at 4-10°C before use.

## **14. Technique used**

**1.** Gel plates were placed on a flat surface. With a plastic "feather" glass was removed. The gel was caught on the short board.

\*Solution was added directly above solution developer to stop the developer reaction.

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**15. Mutations identification through DGGE technique and silver or**

type (same in all cases) and the other representing the analyzed case.

After amplification the samples were checked to confirm successful amplification by agarose gel electrophoresis. For migration were applied two tests, one that was considered the normal

To see if amplifyed amplicons in the studied cases presented mutations, we used samples

examined by agarose gel electrophoresis, for electrophoresis on polyacrylamide 6%.

Statistical analysis was performed using Graph Pad InState and Graph Pad State Mate.

Demographic and clinical characteristics of patients examined during study period were as

Histopathological classification and localization of tumors in patients investigated through colonoscopy and biopsy referred to genetic analysis of *COL11A1* mutations can be seen in

From the total of 250 patients genetically explored, 178 (71.20%) were diagnosed with adeno‐ carcinoma and TNM staged after hiistopathological and imagistic examinations. Most of the

We analyzed 51 patients diagnosed with advanced adenomatous polyps. Polyps were classified according to hiistopathological features in: 26 polyps with high-grade dysplasia (10.40%), 17 villous adenoma (6.80%), and 8 tubular adenoma bigger than 1 cm (3.20%).

Among the 250 patients studied, 178 had adenocarcinomas, 51 had advanced adenomas, and

The plan for *COL11A1* analyses in feces or biopsy has been described previously and is shown

All samples analyzed for fecal *COL11A1* mutations were processed in a single laboratory.

patients were staged as stage II or III (18.80%, respectively 23.60%).

**4.** We placed the gel upright and dry overnight.

**ethidium bromide staining**

**16. Statistical analysis**

**17. Results**

follows (table 3).

the rest 21 had minor polypspolyps.

table 4.

in figure 2.

	- **a.** fixing /stop solution 20 minutes;
	- **b.** distilled water 2 minutes;
	- **c.** Repeat step "b" 2 times 2 x 2 minutes;
	- **d.** staining solution 30 minutes;
	- **e.** distilled water 10 seconds;
	- **f.** developing solution (4-10°C) up to 5 minutes (to become visible Ladder allele);
	- **g.** fixing/stop solution\* 5 minutes;
	- **h.** distilled water 2 minutes;

\*Solution was added directly above solution developer to stop the developer reaction.

**4.** We placed the gel upright and dry overnight.

## **15. Mutations identification through DGGE technique and silver or ethidium bromide staining**

After amplification the samples were checked to confirm successful amplification by agarose gel electrophoresis. For migration were applied two tests, one that was considered the normal type (same in all cases) and the other representing the analyzed case.

To see if amplifyed amplicons in the studied cases presented mutations, we used samples examined by agarose gel electrophoresis, for electrophoresis on polyacrylamide 6%.

## **16. Statistical analysis**

Statistical analysis was performed using Graph Pad InState and Graph Pad State Mate.

### **17. Results**

**•** 600 G Sodium Carbonate (10 x 60g).

418 Colorectal Cancer - Surgery, Diagnostics and Treatment

**13.6. Materials required**

**•** Fixing solution/stop:

**•** Coloring solution:

**•** Developing solution:

**14. Technique used**

**◦** 200 ml glacial acetic acid; **◦** 1800 ml distilled water;

**◦** silver nitrate (AgNO3) 2 g; **◦** 3 ml 37% formaldehyde; **◦** 2000 ml distilled water;

**◦** 3 ml 37% formaldehyde;

**◦** 2000 ml distilled water;

**◦** sodium carbonate (Na2CO3) 60 g.

gel was caught on the short board.

**3.** Argent coloring followed few steps:

**b.** distilled water – 2 minutes;

**d.** staining solution – 30 minutes;

**g.** fixing/stop solution\* – 5 minutes;

**e.** distilled water – 10 seconds;

**h.** distilled water – 2 minutes;

**a.** fixing /stop solution – 20 minutes;

**c.** Repeat step "b" 2 times 2 x 2 minutes;

**◦** Sodium thiosulfate 10 mg/ml, (Na2S2O3 x 5H2O) 400 μl ;

**2.** The gel attached on short plate was placed in a plastic tray.

We prepared the solution just in time to use it, cooled at 4-10°C before use.

**1.** Gel plates were placed on a flat surface. With a plastic "feather" glass was removed. The

**f.** developing solution (4-10°C) up to 5 minutes (to become visible Ladder allele);

Demographic and clinical characteristics of patients examined during study period were as follows (table 3).

Histopathological classification and localization of tumors in patients investigated through colonoscopy and biopsy referred to genetic analysis of *COL11A1* mutations can be seen in table 4.

From the total of 250 patients genetically explored, 178 (71.20%) were diagnosed with adeno‐ carcinoma and TNM staged after hiistopathological and imagistic examinations. Most of the patients were staged as stage II or III (18.80%, respectively 23.60%).

We analyzed 51 patients diagnosed with advanced adenomatous polyps. Polyps were classified according to hiistopathological features in: 26 polyps with high-grade dysplasia (10.40%), 17 villous adenoma (6.80%), and 8 tubular adenoma bigger than 1 cm (3.20%).

Among the 250 patients studied, 178 had adenocarcinomas, 51 had advanced adenomas, and the rest 21 had minor polypspolyps.

All samples analyzed for fecal *COL11A1* mutations were processed in a single laboratory.

The plan for *COL11A1* analyses in feces or biopsy has been described previously and is shown in figure 2.


**I. Genomic DNA extraction from the analyzed samples**

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

**II. Amplification of the interested gene amplicons through PCR reaction**

**III . Electrophoresis of amplified samples for heteroduplex evidence**

**IV . DGGE analysis of** *COL11A1* **gene mutations through DNA heteroduplexes**

We considered a positive result any modified component of the study gene, and we noted any

*COL11A1* is located on chromosome 1p21 and consists of 232,030 bases. It contains 68 exons, yet not wholly sequenced, of which exons 38, 41, 16, 54, 55, 56 and 57 were until now studied.

**Figure 2.** Approach to Extraction and Analysis of Fecal and Tumor DNA analysis.

Also laboratory handling of all samples was fully described above.

Each exon of gene *COL11A1* studied was assessed independently.

**18. DGGE analysis of** *COL11A1* **gene mutations through DNA**

mutation as a positive fecal DNA test.

HE analysis for exons 38, 41 and 16

**heteroduplexes**

**Exfoliated cells from feces**

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**Validation of human origin of DNA extracted from stool by STR loci typing**

**Tumor tissue obtained through biopsy**

**Purification of DNA from a tissue sample**

**Table 3.** Demographic characteristics of patients enrolled in the study.


**Table 4.** Hiistopathological classification and tumor localization.

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk http://dx.doi.org/10.5772/57327 421

**Figure 2.** Approach to Extraction and Analysis of Fecal and Tumor DNA analysis.

Also laboratory handling of all samples was fully described above.

Each exon of gene *COL11A1* studied was assessed independently.

We considered a positive result any modified component of the study gene, and we noted any mutation as a positive fecal DNA test.

## **18. DGGE analysis of** *COL11A1* **gene mutations through DNA heteroduplexes**

*COL11A1* is located on chromosome 1p21 and consists of 232,030 bases. It contains 68 exons, yet not wholly sequenced, of which exons 38, 41, 16, 54, 55, 56 and 57 were until now studied.

HE analysis for exons 38, 41 and 16

**Characteristic No. %**

Mean (yr) 67.44 ± 8.97 20.40 40-49 51 31.60 50-59 79 34.80 60-69 87 9.20 70-79 23 4.00

Male 189 75.60 Female 61 24.4

Caucasians 203 81.20 Other 47 18.80

APC (adenomatous polyposis coli) 16 6.40 CRC 49 19.60 Other cancer 37 14.80 Without family history of cancer/polyps 148 59.20

> **Ascendinging Colon**

> > 41/178 [23.03] 6 [3.37] 7 [3.93] 14 [7.86] 14 [7.86]

12/51 [23.52] 8 [15.6] 3 [5.88] 1 [1.96]

3/21 [14.28] 1 [4.76] 1 [4.76] 1 [4.76] **Localisation – no./%**

62/178 [34.83] 12 [6.74] 18 [10.11] 22 [12.35] 10 [5.61]

16/51 [31.72] 7 [13.72] 5 [9.80] 4 [7.84]

5/21 [23.80] 2 [9.52] 3 [14.28] –

**colon Sigmoid Rectumum**

44/178 [24.71] 7 [3.93] 12 [6.74] 12 [6.74] 13 [7.30]

14/51 [27.45] 7 [13.72] 6 [11.76] 1 [1.96]

6/21 [28.57] 3 [14.28] 2 [9.52] 1 [0.56]

10/178 [4.00] 3 [1.68] 4 [2.24] 3 [1.68] 0 [0.00]

2/51 [3.92] – 2 [3.93] –

2/21 [9.52] – 2 [9.52] –

**Transvers Descendinging**

21/178 [11.79] 5 [2.80] 6 [3.37] 8 [4.49] 2 [2.23]

7/51 [13.72] 4 [7.84] 1 [1.96] 2 [3.93]

5/21 [23.80] 2 [9.52] 3 [14.28] –

≥ 80 10

420 Colorectal Cancer - Surgery, Diagnostics and Treatment

**Table 3.** Demographic characteristics of patients enrolled in the study.

**No./%**

178/250 [71.2] 33 [13.20] 47 [18.80] 59 [23.60] 39 [15.60]

51/250 [20.40] 26 [10.40] 17 [6.80] 8 [3.20]

21/250 [8.40] 9 [3.60] 10 [4.00] 2 [0.8]

**Table 4.** Hiistopathological classification and tumor localization.

**Age**

**Sex**

**Ethnicity**

**Family history**

**Histopathological feature**

**Adenocarcinoma** Stage TNM I Stage TNM II Stage TNM III Stage TNM IV

**Advanced adenoma** High-grade dysplasia Villous adenoma Tubular adenoma ≥ 1cm

**Minor polyps** Tubular adenoma <1cm Hiperplastic Unspecified

For all 3 analyzed amplicons in all 250 studied cases, the migration speed was identical for both control and samples.

**No. Pacient no. DNA sample**

16 46

17 48

18 56

19 59

20 74

21 78

22 84

23 89

24 93

25 96

26 104

27 107

28 109

29 116

30 119

31 121

32 129

33 132

**Mutations/amplicons 38 41 16 54 55 56 57**

http://dx.doi.org/10.5772/57327

423

Biopsy - - - + - - -

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

Faeces - - - + - Biopsy - - - + - + -

Biopsy - - - + - - - Faeces - - - + -

Biopsy - - - - - + - Faeces - - - + -

Biopsy - - - + - + - Faeces - - - - - + -

Biopsy - - - - - + + Faeces - - - - - + -

Biopsy - - - + - - - Faeces - - - + -

Biopsy - - - + - - - Biopsy - - - + - - -

Faeces - - - + - Biopsy - - - + - - -

Biopsy - - - + - - - Faeces - - - + -

Biopsy - - - + - + - Biopsy - - - + - - -

Faeces - - - + + Biopsy - - - + - - +

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - - - + -

Biopsy - - - + - - - Biopsy - - - + - - -

Faeces - - - + - - - Biopsy - - - + - - -

Biopsy - - - + - + - Faeces + - - -

Biopsy - - - + - - + Faeces - - - + - - +

Biopsy - - - + - - - Faeces - - - + - - -

Faeces - - - - - +

HE analysis for exons 54, 55, 56 and 57

HE analysis of exons 54 clearly demonstrated in 52 cases (20.80%) the presence of the same displaced bands pattern in the biopsy and stool extracted cells samples compared with the control. This pattern of mutation was correlated positively with male gender, TNM stage II/III tumors, vegetative pattern, descendent and sigmoid localization – table 5.


*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk http://dx.doi.org/10.5772/57327 423

For all 3 analyzed amplicons in all 250 studied cases, the migration speed was identical for

HE analysis of exons 54 clearly demonstrated in 52 cases (20.80%) the presence of the same displaced bands pattern in the biopsy and stool extracted cells samples compared with the control. This pattern of mutation was correlated positively with male gender, TNM stage

> **Mutations/amplicons 38 41 16 54 55 56 57**

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - - - + - Faeces - - - - - + -

Biopsy - - - + - - - Faeces - - - + - - +

Biopsy - - - + - - - Faeces - - - + - - +

Biopsy - - - + - - + Faeces - - - + - - +

Biopsy - - - + - - + Faeces - - - + - - -

Biopsy - - - - - + - Faeces - - - - - + -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - - - + - Faeces - - - + - + -

Biopsy - - - - - + - Faeces - - - - - + -

Biopsy - - - + - - - Faeces - - - + - - +

Biopsy - - - + - + - Biopsy - - - + - + -

Faeces - - - + - + - Biopsy - - - + - + -

Biopsy - - - + - + - Faeces - - - + + -

15 38 Biopsy - - - + - - -

II/III tumors, vegetative pattern, descendent and sigmoid localization – table 5.

both control and samples.

1 1

2 4

3 7

4 8

5 11

6 13

7 14

8 16

9 17

10 20

11 21

12 26

13 29

14 34

HE analysis for exons 54, 55, 56 and 57

422 Colorectal Cancer - Surgery, Diagnostics and Treatment

**No. Pacient no. DNA sample**



**No. Pacient no. DNA sample**

53 228

54 230

55 236

56 237

57 211

58 220

59 224

60 228

61 230

62 236

63 237

64 238

65 241

66 244

67 248

68 249

69 250

**Table 5.** Patients with *COL11A1* gene mutations

**Mutations/amplicons 38 41 16 54 55 56 57**

http://dx.doi.org/10.5772/57327

425

Faeces - - - + - - -

Biopsy - - - - - - - Biopsy - - - - - - -

Biopsy - - - + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - + Faeces - - - + - - -

Biopsy - - - - - - + Biopsy - - - - - - +

Faeces + - Biopsy - - - + - - -

Biopsy - - - + - - + Faeces + +

Biopsy - - - + - - - Faeces - - - + - - -

Faeces - - - - - - + Biopsy - - - - - - +

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - - - - + Biopsy - - - - - - +

Faeces - - - + - - + Biopsy - - - + - - +

Biopsy - - - + - - - Faeces - - - - - - -

Biopsy - - - + - - - Faeces - - - + - - -

Faeces - - - + - - - Biopsy - - - + - - -

Faeces - - - +

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk http://dx.doi.org/10.5772/57327 425


**Table 5.** Patients with *COL11A1* gene mutations

**No. Pacient no. DNA sample**

424 Colorectal Cancer - Surgery, Diagnostics and Treatment

34 134

35 138

36 143

37 146

38 147

39 159

40 166

41 168

42 171

43 177

44 179

45 182

46 189

47 201

48 203

49 208

50 211

51 220

**Mutations/amplicons 38 41 16 54 55 56 57**

Biopsy - - - + - + - Faeces - - - + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - + - Biopsy - - - + - + -

Faeces - - - - - + - Biopsy - - - - - + -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - - - + - Biopsy - - - - - + -

Faeces - - - + - + - Biopsy - - - + - + +

Biopsy - - - + - + - Faeces - - - + - + -

Biopsy - - - - - + - Faeces - - - - - + -

Biopsy - - - + - - - Biopsy - - - + - - -

Faeces - - - + - - - Biopsy - - - + - - -

Biopsy - - - + - - + Faeces - - - + - - +

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - - Faeces + - - -

Biopsy - - - + - - - Faeces - - - + - - -

Biopsy - - - + - - - Biopsy - - - + - - -

Faeces - - - - - + + Biopsy - - - - - + +

52 224 Biopsy - - - + - - -

We also noticed the same pattern of different speed migration in case of HE analysis of exon 56 in 18 patients (7.20%) and exon 57 in 11 patients (4.40%).

Statistic analysis revealed that the last two kind of mutations were correlated with tumor stage IV, male gender and advanced age (> 70 yrs old) – table 6.


**Table 6.** Correlation between hiistopathological examination and genetic analysis.

The migrating front presented two bands, out of which the slowest part generates the hetero‐ duplexes obtained through denaturation-renaturation, and the faster one, the homoduplexes (figure 3).

Among 229 patients with advanced neoplasia (tubular adenoma 1 cm in diameter or larger, villous polyp, polyps with high-grade dysplasia, or cancer), 69 patients (27.60%) presented

L – molecular weight ladder. M – healthy individual allele (control). P – unprocessed allele for exon 54. M+P – dena‐

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk

http://dx.doi.org/10.5772/57327

427

**Figure 3.** Electrophoresis in 6% polyacrylamid gel of the processed samples in order to point out heteroduplexes for

*COL11A1* gene overexpression has been implicated as a candidate marker of various types of cancers [26]. Previous studies have found overexpression of the *COL11A1* gene in different types of cancers, such as non-small cell lung (NSCLC), ovarian, oral cavity and colorectal cancers [13-16]. In particular, overexpression of the *COL11A1* gene was found to be correlated

As we previously detected in a pilot study regarding genetic mutations related to *COL11A1* gene in exfoliated epithelial cells in the stool, we found mutations involving exon 54 [27].

mutations in *COL11A1* gene in at least 1 exon (table no. 5 and 6).

**19. Disscusions and conclusions**

tured-renatured sample.

exon 54, using silver staining.

with invasion and metastasis of these cancers [13-16].

Regarding benign polyps, none of patients presented *COL11A1* mutations.

The samples were different from the wild type due to the fact that they contain amplified mutant type DNA, which through electrophoresis leads to speed migration modification.

The mutation detected by us is a substitutive type one as a series of 2 bands was evident on the migration front.

There were no seen mutations for the rest of the analyzed cases for the exon 55.

All detected mutations can be observed in table no. 5

*COL11A1* — Genetic Biomarker Targeted in Stool Samples for Early Diagnosis of Colorectal Cancer in Patients at Risk http://dx.doi.org/10.5772/57327 427

L – molecular weight ladder. M – healthy individual allele (control). P – unprocessed allele for exon 54. M+P – dena‐ tured-renatured sample.

**Figure 3.** Electrophoresis in 6% polyacrylamid gel of the processed samples in order to point out heteroduplexes for exon 54, using silver staining.

Among 229 patients with advanced neoplasia (tubular adenoma 1 cm in diameter or larger, villous polyp, polyps with high-grade dysplasia, or cancer), 69 patients (27.60%) presented mutations in *COL11A1* gene in at least 1 exon (table no. 5 and 6).

Regarding benign polyps, none of patients presented *COL11A1* mutations.

## **19. Disscusions and conclusions**

We also noticed the same pattern of different speed migration in case of HE analysis of exon

Statistic analysis revealed that the last two kind of mutations were correlated with tumor stage

Localisation Descendent/Sigmoid

The migrating front presented two bands, out of which the slowest part generates the hetero‐ duplexes obtained through denaturation-renaturation, and the faster one, the homoduplexes

The samples were different from the wild type due to the fact that they contain amplified mutant type DNA, which through electrophoresis leads to speed migration modification.

The mutation detected by us is a substitutive type one as a series of 2 bands was evident on

There were no seen mutations for the rest of the analyzed cases for the exon 55.

TNM classification Stage II/III

**Table 6.** Correlation between hiistopathological examination and genetic analysis.

All detected mutations can be observed in table no. 5

2 [2.89] 18 [26.08] 27 [39.13] 3 [4.34]

> 0 1 [1.44] 1 [1.44]

> > 0 0 0

> 70 yrs (p=0.0478, 95%CI 11.781-49.552)

M/F=3.72 (p=0.021, 95%CI 26.330-49.312)

CaucasianCaucasian/other (p=0.0037, 95%CI 14.114-49.226)

(p=0.02, 95%CI 29.481-50.227)

(p=0.009, 95%CI 7.336-39.386)

**Histopathological and clinical features** *COL11A1 mutations (No./%)*

56 in 18 patients (7.20%) and exon 57 in 11 patients (4.40%).

IV, male gender and advanced age (> 70 yrs old) – table 6.

Adenocarcinoma Stage TNM I Stage TNM II Stage TNM III Stage TNM IV

426 Colorectal Cancer - Surgery, Diagnostics and Treatment

Advanced adenoma High-grade dysplasia VillousVillous adenoma Tubular adenoma ≥1cm

Minor polyps Tubular adenoma <1cm HyperplasticHyperplastic Unspecified

Age (only for exon 56, 57)

Gender ratio

EthnicityEthnicity

(figure 3).

the migration front.

*COL11A1* gene overexpression has been implicated as a candidate marker of various types of cancers [26]. Previous studies have found overexpression of the *COL11A1* gene in different types of cancers, such as non-small cell lung (NSCLC), ovarian, oral cavity and colorectal cancers [13-16]. In particular, overexpression of the *COL11A1* gene was found to be correlated with invasion and metastasis of these cancers [13-16].

As we previously detected in a pilot study regarding genetic mutations related to *COL11A1* gene in exfoliated epithelial cells in the stool, we found mutations involving exon 54 [27].

Our present study confirmed the presence of *COL11A1* mutations in patients with colorectal adenomas or cancer. Polyacrylamide gel electrophoresis method for the heteroduplex analysis (HA) was a sensitive genetic method to diagnose mutations of *COL11A1*.

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Mutations detected in biopsy cells were present in exfoliated cells from feaces, proving the usefulness of this genetic approach for noninvasive early diagnosis. Genetic alterations were detected at the level of exons 54, 56 and 57.

Our results are similar with the results of other studies which have previously shown that *COL11A1* is upregulated in the majority of sporadic colorectal cancer [28], emphasizing the fact that the expression of *COL11A1* could be the primary change giving rise to a tumorigenic response in epithelial cells [28].


Joined by other well known genetic tools already examined in the stool cell's DNA involved in the development of some colorectal cancers, *COL11A1* could be a feasible genetic biomarker targeted in stool samples for early diagnosis of colorectal cancer at risk patients.

## **Acknowledgements**

This work was accomplished with the support of Professor Mixici Fr.

## **Author details**

Andra Iulia Suceveanu1 , Laura Mazilu2 and Adrian-Paul Suceveanu3

\*Address all correspondence to: andrasuceveanu@yahoo.com

1 Gastroenterology Department, Emergency Hospital of Constanta, Faculty of Medicine, Ovidius University of Constanta, Romania

2 Oncology Department, Emergency Hospital of Constanta, Faculty of Medicine, Ovidius University of Constanta, Romania

3 Internal Medicine Department, Emergency Hospital of Constanta, Faculty of Medicine, Ovidius University of Constanta, Romania

## **References**

Our present study confirmed the presence of *COL11A1* mutations in patients with colorectal adenomas or cancer. Polyacrylamide gel electrophoresis method for the heteroduplex analysis

Mutations detected in biopsy cells were present in exfoliated cells from feaces, proving the usefulness of this genetic approach for noninvasive early diagnosis. Genetic alterations were

Our results are similar with the results of other studies which have previously shown that *COL11A1* is upregulated in the majority of sporadic colorectal cancer [28], emphasizing the fact that the expression of *COL11A1* could be the primary change giving rise to a tumorigenic

**1.** Another study found a statistically significant overexpression of *COL11A1* in polyps from a patient with FAP [29]. The results from this study suggested that the expression of COL11A1 could directly contribute to tumorigenesis in fibroblasts in FAP and explain osteomas and desmoids, or indirectly to polyp-formation and tumor progression in

**2.** The study of Croner R et al [30] also showed up-regulation of *COL11A1* in CRC versus normal colonic mucosa (p<0.001). The same result was shown by Lascorz et al study, in which extracellular matrix receptor interaction and focal adhesion shared nine genes (*COL1A1, COL1A2, COL3A1, COL4A1, COL11A1, FN1, ITGA2, SPP1*, and *THBS2*) were

Joined by other well known genetic tools already examined in the stool cell's DNA involved in the development of some colorectal cancers, *COL11A1* could be a feasible genetic biomarker

and Adrian-Paul Suceveanu3

1 Gastroenterology Department, Emergency Hospital of Constanta, Faculty of Medicine,

2 Oncology Department, Emergency Hospital of Constanta, Faculty of Medicine, Ovidius

3 Internal Medicine Department, Emergency Hospital of Constanta, Faculty of Medicine,

targeted in stool samples for early diagnosis of colorectal cancer at risk patients.

This work was accomplished with the support of Professor Mixici Fr.

, Laura Mazilu2

\*Address all correspondence to: andrasuceveanu@yahoo.com

Ovidius University of Constanta, Romania

Ovidius University of Constanta, Romania

University of Constanta, Romania

(HA) was a sensitive genetic method to diagnose mutations of *COL11A1*.

detected at the level of exons 54, 56 and 57.

428 Colorectal Cancer - Surgery, Diagnostics and Treatment

upregulated in colorectal cancer [31].

response in epithelial cells [28].

sporadic CRC [29].

**Acknowledgements**

**Author details**

Andra Iulia Suceveanu1


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**Chapter 17**

**The Complexity of Colorectal Cancer Biology — Putting**

Boveri's hypothesis about the genetic basis of cancer, a century ago, subsequently confirmed by Loeb et al. in 1974, opened the gate for genetic studies that became essential for cancer

Cancer is a disease that arises from altered cell due to multiple genetic and epigenetic altera‐ tions that confer them the properties of apoptosis evasion and growth advantage. These properties represent a competitive advantage over normal cells, leading to the expansion and colonization of other tissues by these cells, which cause patient´s death by interfering with the

Introduction of chemotherapy in cancer treatments has supposed an important improvement in progression-free survival but, it is also associated to life threatening secondary effects, in the worst scenario, and an important quality life reduction in the best one. Furthermore, due to the difficulty to stratify patients in low and high risk, there are a substantial number of them that will receive the therapy but will not experience any benefit from it. These consequences,

The first chemotherapy treatments were based on a frequently observed characteristic of cancer cells, this is, a high proliferation index. Their effectiveness rates vary among cancers, but all of them are characterized by important secondary effects as consequence of their low specificity,

The use of this traditional chemotherapy effectively shrinks tumor mass but, observation of tumor metastases and recurrences led to the idea of the existence of cell populations unaffected by the treatment, either because they are a type of cells with different characteristics from the

> © 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

underline the importance of personalized treatment in cancer management. [4, 5]

since these chemotherapeutics also affects normal cells.

**Bricks on the Path to Personalized Medicine**

Emilia Balboa, Angel Carracedo and

Additional information is available at the end of the chapter

Francisco Barros

**1. Introduction**

management. [1, 2]

normal function of its organs. [3]

http://dx.doi.org/10.5772/57172

## **The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine**

Emilia Balboa, Angel Carracedo and

Francisco Barros

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57172

## **1. Introduction**

Boveri's hypothesis about the genetic basis of cancer, a century ago, subsequently confirmed by Loeb et al. in 1974, opened the gate for genetic studies that became essential for cancer management. [1, 2]

Cancer is a disease that arises from altered cell due to multiple genetic and epigenetic altera‐ tions that confer them the properties of apoptosis evasion and growth advantage. These properties represent a competitive advantage over normal cells, leading to the expansion and colonization of other tissues by these cells, which cause patient´s death by interfering with the normal function of its organs. [3]

Introduction of chemotherapy in cancer treatments has supposed an important improvement in progression-free survival but, it is also associated to life threatening secondary effects, in the worst scenario, and an important quality life reduction in the best one. Furthermore, due to the difficulty to stratify patients in low and high risk, there are a substantial number of them that will receive the therapy but will not experience any benefit from it. These consequences, underline the importance of personalized treatment in cancer management. [4, 5]

The first chemotherapy treatments were based on a frequently observed characteristic of cancer cells, this is, a high proliferation index. Their effectiveness rates vary among cancers, but all of them are characterized by important secondary effects as consequence of their low specificity, since these chemotherapeutics also affects normal cells.

The use of this traditional chemotherapy effectively shrinks tumor mass but, observation of tumor metastases and recurrences led to the idea of the existence of cell populations unaffected by the treatment, either because they are a type of cells with different characteristics from the

cells that the drug was designed to, because they have undergone genetic changes that confer them resistance or because the microenvironment protects them. Identification of the resist‐ ance cause is one of the cornerstones of cancer treatment and in this attempt, identification of cells that have tumorigenic potential to sustain cancer is fundamental. [6]

Nonetheless, cells in this tissue are not independent units, there is a communication between them and even collaboration has been proved in leukemogenic cells. [16] This communication is performed through the extracellular matrix by different signals to which cells respond and its behavior is modulated by these signals as them change over time. Hence, during cancer development, cells in a tumor, experiment different genetic alterations selected by their fitness which is determined by the tumor microenvironment and tissue characteristics where the tumor is being developed. All these characteristics explain the observed intra-tumor hetero‐ geneity in cancer and the different subtypes identify in a specific type of cancer, which added to the modification performed by the individual genetic background makes each cancer a

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435

To add more complexity to the system, not all the mutations within a tumor are important for its progression or survival. Due to alterations in DNA repair systems, numerous mutations are produced that do not provide any advantage nor disadvantage to cells at a given moment but, its presence and proportion in the tumor mass will depend on if they are produced in clones which have driver mutations, this is mutations that will lead tumor development and response to the environment. Differentiate which mutations are drivers from passengers it is another important and confounding factor for both, identification of tumor and pharmacoge‐

Equally importantly is to determine the global effects that mutations cause, since understand‐ ing the aims of the tumor through the modulation of the pathways that performs will help us to predict the compensatory mechanism that executes. [3] Knudson´s two hits hypothesis postulates that more than one mutation is needed in cells to become malignant. [19, 20] The fine regulation that tumor cells exert, and the importance of the molecular pathways implied is exemplified by the °Just-right hypothesis° that postulates that the second mutation in the adenomatous polyposis coli [APC] gene [which is a gene where germline mutations are found to be associated to an hereditary form of colorectal cancer] produces in a tumor is dependent on the type and localization of the germline mutation in a patient in order to maintain some

Apart from all these convolutions, each tumor has an inherent progression; there is a pattern of genetic alterations typical of each tumor, whose establishment is a priority when designing cancer treatments. The goal is to increase drug efficiency along with its specificity in order to diminish the secondary effects. In this road, there have been two important events that have

Firstly, advances in knowledge of genetics have allowed us to discover the hereditary compo‐ nent of cancer as well as the steps that follow in cancer development, the more important pathways triggerinthemandhavepointedoutthekeyderegulatedmoleculesagainsttospecific drugs can be designed. The studies realized to determine the cancer characteristics have also

Secondly, drug development research has focused their efforts in the development of target drugs that act specifically on those molecules in order to avoid the important secondary effects

contributed to the discovery of specific and differential patterns of each cancer. [22-25]

basal APC activity, which it is needed for cell functioning. [21]

helped us to achieve this ultimate goal.

of classical chemotherapy.

unique entity. [7]

netic markers. [7, 17, 18]

Based on this, studies of tumor organization were performed. As indicated by Shackleton et al, research on tumor organization intends to determine which cells have tumorigenic potential to sustain cancer, this is, all cells in a cancer or only a specific population of them. There are two principal models of tumor organization, not mutually exclusive, the clonal evolution model [stochastic] and the stem cell model [hierarchical], that have been subjected to deep examination owing to their implications in cancer management. [6]

The clonal evolution model was described by Nowell in 1976, and it is quite verified that it seems to be ubiquitous in all cancers. It describes cancer development by the successive acquisition of differential features in the derived cells giving rise to the formation of cell clones, this is, group of cells with common features because they originate from the same progenitor cell that can be a stem cell or not. Some of these features can be positive and provide a selective advantage to these cells over the others, with the consequent establishment of these clones. This model supports the idea that all cells in a tumor are important since the cancer can be sustained due to the possible acquisition of resistance or advantage features in the derived cells. On the other hand, this process is not random, tumors share similarities, but these similarities will be modulated by the tumor environment turning each tumor into unique entities. [3, 7]

To establish a model of tumor organization is fundamental since it should drastically change treatment cancer approach. Identification of cells that drive tumor progression will allow us to design target drugs against this cells instead of nonspecific drugs that treat all cancer cells, even normal cells. Tumors that have a hierarchical organization from stem cells to more differentiated cells are said to follow the stem cell model that have been recently proved in a few cancers, among them, the colorectal cancer. [3, 6-13] Stem cells are a very specific type of cells that possess differential capabilities such as being pluripotent, remain in a quiescent state, have a long life as well as self-renewal capacity which allows them to perpetuate themselves and repopulate different cells linages.

Nonetheless, both models are not incompatible, mutation causing clonal expansion may happen in the stem cell compartment and manifests its effects on the progenitors cells or may happen in the progenitors cells that can re-activate the auto-renewal machinery to generate stem cells. [14] As long as the disease progresses, these changes can induce alterations in the normal patterns of development of these cells, reducing their ability to differentiate and increasing their auto-renewal capacity, causing the uncontrolled increase of undifferentiated cells, as it happens in leukemia. [15] As Nowell denoted the observation of non-differentiation of tumor cells is explained by focus the cell resources in increasing cell proliferation and invasiveness. [3]

Both models describe a scenario of intratumor genetic heterogeneity that reproduces the tumor tissue heterogeneity observed in patients, and also describes the heterogeneity observed in the different stages of cancer as consequence of selection in different environments. [3, 7]

Nonetheless, cells in this tissue are not independent units, there is a communication between them and even collaboration has been proved in leukemogenic cells. [16] This communication is performed through the extracellular matrix by different signals to which cells respond and its behavior is modulated by these signals as them change over time. Hence, during cancer development, cells in a tumor, experiment different genetic alterations selected by their fitness which is determined by the tumor microenvironment and tissue characteristics where the tumor is being developed. All these characteristics explain the observed intra-tumor hetero‐ geneity in cancer and the different subtypes identify in a specific type of cancer, which added to the modification performed by the individual genetic background makes each cancer a unique entity. [7]

cells that the drug was designed to, because they have undergone genetic changes that confer them resistance or because the microenvironment protects them. Identification of the resist‐ ance cause is one of the cornerstones of cancer treatment and in this attempt, identification of

Based on this, studies of tumor organization were performed. As indicated by Shackleton et al, research on tumor organization intends to determine which cells have tumorigenic potential to sustain cancer, this is, all cells in a cancer or only a specific population of them. There are two principal models of tumor organization, not mutually exclusive, the clonal evolution model [stochastic] and the stem cell model [hierarchical], that have been subjected to deep

The clonal evolution model was described by Nowell in 1976, and it is quite verified that it seems to be ubiquitous in all cancers. It describes cancer development by the successive acquisition of differential features in the derived cells giving rise to the formation of cell clones, this is, group of cells with common features because they originate from the same progenitor cell that can be a stem cell or not. Some of these features can be positive and provide a selective advantage to these cells over the others, with the consequent establishment of these clones. This model supports the idea that all cells in a tumor are important since the cancer can be sustained due to the possible acquisition of resistance or advantage features in the derived cells. On the other hand, this process is not random, tumors share similarities, but these similarities will be modulated by the tumor environment turning each tumor into unique

To establish a model of tumor organization is fundamental since it should drastically change treatment cancer approach. Identification of cells that drive tumor progression will allow us to design target drugs against this cells instead of nonspecific drugs that treat all cancer cells, even normal cells. Tumors that have a hierarchical organization from stem cells to more differentiated cells are said to follow the stem cell model that have been recently proved in a few cancers, among them, the colorectal cancer. [3, 6-13] Stem cells are a very specific type of cells that possess differential capabilities such as being pluripotent, remain in a quiescent state, have a long life as well as self-renewal capacity which allows them to perpetuate themselves

Nonetheless, both models are not incompatible, mutation causing clonal expansion may happen in the stem cell compartment and manifests its effects on the progenitors cells or may happen in the progenitors cells that can re-activate the auto-renewal machinery to generate stem cells. [14] As long as the disease progresses, these changes can induce alterations in the normal patterns of development of these cells, reducing their ability to differentiate and increasing their auto-renewal capacity, causing the uncontrolled increase of undifferentiated cells, as it happens in leukemia. [15] As Nowell denoted the observation of non-differentiation of tumor cells is explained by focus the cell resources in increasing cell proliferation and

Both models describe a scenario of intratumor genetic heterogeneity that reproduces the tumor tissue heterogeneity observed in patients, and also describes the heterogeneity observed in the

different stages of cancer as consequence of selection in different environments. [3, 7]

cells that have tumorigenic potential to sustain cancer is fundamental. [6]

examination owing to their implications in cancer management. [6]

entities. [3, 7]

invasiveness. [3]

and repopulate different cells linages.

434 Colorectal Cancer - Surgery, Diagnostics and Treatment

To add more complexity to the system, not all the mutations within a tumor are important for its progression or survival. Due to alterations in DNA repair systems, numerous mutations are produced that do not provide any advantage nor disadvantage to cells at a given moment but, its presence and proportion in the tumor mass will depend on if they are produced in clones which have driver mutations, this is mutations that will lead tumor development and response to the environment. Differentiate which mutations are drivers from passengers it is another important and confounding factor for both, identification of tumor and pharmacoge‐ netic markers. [7, 17, 18]

Equally importantly is to determine the global effects that mutations cause, since understand‐ ing the aims of the tumor through the modulation of the pathways that performs will help us to predict the compensatory mechanism that executes. [3] Knudson´s two hits hypothesis postulates that more than one mutation is needed in cells to become malignant. [19, 20] The fine regulation that tumor cells exert, and the importance of the molecular pathways implied is exemplified by the °Just-right hypothesis° that postulates that the second mutation in the adenomatous polyposis coli [APC] gene [which is a gene where germline mutations are found to be associated to an hereditary form of colorectal cancer] produces in a tumor is dependent on the type and localization of the germline mutation in a patient in order to maintain some basal APC activity, which it is needed for cell functioning. [21]

Apart from all these convolutions, each tumor has an inherent progression; there is a pattern of genetic alterations typical of each tumor, whose establishment is a priority when designing cancer treatments. The goal is to increase drug efficiency along with its specificity in order to diminish the secondary effects. In this road, there have been two important events that have helped us to achieve this ultimate goal.

Firstly, advances in knowledge of genetics have allowed us to discover the hereditary compo‐ nent of cancer as well as the steps that follow in cancer development, the more important pathways triggerinthemandhavepointedoutthekeyderegulatedmoleculesagainsttospecific drugs can be designed. The studies realized to determine the cancer characteristics have also contributed to the discovery of specific and differential patterns of each cancer. [22-25]

Secondly, drug development research has focused their efforts in the development of target drugs that act specifically on those molecules in order to avoid the important secondary effects of classical chemotherapy.

Molecular specific drugs, like tyrosine kinase inhibitors or antibody-based therapies are the next-generation cancer treatment. [4] As result of this molecular specificity, effectiveness of these selective treatments is more dependent on the biology of the target cell. Consequently, the pace of the improvements in cancer treatments is highly dependent on the knowledge of cancer cells biology.

of genomic alterations become tumor cells. [11-13, 31, 32] It can arise in a sporadic form or it

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

437

Identification of the cause that predisposes to cancer in the hereditary syndromes have given us clues, due to the similarities of the mechanisms identified, to understand what happen in the sporadic tumors, that involves the majority of the colorectal cancer cases. Germline mutations in known oncogenes or DNA repair genes have been identify as causative of a predisposition to endure colorectal cancer but the origin of the sporadic form is still unclear and it is attributed to genetic alterations caused by the environmental as chemical carcinogens, age related factors which increase DNA errors rate and nutritious factors. All these conditions will probably determine the activated cancer mechanism depending on which factor has triggered the cancer. But, environment is also an important factor that modulates colorectal cancer appearance in patients with a hereditary component since germline mutations cause a predisposition to cancer, but another mutation is needed in the cells for them to become

In recent times it has become evident the need of establish subtypes in colorectal cancer due to the differential characteristics of the proximal and distal segments of the colon as well as diverse features, at both histological and molecular level, observed in colorectal cancer.

Proximal and distal colon, proceed from a different embryological origin, midgut and hindgut respectively. Besides the embryological origin, its distinctions span from innervation and

At histological level, most the polyps are adenomatous [95%], but only a small percentage of them progress to cancer and not all the colorectal cancer cases are presented with polyps. [35-37] Actually, prevalence of each type of polyp is only rough since it is population depend‐ ent, due to its genetic background and environmental dependence apart from the expertise of the pathologist to identify the polyp, which sometimes is difficult. [37, 38] Histological features of the tumors are associated to the underlying molecular pathway. So far, two main types of carcinoma have been identified, traditional and serrated carcinomas, that have several subtypes and whose development is driven by three main molecular mechanisms, chromo‐ somal instability (CIN), microsatellite instability (MSI) and CpG island methylator phenotype (CIMP). Combinations of these mechanism and some additional genetic and epigenetics changes according to the tumor environment give raise to the large varieties of histological

On molecular basis, colorectal cancer development is mainly, but not exclusively, driven by the deregulation of one of these mechanisms (CIN, MSI or CIMP), CIN being the most prevalent. [23, 39-44] But it not clear if these mechanisms are the cause or the major alterations

The predominance, of one of these mechanisms over the others, since they are not mutually exclusive, provides the tumor their differential features, which includes morphological characteristics, cancer prognosis and treatment efficiency. This heterogeneity observed in colorectal cancer is due to the diverse scenarios in which colorectal cancer develops so,

blood supply to functional differences and differential gene expression. [33, 34]

malignant, as it is postulated in Knudson´s two hits hypothesis. [19, 20]

can have a hereditary component.

forms observed. [38]

trigger in cancer. [2]

But, as stated above, cancer cells are not islands, its behavior is modulated by the signals that its surroundings emit, as well as its surroundings control the quantity of nutrients, oxygen and chemicals that reach the tumor. Therefore, treatment efficiency is influenced by drug phar‐ macokinetics, that is dependent of the biology of the normal cells, as well as the secondary effects are determined by drug pharmacodynamics, that is subject to drug specificity and the inherited sensibility of normal cells to chemotherapeutic agents determined by different mechanisms, for example, detoxifying mechanisms. [3] Subsequently, when trying to person‐ alize treatments it is important to identify both, the genetic of the tumor and the genetic of normal cells. This is one of the causes that explain the variability in response to chemotherapy observed in patients with similar tumor characteristics. [4]

Despite the efforts realized, the only pharmacogenetics markers used today in clinic are KRAS and BRAF mutations. Some of the causes of this delay in markers discovery are then. No intention of this chapter is to provide a deep review of the different subtypes but offer an outline of the principal characteristics of the diverse subtypes according to the literature, in order to expose the cause of the delay in markers discovery that was previously mentioned, and reflect that problems in pharmacogenetic studies obtained are due, in part, to the high heterogeneity in colorectal cancer which makes difficult to establish clearly differentiated groups of study and at the same time, to reflect that intense research has a positive point of view, since important advances in tumor characterization and target molecules discovery have also been done.

## **2. Colorectal cancer biology — Heterogeneity of colorectal cancer**

Colon tissue is organized in a repetition of structural subunits called crypts. Cells in each crypt have an ordered configuration, being the stem cells at the base of the crypt and the subsequent differentiated cells upwards along the crypt. The main conductor in the colonic cell differen‐ tiation is the Wnt/β-catenin signaling pathway. [26] β-Catenin is a transcriptional co-activator of genes implicated in cell growth and differentiation. Activation of the Wnt pathway disrupts the cytoplasmatic complex that marks β-catenin for degradation allowing it to enter the nucleus were exerts its activity. [27-29] APC protein forms part of the degradation complex. Concordant to their function in the differentiation and growing pattern, there is an inverse gradient of APC/β-catenin expression along the crypt axle, being APC mostly expressed in the upper part of the crypt and β-catenin in the lower part on the crypt. [30]

Colorectal cancer is a highly heterogeneous malignancy caused by genetic and epigenetic alterations in the stem cells of the crypt of the bowel which give rise to precancerous lesion, aberrant crypt foci, that overgrow usually forming polyps that after a successful accumulation of genomic alterations become tumor cells. [11-13, 31, 32] It can arise in a sporadic form or it can have a hereditary component.

Molecular specific drugs, like tyrosine kinase inhibitors or antibody-based therapies are the next-generation cancer treatment. [4] As result of this molecular specificity, effectiveness of these selective treatments is more dependent on the biology of the target cell. Consequently, the pace of the improvements in cancer treatments is highly dependent on the knowledge of

But, as stated above, cancer cells are not islands, its behavior is modulated by the signals that its surroundings emit, as well as its surroundings control the quantity of nutrients, oxygen and chemicals that reach the tumor. Therefore, treatment efficiency is influenced by drug phar‐ macokinetics, that is dependent of the biology of the normal cells, as well as the secondary effects are determined by drug pharmacodynamics, that is subject to drug specificity and the inherited sensibility of normal cells to chemotherapeutic agents determined by different mechanisms, for example, detoxifying mechanisms. [3] Subsequently, when trying to person‐ alize treatments it is important to identify both, the genetic of the tumor and the genetic of normal cells. This is one of the causes that explain the variability in response to chemotherapy

Despite the efforts realized, the only pharmacogenetics markers used today in clinic are KRAS and BRAF mutations. Some of the causes of this delay in markers discovery are then. No intention of this chapter is to provide a deep review of the different subtypes but offer an outline of the principal characteristics of the diverse subtypes according to the literature, in order to expose the cause of the delay in markers discovery that was previously mentioned, and reflect that problems in pharmacogenetic studies obtained are due, in part, to the high heterogeneity in colorectal cancer which makes difficult to establish clearly differentiated groups of study and at the same time, to reflect that intense research has a positive point of view, since important advances in tumor characterization and target molecules discovery have

**2. Colorectal cancer biology — Heterogeneity of colorectal cancer**

upper part of the crypt and β-catenin in the lower part on the crypt. [30]

Colon tissue is organized in a repetition of structural subunits called crypts. Cells in each crypt have an ordered configuration, being the stem cells at the base of the crypt and the subsequent differentiated cells upwards along the crypt. The main conductor in the colonic cell differen‐ tiation is the Wnt/β-catenin signaling pathway. [26] β-Catenin is a transcriptional co-activator of genes implicated in cell growth and differentiation. Activation of the Wnt pathway disrupts the cytoplasmatic complex that marks β-catenin for degradation allowing it to enter the nucleus were exerts its activity. [27-29] APC protein forms part of the degradation complex. Concordant to their function in the differentiation and growing pattern, there is an inverse gradient of APC/β-catenin expression along the crypt axle, being APC mostly expressed in the

Colorectal cancer is a highly heterogeneous malignancy caused by genetic and epigenetic alterations in the stem cells of the crypt of the bowel which give rise to precancerous lesion, aberrant crypt foci, that overgrow usually forming polyps that after a successful accumulation

observed in patients with similar tumor characteristics. [4]

cancer cells biology.

436 Colorectal Cancer - Surgery, Diagnostics and Treatment

also been done.

Identification of the cause that predisposes to cancer in the hereditary syndromes have given us clues, due to the similarities of the mechanisms identified, to understand what happen in the sporadic tumors, that involves the majority of the colorectal cancer cases. Germline mutations in known oncogenes or DNA repair genes have been identify as causative of a predisposition to endure colorectal cancer but the origin of the sporadic form is still unclear and it is attributed to genetic alterations caused by the environmental as chemical carcinogens, age related factors which increase DNA errors rate and nutritious factors. All these conditions will probably determine the activated cancer mechanism depending on which factor has triggered the cancer. But, environment is also an important factor that modulates colorectal cancer appearance in patients with a hereditary component since germline mutations cause a predisposition to cancer, but another mutation is needed in the cells for them to become malignant, as it is postulated in Knudson´s two hits hypothesis. [19, 20]

In recent times it has become evident the need of establish subtypes in colorectal cancer due to the differential characteristics of the proximal and distal segments of the colon as well as diverse features, at both histological and molecular level, observed in colorectal cancer.

Proximal and distal colon, proceed from a different embryological origin, midgut and hindgut respectively. Besides the embryological origin, its distinctions span from innervation and blood supply to functional differences and differential gene expression. [33, 34]

At histological level, most the polyps are adenomatous [95%], but only a small percentage of them progress to cancer and not all the colorectal cancer cases are presented with polyps. [35-37] Actually, prevalence of each type of polyp is only rough since it is population depend‐ ent, due to its genetic background and environmental dependence apart from the expertise of the pathologist to identify the polyp, which sometimes is difficult. [37, 38] Histological features of the tumors are associated to the underlying molecular pathway. So far, two main types of carcinoma have been identified, traditional and serrated carcinomas, that have several subtypes and whose development is driven by three main molecular mechanisms, chromo‐ somal instability (CIN), microsatellite instability (MSI) and CpG island methylator phenotype (CIMP). Combinations of these mechanism and some additional genetic and epigenetics changes according to the tumor environment give raise to the large varieties of histological forms observed. [38]

On molecular basis, colorectal cancer development is mainly, but not exclusively, driven by the deregulation of one of these mechanisms (CIN, MSI or CIMP), CIN being the most prevalent. [23, 39-44] But it not clear if these mechanisms are the cause or the major alterations trigger in cancer. [2]

The predominance, of one of these mechanisms over the others, since they are not mutually exclusive, provides the tumor their differential features, which includes morphological characteristics, cancer prognosis and treatment efficiency. This heterogeneity observed in colorectal cancer is due to the diverse scenarios in which colorectal cancer develops so, characterization of the colorectal cancer in different subtypes, according to its distinctive signatures, will help us to stratify cancer progression risk and personalize treatments. [45-47]

associated to the transition from adenoma to carcinoma. This pathway has also a function on

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

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Because of its important and numerous functions in cells, like cell cycle regulation or mainte‐ nance of genomic integrity, p53 (chr.17p) is called the guardian of the genome. Being one of the most frequently mutated genes in cancer, its inactivation is associated to metastasis. [58, 61] Nonetheless, the establishment of the adenoma-carcinoma sequence does not implied that all mutations described are needed for the progression of cancer nor the uniques but the more

Microsatellite instability (MSI) is defined by the detection of alterations in the length of short repeated sequences known as microsatellite, which is indicative of defects in the DNA mismatch repair system (MMR). These alterations influence expression of the affected genes. [63] The genes that have been found associated to this altered mechanism are MLH1, PMS2, PMS1 and MSH6. This mechanism is detected in 15-20% of colorectal cancers in both sporadic and hereditary tumors. It is the main feature of another hereditary syndrome, Lynch syndrome that accounts for 2-3% of colorectal cases. [38, 64] The number of altered microsatellites, is also

Mutations in MUTYH are associated to another hereditary syndrome, rarely found in sporadic cases, called adenomatous polyposis associated to Mutyh (MAP). This protein belongs to the DNA base-excision repair system, which is important in DNA oxidative damage repair that causes guanosine (G) to thymidine (T) transversions. [66] Molecular mechanisms are not yet totally clarified and polyps from MAP have some of the features but not all of both, CIN and

CpG island methylator phenotype (CIMP) is defined by the detection of high degree of methylation. [69] Hypermethylation of the promoter region causes silencing expression of affected genes. It is generally age-related and it is related to cell response to inflammation. [65] This mechanism is frequent in sporadic tumor and has also been detected associated to hereditary mechanisms with a non-Darwinian patter of inheritance. [58, 70-75] There are two panels of genes studied to identify the CIMP state, which define two subtypes, CIMP-high and CIMP-low. CIMP-H is associated to neoplastic methylation meanwhile CIMP-L are age related.

The traditional pathway of colorectal cancer is the most prevalent, 60% of CCR arise by this pathway. [76] Histologically, tumors that follow the traditional pathway are tubular polyps that can be subdivided into tubular, tubulovillous and villous, being the former the most

*2.2.1. Traditional pathway (Chromosomal instability mechanism – CIN)*

important, defining two subtypes as this number is high, MSI-H, or low, MSI-L. [65]

the microenvironment regulation of cell by autocrine and paracrine factors. [58, 60]

frequently ones detected, with different prevalence across the stages. [22]

*2.1.2. Microsatellite instability (MSI)*

MSI mechanism. [67, 68]

**2.2. Molecular pathways**

*2.1.3. Methylator Phenotype (CIMP)*

But these subtypes are not mutually exclusive, the intra-heterogeneity observed in a patient´s polyps reflects the heterogeneity of the molecular pathways and mechanisms that can be implicated. [37]

Despite this overlap, predominant characteristics can be distinguished into the subtypes and even alterations that are, in principal, mutually exclusive have been identified, that reflect the unique signature of each tumor. [48, 49]

#### **2.1. Molecular mechanism**

#### *2.1.1. Chromosomal instability mechanism – CIN*

Chromosomal instability mechanism (CIN) is detected in the 65-70% of the colorectal cancers. It is defined by the identification of changes at chromosomal level in tumor cells that cause gene dose variations. [2] This mechanism is associated to the major hereditary syndrome, the polyposis adenomatous familiar (FAP) as well as its attenuated variant (AFAP), that accounts for 1% of the colorectal cases and it is the most frequently detected in the sporadic form [38, 50-52]. Less commonly, CIN is categorized in subtypes as CIN-high and low. [47, 52, 62]

The molecular steps that describe this mechanism were proposed by Fear and Vogelstein in the °adenoma-carcinoma sequence°, where mutations in the APC gene (chr.5q) is the first step identified in a sequence of genetic alterations on oncogenes and tumor suppressor genes that leads to its keys characteristics, the aneuploidy and loss of heterozigosity. [22, 52-54]

Germline mutations in the APC gene are associated with these hereditary syndromes, as well as mutations in this gene are detected in the 72%-85 of sporadic colorectal cancer cases and hypermethylation of its promoter in the 18%. According to the importance of the Wnt pathway in the colorectal cancer, in half of the patients where genetic alterations in APC are not detected, gain of function mutations in the β-catenin gene have been found that account for 10% of colorectal cases. [52, 55-57]

Besides its function in the repression complex of the β-catenin, APC has numerous functions, among which highlights its implication in chromosomal segregation and, according to its parallel increasing expression with cell differentiation, plays a role in different features of cell differentiation. [52, 55, 56]

Mutations in APC are followed by genetic alterations with a different frequency, in KRAS, DCC, SMAD4 and p53 that are detected in the progression of a tumor from adenoma to carcinoma. [22, 58] All these genes are key points of regulation of important pathways that control cell behavior thus, KRAS [chr.12p] is member of the Ras and PI3K pathway, which are usually dysregulated in cancer and is implicated in cell proliferation, differentiation, survival, metabolism and apoptosis. Its activation triggers both pathways. [58, 59]

SMAD4 belongs to the transforming growth factor β pathway signaling which is a tumor suppressor pathway. Its inactivation is related to tumor progression and invasion, being associated to the transition from adenoma to carcinoma. This pathway has also a function on the microenvironment regulation of cell by autocrine and paracrine factors. [58, 60]

Because of its important and numerous functions in cells, like cell cycle regulation or mainte‐ nance of genomic integrity, p53 (chr.17p) is called the guardian of the genome. Being one of the most frequently mutated genes in cancer, its inactivation is associated to metastasis. [58, 61]

Nonetheless, the establishment of the adenoma-carcinoma sequence does not implied that all mutations described are needed for the progression of cancer nor the uniques but the more frequently ones detected, with different prevalence across the stages. [22]

### *2.1.2. Microsatellite instability (MSI)*

characterization of the colorectal cancer in different subtypes, according to its distinctive signatures, will help us to stratify cancer progression risk and personalize treatments. [45-47] But these subtypes are not mutually exclusive, the intra-heterogeneity observed in a patient´s polyps reflects the heterogeneity of the molecular pathways and mechanisms that can be

Despite this overlap, predominant characteristics can be distinguished into the subtypes and even alterations that are, in principal, mutually exclusive have been identified, that reflect the

Chromosomal instability mechanism (CIN) is detected in the 65-70% of the colorectal cancers. It is defined by the identification of changes at chromosomal level in tumor cells that cause gene dose variations. [2] This mechanism is associated to the major hereditary syndrome, the polyposis adenomatous familiar (FAP) as well as its attenuated variant (AFAP), that accounts for 1% of the colorectal cases and it is the most frequently detected in the sporadic form [38, 50-52]. Less commonly, CIN is categorized in subtypes as CIN-high and low. [47, 52, 62]

The molecular steps that describe this mechanism were proposed by Fear and Vogelstein in the °adenoma-carcinoma sequence°, where mutations in the APC gene (chr.5q) is the first step identified in a sequence of genetic alterations on oncogenes and tumor suppressor genes that

Germline mutations in the APC gene are associated with these hereditary syndromes, as well as mutations in this gene are detected in the 72%-85 of sporadic colorectal cancer cases and hypermethylation of its promoter in the 18%. According to the importance of the Wnt pathway in the colorectal cancer, in half of the patients where genetic alterations in APC are not detected, gain of function mutations in the β-catenin gene have been found that account for 10% of

Besides its function in the repression complex of the β-catenin, APC has numerous functions, among which highlights its implication in chromosomal segregation and, according to its parallel increasing expression with cell differentiation, plays a role in different features of cell

Mutations in APC are followed by genetic alterations with a different frequency, in KRAS, DCC, SMAD4 and p53 that are detected in the progression of a tumor from adenoma to carcinoma. [22, 58] All these genes are key points of regulation of important pathways that control cell behavior thus, KRAS [chr.12p] is member of the Ras and PI3K pathway, which are usually dysregulated in cancer and is implicated in cell proliferation, differentiation, survival,

SMAD4 belongs to the transforming growth factor β pathway signaling which is a tumor suppressor pathway. Its inactivation is related to tumor progression and invasion, being

metabolism and apoptosis. Its activation triggers both pathways. [58, 59]

leads to its keys characteristics, the aneuploidy and loss of heterozigosity. [22, 52-54]

implicated. [37]

unique signature of each tumor. [48, 49]

438 Colorectal Cancer - Surgery, Diagnostics and Treatment

*2.1.1. Chromosomal instability mechanism – CIN*

**2.1. Molecular mechanism**

colorectal cases. [52, 55-57]

differentiation. [52, 55, 56]

Microsatellite instability (MSI) is defined by the detection of alterations in the length of short repeated sequences known as microsatellite, which is indicative of defects in the DNA mismatch repair system (MMR). These alterations influence expression of the affected genes. [63] The genes that have been found associated to this altered mechanism are MLH1, PMS2, PMS1 and MSH6. This mechanism is detected in 15-20% of colorectal cancers in both sporadic and hereditary tumors. It is the main feature of another hereditary syndrome, Lynch syndrome that accounts for 2-3% of colorectal cases. [38, 64] The number of altered microsatellites, is also important, defining two subtypes as this number is high, MSI-H, or low, MSI-L. [65]

Mutations in MUTYH are associated to another hereditary syndrome, rarely found in sporadic cases, called adenomatous polyposis associated to Mutyh (MAP). This protein belongs to the DNA base-excision repair system, which is important in DNA oxidative damage repair that causes guanosine (G) to thymidine (T) transversions. [66] Molecular mechanisms are not yet totally clarified and polyps from MAP have some of the features but not all of both, CIN and MSI mechanism. [67, 68]

#### *2.1.3. Methylator Phenotype (CIMP)*

CpG island methylator phenotype (CIMP) is defined by the detection of high degree of methylation. [69] Hypermethylation of the promoter region causes silencing expression of affected genes. It is generally age-related and it is related to cell response to inflammation. [65]

This mechanism is frequent in sporadic tumor and has also been detected associated to hereditary mechanisms with a non-Darwinian patter of inheritance. [58, 70-75] There are two panels of genes studied to identify the CIMP state, which define two subtypes, CIMP-high and CIMP-low. CIMP-H is associated to neoplastic methylation meanwhile CIMP-L are age related.

#### **2.2. Molecular pathways**

#### *2.2.1. Traditional pathway (Chromosomal instability mechanism – CIN)*

The traditional pathway of colorectal cancer is the most prevalent, 60% of CCR arise by this pathway. [76] Histologically, tumors that follow the traditional pathway are tubular polyps that can be subdivided into tubular, tubulovillous and villous, being the former the most prevalent. Colorectal cancer from FAP and AFAP patients, are the canonical tumors develop by these pathway. This type of adenomas affects the epithelial layer and are originated from dysplastic aberrant crypt foci. [77]

HP can distinguish polyps of microvesicular type (MVHP), Goblet cell–rich type (GCHP) or Mucin poor type (MPHP), according to their content in mucin. SSA can be with/without cytological dysplasia as well as TSA can be with/without conventional dysplasia. [37, 76]

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

441

The molecular characteristic of the majority of serrated polyps is the BRAF mutation and CIMP

The CpG island methylator phenotype (CIMP) is detected in 15%-40% of the colorectal tu‐ mors. [94, 95] This kind of tumor is mostly related to ageing and environmental factors. One of these genes identified as susceptible of hypermethylation is MLH1, which belongs to the DNA mismatch repair system (MMR), being the causal mechanism of MSI in the serrated pathway.

The sequential steps described in this pathway from normal mucosa to carcinoma goes from the presence of BRAF mutation in microvesicular hyperplastic polyps and posterior acquisi‐ tion of CIMP phenotype in sessile serrated polyps to a co-occurrence of both genetics alteration leading to sessile serrated polyps. The acquisition of MLH1 promoter methylation is related

Goblet cell-rich hyperplastic polyps (GCHP) and traditional serrated adenomas (TSA) are associated to KRAS mutations and while it has not been demonstrated a progression of GCHP to carcinoma, it was proved in TSA. It has also been suggested MSI-L after MGMT methylation

Tumors associated to MUTYH can be since hyperplastic and sessile serrated polyps to no polyps at CRC presentation. A higher association of KRAS mutations (70%) has been found in MAP tumors that follow the serrated pathway compared to sporadic (17%), as well as an increased on G:C to T:A transversions (94% vs. 29%). The findings of mutations on APC in

Personalized medicine is based on the clinical use of molecular biomarkers. A biomarker is any specific physical trait or measurable biological change in the organism related to disease or health conditions, being a very broad concept that includes many different measurements

Besides being diagnostic [used for the establishment of a particular disease present in the patient sample [97]] or prognostic [used for the establishment of an association with clinical outcomes, such as overall survival or recurrence-free survival independently of the treatment [98] biomarkers can be predictive, by the assessment of the likely benefit of a specific treatment to a specific patient, [99] or pharmacodynamic, by the measurement of the drug effect in a

adenomas indicate two pathways of development of MAP tumors. [67, 96]

These data seem to confirm that are, at least, as many cancers as patients.

+ mechanism. [93]

to the carcinoma stage. [76]

of a biologic status.

disease [100].

or partial MLH1 methylation. [76]

**3. State of the art of pharmacogenetics**

[37, 65, 69]

CIN is the most prevalent molecular mechanism in the traditional pathway of colorectal cancer, which is also characterized for being microsatellite stable (MSS) and CIMP-. Tumors driven by this mechanism are more frequently detected in distal localization and have a worse prognosis than MSI tumors. They recently have showed the use of CIN as useful marker for predicting survival, being patients that harbors CIN high tumors associated with a poor survival. [62]

Adenoma – carcinoma sequence also lies beneath Lynch syndrome polyps but develops at a faster tempo. [78, 79] Lynch syndrome polyps are more frequently associated to the proximal colon, and even though it can be tubular, are more frequently associated with a mucinous or signet ring histology and villous structures. These polyps show a high grade dysplasia, poorly differentiated cells and Crohn's-like infiltration of lymphocytes which has been found associated to an increased survival. These polyps have higher risk of cancer but are less invasive, have a better prognosis and a different response to chemotherapeutics. Less fre‐ quently these polyps have KRAS or p53 mutations. [64, 65, 78-80]

Although, presence of this mechanism in tumors has been reported to be inversely related to CIMP, either CIMP-L or CIMP-H, [81, 82] there is a subgroup of CIN/MSS tumors characterized by the presence of BRAF mutation that seems to be correlated with CIMP and poor survival. [83] BRAF is implicated in MERK-ERK activation pathway by its recruitment by KRAS. Confirming previous reports of KRAS and BRAF mutations as mutually exclusive, these tumors are wild type KRAS. [84]

#### *2.2.2. Alternative pathway (KRAS)*

The alternative pathway is still not very well characterized. Some studies indicate the presence of KRAS as its hallmark. [85] Histologically, the presence of KRAS, p53 mutation and recently GNAS, has been associated to villous histology and a high grade dysplasia [86-88] and the presence of CIMP+ to tubule villous size, right side localization and amount of villous, [89, 90] as well as to a differential pattern of the Wnt pathway genes. [91] Villous polyps are also characterized for being microsatellite stable [MSS] and CIMP-L.

#### *2.2.3. Serrated pathway CpG Island [methylator phenotype (CIMP)*

The serrated pathway underlines the 20-35% of colorectal cancer cases. [37, 76] Histologically, it is characterized by hyperplastic polyps, sessile serrated polyps or traditional serrated adenomas, originated from non-dysplastic aberrant crypt foci that can either be mucinous or not mucinous. [77, 85, 92] This type of tumor is mostly localized in the proximal colon and has bad prognosis. [37]

Serrated polyps can be hyperplastic (HP) (20-30%), sessile serrated adenomas (SSA) (2-9%) and traditional serrated adenomas (TSA) (0.3%) that are subsequently divided into subtypes. HP can distinguish polyps of microvesicular type (MVHP), Goblet cell–rich type (GCHP) or Mucin poor type (MPHP), according to their content in mucin. SSA can be with/without cytological dysplasia as well as TSA can be with/without conventional dysplasia. [37, 76]

The molecular characteristic of the majority of serrated polyps is the BRAF mutation and CIMP + mechanism. [93]

The CpG island methylator phenotype (CIMP) is detected in 15%-40% of the colorectal tu‐ mors. [94, 95] This kind of tumor is mostly related to ageing and environmental factors. One of these genes identified as susceptible of hypermethylation is MLH1, which belongs to the DNA mismatch repair system (MMR), being the causal mechanism of MSI in the serrated pathway. [37, 65, 69]

The sequential steps described in this pathway from normal mucosa to carcinoma goes from the presence of BRAF mutation in microvesicular hyperplastic polyps and posterior acquisi‐ tion of CIMP phenotype in sessile serrated polyps to a co-occurrence of both genetics alteration leading to sessile serrated polyps. The acquisition of MLH1 promoter methylation is related to the carcinoma stage. [76]

Goblet cell-rich hyperplastic polyps (GCHP) and traditional serrated adenomas (TSA) are associated to KRAS mutations and while it has not been demonstrated a progression of GCHP to carcinoma, it was proved in TSA. It has also been suggested MSI-L after MGMT methylation or partial MLH1 methylation. [76]

Tumors associated to MUTYH can be since hyperplastic and sessile serrated polyps to no polyps at CRC presentation. A higher association of KRAS mutations (70%) has been found in MAP tumors that follow the serrated pathway compared to sporadic (17%), as well as an increased on G:C to T:A transversions (94% vs. 29%). The findings of mutations on APC in adenomas indicate two pathways of development of MAP tumors. [67, 96]

These data seem to confirm that are, at least, as many cancers as patients.

## **3. State of the art of pharmacogenetics**

prevalent. Colorectal cancer from FAP and AFAP patients, are the canonical tumors develop by these pathway. This type of adenomas affects the epithelial layer and are originated from

CIN is the most prevalent molecular mechanism in the traditional pathway of colorectal cancer, which is also characterized for being microsatellite stable (MSS) and CIMP-. Tumors driven by this mechanism are more frequently detected in distal localization and have a worse prognosis than MSI tumors. They recently have showed the use of CIN as useful marker for predicting survival, being patients that harbors CIN high tumors associated with a poor

Adenoma – carcinoma sequence also lies beneath Lynch syndrome polyps but develops at a faster tempo. [78, 79] Lynch syndrome polyps are more frequently associated to the proximal colon, and even though it can be tubular, are more frequently associated with a mucinous or signet ring histology and villous structures. These polyps show a high grade dysplasia, poorly differentiated cells and Crohn's-like infiltration of lymphocytes which has been found associated to an increased survival. These polyps have higher risk of cancer but are less invasive, have a better prognosis and a different response to chemotherapeutics. Less fre‐

Although, presence of this mechanism in tumors has been reported to be inversely related to CIMP, either CIMP-L or CIMP-H, [81, 82] there is a subgroup of CIN/MSS tumors characterized by the presence of BRAF mutation that seems to be correlated with CIMP and poor survival. [83] BRAF is implicated in MERK-ERK activation pathway by its recruitment by KRAS. Confirming previous reports of KRAS and BRAF mutations as mutually exclusive, these

The alternative pathway is still not very well characterized. Some studies indicate the presence of KRAS as its hallmark. [85] Histologically, the presence of KRAS, p53 mutation and recently GNAS, has been associated to villous histology and a high grade dysplasia [86-88] and the presence of CIMP+ to tubule villous size, right side localization and amount of villous, [89, 90] as well as to a differential pattern of the Wnt pathway genes. [91] Villous polyps are also

The serrated pathway underlines the 20-35% of colorectal cancer cases. [37, 76] Histologically, it is characterized by hyperplastic polyps, sessile serrated polyps or traditional serrated adenomas, originated from non-dysplastic aberrant crypt foci that can either be mucinous or not mucinous. [77, 85, 92] This type of tumor is mostly localized in the proximal colon and has

Serrated polyps can be hyperplastic (HP) (20-30%), sessile serrated adenomas (SSA) (2-9%) and traditional serrated adenomas (TSA) (0.3%) that are subsequently divided into subtypes.

quently these polyps have KRAS or p53 mutations. [64, 65, 78-80]

characterized for being microsatellite stable [MSS] and CIMP-L.

*2.2.3. Serrated pathway CpG Island [methylator phenotype (CIMP)*

dysplastic aberrant crypt foci. [77]

440 Colorectal Cancer - Surgery, Diagnostics and Treatment

tumors are wild type KRAS. [84]

*2.2.2. Alternative pathway (KRAS)*

bad prognosis. [37]

survival. [62]

Personalized medicine is based on the clinical use of molecular biomarkers. A biomarker is any specific physical trait or measurable biological change in the organism related to disease or health conditions, being a very broad concept that includes many different measurements of a biologic status.

Besides being diagnostic [used for the establishment of a particular disease present in the patient sample [97]] or prognostic [used for the establishment of an association with clinical outcomes, such as overall survival or recurrence-free survival independently of the treatment [98] biomarkers can be predictive, by the assessment of the likely benefit of a specific treatment to a specific patient, [99] or pharmacodynamic, by the measurement of the drug effect in a disease [100].

The term, Pharmacogenetics, was first used by Vogel in 1959 as the science about the effects of heritability on drug response [101]. According to the definitions approved by the US Food and Drug Administration (FDA), pharmacogenetics is 'the study of variations in DNA sequence as related to drug response' [102] while the more comprehensive term Pharmaco‐ genomics is defined as 'the study of variations of DNA and RNA characteristics as related to drug response' [103]. Sometimes used indistinctly, Pharmacogenomics is related to the study of whole genome, the gene transcripts and population variability, with the aim of predicting the right treatment in individual patients and designing new drugs.

platin or irinotecan that have dramatically improved survival. [109-111]. The preoperative application of radiotherapy with infusional 5-FU have significantly decreased, the rate of local recurrence [112-114]. In advanced colorectal cancer fluoropyrimidine chemotherapies are basics for treatment in combination with oxaliplatin or irinotecan [115]. The integration of biological agents with conventional cytotoxic drugs has expanded the treatment of metastatic disease, resulting in an increased response rate and survival and achieving downstaging for surgical resection and potential cure. The currently approved and widely used targeted treatments are the monoclonal antibodies bevacizumab that recognizes the vasculature endothelial growth factor (VEGF) and cetuximab and panitumumab, targeting the epidermal growth factor receptor [EGFR]. These combinations reach response rates of up to 50% with a median time of progression free survival of 10–12 months for patients with advanced CRC. Biomarker development is now essential to aid selection of patients likely to respond to therapy, rationalizing treatments and improving outcomes. But the different approaches used in order to establish biomarkers of the response to treatments in patients with CRC are not lacking in controversial. Even though numerous biomarkers have been postulated to be used as pharmacogenetic markers, only a few of them are actually being used to manage cancer

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

443

Thymidylate synthase (TS) is the primary intracellular target of 5-FU. 5-FU acts by preventing the methylation of the deoxyuridine monophosphate to deoxythymidine monophosphate by forming a stable complex, 5-FU–TYMS, causing a thymine deficiency. [117] In CRC, the overexpression of TS has been associated with 5-FU resistance. [118] Several studies analysed genetic polymorphisms as potential predictive factors to 5-FU response [119] but the associa‐ tion between TS expression or TS polymorphisms and response after 5-FU adjuvant treatment is still largely unclear. Thus, although most studies report a TS expression decrease with a better response, [120] there are studies that contradict this association, regarding both the genotype and level of expression, and that link genotypes of high expression of TS with a better response [121] and even a lack of association. [116, 122] Among the several factors that can explain the variability of results, a relevant role might be played by the use of germline genetic data despite the target of 5-FU is the tumor cell. In fact, the TS genotypes from germline and tumor cells from a single patient can differ widely in rectal cancer, distorting the influence of

Although MSI CRCs have a prognostic advantage, [123] mainly due to the minor metastatic potential of MSI CRCs, [124] the predictive value of MSI is still controversial. [125-127] MSI is a strong and well validated prognostic marker to be used in the decision making process in an appropriate clinical setting, for example in stage II, the favourable outcome of patients with

Loss of heterozygosity (LOH) or allelic imbalance (AI) is common in chromosomal instability (CIN) CRC. LOH of chromosome 18q leads to the loss of the tumor suppressor gene Deleted in Colon Cancer (DCC) and had been associated with a poor prognosis of stage II and III CRC patients in several studies [129], but these data were not confirmed. [130] In addition, their role

MSI CRC suggests that adjuvant chemotherapy could be avoided. [128]

treatment [116].

**3.2. Biomarkers of 5-FU response**

TS on the response to 5-FU. [116]

In last years work in the field has grown almost exponentially [104], at the same pace as the expectations about the increasing of clinical benefit and reduction of the risk of adverse drug reactions (ADR), at least in outliers, i.e. people whose drug responses are not "average" [105].

Nonetheless, adoption of validated pharmacogenetic markers into routine clinical practice has been slow, mainly in the oncological field. Pharmacogenetics has mainly focused on the association between monogenic polymorphisms and in variations in drug metabolism. [102] But, limitations exist on the role of pharmacogenetics in cancer therapy, mainly because of the non-concordance at genetic level between germinal and somatic line of patients [106]. Herit‐ ability can be used to assess toxicity, but there are major concerns in their use to assess effectivity.

Today, more than a 100 drugs have pharmacogenomic biomarkers in drug labels approved by the U.S. Food and Drug Administration (FDA), being 35 oncology drugs [107]. In the opposite sense, the European Medicines Agency (EMA) has been more conservative in the implemen‐ tation of pharmacogenetic markers in drug labels.

In the oncology field, hematology has been the more rewarding, due in part to the lack of some of the architectural barriers found in solid tumors. As result of the pharmacogenetic manage‐ ment, survival rates of some leukemias have improved drastically. Albeit the efforts realized to infer drug efficiency from germline markers, the only ones that have been consistently replicated across the studies for efficiency, are tumor markers, leaving germline markers for the identification of patients with toxicity risk and posterior evaluation of risk/benefit of the drug.

#### **3.1. Colorectal cancer treatment efficiency**

In colorectal cancer, 75% of patients with stage I to III can be treated with surgery alone or in combination with chemotherapy, with a 5-year survival rate of 93.2%, 82.5%, and 59.5%, respectively,incontrastwithonly8.1%survivalrateofpatientsharbouringstageIVdisease.[108]

For patients management, the probability of distant metastasis and response to chemotherapy, are the most important clinical variables. With or without surgery, adjuvant chemotherapy is routinely employed to treat those colorectal cancer patients at high risk of developing recur‐ rence or, those who already have metastatic disease at the time of diagnosis (up to 20 %).

The initial standard treatment with 5-fluorouracil (5-FU), with a median overall survival of 12 months or less and an overall response rate of 10%, has evolved to combinations with oxali‐ platin or irinotecan that have dramatically improved survival. [109-111]. The preoperative application of radiotherapy with infusional 5-FU have significantly decreased, the rate of local recurrence [112-114]. In advanced colorectal cancer fluoropyrimidine chemotherapies are basics for treatment in combination with oxaliplatin or irinotecan [115]. The integration of biological agents with conventional cytotoxic drugs has expanded the treatment of metastatic disease, resulting in an increased response rate and survival and achieving downstaging for surgical resection and potential cure. The currently approved and widely used targeted treatments are the monoclonal antibodies bevacizumab that recognizes the vasculature endothelial growth factor (VEGF) and cetuximab and panitumumab, targeting the epidermal growth factor receptor [EGFR]. These combinations reach response rates of up to 50% with a median time of progression free survival of 10–12 months for patients with advanced CRC.

Biomarker development is now essential to aid selection of patients likely to respond to therapy, rationalizing treatments and improving outcomes. But the different approaches used in order to establish biomarkers of the response to treatments in patients with CRC are not lacking in controversial. Even though numerous biomarkers have been postulated to be used as pharmacogenetic markers, only a few of them are actually being used to manage cancer treatment [116].

#### **3.2. Biomarkers of 5-FU response**

The term, Pharmacogenetics, was first used by Vogel in 1959 as the science about the effects of heritability on drug response [101]. According to the definitions approved by the US Food and Drug Administration (FDA), pharmacogenetics is 'the study of variations in DNA sequence as related to drug response' [102] while the more comprehensive term Pharmaco‐ genomics is defined as 'the study of variations of DNA and RNA characteristics as related to drug response' [103]. Sometimes used indistinctly, Pharmacogenomics is related to the study of whole genome, the gene transcripts and population variability, with the aim of predicting

In last years work in the field has grown almost exponentially [104], at the same pace as the expectations about the increasing of clinical benefit and reduction of the risk of adverse drug reactions (ADR), at least in outliers, i.e. people whose drug responses are not "average" [105].

Nonetheless, adoption of validated pharmacogenetic markers into routine clinical practice has been slow, mainly in the oncological field. Pharmacogenetics has mainly focused on the association between monogenic polymorphisms and in variations in drug metabolism. [102] But, limitations exist on the role of pharmacogenetics in cancer therapy, mainly because of the non-concordance at genetic level between germinal and somatic line of patients [106]. Herit‐ ability can be used to assess toxicity, but there are major concerns in their use to assess

Today, more than a 100 drugs have pharmacogenomic biomarkers in drug labels approved by the U.S. Food and Drug Administration (FDA), being 35 oncology drugs [107]. In the opposite sense, the European Medicines Agency (EMA) has been more conservative in the implemen‐

In the oncology field, hematology has been the more rewarding, due in part to the lack of some of the architectural barriers found in solid tumors. As result of the pharmacogenetic manage‐ ment, survival rates of some leukemias have improved drastically. Albeit the efforts realized to infer drug efficiency from germline markers, the only ones that have been consistently replicated across the studies for efficiency, are tumor markers, leaving germline markers for the identification of patients with toxicity risk and posterior evaluation of risk/benefit of the

In colorectal cancer, 75% of patients with stage I to III can be treated with surgery alone or in combination with chemotherapy, with a 5-year survival rate of 93.2%, 82.5%, and 59.5%, respectively,incontrastwithonly8.1%survivalrateofpatientsharbouringstageIVdisease.[108]

For patients management, the probability of distant metastasis and response to chemotherapy, are the most important clinical variables. With or without surgery, adjuvant chemotherapy is routinely employed to treat those colorectal cancer patients at high risk of developing recur‐ rence or, those who already have metastatic disease at the time of diagnosis (up to 20 %).

The initial standard treatment with 5-fluorouracil (5-FU), with a median overall survival of 12 months or less and an overall response rate of 10%, has evolved to combinations with oxali‐

the right treatment in individual patients and designing new drugs.

442 Colorectal Cancer - Surgery, Diagnostics and Treatment

tation of pharmacogenetic markers in drug labels.

**3.1. Colorectal cancer treatment efficiency**

effectivity.

drug.

Thymidylate synthase (TS) is the primary intracellular target of 5-FU. 5-FU acts by preventing the methylation of the deoxyuridine monophosphate to deoxythymidine monophosphate by forming a stable complex, 5-FU–TYMS, causing a thymine deficiency. [117] In CRC, the overexpression of TS has been associated with 5-FU resistance. [118] Several studies analysed genetic polymorphisms as potential predictive factors to 5-FU response [119] but the associa‐ tion between TS expression or TS polymorphisms and response after 5-FU adjuvant treatment is still largely unclear. Thus, although most studies report a TS expression decrease with a better response, [120] there are studies that contradict this association, regarding both the genotype and level of expression, and that link genotypes of high expression of TS with a better response [121] and even a lack of association. [116, 122] Among the several factors that can explain the variability of results, a relevant role might be played by the use of germline genetic data despite the target of 5-FU is the tumor cell. In fact, the TS genotypes from germline and tumor cells from a single patient can differ widely in rectal cancer, distorting the influence of TS on the response to 5-FU. [116]

Although MSI CRCs have a prognostic advantage, [123] mainly due to the minor metastatic potential of MSI CRCs, [124] the predictive value of MSI is still controversial. [125-127] MSI is a strong and well validated prognostic marker to be used in the decision making process in an appropriate clinical setting, for example in stage II, the favourable outcome of patients with MSI CRC suggests that adjuvant chemotherapy could be avoided. [128]

Loss of heterozygosity (LOH) or allelic imbalance (AI) is common in chromosomal instability (CIN) CRC. LOH of chromosome 18q leads to the loss of the tumor suppressor gene Deleted in Colon Cancer (DCC) and had been associated with a poor prognosis of stage II and III CRC patients in several studies [129], but these data were not confirmed. [130] In addition, their role as predictor of outcome in CCR patients following 5-FU based adjuvant therapy, is contro‐ versial too.

in tumors. [148] The most frequent BRAF mutation (V600E) represents 50% of BRAF mutations in CCR, being more common in MSI CRC, than in microsatellite stable tumors. [128] BRAF mutation is involved in MEK-ERK pathway activation and CRC carcinogenesis. BRAF V600E is also associated with the CIMP phenotype, 70% of CIMP CRC can harbour BRAF mutations. [93] BRAF mutations have been associated with poor prognosis in patients with stage IV CRC. In agreement with the role of BRAF mutations in enhancing stimulation of downstream MEK-ERK signalling, in patients with metastatic CRC, BRAF mutations are predictive of non-

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

As stated previously, more than a 100 drugs have pharmacogenomic biomarkers in drug labels approved by the FDA. It is paradoxical that, while germline genetical markers should be better for the identification of patients with toxicity risk, the efforts in pharmacogenetic studies were realized to infer drug efficiency. Only six of the FDA approved oncology biomarkers are associated with toxicity. DPYD\*2A for capecitabine and UGT1A1\*28 irinotecan are the

With this data, the problem related to discovering biomarkers of ADRs is clear. Most studied biomarkers related to ADRs are reflected in Table 1, but they are not extensively used in clinical

> Amstutz U et al. Pharmacogenomics. 2011, 12 [9]:1321-36 FDA: XELODA® [capecitabine] Label [http:// www.accessdata.fda.gov/drugsatfda\_docs/label/ 2011/020896s026lbl.pdf]

http://dx.doi.org/10.5772/57172

445

Marques SC, Hum Genomics. 2010, 4 [4]:238-49 FDA Camptosar® Label [http://www.accessdata.fda.gov/ drugsatfda\_docs/label/2006/020571s030lbl.pdf]

26 [28]: 4672–4678

1715–1723.

Cortejoso L, López-Fernández LA. Pharmacogenomics. 2012, 12 [10]:1173-1191

**Gene Treatment Toxicity Review**

diarrhea

Neurotoxicity neutropenia hematotoxicity hematotoxicity gastrointestinal

EGFR EGFR inhibitors Skin rash Galvani E, Future Oncol. 2012, 8 [8]: 1015-29

ABCB1 capecitabine neutropenia Gonzalez-Haba E, Pharmacogenomics. 2010, 11 [12],

VEGF VEGF inhibitors hypertension Schneider BP, J. Clin. Oncol. 2008,

response to EGFR-targeted agents. [149]

biomarker associated to CRC chemotherapy. [107]

DPYD fluoropyrimidine myelotoxicity

UGT1A1 irinotecan Myelotoxicity severe

platin-based platinbased oxaliplatin oxaliplatin platin-based

**Table 1.** Association of genes to toxicity in colorectal treatments.

**3.5. Biomarkers of toxicity**

practice.

GSTP1 GSTM1 ERCC1 XPD [ERCC2] XRCC1

Near 30–50% of colorectal tumors harbour mutations in the KRAS oncogene, 90% of the mutations occurring either in codon 12 or 13. [131] However, there is no consensus about the role of KRAS as a prognostic marker [132] and KRAS mutation can hardly be expected to be a predictive marker of response to standard chemotherapy. [132, 133]

Global hypomethylation and hypermethylation of tumor, characterize epigenomic instability. Due to this context of genomic instability is difficult to know how the hypermethylated phenotype "CpG island methylator phenotype" (CIMP) affect survival rate. Despite initial results, [134] CIMP positivity in CRC seems not to be a significant independent predictor of survival benefit from 5-FU chemotherapy. [135]

#### **3.3. Biomarkers of platinum response**

Glutathione, a ubiquitous tripeptide thiol, is a vital antioxidant and has a protective role against a range of toxins including metal compounds such as cisplatin. Glutathione S-transferase P1 (GSTP1) acts directly in the detoxification of platinum compounds so it is an important factor related to resistance to platinum [136]. However, and despite initial studies [137] reporting the association between GSTP1 Ile105Val and oxaliplatin efficacy and toxicity, results of subse‐ quent studies were inconclusive. [138, 139]

High levels of excision repair cross-complementing 1 (ERCC1), an endonuclease of the nucleotide excision repair (NER) system, are associated with an increased platinum resistance. [140, 141] The x-ray repair cross complementing group 1 (XRCC1), a member of the base excision repair (BER) pathway, links to other proteins related to the BER pathways and repair specific base damage, caused by oxaliplatin. [142] XRCC1 polymorphisms increase the risk of oxaliplatin resistance, via inadequate repair or increased damage tolerance. [143] XPD (ERCC2) has an important role in DNA repair by removing bulky DNA adducts produced by environmental toxins and xenobiotics. The XPD Lys751Gln polymorphism has been associated to clinical outcome following platinum-based chemotherapy. [136, 139, 144]

#### **3.4. Biomarkers of monoclonal antibodies response**

There is a wide consensus on the predictive value of KRAS mutations in response to treatment with anti-EGFR drugs. Interestingly, a single first study, in barely 30 patients with metastatic CRC treated with cetuximab, demonstrated the relation between KRAS mutation and nonresponse: KRAS mutations were found in 68% of non-responding patients but in none of the responders. [145] [145]. The fact is that KRAS is downstream in the EGFR signalling pathway and that pathway is activated by KRAS mutations irrespective of the receptor status, overrid‐ ing the efficacy of anti-EGFR therapy. The Food and Drug Administration (FDA) approved, in a record time, label changes to cetuximab and panitumumab to advise against their use in patients with KRAS positive metastatic CCR [146, 147]

BRAF mutations also affects the EGFR signalling pathway and are found in CRC at lower frequency than KRAS (≤10%), in fact BRAF and KRAS mutations are mutually exclusive events in tumors. [148] The most frequent BRAF mutation (V600E) represents 50% of BRAF mutations in CCR, being more common in MSI CRC, than in microsatellite stable tumors. [128] BRAF mutation is involved in MEK-ERK pathway activation and CRC carcinogenesis. BRAF V600E is also associated with the CIMP phenotype, 70% of CIMP CRC can harbour BRAF mutations. [93] BRAF mutations have been associated with poor prognosis in patients with stage IV CRC. In agreement with the role of BRAF mutations in enhancing stimulation of downstream MEK-ERK signalling, in patients with metastatic CRC, BRAF mutations are predictive of nonresponse to EGFR-targeted agents. [149]

#### **3.5. Biomarkers of toxicity**

as predictor of outcome in CCR patients following 5-FU based adjuvant therapy, is contro‐

Near 30–50% of colorectal tumors harbour mutations in the KRAS oncogene, 90% of the mutations occurring either in codon 12 or 13. [131] However, there is no consensus about the role of KRAS as a prognostic marker [132] and KRAS mutation can hardly be expected to be

Global hypomethylation and hypermethylation of tumor, characterize epigenomic instability. Due to this context of genomic instability is difficult to know how the hypermethylated phenotype "CpG island methylator phenotype" (CIMP) affect survival rate. Despite initial results, [134] CIMP positivity in CRC seems not to be a significant independent predictor of

Glutathione, a ubiquitous tripeptide thiol, is a vital antioxidant and has a protective role against a range of toxins including metal compounds such as cisplatin. Glutathione S-transferase P1 (GSTP1) acts directly in the detoxification of platinum compounds so it is an important factor related to resistance to platinum [136]. However, and despite initial studies [137] reporting the association between GSTP1 Ile105Val and oxaliplatin efficacy and toxicity, results of subse‐

High levels of excision repair cross-complementing 1 (ERCC1), an endonuclease of the nucleotide excision repair (NER) system, are associated with an increased platinum resistance. [140, 141] The x-ray repair cross complementing group 1 (XRCC1), a member of the base excision repair (BER) pathway, links to other proteins related to the BER pathways and repair specific base damage, caused by oxaliplatin. [142] XRCC1 polymorphisms increase the risk of oxaliplatin resistance, via inadequate repair or increased damage tolerance. [143] XPD (ERCC2) has an important role in DNA repair by removing bulky DNA adducts produced by environmental toxins and xenobiotics. The XPD Lys751Gln polymorphism has been associated

There is a wide consensus on the predictive value of KRAS mutations in response to treatment with anti-EGFR drugs. Interestingly, a single first study, in barely 30 patients with metastatic CRC treated with cetuximab, demonstrated the relation between KRAS mutation and nonresponse: KRAS mutations were found in 68% of non-responding patients but in none of the responders. [145] [145]. The fact is that KRAS is downstream in the EGFR signalling pathway and that pathway is activated by KRAS mutations irrespective of the receptor status, overrid‐ ing the efficacy of anti-EGFR therapy. The Food and Drug Administration (FDA) approved, in a record time, label changes to cetuximab and panitumumab to advise against their use in

BRAF mutations also affects the EGFR signalling pathway and are found in CRC at lower frequency than KRAS (≤10%), in fact BRAF and KRAS mutations are mutually exclusive events

to clinical outcome following platinum-based chemotherapy. [136, 139, 144]

a predictive marker of response to standard chemotherapy. [132, 133]

survival benefit from 5-FU chemotherapy. [135]

**3.3. Biomarkers of platinum response**

444 Colorectal Cancer - Surgery, Diagnostics and Treatment

quent studies were inconclusive. [138, 139]

**3.4. Biomarkers of monoclonal antibodies response**

patients with KRAS positive metastatic CCR [146, 147]

versial too.

As stated previously, more than a 100 drugs have pharmacogenomic biomarkers in drug labels approved by the FDA. It is paradoxical that, while germline genetical markers should be better for the identification of patients with toxicity risk, the efforts in pharmacogenetic studies were realized to infer drug efficiency. Only six of the FDA approved oncology biomarkers are associated with toxicity. DPYD\*2A for capecitabine and UGT1A1\*28 irinotecan are the biomarker associated to CRC chemotherapy. [107]

With this data, the problem related to discovering biomarkers of ADRs is clear. Most studied biomarkers related to ADRs are reflected in Table 1, but they are not extensively used in clinical practice.


**Table 1.** Association of genes to toxicity in colorectal treatments.

#### **3.6. Biomarkers used in clinical practice**

In conclusion, currently the UICC/AJCC Tumor Node Metastasis (TNM) stage system remains the only valid prognostic marker for predicting the outcome of CRC patients. [150-155] Besides different histomorphological, immunohistochemical and molecular biomarkers have been proposed [156, 157] to improve stratification of CRC patients into prognostic subgroups. But, if no additional prognostic and predictive factors were included in the pre- and postoperative management of non-metastatic CRC until now, for metastatic CRC patients gene mutations are arising as predictive biomarker, mainly the KRAS mutational status, with the implemen‐ tation of anti-EGFR therapy.

Indeed, modification of tumor microenvironment is one of the novel mechanisms to overcome

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

447

It is already established that tumor microenvironment has an important role in tumor behavior as well as physical impediment of drug delivery but its function in promoting cancer devel‐ opment and drug resistance by segregating molecules by stromal cells have been recently

In colorectal cancer, presence of tumor-infiltrating lymphocytes, as part of the immune system response,hasbeenassociatedpositivelytobothsurvival andchemotherapyresponse.[165, 166]

Straussman et al. showed that resistance to RAF inhibitors are not only due to gene activated mutations but mediated by the segregation of hepatocyte growth factor (HGF) by the stromal cells. Their work confirmed the microenvironment as a frequent cause of chemotherapy

Similar to other natural ecosystems, tumor growth and development is dependent on the niche conditions. In the case of a tumor, these conditions are primarily determined by the genetic background and physiological state of the patient and lately, determined by the genetic of the tumor itself. And as it happens in all ecosystems, tumor is not in a static state, as the environ‐ ment changes, the tumor will be adapted to the changed conditions. The different conditions in which a tumor will be developed [a unique mixture of genomic and epigenomic features] determine its specific features, which are improbable to be parallel in another organism. [167]

Albeit colorectal cancer is governed by the general mechanisms described above, the existence of a different mutational spectrum between patients with the same type of cancer has been broadly reported. [168] The experimental confirmation of the 'just right hypothesis' [169] provided new insights into the importance of the genetic background of the patient in

Even the triggered mechanisms into the tumor cells contribute to such divergence: Bielas et al. determined the mutational rate in tumors and found that was, on average, 200 times greater than in normal cells. This finding uncovered a novel cancer mechanism called point mutation instability (PIN) [170, 171], and can have consequences over pharmacogenomic assays.

As stated before [116], intratumor heterogeneity may explain the difficulties encountered in the validation of oncology biomarkers owing to sampling bias. As consequence of the different conditions that tumor cells undergone, tumor cells have to adjust their behavior. The adapta‐ tion process to these variable circumstances is accompanied by a differential mutational

drug resistance. [160, 161]

proved. [161-164]

**4.2. Tumor microenvironment**

**4.3. Intertumor heterogeneity**

**4.4. Intratumor heterogeneity**

resistance, principally to targeted drugs [164].

determining tumourigenesis and tumor progression.

process that results in a genetic heterogeneous blend of cells.

## **4. Establishment issue of genotype-phenotype correlations in cancer**

In the last years, numerous candidate prognostic and predictive markers have been reported in hundreds of studies and failed to demonstrate clinical utility. It is difficult to review, even monthly, all described molecular markers of prognosis. Clearly a validation is necessary to establish an association between any of these markers with prognosis or with the response to therapy but the validation itself is not an explanation of why so many potential markers fail to be validated. Inconsistencies can arise between initial reports and subsequent studies because differences in assays, study design, genetic substructure of human populations, statistical power or methodologies. But the establishment of clear genotype-phenotypes correlations, mostly in solid tumors, is still a wide and difficult field of study due to several reasons:

#### **4.1. Architecture of solid tumor**

Hematologic cancers treatments have turned them, in some cases, in chronic diseases with the appropriate treatment. Even though they share a common problem with solid tumor, this is, localization and properties of the cancer stem cells, majority of leukemia cells are located in the bloodstream so once drugs reach the bloodstream do not have additional barriers to trespass but the cellular membrane. This more easily access by the drug allows reduce cancer cells load.

But in solid tumors, drugs have to overcome several barriers to access the cells. To get access to tumor drugs first have to extravasate and diffuse across the extracellular matrix to reach all the cells in a tumor, included not well irrigated zones where transportation into the cells is even more difficult due to the extracellular acidic pH. [158, 159]

Tumor mass is a not equally organized mass of cells with an equally distributed blood capillary network that supplies all cells in a tumor but a disorganized mass of different cells with unequally blood supply subject to a different interstitial fluid pressure that produce differential gradient of molecules distribution, among them, drugs. Thus, obstruction of an adequate intratumoral drug delivery in one the cause is one of the causes for cancer recurrence. [158, 159] Indeed, modification of tumor microenvironment is one of the novel mechanisms to overcome drug resistance. [160, 161]

#### **4.2. Tumor microenvironment**

**3.6. Biomarkers used in clinical practice**

446 Colorectal Cancer - Surgery, Diagnostics and Treatment

tation of anti-EGFR therapy.

**4.1. Architecture of solid tumor**

reasons:

cells load.

In conclusion, currently the UICC/AJCC Tumor Node Metastasis (TNM) stage system remains the only valid prognostic marker for predicting the outcome of CRC patients. [150-155] Besides different histomorphological, immunohistochemical and molecular biomarkers have been proposed [156, 157] to improve stratification of CRC patients into prognostic subgroups. But, if no additional prognostic and predictive factors were included in the pre- and postoperative management of non-metastatic CRC until now, for metastatic CRC patients gene mutations are arising as predictive biomarker, mainly the KRAS mutational status, with the implemen‐

**4. Establishment issue of genotype-phenotype correlations in cancer**

In the last years, numerous candidate prognostic and predictive markers have been reported in hundreds of studies and failed to demonstrate clinical utility. It is difficult to review, even monthly, all described molecular markers of prognosis. Clearly a validation is necessary to establish an association between any of these markers with prognosis or with the response to therapy but the validation itself is not an explanation of why so many potential markers fail to be validated. Inconsistencies can arise between initial reports and subsequent studies because differences in assays, study design, genetic substructure of human populations, statistical power or methodologies. But the establishment of clear genotype-phenotypes correlations, mostly in solid tumors, is still a wide and difficult field of study due to several

Hematologic cancers treatments have turned them, in some cases, in chronic diseases with the appropriate treatment. Even though they share a common problem with solid tumor, this is, localization and properties of the cancer stem cells, majority of leukemia cells are located in the bloodstream so once drugs reach the bloodstream do not have additional barriers to trespass but the cellular membrane. This more easily access by the drug allows reduce cancer

But in solid tumors, drugs have to overcome several barriers to access the cells. To get access to tumor drugs first have to extravasate and diffuse across the extracellular matrix to reach all the cells in a tumor, included not well irrigated zones where transportation into the cells is

Tumor mass is a not equally organized mass of cells with an equally distributed blood capillary network that supplies all cells in a tumor but a disorganized mass of different cells with unequally blood supply subject to a different interstitial fluid pressure that produce differential gradient of molecules distribution, among them, drugs. Thus, obstruction of an adequate intratumoral drug delivery in one the cause is one of the causes for cancer recurrence. [158, 159]

even more difficult due to the extracellular acidic pH. [158, 159]

It is already established that tumor microenvironment has an important role in tumor behavior as well as physical impediment of drug delivery but its function in promoting cancer devel‐ opment and drug resistance by segregating molecules by stromal cells have been recently proved. [161-164]

In colorectal cancer, presence of tumor-infiltrating lymphocytes, as part of the immune system response,hasbeenassociatedpositivelytobothsurvival andchemotherapyresponse.[165, 166]

Straussman et al. showed that resistance to RAF inhibitors are not only due to gene activated mutations but mediated by the segregation of hepatocyte growth factor (HGF) by the stromal cells. Their work confirmed the microenvironment as a frequent cause of chemotherapy resistance, principally to targeted drugs [164].

#### **4.3. Intertumor heterogeneity**

Similar to other natural ecosystems, tumor growth and development is dependent on the niche conditions. In the case of a tumor, these conditions are primarily determined by the genetic background and physiological state of the patient and lately, determined by the genetic of the tumor itself. And as it happens in all ecosystems, tumor is not in a static state, as the environ‐ ment changes, the tumor will be adapted to the changed conditions. The different conditions in which a tumor will be developed [a unique mixture of genomic and epigenomic features] determine its specific features, which are improbable to be parallel in another organism. [167]

Albeit colorectal cancer is governed by the general mechanisms described above, the existence of a different mutational spectrum between patients with the same type of cancer has been broadly reported. [168] The experimental confirmation of the 'just right hypothesis' [169] provided new insights into the importance of the genetic background of the patient in determining tumourigenesis and tumor progression.

Even the triggered mechanisms into the tumor cells contribute to such divergence: Bielas et al. determined the mutational rate in tumors and found that was, on average, 200 times greater than in normal cells. This finding uncovered a novel cancer mechanism called point mutation instability (PIN) [170, 171], and can have consequences over pharmacogenomic assays.

#### **4.4. Intratumor heterogeneity**

As stated before [116], intratumor heterogeneity may explain the difficulties encountered in the validation of oncology biomarkers owing to sampling bias. As consequence of the different conditions that tumor cells undergone, tumor cells have to adjust their behavior. The adapta‐ tion process to these variable circumstances is accompanied by a differential mutational process that results in a genetic heterogeneous blend of cells.

Gerlinger et al [172] demonstrated performing exome sequencing in primary renal carcinomas that 63 to 69% of all somatic mutations were not detectable in all the samples from different tumor sections. They also found biomarkers of good and poor prognosis in the analysis of different regions of the same tumor and high intratumor heterogeneity when ploidy was measured. [172] These findings indicate that intratumor heterogeneity is one of the most important obstacles in the establishment of biomarkers of both prognosis and response to treatment, what implies that the approaches that, so far, have been realized have to change.

Detection of genetic abnormalities is subject to the proper target identification and design of the methodologies used. For example, one of the difficulties to categorized CIMP is the choice

The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

449

The classification of the groups is often different among studies. To analyse the statistical association of a biomarker, some studies group patients in I-II stage and III-IV of cancer, having each group a different association [positive, negative or not association with respect to the analysed trait] meanwhile others does that with II-III stages. The different criteria used to group patients, is obviously a source of contradictions, since studies compare results obtained from patients with different characteristics. The different methodologies used between studies

Some limitations in studies design are an obviously consequence of the resources restraints, either economic or by shortage of the sample but extrapolation of results from these studies

The reality of high tumor heterogeneity and dynamic change of tumor behaviour makes easy to understand the very little information we can acquire when study only one, two or three markers in one slice of the tumor and this is even worse when study not targeted drugs since

As Greaves and Maley expose °genome profiles under-estimate complexity° and continue ° It may be that only a modest number of phenotypic traits are required to negotiate all constraints and evolve to full malignant or metastatic status but the inference is that this can be achieved by an almost infinite variety of evolutionary trajectories and with multiple, different combi‐

The limited capacity to detect low- prevalence clones are another source of a possible future

Another reason for inconsistencies is small study sample sizes. Typically biomarker studies are done in a subset of patients enrolled in a main study and, therefore, often not statistically adequate to answer clinical questions. Analysis is hampered further by multiple comparisons in correlative studies. Although this approach is crucial to sound statistical methodology, correction for multiple comparisons [or the failure to do so] has probably led to heterogeneity. A major statistical flaw is the potential for false-positive associations because of assessment of multiple SNPs. The opposite is a concern too; biologically important associations frequently cannot be detected after stringent correction because the selection of SNPs is too broad. Study power might also be inadequate if SNPs with excessively rare minor allele frequency are selected. Finally, racial heterogeneity within the trial is important to take into account, and

proper correction or analysis of patients in subgroups by ethnic origin must be done.

resources for their study, consolidate research consortia has become imperative.

Due to the need of major research projects, both in number of samples as in appropriate

The establishment of clear genotype-phenotypes correlations is still a wide and difficult field of study due to the previously exposed heterogeneity and overlapping characteristics observed

cell have more options to overcome their effect like compensatory mechanisms.

of the appropriate panel of loci to study methylation. [175, 176]

**4.9. Studies design**

are more hazardous.

is another source of confuse. [62, 83]

nations of driver mutations° [7]

selection of resistance. [7]

#### **4.5. Stem cells**

Other possible pitfall can be the contribution of cancer stem cells to drug resistance. As explained before, identification of the appropriate cell to direct therapy is essential to eradicate cancer. Even though treatments can decrease tumor burden, if drugs do not target the appropriate cell, chemotherapy can, as much, become a disease in chronic but not eliminate it from the organism, as it has proved in leukemias. Stem cells are the only tumor-initiating cells within a malignancy and therefore have been shown to maintain colorectal cells population, [173] in fact, they account for about 2.5%% of cancer cells in CRC. [13] But the current chemo‐ therapy is not specific for these cells, and possibly cancer stem cells are naturally resistant to chemotherapy through quiescence, capacity for DNA repair or expression of genes affecting transport and effective drug release into the cells as ABC-transporter. [174]

Even more, stem cells itself are related to genetic background of the tumor. Mutations in APC gene can increase the number of stem cells via Wnt signaling, promoting tumorigenesis [169].

#### **4.6. Response to chemotherapy**

Introduction of chemotherapy is a determinant selection factor of cell survival. The appearance of resistance cells to treatments due to mutations that prevent treatment efficiency either by selection of pre-existent resistant clones, either by the emergence of mutants clones induced by the drug, either by inducing the segregation of protective molecules by autocrine or paracrine mechanism or molecules that bypass the activity of the drug, adds new difficulties to both, discovery of clear biomarkers and development of drugs that cure cancer.

#### **4.7. Difficulty of identification or characterization of specific histologic subtypes**

Histological identification of different colorectal cancer subtypes can be tough due to its heterogeneity which makes it hardly dependent on the pathologist to identify the polyp. [37] This fact introduces an error in the genotype-phenotype correlations that obscures biomarkers identification.

#### **4.8. Techniques limitations**

The existence of high intratumor heterogeneity reveals the scarcity in the information that can be obtained from a tumor and the impossibility, so far, of study bigger regions of the tumor either because of the limited laboratory resources and high cost disclose high intratumor heterogeneity is a difficult obstacle to overcome.

Detection of genetic abnormalities is subject to the proper target identification and design of the methodologies used. For example, one of the difficulties to categorized CIMP is the choice of the appropriate panel of loci to study methylation. [175, 176]

#### **4.9. Studies design**

Gerlinger et al [172] demonstrated performing exome sequencing in primary renal carcinomas that 63 to 69% of all somatic mutations were not detectable in all the samples from different tumor sections. They also found biomarkers of good and poor prognosis in the analysis of different regions of the same tumor and high intratumor heterogeneity when ploidy was measured. [172] These findings indicate that intratumor heterogeneity is one of the most important obstacles in the establishment of biomarkers of both prognosis and response to treatment, what implies that the approaches that, so far, have been realized have to change.

Other possible pitfall can be the contribution of cancer stem cells to drug resistance. As explained before, identification of the appropriate cell to direct therapy is essential to eradicate cancer. Even though treatments can decrease tumor burden, if drugs do not target the appropriate cell, chemotherapy can, as much, become a disease in chronic but not eliminate it from the organism, as it has proved in leukemias. Stem cells are the only tumor-initiating cells within a malignancy and therefore have been shown to maintain colorectal cells population, [173] in fact, they account for about 2.5%% of cancer cells in CRC. [13] But the current chemo‐ therapy is not specific for these cells, and possibly cancer stem cells are naturally resistant to chemotherapy through quiescence, capacity for DNA repair or expression of genes affecting

Even more, stem cells itself are related to genetic background of the tumor. Mutations in APC gene can increase the number of stem cells via Wnt signaling, promoting tumorigenesis [169].

Introduction of chemotherapy is a determinant selection factor of cell survival. The appearance of resistance cells to treatments due to mutations that prevent treatment efficiency either by selection of pre-existent resistant clones, either by the emergence of mutants clones induced by the drug, either by inducing the segregation of protective molecules by autocrine or paracrine mechanism or molecules that bypass the activity of the drug, adds new difficulties

Histological identification of different colorectal cancer subtypes can be tough due to its heterogeneity which makes it hardly dependent on the pathologist to identify the polyp. [37] This fact introduces an error in the genotype-phenotype correlations that obscures biomarkers

The existence of high intratumor heterogeneity reveals the scarcity in the information that can be obtained from a tumor and the impossibility, so far, of study bigger regions of the tumor either because of the limited laboratory resources and high cost disclose high intratumor

to both, discovery of clear biomarkers and development of drugs that cure cancer.

**4.7. Difficulty of identification or characterization of specific histologic subtypes**

transport and effective drug release into the cells as ABC-transporter. [174]

**4.5. Stem cells**

448 Colorectal Cancer - Surgery, Diagnostics and Treatment

**4.6. Response to chemotherapy**

identification.

**4.8. Techniques limitations**

heterogeneity is a difficult obstacle to overcome.

The classification of the groups is often different among studies. To analyse the statistical association of a biomarker, some studies group patients in I-II stage and III-IV of cancer, having each group a different association [positive, negative or not association with respect to the analysed trait] meanwhile others does that with II-III stages. The different criteria used to group patients, is obviously a source of contradictions, since studies compare results obtained from patients with different characteristics. The different methodologies used between studies is another source of confuse. [62, 83]

Some limitations in studies design are an obviously consequence of the resources restraints, either economic or by shortage of the sample but extrapolation of results from these studies are more hazardous.

The reality of high tumor heterogeneity and dynamic change of tumor behaviour makes easy to understand the very little information we can acquire when study only one, two or three markers in one slice of the tumor and this is even worse when study not targeted drugs since cell have more options to overcome their effect like compensatory mechanisms.

As Greaves and Maley expose °genome profiles under-estimate complexity° and continue ° It may be that only a modest number of phenotypic traits are required to negotiate all constraints and evolve to full malignant or metastatic status but the inference is that this can be achieved by an almost infinite variety of evolutionary trajectories and with multiple, different combi‐ nations of driver mutations° [7]

The limited capacity to detect low- prevalence clones are another source of a possible future selection of resistance. [7]

Another reason for inconsistencies is small study sample sizes. Typically biomarker studies are done in a subset of patients enrolled in a main study and, therefore, often not statistically adequate to answer clinical questions. Analysis is hampered further by multiple comparisons in correlative studies. Although this approach is crucial to sound statistical methodology, correction for multiple comparisons [or the failure to do so] has probably led to heterogeneity. A major statistical flaw is the potential for false-positive associations because of assessment of multiple SNPs. The opposite is a concern too; biologically important associations frequently cannot be detected after stringent correction because the selection of SNPs is too broad. Study power might also be inadequate if SNPs with excessively rare minor allele frequency are selected. Finally, racial heterogeneity within the trial is important to take into account, and proper correction or analysis of patients in subgroups by ethnic origin must be done.

Due to the need of major research projects, both in number of samples as in appropriate resources for their study, consolidate research consortia has become imperative.

The establishment of clear genotype-phenotypes correlations is still a wide and difficult field of study due to the previously exposed heterogeneity and overlapping characteristics observed in colorectal cancer in both histological and molecular level, exacerbated by the confusion in identifying some histologic subtypes of polyps and the designing problem of the studies, which often compare only a few markers and patients in different stages, and with different treatments, that as previously show have an impact in the molecular mechanism trigger. As consequence, some of the published associations are not lately replicated

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The Complexity of Colorectal Cancer Biology — Putting Bricks on the Path to Personalized Medicine

http://dx.doi.org/10.5772/57172

451

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2012/08/03. eng.

## **5. Conclusion**

The clinical application of pharmacogenetic tests is still limited to a few drugs. But, the fact that a significant number of patients obtain no advantage receiving chemotherapy encourage us to increase the efforts to get more and better biomarkers. Knowledge of the problems outlined above gives us a better understanding of the challenges of pharmacogenetics and allow us to reach a better understanding of the biological basis of cancer treatments. While that work continues, new genomic technologies now in development are enabling to bring useful biomarkers from the bench to bedside in a more rapid and effective way.

## **Acknowledgements**

This work was supported in part by a grant from Acción Estratégica de Salud (ISCIII-Mineo) (PS09/02368)

## **Author details**

Emilia Balboa1 , Angel Carracedo1,2,3 and Francisco Barros1

1 Grupo Medicina Xenómica – CIBERER, Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain

2 Grupo Medicina Xenómica – CIBERER, Universidad de Santiago de Compostela, Spain

3 Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia

### **References**

[1] Loeb LA, Springgate CF, Battula N. Errors in DNA replication as a basis of malignant changes. Cancer research. 1974 Sep;34 (9):2311-21. PubMed PMID: 4136142. Epub 1974/09/01. eng.

[2] Holland AJ, Cleveland DW. Boveri revisited: chromosomal instability, aneuploidy and tumorigenesis. Nat Rev Mol Cell Biol. 2009 Jul;10 (7):478-87. PubMed PMID: 19546858. Pubmed Central PMCID: PMC3154738. Epub 2009/06/24. eng.

in colorectal cancer in both histological and molecular level, exacerbated by the confusion in identifying some histologic subtypes of polyps and the designing problem of the studies, which often compare only a few markers and patients in different stages, and with different treatments, that as previously show have an impact in the molecular mechanism trigger. As

The clinical application of pharmacogenetic tests is still limited to a few drugs. But, the fact that a significant number of patients obtain no advantage receiving chemotherapy encourage us to increase the efforts to get more and better biomarkers. Knowledge of the problems outlined above gives us a better understanding of the challenges of pharmacogenetics and allow us to reach a better understanding of the biological basis of cancer treatments. While that work continues, new genomic technologies now in development are enabling to bring

This work was supported in part by a grant from Acción Estratégica de Salud (ISCIII-Mineo)

1 Grupo Medicina Xenómica – CIBERER, Fundación Pública Galega de Medicina Xenómica,

3 Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University,

[1] Loeb LA, Springgate CF, Battula N. Errors in DNA replication as a basis of malignant changes. Cancer research. 1974 Sep;34 (9):2311-21. PubMed PMID: 4136142. Epub

2 Grupo Medicina Xenómica – CIBERER, Universidad de Santiago de Compostela, Spain

useful biomarkers from the bench to bedside in a more rapid and effective way.

, Angel Carracedo1,2,3 and Francisco Barros1

consequence, some of the published associations are not lately replicated

**5. Conclusion**

450 Colorectal Cancer - Surgery, Diagnostics and Treatment

**Acknowledgements**

(PS09/02368)

**Author details**

Jeddah, Saudi Arabia

**References**

Santiago de Compostela, Spain

1974/09/01. eng.

Emilia Balboa1


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**Chapter 18**

**The Role, Significance and Applicability of Aberrant**

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortalities in the Western world, with over 1.2 million new cases and over 0.6 million deaths being recorded in 2008 [1]. Major risk factors of CRC are personal history of precursor lesion, inflammatory bowel disease, age (about 90% of cases occur after age 50) and family history of CRC or a genetic susceptibility to the development of CRC resulting from DNA mutations. It is estimated that approximately 15% of CRC cases develop as a result of inherited factors and 5-10% of them result from known genetic syndroms, e.g., familial adenomatous polyposis (FAP) and hereditary non-polyposis colorectal carcinoma (HNPCC), while most cases of CRC occurs sporadically (70-80%) [2]. In patiens with inherited genetic factors CRC occurs early in life, usualy before 40 years of their age, while in sporadic cases cancer develops after 40 years of age with the highest incidence between 60 and 70 years of age. CRC remains asymptomatic for years. Symptoms develop insidiously and are frequently present for months, sometimes years, before being diagnosed. If colon tumors are not identified and removed at the precancerous or adenoma stage, the disease gradually progresses into carcinoma stage where cancer cells invade the wall of the

There are different approaches and strategies concerning how to reduce the mortality due to CRC. The surgical and chemotherapeutic treatment of CRC is usually costly, painful and the prognosis is not promisig. Therefore, in clinical practice efforts have been directed toward identification and removal of precancerous lesions. Screening programs, which are based upon detection and removal of visible polypoid adenomas, have been implemented in a number of

Global cancer statistics shows that CRC-related mortality has been decreasing in Western countries due to improved treatment and early detection, which indicates that screening

> © 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Crypt Foci in Clinical Practice**

Additional information is available at the end of the chapter

Martina Perše and Anton Cerar

http://dx.doi.org/10.5772/57474

intestine and distant organs [1].

countries on nationwide scale.

**1. Introduction**


## **The Role, Significance and Applicability of Aberrant Crypt Foci in Clinical Practice**

Martina Perše and Anton Cerar

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57474

## **1. Introduction**

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466 Colorectal Cancer - Surgery, Diagnostics and Treatment

22397650.

PMID: 18829469.

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortalities in the Western world, with over 1.2 million new cases and over 0.6 million deaths being recorded in 2008 [1].

Major risk factors of CRC are personal history of precursor lesion, inflammatory bowel disease, age (about 90% of cases occur after age 50) and family history of CRC or a genetic susceptibility to the development of CRC resulting from DNA mutations. It is estimated that approximately 15% of CRC cases develop as a result of inherited factors and 5-10% of them result from known genetic syndroms, e.g., familial adenomatous polyposis (FAP) and hereditary non-polyposis colorectal carcinoma (HNPCC), while most cases of CRC occurs sporadically (70-80%) [2]. In patiens with inherited genetic factors CRC occurs early in life, usualy before 40 years of their age, while in sporadic cases cancer develops after 40 years of age with the highest incidence between 60 and 70 years of age. CRC remains asymptomatic for years. Symptoms develop insidiously and are frequently present for months, sometimes years, before being diagnosed. If colon tumors are not identified and removed at the precancerous or adenoma stage, the disease gradually progresses into carcinoma stage where cancer cells invade the wall of the intestine and distant organs [1].

There are different approaches and strategies concerning how to reduce the mortality due to CRC. The surgical and chemotherapeutic treatment of CRC is usually costly, painful and the prognosis is not promisig. Therefore, in clinical practice efforts have been directed toward identification and removal of precancerous lesions. Screening programs, which are based upon detection and removal of visible polypoid adenomas, have been implemented in a number of countries on nationwide scale.

Global cancer statistics shows that CRC-related mortality has been decreasing in Western countries due to improved treatment and early detection, which indicates that screening

© 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

program is one of the important steps in reducing the mortality due to CRC [1]. However, although screening programs are promising and represent one of the important steps in reducing the mortality due to CRC, reports demonstrate that there is still 25% of false-negative results due to flat or depressed precancerous lesions, which are commonly missed during conventional colonoscopy [3].

To better understand the histological background of ACF as well as molecular alterations recognized and described at this stage of colon carcinogenesis, the next section is brief overview of histological criteria and classification of ACF, histologically denoted as colorectal

The Role, Significance and Applicability of Aberrant Crypt Foci in Clinical Practice

http://dx.doi.org/10.5772/57474

469

Histologically, ACF are heterogeneous group of intraepithelial lesions that exhibit variable features, ranging from almost normal or mild atypia to severe dysplasia. Based on their

According to World Health Organization ACF are histologically classified into two groups,

It has been demonstrated that the majority of observed ACF, including ACF identified in patients with sporadic CRC, are classified as almost histologically normal (Figure 1). These ACF are composed of crypts with almost normal histological appearance. The major histologic difference that distinguishes this type of ACF from normal crypts is slightly enlarged crypt diameter. The crypt diameter in this type of ACF measures up to 1.5 times the diameter of a normal crypt. They show no other histological or molecular alterations and they even spon‐ taneously regress. Accordingly, it was found that this type of ACF has no clinical diagnostic

**Figure 1.** A normal human (left) and rat (right) colorectal mucosa. Crypts are parallel. The mucin is stained blue (Krey‐

histological characteristics they can be divided into three main categories [7; 14]:

i.e. ACF with hyperplastic crypts and ACF with dysplastic crypts [19].

intraepithelial lesions [17; 18].

**3. Histological characteristics of ACF**

**1.** ACF that are almost histologically normal,

**2.** ACF with hyperplastic crypts and

**3.** ACF with dysplastic crypts.

value [7; 14].

berg trichrom stain).

Recently, another promising approach has been demonstrated. It is directed toward identifi‐ cation of aberrant crypt foci (ACF), intermediate biomarkers predictive for CRC. The associa‐ tion of ACF with CRC is supported by shared histological and molecular features of ACF with colonic polyps and adenomas [4-7].

The aim of the present chapter is to summarize experimental and clinical results regarding morphological, histological and molecular characteristics of ACF with emphasis on current progress in the knowledge of CRC development. The role, significance and applicability of ACF in clinical practice is also presented and discussed.

## **2. Aberrant crypt foci (ACF)**

ACF are the first lesions in multistep development of CRC, which can be seen on the colon surface with aid of magnification and/or dye.

ACF were first identified in 1987 by Bird on whole unembedded colon of carcinogen treated mouse [8]. Colon was fixed, stained with methylene blue and observed under low-magnifi‐ cation (10-40x M) stereomicroscope [9; 10]. This simple and rapid methodological approach enabled visualization of all crypts on the surface of the colon mucosa. Since their first identi‐ fication numerous studies investigating morphology, distribution, histology and molecular characteristics of ACF have been performed. In 1991 reports on identification of ACF in the human colon were published. ACF were identified under a dissecting microscope after methylene blue staining on the mucosal surface of both formalin-fixed human colon resections and fresh (unfixed) colon resections [11-13].

Based on morphological appearance of crypts on the colon surface crypts can be regarded as normal or aberrant. Aberrant crypts can be observed as single altered crypt or as a cluster of altered crypts that form a focus termed ACF [8; 14; 15].

It is important to keep in mind that ACF is a term that denotes topographic or endoscopic observation. ACF can be identified as clusters of altered crypts in unembedded colon mucosa (fixed or fresh) under magnification after visualization by different dyes. In studies using animal models ACF are usually observed under stereomicroscope on whole colon mucosa that is fixed flat (to prevent excessive unevenness while viewing) and stained with methylene blue [9; 10]. In clinical practice ACF can be observed *in vivo* endoscopically with aid of dye spray (methylene blue or indigo carmine) using high magnification colonoscopy [6; 7; 16].

ACF is not a histological diagnosis. Structural and cytological features of ACF can be recog‐ nized or confirmed only after histological examination. However, at the same time it is noteworthy to mention that lesions seen in histologic sections of colon without prior topo‐ graphic identification on colon surface can not be termed ACF.

To better understand the histological background of ACF as well as molecular alterations recognized and described at this stage of colon carcinogenesis, the next section is brief overview of histological criteria and classification of ACF, histologically denoted as colorectal intraepithelial lesions [17; 18].

## **3. Histological characteristics of ACF**

Histologically, ACF are heterogeneous group of intraepithelial lesions that exhibit variable features, ranging from almost normal or mild atypia to severe dysplasia. Based on their histological characteristics they can be divided into three main categories [7; 14]:


program is one of the important steps in reducing the mortality due to CRC [1]. However, although screening programs are promising and represent one of the important steps in reducing the mortality due to CRC, reports demonstrate that there is still 25% of false-negative results due to flat or depressed precancerous lesions, which are commonly missed during

Recently, another promising approach has been demonstrated. It is directed toward identifi‐ cation of aberrant crypt foci (ACF), intermediate biomarkers predictive for CRC. The associa‐ tion of ACF with CRC is supported by shared histological and molecular features of ACF with

The aim of the present chapter is to summarize experimental and clinical results regarding morphological, histological and molecular characteristics of ACF with emphasis on current progress in the knowledge of CRC development. The role, significance and applicability of

ACF are the first lesions in multistep development of CRC, which can be seen on the colon

ACF were first identified in 1987 by Bird on whole unembedded colon of carcinogen treated mouse [8]. Colon was fixed, stained with methylene blue and observed under low-magnifi‐ cation (10-40x M) stereomicroscope [9; 10]. This simple and rapid methodological approach enabled visualization of all crypts on the surface of the colon mucosa. Since their first identi‐ fication numerous studies investigating morphology, distribution, histology and molecular characteristics of ACF have been performed. In 1991 reports on identification of ACF in the human colon were published. ACF were identified under a dissecting microscope after methylene blue staining on the mucosal surface of both formalin-fixed human colon resections

Based on morphological appearance of crypts on the colon surface crypts can be regarded as normal or aberrant. Aberrant crypts can be observed as single altered crypt or as a cluster of

It is important to keep in mind that ACF is a term that denotes topographic or endoscopic observation. ACF can be identified as clusters of altered crypts in unembedded colon mucosa (fixed or fresh) under magnification after visualization by different dyes. In studies using animal models ACF are usually observed under stereomicroscope on whole colon mucosa that is fixed flat (to prevent excessive unevenness while viewing) and stained with methylene blue [9; 10]. In clinical practice ACF can be observed *in vivo* endoscopically with aid of dye spray

ACF is not a histological diagnosis. Structural and cytological features of ACF can be recog‐ nized or confirmed only after histological examination. However, at the same time it is noteworthy to mention that lesions seen in histologic sections of colon without prior topo‐

(methylene blue or indigo carmine) using high magnification colonoscopy [6; 7; 16].

conventional colonoscopy [3].

colonic polyps and adenomas [4-7].

468 Colorectal Cancer - Surgery, Diagnostics and Treatment

**2. Aberrant crypt foci (ACF)**

surface with aid of magnification and/or dye.

and fresh (unfixed) colon resections [11-13].

altered crypts that form a focus termed ACF [8; 14; 15].

graphic identification on colon surface can not be termed ACF.

ACF in clinical practice is also presented and discussed.

According to World Health Organization ACF are histologically classified into two groups, i.e. ACF with hyperplastic crypts and ACF with dysplastic crypts [19].

It has been demonstrated that the majority of observed ACF, including ACF identified in patients with sporadic CRC, are classified as almost histologically normal (Figure 1). These ACF are composed of crypts with almost normal histological appearance. The major histologic difference that distinguishes this type of ACF from normal crypts is slightly enlarged crypt diameter. The crypt diameter in this type of ACF measures up to 1.5 times the diameter of a normal crypt. They show no other histological or molecular alterations and they even spon‐ taneously regress. Accordingly, it was found that this type of ACF has no clinical diagnostic value [7; 14].

**Figure 1.** A normal human (left) and rat (right) colorectal mucosa. Crypts are parallel. The mucin is stained blue (Krey‐ berg trichrom stain).

On the other hand, other two groups of ACF have been found to have potential clinical value as biomarker predictive for CRC risk [7; 14].

synonymous with terms atypical hyperplasia, microadenoma, carcinoma *in situ* and dysplasia. Depending on cytological and architectural features IEN is classified as low-grade or high grade. The differential histological criteria involve hypercellularity with enlarged, hyperchro‐ matic nuclei, varying degrees of nuclear stratification, loss of polarity, high nuclear/cytoplas‐ mic ratio, nuclear crowding, increased mitotic index and decreased mucin excretion [17; 20].

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**Figure 3.** Dysplastic aberrant crypts of human colorectal mucosa accompanying FAP (left). The focus is composed of 4 crypts. The level of focus is higher then that of the surrounding mucosa. The epithelial cells covering the aberrant crypts are classified as mild dysplasia. On the right there are dysplastic aberrant crypts of rat colorectal mucosa in‐ duced by carcinogen. The focus is composed of 3 crypts that show severe mucin depletion. Numerous mitoses, stratifi‐ cation of nuclei, atypical epithelial cells, and architectural atypia are the components of dysplasia (Kreyberg trichrom

Evidence from experimental and clinical studies demonstrates that ACF share similar histo‐ logical and molecular features as colonic tumors (i.e. adenomas and adenocarcinomas) [15; 21; 22]. Today, high-magnification chromoscopic colonoscopy allows detection and biopsy of ACF *in vivo* in man. It also provides opportunity to investigate and characterize the earliest genetic and molecular alterations in CRC development in man. ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC.

It has been found that ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC. Genetic alterations found in human ACF include mutations in tumor suppressor genes, microsatellite instability, aberrant meth‐ ylation as well as aberrant expression of proteins (summarized in Figure 4). Up to date, three molecular pathways of CRC development have been identified and described, i.e. chromoso‐ mal instability, microsatellite instability and CpG island methylator phenotype. All three types

stain).

**6. Molecular characteristics of ACF**

of molecular alterations have also been found in ACF [22; 23].

## **4. ACF with hyperplastic crypts (hyperplastic intraepithelial lesions)**

Hyperplastic epithelial lesions are composed of mixture of goblet and absorptive cells with enlarged or sometimes crowded nuclei without stratification (Figure 2).

**Figure 2.** Hyperplastic aberrant crypts of human (left) colorectal mucosa accompanying resected sporadic colorectal adenoma. The focus is composed of 3 hyperplastic crypts that are much wider then surrounding normal crypts. The epithelial cells of the hyperplastic crypts are higher and composed of one layer. On the right there are hyperplastic aberrant crypts of rat colorectal mucosa, induced by carcinogen. The focus is composed of 3 crypts with slight mucin depletion. The level of focus is higher then of the surrounding mucosa. The epithelial cells of the hyperplastic crypts are higher and composed of one layer (Kreyberg trichrom stain).

Mitotic figures are limited to the lower two-thirds of the crypts and are never observed on the surface of crypts. Nuclei are basally located, ovoid or round, with occasional visible nucleoli and usually uniformly dark. The luminal opening of crypts is slightly elevated from the surrounding normal mucosa and the crypts are elongated and occasionally branching with partial mucin depletion [17]. The role of hyperplastic aberrant crypts in the process of colon carcinogenesis is not clear and is a matter of debate and further investigations [15].

## **5. ACF with dysplastic crypts (intraepithelial neoplasia/dysplasia)**

Presence of dysplasia is regarded as early histopathological changes in the precursor lesions of colon cancer. The word dysplasia is histological term that describes structural and cytolog‐ ical alterations in the epithelium that predispose an organ to cancer development. Inraepithe‐ lial neoplasia (IEN) is a histological term for dysplastic lesions in the epithelial layer of colon mucosa that can be identified only after careful histological examination (Figure 3). IEN is synonymous with terms atypical hyperplasia, microadenoma, carcinoma *in situ* and dysplasia. Depending on cytological and architectural features IEN is classified as low-grade or high grade. The differential histological criteria involve hypercellularity with enlarged, hyperchro‐ matic nuclei, varying degrees of nuclear stratification, loss of polarity, high nuclear/cytoplas‐ mic ratio, nuclear crowding, increased mitotic index and decreased mucin excretion [17; 20].

**Figure 3.** Dysplastic aberrant crypts of human colorectal mucosa accompanying FAP (left). The focus is composed of 4 crypts. The level of focus is higher then that of the surrounding mucosa. The epithelial cells covering the aberrant crypts are classified as mild dysplasia. On the right there are dysplastic aberrant crypts of rat colorectal mucosa in‐ duced by carcinogen. The focus is composed of 3 crypts that show severe mucin depletion. Numerous mitoses, stratifi‐ cation of nuclei, atypical epithelial cells, and architectural atypia are the components of dysplasia (Kreyberg trichrom stain).

## **6. Molecular characteristics of ACF**

On the other hand, other two groups of ACF have been found to have potential clinical value

Hyperplastic epithelial lesions are composed of mixture of goblet and absorptive cells with

**Figure 2.** Hyperplastic aberrant crypts of human (left) colorectal mucosa accompanying resected sporadic colorectal adenoma. The focus is composed of 3 hyperplastic crypts that are much wider then surrounding normal crypts. The epithelial cells of the hyperplastic crypts are higher and composed of one layer. On the right there are hyperplastic aberrant crypts of rat colorectal mucosa, induced by carcinogen. The focus is composed of 3 crypts with slight mucin depletion. The level of focus is higher then of the surrounding mucosa. The epithelial cells of the hyperplastic crypts

Mitotic figures are limited to the lower two-thirds of the crypts and are never observed on the surface of crypts. Nuclei are basally located, ovoid or round, with occasional visible nucleoli and usually uniformly dark. The luminal opening of crypts is slightly elevated from the surrounding normal mucosa and the crypts are elongated and occasionally branching with partial mucin depletion [17]. The role of hyperplastic aberrant crypts in the process of colon

carcinogenesis is not clear and is a matter of debate and further investigations [15].

**5. ACF with dysplastic crypts (intraepithelial neoplasia/dysplasia)**

Presence of dysplasia is regarded as early histopathological changes in the precursor lesions of colon cancer. The word dysplasia is histological term that describes structural and cytolog‐ ical alterations in the epithelium that predispose an organ to cancer development. Inraepithe‐ lial neoplasia (IEN) is a histological term for dysplastic lesions in the epithelial layer of colon mucosa that can be identified only after careful histological examination (Figure 3). IEN is

**4. ACF with hyperplastic crypts (hyperplastic intraepithelial lesions)**

enlarged or sometimes crowded nuclei without stratification (Figure 2).

as biomarker predictive for CRC risk [7; 14].

470 Colorectal Cancer - Surgery, Diagnostics and Treatment

are higher and composed of one layer (Kreyberg trichrom stain).

Evidence from experimental and clinical studies demonstrates that ACF share similar histo‐ logical and molecular features as colonic tumors (i.e. adenomas and adenocarcinomas) [15; 21; 22]. Today, high-magnification chromoscopic colonoscopy allows detection and biopsy of ACF *in vivo* in man. It also provides opportunity to investigate and characterize the earliest genetic and molecular alterations in CRC development in man. ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC.

It has been found that ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC. Genetic alterations found in human ACF include mutations in tumor suppressor genes, microsatellite instability, aberrant meth‐ ylation as well as aberrant expression of proteins (summarized in Figure 4). Up to date, three molecular pathways of CRC development have been identified and described, i.e. chromoso‐ mal instability, microsatellite instability and CpG island methylator phenotype. All three types of molecular alterations have also been found in ACF [22; 23].

**8. The microsatellite instability (MSI)**

and less hyperplastic ACF (7%) [32].

patients with sporadic CRC (82%) [7].

patients with HNPCC (90%) but also found in sporadic CRC (15%).

**9. The CpG island methylator phenotype (CIMP)**

in human CRC are *p16, hMLH1, MGMT, MINT1,2,12*, and *31 [22; 23]*.

**10. ACF revealing new insight into CRC development**

knowledge into first alterations and risk factors in CRC development.

MSI is a hallmark of defective DNA mismatch repair (MMR) genes such as *hMLH1* or *hMSH2* and leads to the accumulation of a high frequency of somatic mutations [24]. It is frequent in

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MSI was identified in 30% ACF from patients of elevated risk (family or personal history) and 13% lesions from average risk patients (subjects without family or personal history) [24-26].

CIMP is epigenetic mechanism characterized by hypermethylation of cytosine residue within CpG islands in the promoter regions of certain genes (which are particularly rich in CpG nucleotides such as tumor suppressor and MMR genes) and results in their inactivation (loss of gene expression). Genes that have been shown to be silenced by promoter hypermethylation

Methylation of CpG islands was found in 34% ACF obtained from patients with both FAP and sporadic CRC, but was more frequent in sporadic ACF (53%), especially dysplastic ACF (75%)

In ACF hypermethylation of the MMR genes such as *hHLM1* and *MGMT* (in hyperplastic ACF) [26] and tumor suppressor genes such as *p16*, *MINT31* [32], *RASSF1A* were found [26].

As high-magnification chromoscopic colonoscopy now allow detection and biopsy of ACF in the mucosa of large bowel, ACF might serve as a research tool for revealing new insights and

Evidence shows that ACF in FAP patients differ from ACF in subjects with sporadic CRC. Differences can be observed regarding endoscopic, histological and molecular characteristics. Patients with FAP have significantly increased number of ACF than patients with sporadic CRC. Most of the ACF in FAP patients is histologically diagnosed as dysplastic (89%), while patients with sporadic CRC have mostly ACF with hyperplastic crypts (82%). *K-RAS* mutation was found very rarely in dysplastic ACF of FAP patients, but frequently in ACF obtained from

Conversely, *APC* mutations were very rarely found in dysplastic ACF from patients with sporadic CRC, while in ACF from FAP patients were almost always present. Methylation of

Differences in the endoscopic appearance and genetic features were observed also in ACF obtained from patients with ulcerative colitis (UC). In ACF from patients with UC *K-RAS*

CpG islands was found in sporadic ACF but not in ACF from FAP patients [32].

**Figure 4.** Phenotypic, genetic and epigenetic alteration involved in multistep development of colon carcinogenesis.

## **7. The chromosomal instability (CIN)**

CIN is the most common in sporadic CRC and shows chromosomal abnormalities such as chromosome breaks, duplication, rearrangements, loss of heterozygosity (LOH) and sequen‐ tial inactivation of tumor suppressor genes such as APC (5q), P53 (17p) and SMAD4 (18q), which are frequently found in sporadic carcinomas. It is known that germ line mutations in APC lead to the hereditary syndrome of FAP [22; 23].

Loss of heterozygosity (LOH) was observed in ACF at 18q (locus that maps close to the DCC and DPC4 genes) [24], in 67% LOH was found at locus 11p11, the location of the gene for protein tyrosine phosphatase receptor type J (PTPRJ; tumor suppressor gene), at locus 5q21 and 18q21 [25]. LOH was identified near the APC tumor suppressor gene (at the D5S346 marker) [26].

APC mutation was found in ACF with dysplastic crypts but not in ACF with hyperplastic crypts. This was frequently observed in ACF obtained from patients with FAP, while in ACF obtained from patients with sporadic CRC APC mutation was rarely observed [7; 27; 28].

β-catenin mutation, which is found in 12% of adenomas and 16% of carcinomas, was not found in ACF, regardless of the histologic type of ACF [5; 29]. Only increased expression of β-catenin was found in the cytosol of ACF with dysplastic crypts (54%) [30; 31].

K-RAS mutation was found in 13%-95% of ACF and was much more frequent in ACF with hyperplastic crypts (80%-100%) that in ACF with dysplastic crypts (0%-57%) [7; 27; 28; 32-35].

## **8. The microsatellite instability (MSI)**

**Figure 4.** Phenotypic, genetic and epigenetic alteration involved in multistep development of colon carcinogenesis.

CIN is the most common in sporadic CRC and shows chromosomal abnormalities such as chromosome breaks, duplication, rearrangements, loss of heterozygosity (LOH) and sequen‐ tial inactivation of tumor suppressor genes such as APC (5q), P53 (17p) and SMAD4 (18q), which are frequently found in sporadic carcinomas. It is known that germ line mutations in

Loss of heterozygosity (LOH) was observed in ACF at 18q (locus that maps close to the DCC and DPC4 genes) [24], in 67% LOH was found at locus 11p11, the location of the gene for protein tyrosine phosphatase receptor type J (PTPRJ; tumor suppressor gene), at locus 5q21 and 18q21 [25]. LOH was identified near the APC tumor suppressor gene (at the D5S346 marker) [26].

APC mutation was found in ACF with dysplastic crypts but not in ACF with hyperplastic crypts. This was frequently observed in ACF obtained from patients with FAP, while in ACF obtained from patients with sporadic CRC APC mutation was rarely observed [7; 27; 28].

β-catenin mutation, which is found in 12% of adenomas and 16% of carcinomas, was not found in ACF, regardless of the histologic type of ACF [5; 29]. Only increased expression of β-catenin

K-RAS mutation was found in 13%-95% of ACF and was much more frequent in ACF with hyperplastic crypts (80%-100%) that in ACF with dysplastic crypts (0%-57%) [7; 27; 28; 32-35].

was found in the cytosol of ACF with dysplastic crypts (54%) [30; 31].

**7. The chromosomal instability (CIN)**

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APC lead to the hereditary syndrome of FAP [22; 23].

MSI is a hallmark of defective DNA mismatch repair (MMR) genes such as *hMLH1* or *hMSH2* and leads to the accumulation of a high frequency of somatic mutations [24]. It is frequent in patients with HNPCC (90%) but also found in sporadic CRC (15%).

MSI was identified in 30% ACF from patients of elevated risk (family or personal history) and 13% lesions from average risk patients (subjects without family or personal history) [24-26].

## **9. The CpG island methylator phenotype (CIMP)**

CIMP is epigenetic mechanism characterized by hypermethylation of cytosine residue within CpG islands in the promoter regions of certain genes (which are particularly rich in CpG nucleotides such as tumor suppressor and MMR genes) and results in their inactivation (loss of gene expression). Genes that have been shown to be silenced by promoter hypermethylation in human CRC are *p16, hMLH1, MGMT, MINT1,2,12*, and *31 [22; 23]*.

Methylation of CpG islands was found in 34% ACF obtained from patients with both FAP and sporadic CRC, but was more frequent in sporadic ACF (53%), especially dysplastic ACF (75%) and less hyperplastic ACF (7%) [32].

In ACF hypermethylation of the MMR genes such as *hHLM1* and *MGMT* (in hyperplastic ACF) [26] and tumor suppressor genes such as *p16*, *MINT31* [32], *RASSF1A* were found [26].

## **10. ACF revealing new insight into CRC development**

As high-magnification chromoscopic colonoscopy now allow detection and biopsy of ACF in the mucosa of large bowel, ACF might serve as a research tool for revealing new insights and knowledge into first alterations and risk factors in CRC development.

Evidence shows that ACF in FAP patients differ from ACF in subjects with sporadic CRC. Differences can be observed regarding endoscopic, histological and molecular characteristics. Patients with FAP have significantly increased number of ACF than patients with sporadic CRC. Most of the ACF in FAP patients is histologically diagnosed as dysplastic (89%), while patients with sporadic CRC have mostly ACF with hyperplastic crypts (82%). *K-RAS* mutation was found very rarely in dysplastic ACF of FAP patients, but frequently in ACF obtained from patients with sporadic CRC (82%) [7].

Conversely, *APC* mutations were very rarely found in dysplastic ACF from patients with sporadic CRC, while in ACF from FAP patients were almost always present. Methylation of CpG islands was found in sporadic ACF but not in ACF from FAP patients [32].

Differences in the endoscopic appearance and genetic features were observed also in ACF obtained from patients with ulcerative colitis (UC). In ACF from patients with UC *K-RAS* mutation was rarely observed and *APC* mutation was not found. However, in dysplastic ACF frequent methylation of promoter region of *p16* (73%) and *P53* mutation (60%) was found [36].

**12. Prevalence and density of ACF**

**13. Endoscopic detection of ACF**

plastic crypts than normal subjects [6].

depressed carcinoma [16].

prevalence and number of ACF was intermediate [6].

First data about density (average number of ACF per cm2 of mucosa) and anatomical location of ACF in colonic mucosa are based on investigations of colorectal resections. Results have shown that patients with increased risk (personal or family history) have higher average number of ACF per cm2 than persons with average risk (subjects without personal or family history). It was found that FAP patients have significantly higher density of ACF in colon mucosa than patients with sporadic CRC or benign bowel disease. Higher frequencies of ACF were observed in left than in right colon. Results have shown that density of ACF increases from proximal to distal part of the colon, being the highest in the rectosigmoidal region, which

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Similar findings regarding prevalence and distribution of ACF in colorectal mucosa have been observed in humans *in vivo* by using magnifying (40x) endoscopy after endoscopic staining of colon mucosa (methylene blue). Takayama et al. [6] examined 370 subjects (147 normal subjects, 130 patients with adenoma, and 48 patients with carcinoma) and found that ACF were present in almost all patients with adenoma or carcinoma. ACF were most frequently observed in the left colon, where polyps are often found. Additionally, it was found that patients with adenoma or carcinoma had significantly higher estimated relative risks for ACF with dys‐

In normal subjects, both the prevalence and the number of ACF in subjects under 40 years of age were very low (10%) but increased with age, particularly after the age of 40 (54% - 66%). Conversely, patients with cancer had a consistently high prevalence (100%) and large number of ACF regardless of age. In patients with adenoma, the age-associated increment in the

Takayama et al. [6] investigated number, density, and dysplastic features of distal colorectal ACF in patients with exophytic adenomas and carcinomas, while Hurlstone et al. [16] assessed the prevalence and features of ACF in patients with flat and depressed colorectal neoplastic lesions, which account for around one third of all colorectal lesions. High magnification chromoscopic colonoscopy was performed on 574 healthy subjects, 281 patients with flat adenomas and 14 patients with flat carcinomas in which 602 (3% of them dysplastic), 2796 (18% dysplastic) and 594 (61 % dysplastic) ACF were identified, respectively. Similarly as in patients with exophytic colorectal lesions, the number of ACF increased in a stepwise fashion from normal subjects to patients with flat or depressed adenoma and then to patients with flat or

In another study 103 patients with average age of 61 (range of 28-87) were examined by using magnification (60x) chromoscopic colonoscopy. 788 ACF were found in the distal 20 cm of colon/rectum. Patients with a family history of CRC had a significantly higher mean number

of ACF than the average risk subjects (7.6% dysplastic and 46% hyperplastic) [5].

corresponds to anatomical location of CRC development [11-14; 34].

All these data show that ACF provide opportunity to get closer insight into first molecular events that are responsible for initiation and formation of CRC.

## **11. Endoscopic characteristics of ACF**

As already mentioned ACF are the first lesions that can be found on the surface of the fixed or fresh colorectal mucosa. ACF are invisible to standard endoscopic instruments but can now be visualized *in vivo* endoscopically by using specialized magnifying colonoscopes in con‐ junction with dye sprays (methylene blue, indigo carmine), the technique termed highmagnification chromoscopic colonoscopy [6].

Staining of the colonic mucosa at colonoscopy improves the visibility of the morphological characteristics of the crypts in the mucosa, such as shape, size or luminal openings of the crypts. Most prominent feature of aberrant crypts is that they stain more darkly than do normal surrounding crypts. However, there are also other morphological features important for identification of ACF. By definition, ACF are colon crypts that are larger than normal sur‐ rounding crypts, have increased pericryptal space that separates them from the normal crypts, they have a thicker layer of epithelial cells that often stains darker, their luminal openings are not circular but rather oval or even compressed. They are usually not in the same level as the surrounding normal crypts but they are either slightly elevated above the mucosa or may be even depressed. ACF may be composed of one to few hundreds of aberrant crypts per focus (1 to 412) [10; 14; 15].

As explained, ACF are heterogeneous group of lesions that exhibit variability in histological and molecular characteristics as well as variability in morphological characteristics.

Based on the surface morphologic features of ACF, researchers are able to distinguish three types of ACF and predict histologic characteristics of ACF [6].

Aberrant crypts that stain more darkly and are larger, have a thicker epithelial lining and a larger pericryptal zone than normal crypts and exhibit large oval (smooth, dilated) lumens have been histologically diagnosed as almost normal. Such ACF have slight enlargement, irregularity, and elongation of the ducts but show no signs of hyperplasia or dysplasia [6].

Aberrant crypts that have all above-mentioned characteristics and exhibit asteroid or slit shape of lumens have been histologically diagnosed as hyperplastic with serrated luminal pattern. Aberrant crypts that have ticker epithelial lining than both above mentioned types and exhibit compressed or undistinguishable lumen are classified in the third group of ACF, histologically diagnosed as dysplastic. Such ACF show loss of polarity, hyperchromatism and stratification of the nuclei in the crypt epithelium [6; 12; 14].

## **12. Prevalence and density of ACF**

mutation was rarely observed and *APC* mutation was not found. However, in dysplastic ACF frequent methylation of promoter region of *p16* (73%) and *P53* mutation (60%) was found [36].

All these data show that ACF provide opportunity to get closer insight into first molecular

As already mentioned ACF are the first lesions that can be found on the surface of the fixed or fresh colorectal mucosa. ACF are invisible to standard endoscopic instruments but can now be visualized *in vivo* endoscopically by using specialized magnifying colonoscopes in con‐ junction with dye sprays (methylene blue, indigo carmine), the technique termed high-

Staining of the colonic mucosa at colonoscopy improves the visibility of the morphological characteristics of the crypts in the mucosa, such as shape, size or luminal openings of the crypts. Most prominent feature of aberrant crypts is that they stain more darkly than do normal surrounding crypts. However, there are also other morphological features important for identification of ACF. By definition, ACF are colon crypts that are larger than normal sur‐ rounding crypts, have increased pericryptal space that separates them from the normal crypts, they have a thicker layer of epithelial cells that often stains darker, their luminal openings are not circular but rather oval or even compressed. They are usually not in the same level as the surrounding normal crypts but they are either slightly elevated above the mucosa or may be even depressed. ACF may be composed of one to few hundreds of aberrant crypts per focus

As explained, ACF are heterogeneous group of lesions that exhibit variability in histological

Based on the surface morphologic features of ACF, researchers are able to distinguish three

Aberrant crypts that stain more darkly and are larger, have a thicker epithelial lining and a larger pericryptal zone than normal crypts and exhibit large oval (smooth, dilated) lumens have been histologically diagnosed as almost normal. Such ACF have slight enlargement, irregularity, and elongation of the ducts but show no signs of hyperplasia or dysplasia [6].

Aberrant crypts that have all above-mentioned characteristics and exhibit asteroid or slit shape of lumens have been histologically diagnosed as hyperplastic with serrated luminal pattern. Aberrant crypts that have ticker epithelial lining than both above mentioned types and exhibit compressed or undistinguishable lumen are classified in the third group of ACF, histologically diagnosed as dysplastic. Such ACF show loss of polarity, hyperchromatism and stratification

and molecular characteristics as well as variability in morphological characteristics.

types of ACF and predict histologic characteristics of ACF [6].

of the nuclei in the crypt epithelium [6; 12; 14].

events that are responsible for initiation and formation of CRC.

**11. Endoscopic characteristics of ACF**

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magnification chromoscopic colonoscopy [6].

(1 to 412) [10; 14; 15].

First data about density (average number of ACF per cm2 of mucosa) and anatomical location of ACF in colonic mucosa are based on investigations of colorectal resections. Results have shown that patients with increased risk (personal or family history) have higher average number of ACF per cm2 than persons with average risk (subjects without personal or family history). It was found that FAP patients have significantly higher density of ACF in colon mucosa than patients with sporadic CRC or benign bowel disease. Higher frequencies of ACF were observed in left than in right colon. Results have shown that density of ACF increases from proximal to distal part of the colon, being the highest in the rectosigmoidal region, which corresponds to anatomical location of CRC development [11-14; 34].

## **13. Endoscopic detection of ACF**

Similar findings regarding prevalence and distribution of ACF in colorectal mucosa have been observed in humans *in vivo* by using magnifying (40x) endoscopy after endoscopic staining of colon mucosa (methylene blue). Takayama et al. [6] examined 370 subjects (147 normal subjects, 130 patients with adenoma, and 48 patients with carcinoma) and found that ACF were present in almost all patients with adenoma or carcinoma. ACF were most frequently observed in the left colon, where polyps are often found. Additionally, it was found that patients with adenoma or carcinoma had significantly higher estimated relative risks for ACF with dys‐ plastic crypts than normal subjects [6].

In normal subjects, both the prevalence and the number of ACF in subjects under 40 years of age were very low (10%) but increased with age, particularly after the age of 40 (54% - 66%). Conversely, patients with cancer had a consistently high prevalence (100%) and large number of ACF regardless of age. In patients with adenoma, the age-associated increment in the prevalence and number of ACF was intermediate [6].

Takayama et al. [6] investigated number, density, and dysplastic features of distal colorectal ACF in patients with exophytic adenomas and carcinomas, while Hurlstone et al. [16] assessed the prevalence and features of ACF in patients with flat and depressed colorectal neoplastic lesions, which account for around one third of all colorectal lesions. High magnification chromoscopic colonoscopy was performed on 574 healthy subjects, 281 patients with flat adenomas and 14 patients with flat carcinomas in which 602 (3% of them dysplastic), 2796 (18% dysplastic) and 594 (61 % dysplastic) ACF were identified, respectively. Similarly as in patients with exophytic colorectal lesions, the number of ACF increased in a stepwise fashion from normal subjects to patients with flat or depressed adenoma and then to patients with flat or depressed carcinoma [16].

In another study 103 patients with average age of 61 (range of 28-87) were examined by using magnification (60x) chromoscopic colonoscopy. 788 ACF were found in the distal 20 cm of colon/rectum. Patients with a family history of CRC had a significantly higher mean number of ACF than the average risk subjects (7.6% dysplastic and 46% hyperplastic) [5].

Rudolph et al. [37] have demonstrated that the number of ACF is significantly increased in patients with personal history of adenoma in comparison to subjects without personal or family history. They also observed that number of ACF is higher in older persons than in younger subjects [37].

**15. Difficulties or pitfalls in detection of ACF**

activities [49; 51].

**16. Conclusion**

All these data strongly suggest that ACF in the distal colon may be useful and reliable surrogate marker in predicting CRC risk. However, there are also limitations and difficulties. The main limitation is the fact that chromoendoscopy and magnifying endoscopes are largely research tools and not the equipment in gastrointestinal practice. Difficulties were reported in some studies in which endoscopic criteria failed to predict histologic confirmation of ACF or correlation between the number of ACF and CRC risk [46; 47]. It was also found that there was considerable variability among endoscopists regarding accuracy to correctly identify ACF. It was found that in spite of training, accuracy to correctly identify ACF did not improve [46]. Current knowledge about rodents ACF, which share many similarities with human pathology, might be helpful to understand tricks and traps when using ACF. In rodents, ACF are widely accepted as intermediate biomarkers of CRC risk assessment. They have been used as an endpoint in identifying and assessing preventive or promotional role of natural and pharma‐ cological compounds, as well as dietary and environmental factors in the process of colon carcinogenesis [48; 49]. However, limitations to the use of ACF as a biomarker to identify cancer preventive agents exist. Increasing number of studies has demonstrated that ACF in both animals and humans are heterogeneous group of lesions that contain multiple genetic, epigenetic and phenotypic alterations [15; 22; 50]. In rodents, total number of ACF may be considered as a valid biomarker only at very early stage of carcinogenesis, while in subsequent weeks ACF with higher crypt multiplicities (more than 4 crypts) are considered more specific biomarker than total number of ACF. In more advanced stages of colon carcinogenesis ACF may not be reliable intermediate biomarker of colon carcinogenesis (explained in detail in [9] and [51]). It is also important to mention that ACF are not equally distributed among the proximal, middle or distal colon. The majority of ACF develop in the middle and distal colon [52-54], which need to be taken into consideration when using ACF as biomarkers (compre‐ hensively discussed in [9; 10] and [51]. Nevertheless, when considering all above mentioned facts ACF are useful biomarkers for the screening of compounds for their chemopreventive

The Role, Significance and Applicability of Aberrant Crypt Foci in Clinical Practice

http://dx.doi.org/10.5772/57474

477

Based on experimental and clinical studies evidence demonstrates that ACF share similar histological and molecular features as colonic tumors (i.e. adenomas and adenocarcinomas). ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC. Today, high-magnification chromoscopic colonoscopy allows detection and biopsy of ACF *in vivo* in man. It also provides opportunity to investigate and characterize the earliest genetic and molecular alterations in CRC development in man. However, it has been shown that ACF are heterogeneous group of lesions that exhibit variable endoscopic, histological and molecular features. This fact has been shown to cause some difficulties in accuracy of detection and quantification of ACF among endoscopists. However,

## **14. Clinical application**

Clinical application of ACF as an intermediate biomarker for CRC in humans is under development and is thus less conclusive [4; 38].

Recently, few studies investigated relationship of human colorectal ACF and formation of colorectal polyps on repeat colonoscopy. It was found that the number of ACF in the colorec‐ tum was associated with substantial risk for future advanced neoplasia [39-42].

Ohkubo et al. [39] investigated natural history of human ACF and correlation with risk factors for CRC. They examined 82 subjects who underwent total colonoscopy and whose ACF number was examined at least 2 times. They retrospectively evaluated the changes in the ACF number at four different surveillance periods (6 months, 1 year, 2 years, 3 years) and in groups with and without colorectal neoplasms. The subjects were classified into an increased ACF group and a no change/decreased ACF group, and investigated the relationship between the changes in the ACF number and known risk factors for CRC. No significant differences were observed in the ACF number between the first and second observations in any surveillance period groups, and in the groups classified according to the presence or absence of colorectal neoplasms. There were no significant differences between the increased and no change/ decreased ACF groups in terms of gender, smoking habit, current alcohol consumption, age, BMI, HbA1c or serum triglyceride level, whereas a significant difference between the groups was observed in the serum total cholesterol level [39].

All these data strongly implicate that detection and quantification of ACF in the distal colon may be useful in predicting CRC risk and may be considered as a useful marker in chemo‐ preventive trials. Furthermore, it is expected that one of the most important clinical applica‐ tions of ACF observation with magnifying endoscopy will be its use as a target lesion for chemoprevention. Because ACF are small lesions, they are suggested to be eradicated during a short time by administration of chemopreventive agents [43]. Takayama et al. [43] performed an open chemopreventive trial of sulindac and found that the number of ACF was reduced markedly in 2 months. Patients receiving sulindac for more than one year had no ACF in colon mucosa. After 8 to 12 months of follow-up, the number of ACF in colorectal mucosa signifi‐ cantly decreased or even completely disappeared. In the untreated control subjects the number of ACF was either unchanged or slightly increased [6]. Another short-term chemoprevention trial of metformin for colorectal ACF showed suppressive effect of the drug on the formation of ACF [44]. Other chemopreventive a double blind randomized controlled trial targeting ACF are under investigations [43-45].

## **15. Difficulties or pitfalls in detection of ACF**

Rudolph et al. [37] have demonstrated that the number of ACF is significantly increased in patients with personal history of adenoma in comparison to subjects without personal or family history. They also observed that number of ACF is higher in older persons than in

Clinical application of ACF as an intermediate biomarker for CRC in humans is under

Recently, few studies investigated relationship of human colorectal ACF and formation of colorectal polyps on repeat colonoscopy. It was found that the number of ACF in the colorec‐

Ohkubo et al. [39] investigated natural history of human ACF and correlation with risk factors for CRC. They examined 82 subjects who underwent total colonoscopy and whose ACF number was examined at least 2 times. They retrospectively evaluated the changes in the ACF number at four different surveillance periods (6 months, 1 year, 2 years, 3 years) and in groups with and without colorectal neoplasms. The subjects were classified into an increased ACF group and a no change/decreased ACF group, and investigated the relationship between the changes in the ACF number and known risk factors for CRC. No significant differences were observed in the ACF number between the first and second observations in any surveillance period groups, and in the groups classified according to the presence or absence of colorectal neoplasms. There were no significant differences between the increased and no change/ decreased ACF groups in terms of gender, smoking habit, current alcohol consumption, age, BMI, HbA1c or serum triglyceride level, whereas a significant difference between the groups

All these data strongly implicate that detection and quantification of ACF in the distal colon may be useful in predicting CRC risk and may be considered as a useful marker in chemo‐ preventive trials. Furthermore, it is expected that one of the most important clinical applica‐ tions of ACF observation with magnifying endoscopy will be its use as a target lesion for chemoprevention. Because ACF are small lesions, they are suggested to be eradicated during a short time by administration of chemopreventive agents [43]. Takayama et al. [43] performed an open chemopreventive trial of sulindac and found that the number of ACF was reduced markedly in 2 months. Patients receiving sulindac for more than one year had no ACF in colon mucosa. After 8 to 12 months of follow-up, the number of ACF in colorectal mucosa signifi‐ cantly decreased or even completely disappeared. In the untreated control subjects the number of ACF was either unchanged or slightly increased [6]. Another short-term chemoprevention trial of metformin for colorectal ACF showed suppressive effect of the drug on the formation of ACF [44]. Other chemopreventive a double blind randomized controlled trial targeting ACF

tum was associated with substantial risk for future advanced neoplasia [39-42].

younger subjects [37].

**14. Clinical application**

476 Colorectal Cancer - Surgery, Diagnostics and Treatment

development and is thus less conclusive [4; 38].

was observed in the serum total cholesterol level [39].

are under investigations [43-45].

All these data strongly suggest that ACF in the distal colon may be useful and reliable surrogate marker in predicting CRC risk. However, there are also limitations and difficulties. The main limitation is the fact that chromoendoscopy and magnifying endoscopes are largely research tools and not the equipment in gastrointestinal practice. Difficulties were reported in some studies in which endoscopic criteria failed to predict histologic confirmation of ACF or correlation between the number of ACF and CRC risk [46; 47]. It was also found that there was considerable variability among endoscopists regarding accuracy to correctly identify ACF. It was found that in spite of training, accuracy to correctly identify ACF did not improve [46].

Current knowledge about rodents ACF, which share many similarities with human pathology, might be helpful to understand tricks and traps when using ACF. In rodents, ACF are widely accepted as intermediate biomarkers of CRC risk assessment. They have been used as an endpoint in identifying and assessing preventive or promotional role of natural and pharma‐ cological compounds, as well as dietary and environmental factors in the process of colon carcinogenesis [48; 49]. However, limitations to the use of ACF as a biomarker to identify cancer preventive agents exist. Increasing number of studies has demonstrated that ACF in both animals and humans are heterogeneous group of lesions that contain multiple genetic, epigenetic and phenotypic alterations [15; 22; 50]. In rodents, total number of ACF may be considered as a valid biomarker only at very early stage of carcinogenesis, while in subsequent weeks ACF with higher crypt multiplicities (more than 4 crypts) are considered more specific biomarker than total number of ACF. In more advanced stages of colon carcinogenesis ACF may not be reliable intermediate biomarker of colon carcinogenesis (explained in detail in [9] and [51]). It is also important to mention that ACF are not equally distributed among the proximal, middle or distal colon. The majority of ACF develop in the middle and distal colon [52-54], which need to be taken into consideration when using ACF as biomarkers (compre‐ hensively discussed in [9; 10] and [51]. Nevertheless, when considering all above mentioned facts ACF are useful biomarkers for the screening of compounds for their chemopreventive activities [49; 51].

## **16. Conclusion**

Based on experimental and clinical studies evidence demonstrates that ACF share similar histological and molecular features as colonic tumors (i.e. adenomas and adenocarcinomas). ACF exhibit many of the molecular and genetic abnormalities that form the basis for the adenoma-carcinoma sequence in CRC. Today, high-magnification chromoscopic colonoscopy allows detection and biopsy of ACF *in vivo* in man. It also provides opportunity to investigate and characterize the earliest genetic and molecular alterations in CRC development in man.

However, it has been shown that ACF are heterogeneous group of lesions that exhibit variable endoscopic, histological and molecular features. This fact has been shown to cause some difficulties in accuracy of detection and quantification of ACF among endoscopists. However, chromoendoscopy and magnifying endoscopes are largely research tools and future research on that field will bring new information about reliability and applicability of ACF as biomarker of CRC risk in clinical practice.

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The Role, Significance and Applicability of Aberrant Crypt Foci in Clinical Practice

http://dx.doi.org/10.5772/57474

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#### **Acknowledgements**

This work was funded by the Slovenian Ministry of Higher Education, Science and Technology (grant number P3-0054).

## **Author details**

Martina Perše\* and Anton Cerar

\*Address all correspondence to: martina.perse@mf.uni-lj.si

Institute of Pathology, Medical Experimental Centre, Faculty of Medicine, University of Ljubljana, Slovenia

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**Section 6**

**Post operative care**

**Section 6**

**Post operative care**

**Chapter 19**

**ERAS (Enhanced Recovery after Surgery) in Colorectal**

Evidence-based medicine has led to an extensive investigation and development of new therapies and programs to improve the care of the surgical patient, both in the postoperative and in the pre-operative period, known as enhanced recovery after surgery (ERAS) programs,

ERAS programs are evidenced-based protocols designed to standardize and optimize perioperative medical care in order to reduce surgical trauma, perioperative physiological stress and organ dysfunction related to elective procedures [1]. In addition, improved out‐ comes, decreased hospital length of stay and faster patient recovery to normal life are expected to be obtained. Other advantages of this philosophy are the reduction of clinical complications and the health costs together with and increase of patient satisfaction. A diagram with all the

This approach could not be understood and implemented without the participation and commitment of a multidisciplinary team including surgeons, anesthesiologists, nursing staff and hospital administration. Moreover, it is important to make the patient and their families

These kinds of programs are not exclusive of a type of surgery or surgical procedure since they can be applied to different specialties (digestive, vascular, thoracic, etc.), different procedures

> © 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Raúl Sánchez-Jiménez, Alberto Blanco Álvarez, Jacobo Trebol López, Antonio Sánchez Jiménez,

Additional information is available at the end of the chapter

"fast-track" programs or multimodal rehabilitation programs.

core principles of an ERAS program can be seen on Figure 1.

a partner in their care and give them join responsibility for the recovery.

Fernando Gutiérrez Conde and José Antonio Carmona Sáez

http://dx.doi.org/10.5772/57136

**1. Introduction**

**1.1. Definition**

**Surgery**
