**Gliomagenesis**

76 Glioma – Exploring Its Biology and Practical Relevance

Vredenburgh, J. J., et al. (2011). The Addition of Bevacizumab to Standard Radiation

Wang, S. and E. N. Olson (2009). AngiomiRs--key regulators of angiogenesis. *Curr Opin* 

Webster, R. J., et al. (2009). Regulation of epidermal growth factor receptor signaling in human cancer cells by microRNA-7. *J Biol Chem*, Vol. 284, No. 9, (Feb 27) pp. 5731-5741. Wen, P. Y., et al. (2010). Updated response assessment criteria for high-grade gliomas:

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Wick, A., et al. (2007). Efficacy and tolerability of temozolomide in an alternating weekly

Wick, W., et al. (2009). NOA-04 randomized phase III trial of sequential radiochemotherapy

Wick, W., et al. (2010). Phase III study of enzastaurin compared with lomustine in the

Wick, W., et al. (2011). Phase III study of enzastaurin compared with lomustine in the

Wick, W., et al. (2004). One week on/one week off regimen of temozolomide for recurrent

Wick, W. and M. Weller (2005). How lymphotoxic is dose-intensified temozolomide? The

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Yekta, S. e. a. (2004). MicroRNA-directed cleavage of *HOXB8* mRNA. *Science*, Vol. 304, No.,

Zhang, Y., et al. (2009). MicroRNA-128 inhibits glioma cells proliferation by targeting transcription factor E2F3a. *J Mol Med*, Vol. 87, No. 1, (Jan) pp. 43-51.

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**5** 

*Brazil* 

Giovanny Pinto et al.\*

*Federal University of Piauí, Parnaíba,* 

**Genomic Abnormalities in Gliomas** 

In general, studies reveal that cancer arises through genetic and epigenetic alterations that affect specific genes within a given cell type. These changes involve a gain of function when the alterations involve oncogenes, a loss of function when the target genes are tumor suppressor genes. Thus, both genetic and epigenetic changes promote the instability of cellular homeostasis (Bello & Rey, 2006; Richardson, 2003; Sugimura & Ushijima, 2000). This lack of stability reflects the complexity of cancer because the loss of controlled cell growth occurs due to changes in one or more genes. These genetic and epigenetic events are followed by the growing accumulation of changes in hundreds, if not thousands, of genes. Over time, this accumulation causes the tumor to reach its highest degree of malignancy, which usually culminates in metastasis (Bartek & Lukas, 2001). However, in recent years, a subpopulation of tumor cells has been found to display a slow rate of cell division, high tumorigenic potential and characteristics similar to those of normal stem cells. This discovery has changed the concept of metastasis to one associated with strictly terminal

Hanahan & Weinberg (2000) proposed that all tumor cells must acquire six essential alterations in cell physiology that collectively dictate malignant growth: (1) loss of normal signaling for cell proliferation arrest, (2) loss of signaling for cell differentiation, (3) autocrine signaling for cell division, (4) reduction in apoptosis, (5) ability to enter the basement membrane and other tissues and organs, and (6) induction of angiogenesis. All of these processes involve biochemical pathways that form a complex network of cell signaling. These processes are usually altered in tumors because the genes that compose them are changed, resulting in cell cycle dysregulation. Therefore, the identification and determination of oncogenes and tumor suppressor genes is essential for understanding both cancer biology and clinical applications, such as the identification of therapeutic targets, early detection, and prediction of the disease course. Studies concerning cell cycle control genes have served as a starting point for identifying genes related to tumorigenesis and

**1. Introduction** 

states (Stiles & Rowitch, 2008).

Aline Custódio4 and Cacilda Casartelli4 *1Federal University of Piauí, Parnaíba,Brazil 2Federal University of Pará, Belém, Brazil 3University Hospital La Paz, Madrid, Spain 4University of São Paulo, Ribeirão Preto, Brazil* 

their biochemical role in various pathways (Paige, 2003).

\* France Yoshioka1, Fábio Motta1, Renata Canalle1, Rommel Burbano2, Juan Rey3,

## **Genomic Abnormalities in Gliomas**

Giovanny Pinto et al.\*

*Federal University of Piauí, Parnaíba, Brazil* 

#### **1. Introduction**

In general, studies reveal that cancer arises through genetic and epigenetic alterations that affect specific genes within a given cell type. These changes involve a gain of function when the alterations involve oncogenes, a loss of function when the target genes are tumor suppressor genes. Thus, both genetic and epigenetic changes promote the instability of cellular homeostasis (Bello & Rey, 2006; Richardson, 2003; Sugimura & Ushijima, 2000). This lack of stability reflects the complexity of cancer because the loss of controlled cell growth occurs due to changes in one or more genes. These genetic and epigenetic events are followed by the growing accumulation of changes in hundreds, if not thousands, of genes. Over time, this accumulation causes the tumor to reach its highest degree of malignancy, which usually culminates in metastasis (Bartek & Lukas, 2001). However, in recent years, a subpopulation of tumor cells has been found to display a slow rate of cell division, high tumorigenic potential and characteristics similar to those of normal stem cells. This discovery has changed the concept of metastasis to one associated with strictly terminal states (Stiles & Rowitch, 2008).

Hanahan & Weinberg (2000) proposed that all tumor cells must acquire six essential alterations in cell physiology that collectively dictate malignant growth: (1) loss of normal signaling for cell proliferation arrest, (2) loss of signaling for cell differentiation, (3) autocrine signaling for cell division, (4) reduction in apoptosis, (5) ability to enter the basement membrane and other tissues and organs, and (6) induction of angiogenesis. All of these processes involve biochemical pathways that form a complex network of cell signaling. These processes are usually altered in tumors because the genes that compose them are changed, resulting in cell cycle dysregulation. Therefore, the identification and determination of oncogenes and tumor suppressor genes is essential for understanding both cancer biology and clinical applications, such as the identification of therapeutic targets, early detection, and prediction of the disease course. Studies concerning cell cycle control genes have served as a starting point for identifying genes related to tumorigenesis and their biochemical role in various pathways (Paige, 2003).

<sup>\*</sup> France Yoshioka1, Fábio Motta1, Renata Canalle1, Rommel Burbano2, Juan Rey3,

Aline Custódio4 and Cacilda Casartelli4

*<sup>1</sup>Federal University of Piauí, Parnaíba,Brazil* 

*<sup>2</sup>Federal University of Pará, Belém, Brazil* 

*<sup>3</sup>University Hospital La Paz, Madrid, Spain* 

*<sup>4</sup>University of São Paulo, Ribeirão Preto, Brazil* 

Genomic Abnormalities in Gliomas 81

non-promoter regions. In addition, epigenetic abnormalities causing loss of gene function are more frequent than genetic abnormalities in cancer cells (Schuebel et al., 2007). Thus, cellular epigenetic inheritance mediated by aberrant DNA methylation resulting in gene silencing, gene imprinting, andor activation of cancer-associated genes is now accepted as

Tumors of the central nervous system (CNS) are relatively rare and represent approximately 5-9% of all cancers, with an estimated incidence of 4.2 to 5.4 per 100,000 people/year. Moreover, tumors of the CNS carry a very poor prognosis and are associated with considerable morbidity and mortality. They are a leading cause of childhood cancer deaths, the second leading cause of cancer-related death in men aged 20–39, and the fifth leading

Although the incidence of CNS tumors is small compared with the incidence of other cancers, CNS tumors are among the most serious human malignancies because they affect the organ responsible for the coordination and integration of all biological activities. Moreover, as each region of the brain has a vital function, therapies used to treat other cancers (e.g., total surgical removal of an organ or tumor with a generous margin of normal tissue) cannot be applied to brain tumors. The inability to use these therapies hinders

In CNS tumors, the histopathological classifications are extensive and based primarily on descriptive morphology. Because the histogenesis of these tumors is unique and heterogeneous, it is difficult to characterize several of the tumor subtypes, which is reflected

In contrast with the first World Health Organization (WHO) classifications for CNS tumors (Kleihues et al., 1993; Zülch, 1979), the third edition by Kleihues & Cavenee (2000) incorporated genetic profiles as additional aids in defining brain tumors. The fourth edition of the WHO classifications for CNS tumors, which was published in 2007, lists several new characteristics. The fourth edition is based on consensus from an international working group of 25 pathologists and geneticists, as well as contributions from more than 70 international experts. Currently, this edition is the standard for defining brain tumors for

Gliomas are the most common tumors of the CNS. However, in spite of marked progress in characterizing the molecular pathogenesis of gliomas, these tumors remain incurable. In most cases, gliomas are also refractory to treatment because of their molecular heterogeneity. Gliomas rarely metastasize outside of the brain but instead infiltrate extensively into the surrounding normal brain. Therefore, surgery is not curative but can establish the diagnosis and relieve symptoms by decompressing the brain, which is located in the rigid intracranial cavity. Radiation therapy and chemotherapy increase survival;

The following four degrees of malignancy are recognized by the WHO: grades I and II (lowgrade), which are biologically less aggressive and grades III and IV (high-grade), which are the most aggressive. The histological criteria for grading malignancies are not uniform for

clinical oncology and cancer research communities world-wide (Louis et al., 2007).

however, disease recurrence is frequently inevitable (Park & Rich, 2009).

an important factor defining the transformed phenotype (Natsume et al., 2010)

cause of cancer-related death in women aged 20–39 (Ohgaki & Kleihues, 2005).

**2. Tumors of the central nervous system** 

quality of life and patient survival (Louis et al., 2002).

**3. Gliomas** 

in the difficulties encountered in tumor diagnosis (Gilbertson, 2002).

Changes in oncogenes can lead to constitutive activation, which involves activation under conditions in which an oncogene would normally be inactive. For this process to occur, a cell needs only one allele of an oncogene to be altered, resulting in a selective growth advantage. In contrast, changes in tumor suppressor genes often reduce the gene product and consequently its activity. For this reason, cells that develop a selective advantage with changes in tumor suppressor genes usually require inactivation of both alleles of the target gene. Conceptually, tumor suppressor genes can be subdivided into two categories: "gatekeepers" that directly inhibit tumor growth and thereby suppress tumor formation and "caretakers" that ensure DNA integrity by repairing damage or preventing genomic instability (Vogelstein & Kinzler, 2004).

Studies of hereditary and sporadic forms of tumors, particularly retinoblastoma, culminated in the formulation of Knudson's "two events" model in 1971. In hereditary tumors, the first mutation occurs in one allele in the germline and results in a predisposition to develop tumors. Throughout development, a second change (mutation or loss of heterozygosity) inactivates the other allele and silences the altered gene. In contrast, sporadic tumors acquire the two allelic alterations that lead to gene silencing throughout the organism's development (Knudson, 1971). Over time, the neoplastic transformation and metabolicphenotype of the cell can evolve. Ultimately, these changes result in a cancer in which clonal expansion of modified somatic cells destroys the adjacent normal tissue (Bartek & Lukas, 2001).

For many years, research in cancer genetics has prioritized understanding the role of genetic alterations in carcinogenesis. Studies revealed that base deletions, insertions, recombination and amplification in oncogenes and tumor suppressor genes were related to metastasis and invasion. These changes were also closely related to tumorigenesis and tumor progression. For this reason, the scientific community accepted that genetic changes almost exclusively explained the process of carcinogenesis (Sugimura & Ushijima, 2000). However, studies also indicated that embryogenesis and differentiation, which are characterized by specific patterns of gene expression in tissues and organs, can occur without changes in the DNA sequence. This notion has interested the scientific community in potential epigenetic mechanisms of carcinogenesis (Jones & Buckley, 1990; Rush & Plass, 2002).

An epigenetic phenomenon is defined as a change in gene function that is heritable through mitosis or meiosis but cannot be explained by changes in the DNA sequence. Aberrant epigenetic mechanisms, such as promoter hypermethylation, histone modifications, or noncoding RNA expression, are known to be important for tumor formation and comprise the "third pathway" in Knudson's model. These mechanisms result in transcriptional repression equivalent to that observed with the mutations and deletions proposed in Knudson's model (Jones & Baylin, 2007).

DNA methylation, the main epigenetic modification studied, occurs at cytosine residues in the cytosine-guanine sequences (CpG) of DNA through the action of an enzyme family called DNA methyltransferases (DNMT). In humans, approximately 70% of CpG sites, which are generally located in repetitive DNA sequences, are methylated. Clusters of unmethylated CpG sites are present in the genome as well, and these clusters are referred to as CpG islands. Approximately 60% of genes have CpG islands in the promoter regions and in the first exon. CpG islands are often dimethylated when associated with housekeeping genes. Moreover, CpG islands are tissue specific and are generally methylated except in those tissues where the associated gene is expressed (Cross & Bird, 1995; Gonzalez-Gomez et al., 2003). A recent genome-wide analysis revealed that CpG islands are also found in

Changes in oncogenes can lead to constitutive activation, which involves activation under conditions in which an oncogene would normally be inactive. For this process to occur, a cell needs only one allele of an oncogene to be altered, resulting in a selective growth advantage. In contrast, changes in tumor suppressor genes often reduce the gene product and consequently its activity. For this reason, cells that develop a selective advantage with changes in tumor suppressor genes usually require inactivation of both alleles of the target gene. Conceptually, tumor suppressor genes can be subdivided into two categories: "gatekeepers" that directly inhibit tumor growth and thereby suppress tumor formation and "caretakers" that ensure DNA integrity by repairing damage or preventing genomic

Studies of hereditary and sporadic forms of tumors, particularly retinoblastoma, culminated in the formulation of Knudson's "two events" model in 1971. In hereditary tumors, the first mutation occurs in one allele in the germline and results in a predisposition to develop tumors. Throughout development, a second change (mutation or loss of heterozygosity) inactivates the other allele and silences the altered gene. In contrast, sporadic tumors acquire the two allelic alterations that lead to gene silencing throughout the organism's development (Knudson, 1971). Over time, the neoplastic transformation and metabolicphenotype of the cell can evolve. Ultimately, these changes result in a cancer in which clonal expansion of modified somatic cells destroys the adjacent normal tissue (Bartek & Lukas,

For many years, research in cancer genetics has prioritized understanding the role of genetic alterations in carcinogenesis. Studies revealed that base deletions, insertions, recombination and amplification in oncogenes and tumor suppressor genes were related to metastasis and invasion. These changes were also closely related to tumorigenesis and tumor progression. For this reason, the scientific community accepted that genetic changes almost exclusively explained the process of carcinogenesis (Sugimura & Ushijima, 2000). However, studies also indicated that embryogenesis and differentiation, which are characterized by specific patterns of gene expression in tissues and organs, can occur without changes in the DNA sequence. This notion has interested the scientific community in potential epigenetic

An epigenetic phenomenon is defined as a change in gene function that is heritable through mitosis or meiosis but cannot be explained by changes in the DNA sequence. Aberrant epigenetic mechanisms, such as promoter hypermethylation, histone modifications, or noncoding RNA expression, are known to be important for tumor formation and comprise the "third pathway" in Knudson's model. These mechanisms result in transcriptional repression equivalent to that observed with the mutations and deletions proposed in Knudson's model

DNA methylation, the main epigenetic modification studied, occurs at cytosine residues in the cytosine-guanine sequences (CpG) of DNA through the action of an enzyme family called DNA methyltransferases (DNMT). In humans, approximately 70% of CpG sites, which are generally located in repetitive DNA sequences, are methylated. Clusters of unmethylated CpG sites are present in the genome as well, and these clusters are referred to as CpG islands. Approximately 60% of genes have CpG islands in the promoter regions and in the first exon. CpG islands are often dimethylated when associated with housekeeping genes. Moreover, CpG islands are tissue specific and are generally methylated except in those tissues where the associated gene is expressed (Cross & Bird, 1995; Gonzalez-Gomez et al., 2003). A recent genome-wide analysis revealed that CpG islands are also found in

mechanisms of carcinogenesis (Jones & Buckley, 1990; Rush & Plass, 2002).

instability (Vogelstein & Kinzler, 2004).

2001).

(Jones & Baylin, 2007).

non-promoter regions. In addition, epigenetic abnormalities causing loss of gene function are more frequent than genetic abnormalities in cancer cells (Schuebel et al., 2007). Thus, cellular epigenetic inheritance mediated by aberrant DNA methylation resulting in gene silencing, gene imprinting, andor activation of cancer-associated genes is now accepted as an important factor defining the transformed phenotype (Natsume et al., 2010)

#### **2. Tumors of the central nervous system**

Tumors of the central nervous system (CNS) are relatively rare and represent approximately 5-9% of all cancers, with an estimated incidence of 4.2 to 5.4 per 100,000 people/year. Moreover, tumors of the CNS carry a very poor prognosis and are associated with considerable morbidity and mortality. They are a leading cause of childhood cancer deaths, the second leading cause of cancer-related death in men aged 20–39, and the fifth leading cause of cancer-related death in women aged 20–39 (Ohgaki & Kleihues, 2005).

Although the incidence of CNS tumors is small compared with the incidence of other cancers, CNS tumors are among the most serious human malignancies because they affect the organ responsible for the coordination and integration of all biological activities. Moreover, as each region of the brain has a vital function, therapies used to treat other cancers (e.g., total surgical removal of an organ or tumor with a generous margin of normal tissue) cannot be applied to brain tumors. The inability to use these therapies hinders quality of life and patient survival (Louis et al., 2002).

In CNS tumors, the histopathological classifications are extensive and based primarily on descriptive morphology. Because the histogenesis of these tumors is unique and heterogeneous, it is difficult to characterize several of the tumor subtypes, which is reflected in the difficulties encountered in tumor diagnosis (Gilbertson, 2002).

In contrast with the first World Health Organization (WHO) classifications for CNS tumors (Kleihues et al., 1993; Zülch, 1979), the third edition by Kleihues & Cavenee (2000) incorporated genetic profiles as additional aids in defining brain tumors. The fourth edition of the WHO classifications for CNS tumors, which was published in 2007, lists several new characteristics. The fourth edition is based on consensus from an international working group of 25 pathologists and geneticists, as well as contributions from more than 70 international experts. Currently, this edition is the standard for defining brain tumors for clinical oncology and cancer research communities world-wide (Louis et al., 2007).

#### **3. Gliomas**

Gliomas are the most common tumors of the CNS. However, in spite of marked progress in characterizing the molecular pathogenesis of gliomas, these tumors remain incurable. In most cases, gliomas are also refractory to treatment because of their molecular heterogeneity. Gliomas rarely metastasize outside of the brain but instead infiltrate extensively into the surrounding normal brain. Therefore, surgery is not curative but can establish the diagnosis and relieve symptoms by decompressing the brain, which is located in the rigid intracranial cavity. Radiation therapy and chemotherapy increase survival; however, disease recurrence is frequently inevitable (Park & Rich, 2009).

The following four degrees of malignancy are recognized by the WHO: grades I and II (lowgrade), which are biologically less aggressive and grades III and IV (high-grade), which are the most aggressive. The histological criteria for grading malignancies are not uniform for

Genomic Abnormalities in Gliomas 83

Gliomas of astrocytic, oligodendroglial, and ependymal origin account for 80% of CNS tumors. For this reason, some morphological and genetic characteristics of these tumors are

Astrocytomas represent the vast majority of gliomas and account for 70% of the total gliomas seen in patients. Astrocytomas can be further characterized as pilocytic astrocytomas (WHO grade I) or diffuse astrocytomas, including low-grade astrocytomas (WHO grade II), anaplastic astrocytomas (WHO grade III) and glioblastomas (WHO grade

Pilocytic astrocytomas are more commonly seen in children and carry a good prognosis because of their biology. Patients with neurofibromatosis type 1, a familial syndrome caused by germline mutations in the gene *NF1* (neurofibromin 1), have an increased incidence of pilocytic astrocytomas. These tumors are usually not aggressive and stand out among astrocytomas because they have maintained their WHO grade I status for years and even decades, in contrast to diffuse astrocytic tumors (WHO grades II-IV). However, some cases can progress to a higher degree of malignancy, though such a progression is rare (Listernick

More than 100 cases of pilocytic astrocytomas were analyzed by cytogenetics and many others were used for comparative genomic hybridization (CGH); however, the vast majority of the results indicated normal patterns (Bigner et al., 1997; Sanoudou et al., 2000; Zattara-Cannoni et al., 1998). In adults, genetic changes were more frequent but were still rare. The few molecular genetics studies on these tumors indicated allelic loss of both gene loci *TP53* (tumor protein p53) and *NF1* in regions 17p and 17q, respectively. In sporadic tumors, few mutations were reported in the *TP53* locus and none in *NF1* (Gutmann et al., 2000; Kluwe et

The relevance of a malignancy-grading scheme based on histopathology is indicated by the correlation with patient survival. Patients with low-grade astrocytomas (WHO grade II) have a median survival of approximately seven years, whereas patients with anaplastic astrocytomas (WHO grade III) have a mean survival of half that time (McCormack et al., 1992). Patients with glioblastomas have a median survival time of 9 to 11 months (Simpson

Unlike pilocytic astrocytomas, diffuse astrocytic tumors are often seen in adults. Low-grade astrocytomas have a peak incidence between 25 and 50 years of age, whereas glioblastomas

Ng & Lam (1998) suggested dividing glioblastomas into two distinct molecular and clinical entities: primary or de novo glioblastomas, which occur in elderly patients and are clinically very aggressive and secondary glioblastomas, which develop from low-grade astrocytomas

Many mechanisms are involved in the initiation and progression of secondary glioblastomas, including the loss of *NF1* and *TP53* genes and the activation of signal transduction pathways, such as *PDGF* (platelet-derived growth factor) and its receptor *PDGFR* (PDGF receptor). These pathways are involved in the induction of low-grade tumors (e.g., pilocytic astrocytomas), which can progress to high-grade tumors (e.g., anaplastic astrocytomas and secondary glioblastoma). This progression is associated with the lack of a functional *RB1* (retinoblastoma 1) because of the loss of *RB1* or gene amplification/overexpression of *CDK4* (cyclin-dependent kinase 4) (Fig. 1a). In primary

have a peak incidence between 45 and 50 years (Colins, 2004).

and have a more prolonged clinical course.

discussed below.

**3.1 Astrocytomas** 

et al., 1999).

al., 2001).

et al., 1993).

IV) (Kleihues et al., 2002).

all subtypes of gliomas. Thus, all tumors should be classified before the degree of malignancy is determined. This classification is made according to the cell type thought to be responsible for the tumor and based on the characteristics exhibited by astrocytes, oligodendrocytes, ependymal cells, or their neuronal progenitors (Louis et al., 2007). Table 1 shows the heterogeneous WHO classification for gliomas according to the degree of malignancy.


Table 1. WHO grading of gliomas (Louis et al., 2007).

Gliomas of astrocytic, oligodendroglial, and ependymal origin account for 80% of CNS tumors. For this reason, some morphological and genetic characteristics of these tumors are discussed below.

#### **3.1 Astrocytomas**

82 Glioma – Exploring Its Biology and Practical Relevance

all subtypes of gliomas. Thus, all tumors should be classified before the degree of malignancy is determined. This classification is made according to the cell type thought to be responsible for the tumor and based on the characteristics exhibited by astrocytes, oligodendrocytes, ependymal cells, or their neuronal progenitors (Louis et al., 2007). Table 1 shows the heterogeneous WHO classification for gliomas according to the degree of

**Astrocytic tumors I II III IV Ependymal tumors I II III IV** 

cell astrocytoma ● Subependymoma ●

astrocytoma ● Ependymoma ●

Pilocytic astrocytoma ● Myxopapillary

Diffuse astrocytoma ● Anaplastic

Anaplastic astrocytoma ● **Choroid plexus** 

Glioblastoma ● Choroid plexus

Giant cell glioblastoma ● Atypical choroid

Gliosarcoma ● Choroid plexus

Oligodendroglioma ● Angiocentric glioma ●

oligodendroglioma ● Chordoid glioma of

Table 1. WHO grading of gliomas (Louis et al., 2007).

**WHO Grade WHO Grade** 

ependymoma ●

papilloma ●

plexus papilloma ●

the third ventricle ●

carcinoma ●

**tumors** 

**Other** 

**tumors** 

**neuroepithelial** 

ependymoma ●

malignancy.

Pilomyxoid

Pleomorphic

**Oligodendroglial** 

**Oligoastrocytic tumors**

Oligoastrocytoma ●

oligoastrocytoma ●

**tumors** 

Anaplastic

Anaplastic

xanthoastrocytoma ●

Subependymal giant

Astrocytomas represent the vast majority of gliomas and account for 70% of the total gliomas seen in patients. Astrocytomas can be further characterized as pilocytic astrocytomas (WHO grade I) or diffuse astrocytomas, including low-grade astrocytomas (WHO grade II), anaplastic astrocytomas (WHO grade III) and glioblastomas (WHO grade IV) (Kleihues et al., 2002).

Pilocytic astrocytomas are more commonly seen in children and carry a good prognosis because of their biology. Patients with neurofibromatosis type 1, a familial syndrome caused by germline mutations in the gene *NF1* (neurofibromin 1), have an increased incidence of pilocytic astrocytomas. These tumors are usually not aggressive and stand out among astrocytomas because they have maintained their WHO grade I status for years and even decades, in contrast to diffuse astrocytic tumors (WHO grades II-IV). However, some cases can progress to a higher degree of malignancy, though such a progression is rare (Listernick et al., 1999).

More than 100 cases of pilocytic astrocytomas were analyzed by cytogenetics and many others were used for comparative genomic hybridization (CGH); however, the vast majority of the results indicated normal patterns (Bigner et al., 1997; Sanoudou et al., 2000; Zattara-Cannoni et al., 1998). In adults, genetic changes were more frequent but were still rare. The few molecular genetics studies on these tumors indicated allelic loss of both gene loci *TP53* (tumor protein p53) and *NF1* in regions 17p and 17q, respectively. In sporadic tumors, few mutations were reported in the *TP53* locus and none in *NF1* (Gutmann et al., 2000; Kluwe et al., 2001).

The relevance of a malignancy-grading scheme based on histopathology is indicated by the correlation with patient survival. Patients with low-grade astrocytomas (WHO grade II) have a median survival of approximately seven years, whereas patients with anaplastic astrocytomas (WHO grade III) have a mean survival of half that time (McCormack et al., 1992). Patients with glioblastomas have a median survival time of 9 to 11 months (Simpson et al., 1993).

Unlike pilocytic astrocytomas, diffuse astrocytic tumors are often seen in adults. Low-grade astrocytomas have a peak incidence between 25 and 50 years of age, whereas glioblastomas have a peak incidence between 45 and 50 years (Colins, 2004).

Ng & Lam (1998) suggested dividing glioblastomas into two distinct molecular and clinical entities: primary or de novo glioblastomas, which occur in elderly patients and are clinically very aggressive and secondary glioblastomas, which develop from low-grade astrocytomas and have a more prolonged clinical course.

Many mechanisms are involved in the initiation and progression of secondary glioblastomas, including the loss of *NF1* and *TP53* genes and the activation of signal transduction pathways, such as *PDGF* (platelet-derived growth factor) and its receptor *PDGFR* (PDGF receptor). These pathways are involved in the induction of low-grade tumors (e.g., pilocytic astrocytomas), which can progress to high-grade tumors (e.g., anaplastic astrocytomas and secondary glioblastoma). This progression is associated with the lack of a functional *RB1* (retinoblastoma 1) because of the loss of *RB1* or gene amplification/overexpression of *CDK4* (cyclin-dependent kinase 4) (Fig. 1a). In primary

Genomic Abnormalities in Gliomas 85

hypermethylation in diffuse gliomas, and this hypermethylation has been pinpointed as an epigenetic mechanism that reduces *MGMT* expression levels. There are 97 CpG islands in the *MGMT* promoter, and these CpG islands are further divided into two hypermethylated regions (Nakagawachi et al., 2003). Because of its critical role in DNA repair, the epigenetic silencing of *MGMT* is associated with an increased number of mutations and with a poorer outcome in glioblastomas. Thus, *MGMT* silencing is considered to be a biomarker for poor prognosis (Komine et al., 2003). However, an association between *MGMT* promoter methylation and the response of malignant gliomas to alkylating chemotherapy using nitrosourea compounds, temozolomide, or a combination of both has been observed (Esteller et al., 2000; Herrlinger et al., 2006). Furthermore, Hegi et al. (2005) reported that patients treated with radiotherapy and temozolomide, and whose tumors had a methylated *MGMT* promoter (which is seen in approximately 40% of primary glioblastomas), survived significantly longer than did patients whose tumors lacked *MGMT* promoter methylation. Rivera et al. (2010) recently reported that *MGMT* promoter methylation in anaplastic gliomas (WHO grade III) is also predictive of the response to radiotherapy and linked to longer survival in the absence of adjuvant chemotherapy. The use of temozolomide based on *MGMT* methylation status highlights the importance of understanding epigenetic changes in glioblastomas for the discovery of novel therapies and prognostic factors for the

treatment of this deadly cancer (Komine et al., 2003; Nakagawachi et al., 2003)

Oligodendrogliomas represent approximately 10-15% of gliomas, are more common in adults, and can be divided into two histological subtypes: low-grade (WHO grade II) and

Low-grade oligodendrogliomas are less biologically aggressive than are astrocytic tumors. Therefore, the prognosis is quite favorable and survival beyond 15 years is achieved in up to 90% of cases that receive a complete surgical resection. There is potential for malignancy, but even the aggressive tumors respond well to additional treatments (e.g., radiation and chemotherapy). Anaplastic oligodendrogliomas have a more aggressive course; however, survival is still five to eight years longer than that observed with anaplastic astrocytomas

In 1990, the PCV chemotherapy regimen (procarbazine, carmustine, and vincristine) was shown to result in a dramatic tumor response in oligodendrogliomas. Since that time, the identification of all forms of gliomas with oligodendroglial components became crucial (Macdonald et al., 1990). Importantly, these studies indicated that the prognostic power of oligodendroglial components was independent of whether radiotherapy, chemotherapy or combined radio-chemotherapy was used (Wick et al., 2009). This phenomenon is likely due to oligodendrogliomas exhibiting specific genetic abnormalities that distinguish them from other gliomas. Reifenberger et al. (1994), after a thorough analysis of the genome, reported a loss of genetic information in the 1p and 19q loci in oligodendrogliomas, the so-called chromosome 1p/19q co-deletion. This loss was later linked with a good response to PCV and provided the first molecular indicator of treatment response in brain tumors (Cairncross et al., 1998; Reifenberger et al., 2003). Further studies corroborated these findings, and it is now known that the chromosomal loss results from an unbalanced translocation (Franco-Hernandez et al., 2009; Jenkins et al., 2006). Approximately 85% of low-grade oligodendrogliomas and 65% of anaplastic oligodendrogliomas present with 1p/19q co-

**3.2 Oligodendrogliomas** 

(Reifenberger & Louis, 2003).

deletions (Smith et al., 2000).

anaplastic (WHO grade III) (Kleihues et al., 2002).

glioblastomas, the same genetic pathways are disrupted but by different mechanisms. For example, reduction of the *TP53* pathway generally occurs through the loss of the gene *ARF4* (ADP-ribosylation factor 4) or less frequently through amplification of the gene *MDM2* (transformed 3T3 cell double minute 2). The lack of *RB1* also occurs via a loss of the gene *CDKN2A* (cyclin-dependent kinase inhibitor 2A). In primary glioblastomas, amplification and/or mutation of *EGFR* (epidermal growth factor receptor) and loss of *PTEN* (phosphatase and tensin homolog) are the most frequently observed genetic defects (Fig. 1b) (Zu & Parada, 2002).

Fig. 1. Genetic pathways involved in the development of (a) primary and (b) secondary glioblastomas (Zhu & Parada, 2000).

Sequencing of the genome recently identified mutations in the *IDH1/IDH2* genes (isocitrate dehydrogenase 1 and 2 genes) that occur in the majority of WHO grade II–III gliomas and secondary glioblastomas (Hartmann et al., 2009; Yan et al., 2009), all of which harbor a better prognosis compared with the wild-type cases (Sanson et al., 2009). However, pilocytic astrocytomas (WHO grade I) that are potentially curable by complete resection rarely harbor *IDH* mutations. *IDH* appears to function as a tumor suppressor when inactivated through mutation, rendering the IDH enzyme unable to catalyze conversion of isocitrate to alphaketoglutarate. This process also induces HIF1-alpha (hypoxia-inducible factor), which triggers the angiogenic process. However, the precise mechanism of its effect on tumor biology remains unclear (Dang et al., 2009).

Aberrant activation of the *BRAF* proto-oncogene (v-raf murine sarcoma viral oncogene homolog B1) at 7q34, which is most commonly caused by gene duplication and fusion or less frequently by point mutation, has only recently been identified as the characteristic genetic aberration in pilocytic astrocytomas. *BRAF* abnormalities occur in 60–80% of pilocytic astrocytomas but almost never in diffuse, infiltrating astrocytomas (Jones et al., 2009). Thus, testing for *BRAF* gene alterations might be helpful for differentiating during diagnosis between pilocytic astrocytomas and low-grade, diffuse astrocytomas (Korshunov et al., 2009).

The importance of silencing DNA repair pathways, especially the DNA-repair enzyme AGAT (O6-alkylguanine DNA alkyltransferase), which is encoded by the gene *MGMT* (O6 methylguanine-DNA-methyltransferase), has been the subject of substantial debate in recent years (Hofer & Lassman, 2010). The *MGMT* gene is frequently silenced by promoter

glioblastomas, the same genetic pathways are disrupted but by different mechanisms. For example, reduction of the *TP53* pathway generally occurs through the loss of the gene *ARF4* (ADP-ribosylation factor 4) or less frequently through amplification of the gene *MDM2* (transformed 3T3 cell double minute 2). The lack of *RB1* also occurs via a loss of the gene *CDKN2A* (cyclin-dependent kinase inhibitor 2A). In primary glioblastomas, amplification and/or mutation of *EGFR* (epidermal growth factor receptor) and loss of *PTEN* (phosphatase and tensin homolog) are the most frequently observed genetic defects (Fig. 1b)

Fig. 1. Genetic pathways involved in the development of (a) primary and (b) secondary

Sequencing of the genome recently identified mutations in the *IDH1/IDH2* genes (isocitrate dehydrogenase 1 and 2 genes) that occur in the majority of WHO grade II–III gliomas and secondary glioblastomas (Hartmann et al., 2009; Yan et al., 2009), all of which harbor a better prognosis compared with the wild-type cases (Sanson et al., 2009). However, pilocytic astrocytomas (WHO grade I) that are potentially curable by complete resection rarely harbor *IDH* mutations. *IDH* appears to function as a tumor suppressor when inactivated through mutation, rendering the IDH enzyme unable to catalyze conversion of isocitrate to alphaketoglutarate. This process also induces HIF1-alpha (hypoxia-inducible factor), which triggers the angiogenic process. However, the precise mechanism of its effect on tumor

Aberrant activation of the *BRAF* proto-oncogene (v-raf murine sarcoma viral oncogene homolog B1) at 7q34, which is most commonly caused by gene duplication and fusion or less frequently by point mutation, has only recently been identified as the characteristic genetic aberration in pilocytic astrocytomas. *BRAF* abnormalities occur in 60–80% of pilocytic astrocytomas but almost never in diffuse, infiltrating astrocytomas (Jones et al., 2009). Thus, testing for *BRAF* gene alterations might be helpful for differentiating during diagnosis between pilocytic astrocytomas and low-grade, diffuse astrocytomas (Korshunov

The importance of silencing DNA repair pathways, especially the DNA-repair enzyme AGAT (O6-alkylguanine DNA alkyltransferase), which is encoded by the gene *MGMT* (O6 methylguanine-DNA-methyltransferase), has been the subject of substantial debate in recent years (Hofer & Lassman, 2010). The *MGMT* gene is frequently silenced by promoter

(Zu & Parada, 2002).

glioblastomas (Zhu & Parada, 2000).

biology remains unclear (Dang et al., 2009).

et al., 2009).

hypermethylation in diffuse gliomas, and this hypermethylation has been pinpointed as an epigenetic mechanism that reduces *MGMT* expression levels. There are 97 CpG islands in the *MGMT* promoter, and these CpG islands are further divided into two hypermethylated regions (Nakagawachi et al., 2003). Because of its critical role in DNA repair, the epigenetic silencing of *MGMT* is associated with an increased number of mutations and with a poorer outcome in glioblastomas. Thus, *MGMT* silencing is considered to be a biomarker for poor prognosis (Komine et al., 2003). However, an association between *MGMT* promoter methylation and the response of malignant gliomas to alkylating chemotherapy using nitrosourea compounds, temozolomide, or a combination of both has been observed (Esteller et al., 2000; Herrlinger et al., 2006). Furthermore, Hegi et al. (2005) reported that patients treated with radiotherapy and temozolomide, and whose tumors had a methylated *MGMT* promoter (which is seen in approximately 40% of primary glioblastomas), survived significantly longer than did patients whose tumors lacked *MGMT* promoter methylation. Rivera et al. (2010) recently reported that *MGMT* promoter methylation in anaplastic gliomas (WHO grade III) is also predictive of the response to radiotherapy and linked to longer survival in the absence of adjuvant chemotherapy. The use of temozolomide based on *MGMT* methylation status highlights the importance of understanding epigenetic changes in glioblastomas for the discovery of novel therapies and prognostic factors for the treatment of this deadly cancer (Komine et al., 2003; Nakagawachi et al., 2003)

#### **3.2 Oligodendrogliomas**

Oligodendrogliomas represent approximately 10-15% of gliomas, are more common in adults, and can be divided into two histological subtypes: low-grade (WHO grade II) and anaplastic (WHO grade III) (Kleihues et al., 2002).

Low-grade oligodendrogliomas are less biologically aggressive than are astrocytic tumors. Therefore, the prognosis is quite favorable and survival beyond 15 years is achieved in up to 90% of cases that receive a complete surgical resection. There is potential for malignancy, but even the aggressive tumors respond well to additional treatments (e.g., radiation and chemotherapy). Anaplastic oligodendrogliomas have a more aggressive course; however, survival is still five to eight years longer than that observed with anaplastic astrocytomas (Reifenberger & Louis, 2003).

In 1990, the PCV chemotherapy regimen (procarbazine, carmustine, and vincristine) was shown to result in a dramatic tumor response in oligodendrogliomas. Since that time, the identification of all forms of gliomas with oligodendroglial components became crucial (Macdonald et al., 1990). Importantly, these studies indicated that the prognostic power of oligodendroglial components was independent of whether radiotherapy, chemotherapy or combined radio-chemotherapy was used (Wick et al., 2009). This phenomenon is likely due to oligodendrogliomas exhibiting specific genetic abnormalities that distinguish them from other gliomas. Reifenberger et al. (1994), after a thorough analysis of the genome, reported a loss of genetic information in the 1p and 19q loci in oligodendrogliomas, the so-called chromosome 1p/19q co-deletion. This loss was later linked with a good response to PCV and provided the first molecular indicator of treatment response in brain tumors (Cairncross et al., 1998; Reifenberger et al., 2003). Further studies corroborated these findings, and it is now known that the chromosomal loss results from an unbalanced translocation (Franco-Hernandez et al., 2009; Jenkins et al., 2006). Approximately 85% of low-grade oligodendrogliomas and 65% of anaplastic oligodendrogliomas present with 1p/19q codeletions (Smith et al., 2000).

Genomic Abnormalities in Gliomas 87

one polymorphism every 1.91 Kb. Therefore, 90% of sequences greater than 20 Kb in length have at least one SNP, and this density can be higher in genic regions. Of the known genes, 93% contain SNPs and 98% are at least 5 Kb away from a SNP. Soon, almost all genes or gene regions will be marked by one of these variable sequences (Sachidanandam et al.,

better prognosis in these tumors

astrocytoma patients is unknown

 Diagnostic marker for diffuse WHO grade II and III gliomas, as well as secondary glioblastomas, and associated with a

Rare in primary glioblastomas, but when present, it is

Predictive for response of glioblastomas to alkylating

 Prognostic in anaplastic glioma patients treated with radiotherapy and/or alkylating chemotherapy

 Associated with longer survival in glioblastoma patients treated with radiotherapy combined with concurrent and

 Associated with improved prognosis in oligodendroglial tumor patients receiving adjuvant radiotherapy and/or

Not predictive for response to a particular type of therapy

Not predictive for response to a particular type of therapy

 Diagnostic marker for pilocytic astrocytomas and helpful in distinguishing these tumors from diffuse astrocytomas Prognostic significance within the group of pilocytic

associated with a more favorable outcome

**Molecular marker Clinical significance** 

chemotherapy

chemotherapy

adjuvant temozolomide

Table 2. The four most relevant markers for the molecular diagnosis of gliomas (Hofer &

Because they are found throughout the genome, some alleles containing SNPs produce functional or physiologically relevant gene products. For example, SNPs in a coding region can affect the coded protein. When located in an intron, SNPs can influence the splicing mechanism, and when located in the promoter, SNPs can alter gene transcription (Krawczak et al., 1992). For this reason, SNPs are recognized as important tools in human genetics and medicine and have been widely used in genetic association studies of various complex diseases, including cancer. In humans, several reviews of SNPs have been carried out in an attempt to determine the patterns of SNP haplotypes in different populations (Conrad et al., 2006; Gonzalez-Neira et al., 2006; Jakobsson et al., 2008; Nothnagel & Rohde, 2005; Salisbury et al., 2003). Data from these tests are extremely useful for studying the genetic basis of cancer. For this reason, several research groups have focused on elucidating the role of SNPs in different genes related to the initiation and progression of gliomas in different populations. We performed association studies between SNPs, the risk of developing gliomas, and the prognosis for gliomas in a Brazilian population. Brazilians form one of the most heterogeneous populations in the world, which is the result of five centuries of

2001).

*IDH1*/*IDH2* mutation

*BRAF* duplication/fusion

*MGMT* promoter methylation

1p/19q co-deletion

Lassman, 2010; Riemenschneider et al., 2010).

Low-grade oligodendrogliomas and astrocytomas present a loss of *ARF4* expression and overexpression of *EGFR* and PDGF signaling. Malignant progression is associated with additional genetic abnormalities that are similar to those described above for astrocytomas, including a lack of the *RB1* pathway, loss of *RB1,* or gene amplification/overexpression of the *CDK4* gene (Franco-Hernandez et al., 2007; Reifenberger & Louis, 2003).

#### **3.3 Ependymomas**

Ependymomas arise in or near the ependymal surface, and these tumors can occur anywhere in the ventricular system, spinal cord and even occasionally at extraneural sites. The most common location is in the fourth ventricle, followed by the spinal cord, the lateral ventricles and the third ventricle. These tumors are more common in children but can also occur in adults (Ebert et al., 1999).

WHO classification identifies four major subtypes of ependymomas: subependymomas (WHO grade I), myxopapillary ependymomas (WHO grade I), low-grade ependymomas (WHO grade II) and anaplastic ependymomas (WHO grade III). Subependymomas are intraventricular in location, while myxopapillary ependymomas are commonly found in the cauda equina. The low-grade ependymomas can be differentiated from their anaplastic counterparts based on the low rate of mitosis and the low level of nuclear polymorphism; however, the distinction between the two tumors remains poorly defined (Kleihues et al., 2002).

In ependymomas, chromosomal abnormalities detected by classic cytogenetics and CGH involve chromosomes 1, 6, 7, 9, 10, 13, 17, 19 and 22. Deletions are the most commonly observed changes, and chromosome 22 losses are common in adults (50%) but rare in pediatric ependymomas (Kraus et al., 2001; Lamszus et al., 2001; von Haken et al., 1996). The target genes, located in regions of chromosomal gain or loss, are unknown, with the exception of cases in which both copies of the wild-type *NF2* gene (neurofibromin 2) are lost in intramedullary ependymomas (Alonso et al., 2002). Isolated cases of *MEN1* gene (multiple endocrine neoplasia I) loss have also been reported (Urioste et al., 2002). Germline mutations in *TP53* are uncommon, in contrast with those seen in diffuse astrocytomas (Nozaki et al., 1998).

When reviewed together, the data on genetic and epigenetic abnormalities presented above allow us to define four molecular biomarkers: *MGMT* hypermethylation in glioblastomas and anaplastic gliomas, *IDH1* and *IDH2* mutations in diffuse gliomas, *BRAF* aberrations in pilocytic astrocytomas, and combined deletions of chromosome arms 1p and 19q in oligodendroglial tumors. These biomarkers and their clinical significance are summarized in Table 2.

#### **4. Single nucleotide polymorphisms and gliomas**

A single nucleotide polymorphism (SNP) is generally defined as a stable replacement of only one DNA base, with a frequency greater than 1% in at least one population (Taylor et al., 2001). In human genetics studies, SNPs are simply referred to as bi-allelic markers because tri-and tetra-allelic markers are rare (Brookes, 1999).

Initially, only a few thousand SNPs were thought to exist in the entire genome. However, since 2000, that number has increased about one thousand-fold. In 2001, an international consortium on mapping SNPs described 1.42 million polymorphic loci. More important than this large number is the precision of their placement in the genome; there is approximately

Low-grade oligodendrogliomas and astrocytomas present a loss of *ARF4* expression and overexpression of *EGFR* and PDGF signaling. Malignant progression is associated with additional genetic abnormalities that are similar to those described above for astrocytomas, including a lack of the *RB1* pathway, loss of *RB1,* or gene amplification/overexpression of

Ependymomas arise in or near the ependymal surface, and these tumors can occur anywhere in the ventricular system, spinal cord and even occasionally at extraneural sites. The most common location is in the fourth ventricle, followed by the spinal cord, the lateral ventricles and the third ventricle. These tumors are more common in children but can also

WHO classification identifies four major subtypes of ependymomas: subependymomas (WHO grade I), myxopapillary ependymomas (WHO grade I), low-grade ependymomas (WHO grade II) and anaplastic ependymomas (WHO grade III). Subependymomas are intraventricular in location, while myxopapillary ependymomas are commonly found in the cauda equina. The low-grade ependymomas can be differentiated from their anaplastic counterparts based on the low rate of mitosis and the low level of nuclear polymorphism; however, the distinction between the two tumors remains poorly defined (Kleihues et al.,

In ependymomas, chromosomal abnormalities detected by classic cytogenetics and CGH involve chromosomes 1, 6, 7, 9, 10, 13, 17, 19 and 22. Deletions are the most commonly observed changes, and chromosome 22 losses are common in adults (50%) but rare in pediatric ependymomas (Kraus et al., 2001; Lamszus et al., 2001; von Haken et al., 1996). The target genes, located in regions of chromosomal gain or loss, are unknown, with the exception of cases in which both copies of the wild-type *NF2* gene (neurofibromin 2) are lost in intramedullary ependymomas (Alonso et al., 2002). Isolated cases of *MEN1* gene (multiple endocrine neoplasia I) loss have also been reported (Urioste et al., 2002). Germline mutations in *TP53* are uncommon, in contrast with those seen in diffuse astrocytomas

When reviewed together, the data on genetic and epigenetic abnormalities presented above allow us to define four molecular biomarkers: *MGMT* hypermethylation in glioblastomas and anaplastic gliomas, *IDH1* and *IDH2* mutations in diffuse gliomas, *BRAF* aberrations in pilocytic astrocytomas, and combined deletions of chromosome arms 1p and 19q in oligodendroglial tumors. These biomarkers and their clinical significance are summarized in

A single nucleotide polymorphism (SNP) is generally defined as a stable replacement of only one DNA base, with a frequency greater than 1% in at least one population (Taylor et al., 2001). In human genetics studies, SNPs are simply referred to as bi-allelic markers

Initially, only a few thousand SNPs were thought to exist in the entire genome. However, since 2000, that number has increased about one thousand-fold. In 2001, an international consortium on mapping SNPs described 1.42 million polymorphic loci. More important than this large number is the precision of their placement in the genome; there is approximately

**4. Single nucleotide polymorphisms and gliomas** 

because tri-and tetra-allelic markers are rare (Brookes, 1999).

the *CDK4* gene (Franco-Hernandez et al., 2007; Reifenberger & Louis, 2003).

**3.3 Ependymomas** 

2002).

(Nozaki et al., 1998).

Table 2.

occur in adults (Ebert et al., 1999).

one polymorphism every 1.91 Kb. Therefore, 90% of sequences greater than 20 Kb in length have at least one SNP, and this density can be higher in genic regions. Of the known genes, 93% contain SNPs and 98% are at least 5 Kb away from a SNP. Soon, almost all genes or gene regions will be marked by one of these variable sequences (Sachidanandam et al., 2001).


Table 2. The four most relevant markers for the molecular diagnosis of gliomas (Hofer & Lassman, 2010; Riemenschneider et al., 2010).

Because they are found throughout the genome, some alleles containing SNPs produce functional or physiologically relevant gene products. For example, SNPs in a coding region can affect the coded protein. When located in an intron, SNPs can influence the splicing mechanism, and when located in the promoter, SNPs can alter gene transcription (Krawczak et al., 1992). For this reason, SNPs are recognized as important tools in human genetics and medicine and have been widely used in genetic association studies of various complex diseases, including cancer. In humans, several reviews of SNPs have been carried out in an attempt to determine the patterns of SNP haplotypes in different populations (Conrad et al., 2006; Gonzalez-Neira et al., 2006; Jakobsson et al., 2008; Nothnagel & Rohde, 2005; Salisbury et al., 2003). Data from these tests are extremely useful for studying the genetic basis of cancer. For this reason, several research groups have focused on elucidating the role of SNPs in different genes related to the initiation and progression of gliomas in different populations. We performed association studies between SNPs, the risk of developing gliomas, and the prognosis for gliomas in a Brazilian population. Brazilians form one of the most heterogeneous populations in the world, which is the result of five centuries of

Genomic Abnormalities in Gliomas 89

et al., 2010). In our results, the genotype and allele frequencies between cases and controls were similar, indicating no significant association with glioma risk (*P* = 0.94 and *P* = 0.887, respectively) and suggesting that *EGF* +61 A>G may not significantly contribute to the susceptibility to gliomas in the Brazilian population. This result is consistent with that of Vauleon et al. (2007) and Liu et al. (2009) in French and Chinese populations, respectively. However, we found that the major +61G allele (frequency among controls, 0.51) was associated with a shorter overall survival in patients (*P* = 0.023). Thus, with regard to patient survival, our results corroborate those of Bhowmick et al. (2004) in a population of North

We have also studied the *GSTP1* gene, which encodes a protein accounting for approximately 90% of the enzymatic activity of the glutathione S-transferase (GST) family (Custodio et al., 2010). GSTs constitute a superfamily of ubiquitous, multifunctional enzymes that are involved in cellular detoxification of a large number of endogenous and exogenous chemical agents that possess electrophilic functional groups (Ryberg et al., 1997). The GSTP1 protein is a pi-class enzyme and *GSTP1* structure has been extensively examined in association with the risk of cancer (White et al., 2008). The influence of the *GSTP1* Ile105Val SNP on cancer has been reported with inconsistent results from different parts of the world (Syamala et al., 2008). Our results demonstrate that the Val105 allele was more frequent in a population of cancer patients than in a healthy population (0.29 and 0.06, respectively; *P* < 0.001) and that the presence of this genotype may increase the risk of developing astrocytomas and glioblastomas (OR = 8.60; 95% CI, 4.14-17.87; *P* < 0.001). However, we did not find an association between the *GSTP1* Ile105Val SNP and patient

Recently, we began studying SNPs in DNA repair genes and we performed association analysis of SNPs in genes for the *XRCC* (X-ray cross-complementing) family, *XRCC1* and *XRCC3*, in a series of gliomas (unpublished data). Human tumors may develop through alterations to the DNA repair system, which is crucially important for cellular life (Kawabata et al., 2005). To ensure the integrity of the genome, a complex system of DNA repair was developed. Base excision repair is the first defense mechanism of cells against DNA damage and a major means for preventing mutagenesis (Hu et al., 2005). Repair genes may play an important role in maintaining genomic stability through different pathways mediating base excision repair (Sreeja et al., 2008). For this reason, much attention has been given to the study of SNPs in *XRCCs* and their involvement in different types of cancer, including gliomas. We performed analysis of the Arg194Trp and Arg399Gln SNPs in *XRCC1* and the Thr241Met SNP in *XRCC3* to assess their roles in the risk and prognosis for gliomas in Brazilians. Our results provide evidence that the *XRCC*1 Arg194Trp SNP may contribute to the etiology of human gliomas because the Trp194 allele was strongly associated with risk and the Gln399 allele revealed a small, increased risk for tumor development. In regard to the *XRCC3* Thr241Met SNP, we also found evidence that *XRRC3* Thr241Met may contribute to the etiology of human gliomas. However, when the Arg194Trp and Arg399Gln SNPs in *XRCC1* and the Thr241Met SNP in *XRCC3* were considered together, we did not find

Around the globe, other groups have analyzed the association between SNPs found in *XRCCs* genes and the risk of developing gliomas. Kiuru et al. (2003) evaluated the association between the *XRCC1* Arg194Trp, Arg280His, and Arg399Gln SNPS, the *XRCC3*

statistical difference between genotypes and patient survival.

American patients.

survival.

interethnic crosses of peoples from three continents: the European colonizers who are mainly represented by the Portuguese, the African slaves, and the autochthonous Amerindians (Parra et al., 2003).

Until recently, we were the only laboratory investigating the association between *WRN* Cys1367Arg, the risk for brain tumor development, and the prognosis of brain tumors, especially with regard to gliomas (Pinto et al., 2008a). Werner syndrome (WS) is a premature aging disorder characterized by early onset of symptoms related to normal aging and is caused by inherited, recessive mutations in the *WRN* gene. The *WRN* gene encodes a member of the RecQ family of helicases involved in DNA replication and in maintaining the integrity of the genome (Harrigan et al., 2006). The cells of WS patients exhibit a high level of chromosomal translocations and deletions, and these patients present an increased predisposition to various types of cancer, including CNS tumors (Kobayashi et al., 1980). However, despite its putative tumor suppressor function, little is known about the contribution of the WRN protein to sporadic human malignancies. Taking into account that almost all cancers occur in the elderly and that mutations in the *WRN* gene lead to accelerated aging, it has been suggested that polymorphisms of the *WRN* gene, similar to Cys1367Arg, might be associated with age-related pathologies and cancer predisposition. However, our data indicate that neither glioma risk (OR = 1.38; 95% CI, 0.78-2.43; *P* = 0.334) nor patient survival (overall and disease-free survival, *P* = 0.396 and *P* = 0.843, respectively) was associated with variant alleles.

Similar results were found when we evaluated the genotype distribution of *TP53* Pro47Ser and Arg72Pro SNPs for their involvement in susceptibility to gliomas and in determining the oncologic prognosis of patients (Pinto et al., 2008b). A critical site in the TP53 protein for apoptosis signaling is a proline-rich region located between codons 64 and 92. Dumont et al. (2003) reported that the homozygous Arg72 allele induces apoptosis at a rate that is 15-fold higher than the Pro72 allele. According to Leu et al. (2004), the apoptosis-inducing ability of the Arg72 allele is in part due to its mitochondrial location, which makes it possible for TP53 to directly interact with the pro-apoptotic protein, BAK. However, the *TP53* Pro47Ser SNP resulted in a significantly decreased ability of the TP53 protein to induce apoptosis. A critical event in TP53-induced apoptosis is phosphorylation of the serine residue at codon 46. This region is where allele Pro47 acts as a substrate for proline-directed kinases such as the MAPK1 protein. Li et al. (2005) reported that the Ser47 allele, which is a poor substrate for MAPK1, has an apoptosis-inducing ability that is 5-fold lower than that of the wild-type Pro47 allele. However, our data again indicated that neither glioma susceptibility nor patient survival was associated with the *TP53* Arg72Pro or Pro47Ser alleles in the Brazilian population.

In 2009, we investigated the role of *EGF* +61 A>G as a potential risk factor and/or prognostic marker for gliomas in the Brazilian population. The *EGF* gene encodes a ligand for EGFR that activates a cascade of events responsible for promoting cell proliferation, inhibition of apoptosis, and differentiation. Alterations in the EGF/EGFR signaling pathway are associated with tumor progression in a variety of human cancers. Therefore, high expression of EGF may play a key role in glioma development and progression (Salomon et al., 1995). Shahbazi et al. (2002) first reported that the +61 A>G SNP in the 5'-UTR region of *EGF* is associated with increased EGF production and risk of malignant melanoma. Since that discovery, other research groups have obtained conflicting findings regarding the relationship of this functional SNP with different human cancers, including gliomas (Bao et al., 2010; Bhowmick et al., 2004; Costa et al., 2007; Liu et al., 2009; Vauleon et al., 2007; Wang

interethnic crosses of peoples from three continents: the European colonizers who are mainly represented by the Portuguese, the African slaves, and the autochthonous

Until recently, we were the only laboratory investigating the association between *WRN* Cys1367Arg, the risk for brain tumor development, and the prognosis of brain tumors, especially with regard to gliomas (Pinto et al., 2008a). Werner syndrome (WS) is a premature aging disorder characterized by early onset of symptoms related to normal aging and is caused by inherited, recessive mutations in the *WRN* gene. The *WRN* gene encodes a member of the RecQ family of helicases involved in DNA replication and in maintaining the integrity of the genome (Harrigan et al., 2006). The cells of WS patients exhibit a high level of chromosomal translocations and deletions, and these patients present an increased predisposition to various types of cancer, including CNS tumors (Kobayashi et al., 1980). However, despite its putative tumor suppressor function, little is known about the contribution of the WRN protein to sporadic human malignancies. Taking into account that almost all cancers occur in the elderly and that mutations in the *WRN* gene lead to accelerated aging, it has been suggested that polymorphisms of the *WRN* gene, similar to Cys1367Arg, might be associated with age-related pathologies and cancer predisposition. However, our data indicate that neither glioma risk (OR = 1.38; 95% CI, 0.78-2.43; *P* = 0.334) nor patient survival (overall and disease-free survival, *P* = 0.396 and *P* = 0.843, respectively)

Similar results were found when we evaluated the genotype distribution of *TP53* Pro47Ser and Arg72Pro SNPs for their involvement in susceptibility to gliomas and in determining the oncologic prognosis of patients (Pinto et al., 2008b). A critical site in the TP53 protein for apoptosis signaling is a proline-rich region located between codons 64 and 92. Dumont et al. (2003) reported that the homozygous Arg72 allele induces apoptosis at a rate that is 15-fold higher than the Pro72 allele. According to Leu et al. (2004), the apoptosis-inducing ability of the Arg72 allele is in part due to its mitochondrial location, which makes it possible for TP53 to directly interact with the pro-apoptotic protein, BAK. However, the *TP53* Pro47Ser SNP resulted in a significantly decreased ability of the TP53 protein to induce apoptosis. A critical event in TP53-induced apoptosis is phosphorylation of the serine residue at codon 46. This region is where allele Pro47 acts as a substrate for proline-directed kinases such as the MAPK1 protein. Li et al. (2005) reported that the Ser47 allele, which is a poor substrate for MAPK1, has an apoptosis-inducing ability that is 5-fold lower than that of the wild-type Pro47 allele. However, our data again indicated that neither glioma susceptibility nor patient survival was associated with the *TP53* Arg72Pro or Pro47Ser alleles in the Brazilian

In 2009, we investigated the role of *EGF* +61 A>G as a potential risk factor and/or prognostic marker for gliomas in the Brazilian population. The *EGF* gene encodes a ligand for EGFR that activates a cascade of events responsible for promoting cell proliferation, inhibition of apoptosis, and differentiation. Alterations in the EGF/EGFR signaling pathway are associated with tumor progression in a variety of human cancers. Therefore, high expression of EGF may play a key role in glioma development and progression (Salomon et al., 1995). Shahbazi et al. (2002) first reported that the +61 A>G SNP in the 5'-UTR region of *EGF* is associated with increased EGF production and risk of malignant melanoma. Since that discovery, other research groups have obtained conflicting findings regarding the relationship of this functional SNP with different human cancers, including gliomas (Bao et al., 2010; Bhowmick et al., 2004; Costa et al., 2007; Liu et al., 2009; Vauleon et al., 2007; Wang

Amerindians (Parra et al., 2003).

was associated with variant alleles.

population.

et al., 2010). In our results, the genotype and allele frequencies between cases and controls were similar, indicating no significant association with glioma risk (*P* = 0.94 and *P* = 0.887, respectively) and suggesting that *EGF* +61 A>G may not significantly contribute to the susceptibility to gliomas in the Brazilian population. This result is consistent with that of Vauleon et al. (2007) and Liu et al. (2009) in French and Chinese populations, respectively. However, we found that the major +61G allele (frequency among controls, 0.51) was associated with a shorter overall survival in patients (*P* = 0.023). Thus, with regard to patient survival, our results corroborate those of Bhowmick et al. (2004) in a population of North American patients.

We have also studied the *GSTP1* gene, which encodes a protein accounting for approximately 90% of the enzymatic activity of the glutathione S-transferase (GST) family (Custodio et al., 2010). GSTs constitute a superfamily of ubiquitous, multifunctional enzymes that are involved in cellular detoxification of a large number of endogenous and exogenous chemical agents that possess electrophilic functional groups (Ryberg et al., 1997). The GSTP1 protein is a pi-class enzyme and *GSTP1* structure has been extensively examined in association with the risk of cancer (White et al., 2008). The influence of the *GSTP1* Ile105Val SNP on cancer has been reported with inconsistent results from different parts of the world (Syamala et al., 2008). Our results demonstrate that the Val105 allele was more frequent in a population of cancer patients than in a healthy population (0.29 and 0.06, respectively; *P* < 0.001) and that the presence of this genotype may increase the risk of developing astrocytomas and glioblastomas (OR = 8.60; 95% CI, 4.14-17.87; *P* < 0.001). However, we did not find an association between the *GSTP1* Ile105Val SNP and patient survival.

Recently, we began studying SNPs in DNA repair genes and we performed association analysis of SNPs in genes for the *XRCC* (X-ray cross-complementing) family, *XRCC1* and *XRCC3*, in a series of gliomas (unpublished data). Human tumors may develop through alterations to the DNA repair system, which is crucially important for cellular life (Kawabata et al., 2005). To ensure the integrity of the genome, a complex system of DNA repair was developed. Base excision repair is the first defense mechanism of cells against DNA damage and a major means for preventing mutagenesis (Hu et al., 2005). Repair genes may play an important role in maintaining genomic stability through different pathways mediating base excision repair (Sreeja et al., 2008). For this reason, much attention has been given to the study of SNPs in *XRCCs* and their involvement in different types of cancer, including gliomas. We performed analysis of the Arg194Trp and Arg399Gln SNPs in *XRCC1* and the Thr241Met SNP in *XRCC3* to assess their roles in the risk and prognosis for gliomas in Brazilians. Our results provide evidence that the *XRCC*1 Arg194Trp SNP may contribute to the etiology of human gliomas because the Trp194 allele was strongly associated with risk and the Gln399 allele revealed a small, increased risk for tumor development. In regard to the *XRCC3* Thr241Met SNP, we also found evidence that *XRRC3* Thr241Met may contribute to the etiology of human gliomas. However, when the Arg194Trp and Arg399Gln SNPs in *XRCC1* and the Thr241Met SNP in *XRCC3* were considered together, we did not find statistical difference between genotypes and patient survival.

Around the globe, other groups have analyzed the association between SNPs found in *XRCCs* genes and the risk of developing gliomas. Kiuru et al. (2003) evaluated the association between the *XRCC1* Arg194Trp, Arg280His, and Arg399Gln SNPS, the *XRCC3*

Genomic Abnormalities in Gliomas 91

*XRCC7* G6721T Risk GG vs. TT, 1.82 (1.13–2.93)1

*XRCC1* Arg399Gln Risk AA vs. GG, 1.23 (0.96–1.57)2

*PARP1* Val762ala Protective CT/CC vs. TT, 0.80 (0.67–0.95)2

*ERCC1* A8092C Risk AA/AC vs. CC, 4.41 (1.6–12.2)5

*ERCC2* Gln751Lys Risk CC vs. AA, 1.19 (0.93–1.52)2

*MGMT* Phe84Leu Protective or risk? CT/TT vs. CC, 0.66 (0.45–0.94)4

Inflammation: *IL13* Arg130Gln Protective AG vs. GG, 0.75 (0.48–1.17)10

Table 3. Selected glioma susceptibility genes and SNPs observed in at least two studies. 1Wang et al. (2004); 2McKean-Cowdin et al. (2009); 3Kiuru et al. (2008); 4Liu et al. (2009); 5Chen et al. (2000); 6Wrensch et al. (2005); 7Felini et al. (2007); 8Bhowmick et al. (2004); 9Costa

Both the invasive nature of the tumor and its heterogeneity probably contribute to the poor response to the treatment regimens available today. Tumor heterogeneity is traditionally attributed to the accumulation of regional variations in the tumor microenvironment and the diversity of subpopulations of cancer cells, which result from random genetic changes

The majority tumors consist of a heterogeneous population of cells with different proliferative potential, as well as the ability to re-form the tumor upon transplantation into immunodeficient mice (Visvader & Lindeman, 2008). Recently, evidence has accumulated that tumors contain a population with characteristics similar to normal stem cells called

GG vs. TT, 1.44 (1.13–1.84)2

 AA vs. GG, 1.32 (0.97–1.81)3 GA/AA vs. GG, 1.44 (1.05–1.92)4

CT/CC vs. TT, 0.71 (0.52–0.97)4

AA/AC vs. CC, 1.67 (0.93–3.02)6

AA vs. AC/CC, 1.66 (1.01–2.72)6

CT/TT vs. CC, 1.26 (0.90–1.75)7

AG/GG vs. AA, 1.52 (1.03–2.23)9

TT vs. CC/CT, 0.39 (0.16–0.93)11

**Main paths, genes Associated SNPs Effect OR (95% CI)** 

et al. (2007); 10Schwartzbaum et al. (2005); 11Amirian et al. (2010).

**5. Cancer stem cells** 

(Reya et al., 2001).

Cell cycle, *EGF* +61 A>G Risk *P* = 0.0328

DNA repair

Thr241Met SNP, and glioma risk in a prospective, population-based, case-control study conducted in Denmark, Finland, Sweden, and the UK. They found no significant association with gliomas for any of the SNPs when examined individually. However, the results indicated possible associations between combinations of *XRCC1* and *XRCC3* SNPs and the risk of glioma development, as carriers of both homozygous variant genotypes, i.e., *XRCC1* Gln399Gln and *XRCC3* Met241Met were associated with a three-fold increased risk of glioma (OR = 3.18; 95% CI, 1.26-8.04). In a haplotype-based approach in a Chinese population, Liu et al. (2007) investigated the role of 22 tagging SNPs (tSNPs) of *XRCC5*, *XRCC6* and *XRCC7*. They found that glioma risk was significantly associated with three of the *XRCC5* tSNPs (rs828704, rs3770502 and rs9288516, *P* = 0.005, 0.042 and 0.003, respectively), one *XRCC6* tSNP (rs6519265, *P* = 0.044), and none of the *XPCC7* tSNPs in a single-locus analysis. Haplotype-based association analysis revealed that glioma risk was significantly associated with one protective *XRCC5* haplotype "CAGTT," which accounted for a 40% reduction (OR = 0.60, 95% CI, 0.43-0.85) in glioma risk. In a study of North Americans, Wang et al. (2004) found that the variant XRCC7T allele of the *XRCC7* G6721T SNP was significantly more common in the glioma cases than in the controls (*P* = 0.045). The *XRCC7* genotype frequency was also significant when comparing the cases and controls (*P* = 0.040). Likewise, the difference in distribution of the combined T-variant genotype (GT + TT) between the cases and controls was also statistically significant (*P* = 0.012), suggesting that the T allele may be a risk factor for glioma.

In addition to the studies mentioned above, several others were published indicating the results of associations, positive or negative, of genomic variations with the risk of developing gliomas. However, the ethnic variations, methodological variations, and the presence of responsible, functionally unknown SNPs in linkage disequilibrium with those SNPs analyzed have contributed to the dissemination of conflicting results in different parts of the world. Gu et al. (2009) presented a review including a list of eight literature-defined, putative, functional, SNPs associated with gliomas in at least two populations from casecontrol studies. A summary of this list is presented in Table 3.

Gene selection for association studies has previously been based on studies reporting the role of genes and their SNPs in the regulation of cellular functions. However, after the completion of the human genome project and the development of analytical platforms capable of parallel genotype processing, which resulted in new selection strategies for identifying susceptibility genes in many complex genetic disorders, gene selection is currently based on genome-wide association (GWA) studies.

The two glioma GWA studies performed so far were published in 2010 in the same issue of Nature Genetics. In the first pages, Shete et al. (2009) presented the results of a meta-analysis of two GWA studies that involved the genotyping of 454,576 tSNPs in a total of 1,878 glioma cases and 3,670 controls, with posterior validation in three additional independent series totaling 2,545 cases and 2,953 controls. The authors identified five risk loci for glioma at 5p15.33 (*TERT* rs2736100), 8q24.21 (*CCDC26* rs4295627), 9p21.3 (*CDKN2A*-*CDKN2B* rs4977756), 11q23.3 (*PHLDB1* rs498872), and 20q13.33 (*RTEL1* rs6010620). In the second study, Wrensch et al. (2009) analyzed 275,895 SNPs in 692 adult patients with high-grade glioma and 3,992 controls, with a replication series of 176 high-grade glioma cases and 174 controls. That analysis provided further evidence to implicate 9p21 (*CDKN2B* rs1412829) and 20q13.3 (*RTEL1* rs6010620) in glioma risk.

Thr241Met SNP, and glioma risk in a prospective, population-based, case-control study conducted in Denmark, Finland, Sweden, and the UK. They found no significant association with gliomas for any of the SNPs when examined individually. However, the results indicated possible associations between combinations of *XRCC1* and *XRCC3* SNPs and the risk of glioma development, as carriers of both homozygous variant genotypes, i.e., *XRCC1* Gln399Gln and *XRCC3* Met241Met were associated with a three-fold increased risk of glioma (OR = 3.18; 95% CI, 1.26-8.04). In a haplotype-based approach in a Chinese population, Liu et al. (2007) investigated the role of 22 tagging SNPs (tSNPs) of *XRCC5*, *XRCC6* and *XRCC7*. They found that glioma risk was significantly associated with three of the *XRCC5* tSNPs (rs828704, rs3770502 and rs9288516, *P* = 0.005, 0.042 and 0.003, respectively), one *XRCC6* tSNP (rs6519265, *P* = 0.044), and none of the *XPCC7* tSNPs in a single-locus analysis. Haplotype-based association analysis revealed that glioma risk was significantly associated with one protective *XRCC5* haplotype "CAGTT," which accounted for a 40% reduction (OR = 0.60, 95% CI, 0.43-0.85) in glioma risk. In a study of North Americans, Wang et al. (2004) found that the variant XRCC7T allele of the *XRCC7* G6721T SNP was significantly more common in the glioma cases than in the controls (*P* = 0.045). The *XRCC7* genotype frequency was also significant when comparing the cases and controls (*P* = 0.040). Likewise, the difference in distribution of the combined T-variant genotype (GT + TT) between the cases and controls was also statistically significant (*P* = 0.012), suggesting

In addition to the studies mentioned above, several others were published indicating the results of associations, positive or negative, of genomic variations with the risk of developing gliomas. However, the ethnic variations, methodological variations, and the presence of responsible, functionally unknown SNPs in linkage disequilibrium with those SNPs analyzed have contributed to the dissemination of conflicting results in different parts of the world. Gu et al. (2009) presented a review including a list of eight literature-defined, putative, functional, SNPs associated with gliomas in at least two populations from case-

Gene selection for association studies has previously been based on studies reporting the role of genes and their SNPs in the regulation of cellular functions. However, after the completion of the human genome project and the development of analytical platforms capable of parallel genotype processing, which resulted in new selection strategies for identifying susceptibility genes in many complex genetic disorders, gene selection is

The two glioma GWA studies performed so far were published in 2010 in the same issue of Nature Genetics. In the first pages, Shete et al. (2009) presented the results of a meta-analysis of two GWA studies that involved the genotyping of 454,576 tSNPs in a total of 1,878 glioma cases and 3,670 controls, with posterior validation in three additional independent series totaling 2,545 cases and 2,953 controls. The authors identified five risk loci for glioma at 5p15.33 (*TERT* rs2736100), 8q24.21 (*CCDC26* rs4295627), 9p21.3 (*CDKN2A*-*CDKN2B* rs4977756), 11q23.3 (*PHLDB1* rs498872), and 20q13.33 (*RTEL1* rs6010620). In the second study, Wrensch et al. (2009) analyzed 275,895 SNPs in 692 adult patients with high-grade glioma and 3,992 controls, with a replication series of 176 high-grade glioma cases and 174 controls. That analysis provided further evidence to implicate 9p21 (*CDKN2B* rs1412829)

that the T allele may be a risk factor for glioma.

control studies. A summary of this list is presented in Table 3.

currently based on genome-wide association (GWA) studies.

and 20q13.3 (*RTEL1* rs6010620) in glioma risk.


Table 3. Selected glioma susceptibility genes and SNPs observed in at least two studies. 1Wang et al. (2004); 2McKean-Cowdin et al. (2009); 3Kiuru et al. (2008); 4Liu et al. (2009); 5Chen et al. (2000); 6Wrensch et al. (2005); 7Felini et al. (2007); 8Bhowmick et al. (2004); 9Costa et al. (2007); 10Schwartzbaum et al. (2005); 11Amirian et al. (2010).

#### **5. Cancer stem cells**

Both the invasive nature of the tumor and its heterogeneity probably contribute to the poor response to the treatment regimens available today. Tumor heterogeneity is traditionally attributed to the accumulation of regional variations in the tumor microenvironment and the diversity of subpopulations of cancer cells, which result from random genetic changes (Reya et al., 2001).

The majority tumors consist of a heterogeneous population of cells with different proliferative potential, as well as the ability to re-form the tumor upon transplantation into immunodeficient mice (Visvader & Lindeman, 2008). Recently, evidence has accumulated that tumors contain a population with characteristics similar to normal stem cells called

Genomic Abnormalities in Gliomas 93

may be strongly influenced by the patterns of SNPs in certain key susceptibility genes; these SNPs are still being identified. The same reasoning can be applied to inter-individual variations in genetic responses to medications, which is a field of great interest to the pharmaceutical industry. The benefit of having a SNP map of different populations is that it allows for coverage of the entire genome so that researchers can compare the patterns and frequencies of SNPs in their patients and associate these patterns with the disease concerned. The GWA studies with significant numbers and carefully matched controls have become a powerful tool in identifying genes involved in common genetic diseases, including gliomas. The identification of susceptibility alleles provides a greater understanding of gliomagenesis and provides target genes for potential therapeutic intervention. Unlike environmental exposure, SNPs do not change during the process of tumorigenesis.

The main features of normal stem cells are the capacity for self-regeneration and differentiation to different cell types. These characteristics are heavily regulated by the local microenvironment. Because studies have shown that cancer stem cells behave like normal stem cells, understanding the regulatory mechanisms of cancer stem cells and their microenvironment has changed our understanding of the biology of gliomas and has precipitated a reassessment of current therapies. The cure of glioma will require the elimination of all tumor cells, including cancer stem cells. Therefore, further studies to provide a better understanding of the origin of cancer stem cells and their interactions with the microenvironment are needed. These findings hold great promise for the development of new therapies that can help us improve the results achieved with current therapies and

Alonso, M.E., Bello, M.J., Arjona, D., Gonzalez-Gomez, P., Lomas, J., de Campos, J.M.,

Amirian, E., Liu, Y., Scheurer, M.E., El-Zein, R., Gilbert, M.R. & Bondy, M.L. (2010). Genetic

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Bao, S., Wu, Q., McLendon, R.E., Hao, Y., Shi, Q., Hjelmeland, A.B., Dewhirst, M.W., Bigner,

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variants in inflammation pathway genes and asthma in glioma susceptibility. *Neuro* 

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targets in malignant glioblastoma microenvironment. *Semin Radiat Oncol*, Vol.19,

Therefore, SNPs may be useful as indicators of risk.

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thereby prolong patient survival.

No.3, pp. 163-170

1002

**7. References** 

1-5

cancer stem cells, which are also multipotent cells. This subpopulation has the ability to repair itself and is believed to control tumor initiation, a process that is responsible for tumor recurrence and the resistance to therapy observed in different tumor types, including gliomas (Bao et al., 2006). The observation that normal stem cells and cancer stem cells share common features (e.g., undifferentiated state and unlimited capacity for self-regeneration) led to the hypothesis of cancer stem cells (Park & Rich, 2009).

A practical component of the cancer stem cell hypothesis is directed to the matter of intrinsic resistance to radiation and chemotherapy. Cancer stem cells are predicted to be difficult targets for tumor therapy because they exhibit a slowed cell cycle and high levels of drug export. Furthermore, these cells may not express or may not be dependent on the oncoproteins that are targeted by the most recent generation of cancer drugs (Cheng et al., 2010).

Cancer stem cells, similar to normal stem cells, are dependent on the microenvironment in which they are located. This microenvironment, formed by cells and extracellular matrix, controls the maintenance of organ functions. Therefore, disturbance of the local microenvironment in neoplastic processes can trigger tumor development (Barcellos-Hoff et al., 2009). In glioma, for example, studies have shown that the microenvironment is surrounded by blood vessels, which provide access to signaling molecules, nutrition, and possibly to the use of the nascent vasculature for migration, which provides direct cell contact and secreted factors that are responsible for maintaining the state of quiescence of cancer stem cells, regulating their self-renewal and multipotency (Gilbertson & Rich, 2007; Jandial et al., 2008). Thus, one can say that cancer stem cells and the microenvironment are parts of the tumor. Therefore, knowledge of the associated characteristics will lead to a new understanding of tumor biology and the development of new therapeutic strategies against these cells. For this reason, it is extremely important to characterize the different subpopulations of cancer stem cells that contribute to tumor formation (Denysenko et al., 2010).

#### **6. Conclusion**

The development and progression of gliomas may likely be due to a multistep process that involves the functional inactivation of tumor suppressor genes and DNA repair genes, as well as the activation of oncogenes. Given the limitations of current therapies, understanding the pathways that lead to tumor progression should remain a high priority in cancer research. If the mechanisms that culminate in metastasis are fully understood, the development of new diagnostic and therapeutic methods may allow for a substantial improvement in the quality of life of affected patients and a better means of predicting patient prognosis. Genetic and epigenetic studies involving large cohorts of glioma patients in different populations have provided important information for understanding the role of key genes in the development and risk of gliomas. Because it is considered a work in progress, the WHO classification for brain tumors may soon incorporate molecular data to refine the classification of these diseases, which are complex from a therapeutic standpoint. SNPs have become increasingly popular in the genetic study of gliomas because of the quick, inexpensive and accurate analysis of SNPs. The identification of SNPs as risk factors for different glioma subtypes can be important for prevention, diagnosis and prognosis. Variations in the genomic sequence contribute to phenotypic diversity and susceptibility to or protection against many complex diseases. Thus, it is estimated that the risk of gliomas

cancer stem cells, which are also multipotent cells. This subpopulation has the ability to repair itself and is believed to control tumor initiation, a process that is responsible for tumor recurrence and the resistance to therapy observed in different tumor types, including gliomas (Bao et al., 2006). The observation that normal stem cells and cancer stem cells share common features (e.g., undifferentiated state and unlimited capacity for self-regeneration)

A practical component of the cancer stem cell hypothesis is directed to the matter of intrinsic resistance to radiation and chemotherapy. Cancer stem cells are predicted to be difficult targets for tumor therapy because they exhibit a slowed cell cycle and high levels of drug export. Furthermore, these cells may not express or may not be dependent on the oncoproteins that are targeted by the most recent generation of cancer drugs (Cheng et al.,

Cancer stem cells, similar to normal stem cells, are dependent on the microenvironment in which they are located. This microenvironment, formed by cells and extracellular matrix, controls the maintenance of organ functions. Therefore, disturbance of the local microenvironment in neoplastic processes can trigger tumor development (Barcellos-Hoff et al., 2009). In glioma, for example, studies have shown that the microenvironment is surrounded by blood vessels, which provide access to signaling molecules, nutrition, and possibly to the use of the nascent vasculature for migration, which provides direct cell contact and secreted factors that are responsible for maintaining the state of quiescence of cancer stem cells, regulating their self-renewal and multipotency (Gilbertson & Rich, 2007; Jandial et al., 2008). Thus, one can say that cancer stem cells and the microenvironment are parts of the tumor. Therefore, knowledge of the associated characteristics will lead to a new understanding of tumor biology and the development of new therapeutic strategies against these cells. For this reason, it is extremely important to characterize the different subpopulations of cancer stem cells that contribute to tumor formation (Denysenko et al.,

The development and progression of gliomas may likely be due to a multistep process that involves the functional inactivation of tumor suppressor genes and DNA repair genes, as well as the activation of oncogenes. Given the limitations of current therapies, understanding the pathways that lead to tumor progression should remain a high priority in cancer research. If the mechanisms that culminate in metastasis are fully understood, the development of new diagnostic and therapeutic methods may allow for a substantial improvement in the quality of life of affected patients and a better means of predicting patient prognosis. Genetic and epigenetic studies involving large cohorts of glioma patients in different populations have provided important information for understanding the role of key genes in the development and risk of gliomas. Because it is considered a work in progress, the WHO classification for brain tumors may soon incorporate molecular data to refine the classification of these diseases, which are complex from a therapeutic standpoint. SNPs have become increasingly popular in the genetic study of gliomas because of the quick, inexpensive and accurate analysis of SNPs. The identification of SNPs as risk factors for different glioma subtypes can be important for prevention, diagnosis and prognosis. Variations in the genomic sequence contribute to phenotypic diversity and susceptibility to or protection against many complex diseases. Thus, it is estimated that the risk of gliomas

led to the hypothesis of cancer stem cells (Park & Rich, 2009).

2010).

2010).

**6. Conclusion** 

may be strongly influenced by the patterns of SNPs in certain key susceptibility genes; these SNPs are still being identified. The same reasoning can be applied to inter-individual variations in genetic responses to medications, which is a field of great interest to the pharmaceutical industry. The benefit of having a SNP map of different populations is that it allows for coverage of the entire genome so that researchers can compare the patterns and frequencies of SNPs in their patients and associate these patterns with the disease concerned. The GWA studies with significant numbers and carefully matched controls have become a powerful tool in identifying genes involved in common genetic diseases, including gliomas. The identification of susceptibility alleles provides a greater understanding of gliomagenesis and provides target genes for potential therapeutic intervention. Unlike environmental exposure, SNPs do not change during the process of tumorigenesis. Therefore, SNPs may be useful as indicators of risk.

The main features of normal stem cells are the capacity for self-regeneration and differentiation to different cell types. These characteristics are heavily regulated by the local microenvironment. Because studies have shown that cancer stem cells behave like normal stem cells, understanding the regulatory mechanisms of cancer stem cells and their microenvironment has changed our understanding of the biology of gliomas and has precipitated a reassessment of current therapies. The cure of glioma will require the elimination of all tumor cells, including cancer stem cells. Therefore, further studies to provide a better understanding of the origin of cancer stem cells and their interactions with the microenvironment are needed. These findings hold great promise for the development of new therapies that can help us improve the results achieved with current therapies and thereby prolong patient survival.

#### **7. References**


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P.E., Osborne, J.E., Lear, J.T., Smith, A.G. & Hutchinson, I.V. (2002). Association between functional polymorphism in EGF gene and malignant melanoma. *Lancet*,

Marie, Y., Boisselier, B., Delattre, J.Y., Hoang-Xuan, K., El Hallani, S., Idbaih, A., Zelenika, D., Andersson, U., Henriksson, R., Bergenheim, A.T., Feychting, M., Lonn, S., Ahlbom, A., Schramm, J., Linnebank, M., Hemminki, K., Kumar, R., Hepworth, S.J., Price, A., Armstrong, G., Liu, Y., Gu, X., Yu, R., Lau, C., Schoemaker, M., Muir, K., Swerdlow, A., Lathrop, M., Bondy, M. & Houlston, R.S. (2009). Genome-wide association study identifies five susceptibility loci for glioma.

Rotman, M., Asbell, S.O., Nelson, J.S. & et al. (1993). Influence of location and extent of surgical resection on survival of patients with glioblastoma multiforme: results of three consecutive Radiation Therapy Oncology Group (RTOG) clinical

Burger, P.C., Scheithauer, B.W. & Jenkins, R.B. (2000). Alterations of chromosome arms 1p and 19q as predictors of survival in oligodendrogliomas, astrocytomas,

Madhavan, J. & Ankathil, R. (2008). Prognostic importance of DNA repair gene polymorphisms of XRCC1 Arg399Gln and XPD Lys751Gln in lung cancer patients


**6** 

**Genetic Diversity of Glioblastoma Multiforme:** 

Glioblastoma multiforme (GBM; WHO grade IV) is the most malignant type of glioma and in addition the most abundant malignant cancer of the adult human brain. Despite progress in diagnosis, surgery and chemotherapy, the median survival time of patients suffering from GBM is approximately 15 months (Stupp et al., 2005). The five years survival time is less than 5% (CBTRUS, 2010). Because glioblastoma cells show a highly infiltrating growth into the brain tissue, a total resection is not possible. In addition, glioblastoma cells are remarkably resistant to chemotherapy and ionizing radiation. In addition, the association of a portion of these cells with hypoxic and necrotic areas within the tumor increases their

1. by histopathology (WHO) in conventional glioblastomas (93%), giant cell glioblastoma

3. by gene expression analysis in (I) classical, (II) mesenchymal, (III) proneural or (IV)

4. by genomic analysis in subgroups harboring specific mutations and/or altered gene

Conventional glioblastomas constitute approximately 93% of all glioblastomas and can be divided into primary or secondary tumors: primary glioblastomas represent approximately 90% and develop de novo, whereas the incidence of secondary glioblastomas that arise from astroyctomas WHO grade II and III is in the range of 5 to 10%. Primary and secondary glioblastomas differ in their genetic defects: for example 39% of primary glioblastomas harbor an amplification of the EGF receptor (EGFR) locus, whereas in secondary glioblastomas no amplification was detected. Mutations within the p53 gene are more abundant in secondary glioblastomas. Unconventional glioblastomas include giant cell

2. by pathogenesis in primary GBM (90%) and secondary GBM (10%);

glioblastomas, gliosarcomas and other rare types (for details see section 4).

**1. Introduction**

resistance.

Gliobastoma multiforme tumors can be classified:

(5%) and gliosarcoma (2%);

dosage/chromosome number.

neural type of GBM;

 **Impact on Future Therapies** 

Franz-Josef Klinz1, Sergej Telentschak1, Roland Goldbrunner2 and Klaus Addicks1

> *1Department of Anatomy I, University of Cologne,*

> > *University of Cologne,*

*Germany* 

<sup>2</sup>*Department of Neurosurgery,* 


## **Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies**

Franz-Josef Klinz1, Sergej Telentschak1,

Roland Goldbrunner2 and Klaus Addicks1 *1Department of Anatomy I, University of Cologne,*  <sup>2</sup>*Department of Neurosurgery, University of Cologne, Germany* 

#### **1. Introduction**

102 Glioma – Exploring Its Biology and Practical Relevance

Wrensch, M., Kelsey, K.T., Liu, M., Miike, R., Moghadassi, M., Sison, J.D., Aldape, K.,

polymorphisms and adult glioma. *Neuro Oncol*, Vol.7, No.4, pp. 495-507 Yan, H., Parsons, D.W., Jin, G., McLendon, R., Rasheed, B.A., Yuan, W., Kos, I., Batinic-

*Rev Cancer*, Vol.2, No.8, pp. 616-626

Organization, Geneva, Switzerland

McMillan, A., Wiemels, J. & Wiencke, J.K. (2005). ERCC1 and ERCC2

Haberle, I., Jones, S., Riggins, G.J., Friedman, H., Friedman, A., Reardon, D., Herndon, J., Kinzler, K.W., Velculescu, V.E., Vogelstein, B. & Bigner, D.D. (2009). IDH1 and IDH2 mutations in gliomas. *N Engl J Med*, Vol.360, No.8, pp. 765-773 Zattara-Cannoni, H., Gambarelli, D., Lena, G., Dufour, H., Choux, M., Grisoli, F. & Vagner-

Capodano, A.M. (1998). Are juvenile pilocytic astrocytomas benign tumors? A cytogenetic study in 24 cases. *Cancer Genet Cytogenet*, Vol.104, No.2, pp. 157-160 Zhu, Y. & Parada, L.F. (2002). The molecular and genetic basis of neurological tumours. *Nat* 

Zülch, K.J. (1979). Histologic typing of tumours of the central nervous system. World Health

Glioblastoma multiforme (GBM; WHO grade IV) is the most malignant type of glioma and in addition the most abundant malignant cancer of the adult human brain. Despite progress in diagnosis, surgery and chemotherapy, the median survival time of patients suffering from GBM is approximately 15 months (Stupp et al., 2005). The five years survival time is less than 5% (CBTRUS, 2010). Because glioblastoma cells show a highly infiltrating growth into the brain tissue, a total resection is not possible. In addition, glioblastoma cells are remarkably resistant to chemotherapy and ionizing radiation. In addition, the association of a portion of these cells with hypoxic and necrotic areas within the tumor increases their resistance.

Gliobastoma multiforme tumors can be classified:


Conventional glioblastomas constitute approximately 93% of all glioblastomas and can be divided into primary or secondary tumors: primary glioblastomas represent approximately 90% and develop de novo, whereas the incidence of secondary glioblastomas that arise from astroyctomas WHO grade II and III is in the range of 5 to 10%. Primary and secondary glioblastomas differ in their genetic defects: for example 39% of primary glioblastomas harbor an amplification of the EGF receptor (EGFR) locus, whereas in secondary glioblastomas no amplification was detected. Mutations within the p53 gene are more abundant in secondary glioblastomas. Unconventional glioblastomas include giant cell glioblastomas, gliosarcomas and other rare types (for details see section 4).

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 105

Unlike oncogenes, tumor suppressor genes generally follow the "two hit" model, which implies that both alleles of a particular tumor suppressor gene have to be inactivated before an effect is manifested. If only one allele is inactivated, the second correct allele can still produce the correct protein. Whereas mutant oncogene alleles are typically dominant,

The mutational activation of oncogenes induces loss of heterozygosity and genomic instability in mammalian cells. These results have used to formulate the oncogene-induced replication stress model (for review see: Halazonetis et al., 2008). In precancerous lesions with intact p53 gene, the oncogene-induced DNA damage leads to p53-dependent apoptosis and/or senescence. After the function of p53 is lost, cells are able to escape its apoptotic and/or senescence effects, and the precancerous lesion is predestinated to become cancerous (Gorgoulis et al., 2005; Bartkova et al., 2005; Bartkova et al., 2006; Di Micco et al., 2006). DNA damage has an important role in promoting polyploidization. If cells with altered DNA enter mitosis, defects in chromosomal segregation and cytokinesis occur (for review see:

The gene for the tumor suppressor protein p53 is mutated in about half of human cancers. It was shown recently by several groups, that eliminating p53 function by mutation leads to dramatically increased reprogramming efficiency of differentiated cells into induced pluripotent stem cells. Important for the field of cancer biology is the report of Mizuno et al. (2010), demonstrating that breast and lung cancers harboring TP53 mutations exhibit stem cell-like transcriptional signatures. These data suggest a role for active p53 in preventing the emergence of cancerous stem-like cells during tumor progression. Since TP53 mutations often arise in a late stage of tumor progression, when many cancer cells with different genetic alterations coexist, some cancer cells may be susceptible to reprogramming to generate stem-like cancer cells, leading to further tumor progression and cellular

DNA sequencing and gene dosage analysis of GBM revealed a high number of shared as well as individual-specific mutations, deletions and amplifications of DNA sequences. A hallmark of many primary GBMs is the loss of one copy of chromosome 10 harboring the locus for the PTEN tumor suppressor gene and/or amplification of the EGF receptor locus at chromosome 7. As a consequence, the Akt signalling pathway is often overactivated in GBM. Array comparative genomic hybridization (CGH) analyses revealed, that primary glioblastomas can be divided into three major genetic subgroups, i.e. tumors with chromosome 7 gain and chromosome 10 loss, tumors with chromosome 10 loss and tumors

Parsons et al. (2008) sequenced 20661 genes coding for proteins in 22 GBM samples and 1 normal sample. They observed that 685 genes contained at least 1 non-silent somatic mutation. 94% of these alterations were single base substitutions that were uniformly distributed among the 21 GBM samples, resulting in an average of 47 mutations per GBM. About 15% of the missense mutations were predicted to have a significant effect on protein function. The same 22 GBM samples were analysed for copy number alterations through hybridization of DNA samples to single nucleotide polymorphism (SNP) arrays, leading to

without copy number changes in chromosomes 7 or 10 (Misra et al., 2005).

the identification of 147 amplifications and 134 homozygous deletions.

mutant tumor suppressor genes are usually recessive.

**2.2 Genetic diversity of glioblastoma multiforme** 

Chow and Poon, 2010).

heterogeneity.


Table 1. Clinical profile of the common histopathological glioblastoma subtypes according to WHO. Modified from Kleihues et al., 2007; Peraud et al., 1997; Peraud et al., 1999 and Reis et al., 2000.

#### **2. Genetics of glioblastoma multiforme**

#### **2.1 Genetic defects in human cancer**

For an introduction into the history of this field the reader is referred to the review of Bignold et al. (2006). Abnormalities of mitoses and chromosomes in cancer cells were described in late 1880s and Hansemann (1890) suggested that cancer cells develop from normal cells due to a tendency to maldistribute chromosomes during mitosis. The term somatic mutation was introduced into tumor biology by Tyzzer (1916). To explain the complexity of cancer phenomena "multi-hit" models (Knudson, 1971) increased in popularity over "single-hit" models of somatic mutation. In the multistep progression model of sporadic colorectal carcinoma five to ten genetic alterations seemed to be necessary for generation of the malignant phenotype (for review see: Fearon and Vogelstein, 1990). The onset and extent of genetic alterations in progression of sporadic colorectal tumors was studied in detail by Stoler et al. (1999). Their observation of about 10,000 genomic alterations occurring per cancer cell has brought into attention the issue of genetic instability in human cancer. Genetic and phenotypic instability are hallmarks of cancer cells and appear early in tumor progression; most cancers are of clonal origin, but individual cancer cells are highly heterogenous. There are three major forms of genetic instability in cancer: (1) aneuploidy, in which entire chromosomes are lost or gained; (2) intrachromosomal instability, distinguished by insertions, deletions, translocations or amplifications and (3) point mutations, which accumulate in certain forms of hereditary cancer as well as in a small portion of sporadic cancers. Stanbridge et al. (1981) reported that specific chromosome loss is associated with the expression of tumorigenicity in human cell hybrids. It was published by Duesberg et al. (1998) that genetic instability of cancer cells is proportional to their degree of aneuploidy. Aneuploidy, an abnormal number of chromosomes, is the result of asymmetrical segregation of chromosomes to daughter cells during mitosis. Once aneuploid, cells will continue to segregate chromosomes asymmetrically during subsequent rounds of mitosis, a process that has been termed "chromosome error propagation" (for review see: Holliday, 1989).

Secondary glioblastoma Giant cell

5% 2%

glioblastoma Gliosarcoma Primary

Conventional Glioblastoma

90% 10%

Clinical onset de novo secondary de novo de novo

(mo) 1,7 >25 1,6 2

Age at diagnosis (yr) 55 39 42 56

Table 1. Clinical profile of the common histopathological glioblastoma subtypes according to WHO. Modified from Kleihues et al., 2007; Peraud et al., 1997; Peraud et al., 1999 and Reis

For an introduction into the history of this field the reader is referred to the review of Bignold et al. (2006). Abnormalities of mitoses and chromosomes in cancer cells were described in late 1880s and Hansemann (1890) suggested that cancer cells develop from normal cells due to a tendency to maldistribute chromosomes during mitosis. The term somatic mutation was introduced into tumor biology by Tyzzer (1916). To explain the complexity of cancer phenomena "multi-hit" models (Knudson, 1971) increased in popularity over "single-hit" models of somatic mutation. In the multistep progression model of sporadic colorectal carcinoma five to ten genetic alterations seemed to be necessary for generation of the malignant phenotype (for review see: Fearon and Vogelstein, 1990). The onset and extent of genetic alterations in progression of sporadic colorectal tumors was studied in detail by Stoler et al. (1999). Their observation of about 10,000 genomic alterations occurring per cancer cell has brought into attention the issue of genetic instability in human cancer. Genetic and phenotypic instability are hallmarks of cancer cells and appear early in tumor progression; most cancers are of clonal origin, but individual cancer cells are highly heterogenous. There are three major forms of genetic instability in cancer: (1) aneuploidy, in which entire chromosomes are lost or gained; (2) intrachromosomal instability, distinguished by insertions, deletions, translocations or amplifications and (3) point mutations, which accumulate in certain forms of hereditary cancer as well as in a small portion of sporadic cancers. Stanbridge et al. (1981) reported that specific chromosome loss is associated with the expression of tumorigenicity in human cell hybrids. It was published by Duesberg et al. (1998) that genetic instability of cancer cells is proportional to their degree of aneuploidy. Aneuploidy, an abnormal number of chromosomes, is the result of asymmetrical segregation of chromosomes to daughter cells during mitosis. Once aneuploid, cells will continue to segregate chromosomes asymmetrically during subsequent rounds of mitosis, a process that has been termed "chromosome error propagation" (for

glioblastoma

Frequency 93%

**2. Genetics of glioblastoma multiforme**

**2.1 Genetic defects in human cancer** 

review see: Holliday, 1989).

Preoperative history

et al., 2000.

Unlike oncogenes, tumor suppressor genes generally follow the "two hit" model, which implies that both alleles of a particular tumor suppressor gene have to be inactivated before an effect is manifested. If only one allele is inactivated, the second correct allele can still produce the correct protein. Whereas mutant oncogene alleles are typically dominant, mutant tumor suppressor genes are usually recessive.

The mutational activation of oncogenes induces loss of heterozygosity and genomic instability in mammalian cells. These results have used to formulate the oncogene-induced replication stress model (for review see: Halazonetis et al., 2008). In precancerous lesions with intact p53 gene, the oncogene-induced DNA damage leads to p53-dependent apoptosis and/or senescence. After the function of p53 is lost, cells are able to escape its apoptotic and/or senescence effects, and the precancerous lesion is predestinated to become cancerous (Gorgoulis et al., 2005; Bartkova et al., 2005; Bartkova et al., 2006; Di Micco et al., 2006). DNA damage has an important role in promoting polyploidization. If cells with altered DNA enter mitosis, defects in chromosomal segregation and cytokinesis occur (for review see: Chow and Poon, 2010).

The gene for the tumor suppressor protein p53 is mutated in about half of human cancers. It was shown recently by several groups, that eliminating p53 function by mutation leads to dramatically increased reprogramming efficiency of differentiated cells into induced pluripotent stem cells. Important for the field of cancer biology is the report of Mizuno et al. (2010), demonstrating that breast and lung cancers harboring TP53 mutations exhibit stem cell-like transcriptional signatures. These data suggest a role for active p53 in preventing the emergence of cancerous stem-like cells during tumor progression. Since TP53 mutations often arise in a late stage of tumor progression, when many cancer cells with different genetic alterations coexist, some cancer cells may be susceptible to reprogramming to generate stem-like cancer cells, leading to further tumor progression and cellular heterogeneity.

#### **2.2 Genetic diversity of glioblastoma multiforme**

DNA sequencing and gene dosage analysis of GBM revealed a high number of shared as well as individual-specific mutations, deletions and amplifications of DNA sequences. A hallmark of many primary GBMs is the loss of one copy of chromosome 10 harboring the locus for the PTEN tumor suppressor gene and/or amplification of the EGF receptor locus at chromosome 7. As a consequence, the Akt signalling pathway is often overactivated in GBM. Array comparative genomic hybridization (CGH) analyses revealed, that primary glioblastomas can be divided into three major genetic subgroups, i.e. tumors with chromosome 7 gain and chromosome 10 loss, tumors with chromosome 10 loss and tumors without copy number changes in chromosomes 7 or 10 (Misra et al., 2005).

Parsons et al. (2008) sequenced 20661 genes coding for proteins in 22 GBM samples and 1 normal sample. They observed that 685 genes contained at least 1 non-silent somatic mutation. 94% of these alterations were single base substitutions that were uniformly distributed among the 21 GBM samples, resulting in an average of 47 mutations per GBM. About 15% of the missense mutations were predicted to have a significant effect on protein function. The same 22 GBM samples were analysed for copy number alterations through hybridization of DNA samples to single nucleotide polymorphism (SNP) arrays, leading to the identification of 147 amplifications and 134 homozygous deletions.

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 107

subtype and infrequently in other subtypes. Even though TP53 is the most frequently mutated gene in GBM (Cancer Genome Atlas Research Network, 2008), there was a distinct lack of TP53 mutations in the Classical subtype samples sequenced. Deletion events at 10q23 harboring the PTEN locus were observed in 100% of the Classical subtype. Focal 9p21.3 homozygous deletion targeting CDKN2A (encoding for both p16INK4A and p14 ARF) was

The Mesenchymal subtype displayed expression of mesenchymal markers as described earlier (Phillips et al. 2006). Genes in the tumor necrosis super family pathway are highly expressed in this subtype. Focal hemizygous deletion of a region at 17q11.2, containing the gene NF1 (coding for neurofibromatosis-related protein NF-1 or neurofibromin 1, a stimulator of GTPase activity of ras proteins) occurred predominantly in the Mesenchymal subtype. NF1 mutations were found in 20 samples, 14 of which were classified as

> Proneural Subtype

TP53 **0%** 32% **54**% 21% 23% PTEN 23% 32% 16% 21% 17% NF1 5% **37**% 5% 16% 13% EGFR 32% 5% 16% 26% 13% IDH1 0% 0% **30**% 5% 8% PIK3R 5% 0% 19% 11% 6% RB1 0% 13% 3% 5% 5% ERBB2 5% 3% 5% 16% 5% EGFRvIII **23**% 3% 3% 0% 5% PIK3CA 5% 3% 8% 5% 4% PDGFRA 0% 0% **11**% 0% 3%

Table 2. Frequently mutated genes in Glioblastoma multiforme and their distribution among GBM subtypes according to Verhaak et al (2010). Outstanding frequencies are grayed out for

The Proneural group showed high expression of oligodendrocytic genes, underlining its status as an atypical GBM subtype. The majority of TP53 mutations and TP53 loss of heterozygosity were found in Proneural samples. The classic GBM signature, chromosome 7 amplification associated with chromosome 10 loss was less prevalent and occurred in only 54% of the Proneural subtype. Focal amplifications of the locus at 4q12 harboring the PDGF Receptor A (PDGFRA) gene were seen in all subtypes of GBM but at a much higher rate

Neural Subtype Approximate Overall Frequency

frequent and co-occurred with EGFR amplification in 94% of the Classical subtype.

Mesenchymal subtype, resulting in 53% of samples with NF1 abnormalities.

Mesenchymal Subtype

comparison between subtypes. Modified from Verhaak et al. (2010).

III. Proneural subtype of GBM (31% of core samples):

II. Mesenchymal subtype of GBM (32% of core samples):

Mutated Gene

Classical Subtype

Parsons et al. (2008) next studied the probabilities that the mutations were either "driver" or "passenger". Driver mutations may provide a selective advantage to the cancer cell, whereas passenger mutations arise by the instability of the tumor genome and have no effect on tumor growth. Analysis of all data was used to identify GBM candidate cancer genes that were likely drivers, pointing to alterations in several signaling pathways: CDKN2A (altered in 50% of GBMs); TP53, EGFR, and PTEN (altered in 30 to 40%); NF1, CDK4, and RB1 (altered in 12 to 15%); and PIK3CA and PIK3R1 (altered in 8 to 10%). By analysing additional gene members within signaling pathways affected by these genes, the authors identified alterations of critical genes in the RB1 pathway (RB1, CDK4, and CDKN2A; altered in 68% of GBMs), TP53 pathway (TP53, MDM2, and MDM4; altered in 64%), and the PI3K/PTEN pathway (PIK3CA, PIK3R1, PTEN, and IRS1; altered in 50%). Mutations in the NF1 gene (coding for neurofibromatosis-related protein NF-1 or neurofibromin 1, a stimulator of GTPase activity of ras proteins) were observed in 16 of 105 GBMs (15%). Mutations in the IDH1 gene (coding for the citric acid cycle enzyme isocitrate dehydrogenase 1) were reported in 18 of 149 GBMs (12%).

The Cancer Genome Atlas Research Network (2008) study analysed 91 GBM samples and found 453 non-silent somatic mutations in 223 genes. Affected signaling pathways include TP53, PTEN, NF1, EGFR, ERBB2, RB1, NF1, PIK3R1, and PIK3CA. High-level amplifications were observed frequently for EGFR, CDK4, PDGFR, MDM2, and MDM4 genes, whereas homozygous deletion events were often associated with CDKN2A/B and PTEN genes. In this study, GBMs from patients treated with temozolomide and/or lomustine were analysed for mutations. Treatment with alkylating agents resulted in more than tenfold increase in the number of mutations, that was dependent on the methylation status of the gene for the DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT).

Bredel et al. (2009) published "A Network Model of a Cooperative Genetic Landscape in Brain Tumors". The authors demonstrate that a multigene risk scoring model based on gene dosis and expression of 7 landscape genes (POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7, and PDCD4) is associated with the overall length of survival in 189 glioblastoma samples. Yadav et al. (2009) reported that loss of function of ANXA7 (annexin 7) stabilizes the EGFR protein and increases EGFR signaling in glioblastoma cells. ANXA7 haploinsuffiency doubles the tumorigenic potential of glioblastoma cells. The heterozygous loss of ANXA7 in about 75% of GBM in the Cancer Genome Atlas Research Network study (2008) plus the observed infrequent ANXA7 mutation in about 6% of GBM is indicative for its role as a haploinsuffiency gene. A multigene predictor model of outcome in GBM based on expression analysis of 9 genes was published by Colman et al. (2009).

Verhaak et al. (2010) used gene expression analysis to divide GBM into 4 subtypes: I. Classical, II. Mesenchymal, III. Proneural, and IV. Neural. The reproducibility of this classification was demonstrated in an independent validation set. To get insight into the genomic events, the authors used copy number and sequence data from the Cancer Genome Atlas Research Network (2008).

I. Classical subtype of GBM (21% of core samples):

Neural precursor and stem cell markers NES, as well as Notch and Sonic hedgehog signaling pathways were highly expressed in the Classical subtype. Chromosome 7 amplification paired with chromosome 10 loss was seen in 100% of the Classical subtype. High level EGF receptor (EGFR) gene amplification was observed in 97% of the Classical

Parsons et al. (2008) next studied the probabilities that the mutations were either "driver" or "passenger". Driver mutations may provide a selective advantage to the cancer cell, whereas passenger mutations arise by the instability of the tumor genome and have no effect on tumor growth. Analysis of all data was used to identify GBM candidate cancer genes that were likely drivers, pointing to alterations in several signaling pathways: CDKN2A (altered in 50% of GBMs); TP53, EGFR, and PTEN (altered in 30 to 40%); NF1, CDK4, and RB1 (altered in 12 to 15%); and PIK3CA and PIK3R1 (altered in 8 to 10%). By analysing additional gene members within signaling pathways affected by these genes, the authors identified alterations of critical genes in the RB1 pathway (RB1, CDK4, and CDKN2A; altered in 68% of GBMs), TP53 pathway (TP53, MDM2, and MDM4; altered in 64%), and the PI3K/PTEN pathway (PIK3CA, PIK3R1, PTEN, and IRS1; altered in 50%). Mutations in the NF1 gene (coding for neurofibromatosis-related protein NF-1 or neurofibromin 1, a stimulator of GTPase activity of ras proteins) were observed in 16 of 105 GBMs (15%). Mutations in the IDH1 gene (coding for the citric acid cycle enzyme isocitrate dehydro-

The Cancer Genome Atlas Research Network (2008) study analysed 91 GBM samples and found 453 non-silent somatic mutations in 223 genes. Affected signaling pathways include TP53, PTEN, NF1, EGFR, ERBB2, RB1, NF1, PIK3R1, and PIK3CA. High-level amplifications were observed frequently for EGFR, CDK4, PDGFR, MDM2, and MDM4 genes, whereas homozygous deletion events were often associated with CDKN2A/B and PTEN genes. In this study, GBMs from patients treated with temozolomide and/or lomustine were analysed for mutations. Treatment with alkylating agents resulted in more than tenfold increase in the number of mutations, that was dependent on the methylation status of the gene for the

Bredel et al. (2009) published "A Network Model of a Cooperative Genetic Landscape in Brain Tumors". The authors demonstrate that a multigene risk scoring model based on gene dosis and expression of 7 landscape genes (POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7, and PDCD4) is associated with the overall length of survival in 189 glioblastoma samples. Yadav et al. (2009) reported that loss of function of ANXA7 (annexin 7) stabilizes the EGFR protein and increases EGFR signaling in glioblastoma cells. ANXA7 haploinsuffiency doubles the tumorigenic potential of glioblastoma cells. The heterozygous loss of ANXA7 in about 75% of GBM in the Cancer Genome Atlas Research Network study (2008) plus the observed infrequent ANXA7 mutation in about 6% of GBM is indicative for its role as a haploinsuffiency gene. A multigene predictor model of outcome in GBM based

Verhaak et al. (2010) used gene expression analysis to divide GBM into 4 subtypes: I. Classical, II. Mesenchymal, III. Proneural, and IV. Neural. The reproducibility of this classification was demonstrated in an independent validation set. To get insight into the genomic events, the authors used copy number and sequence data from the Cancer Genome

Neural precursor and stem cell markers NES, as well as Notch and Sonic hedgehog signaling pathways were highly expressed in the Classical subtype. Chromosome 7 amplification paired with chromosome 10 loss was seen in 100% of the Classical subtype. High level EGF receptor (EGFR) gene amplification was observed in 97% of the Classical

DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT).

on expression analysis of 9 genes was published by Colman et al. (2009).

Atlas Research Network (2008).

I. Classical subtype of GBM (21% of core samples):

genase 1) were reported in 18 of 149 GBMs (12%).

subtype and infrequently in other subtypes. Even though TP53 is the most frequently mutated gene in GBM (Cancer Genome Atlas Research Network, 2008), there was a distinct lack of TP53 mutations in the Classical subtype samples sequenced. Deletion events at 10q23 harboring the PTEN locus were observed in 100% of the Classical subtype. Focal 9p21.3 homozygous deletion targeting CDKN2A (encoding for both p16INK4A and p14 ARF) was frequent and co-occurred with EGFR amplification in 94% of the Classical subtype.

#### II. Mesenchymal subtype of GBM (32% of core samples):

The Mesenchymal subtype displayed expression of mesenchymal markers as described earlier (Phillips et al. 2006). Genes in the tumor necrosis super family pathway are highly expressed in this subtype. Focal hemizygous deletion of a region at 17q11.2, containing the gene NF1 (coding for neurofibromatosis-related protein NF-1 or neurofibromin 1, a stimulator of GTPase activity of ras proteins) occurred predominantly in the Mesenchymal subtype. NF1 mutations were found in 20 samples, 14 of which were classified as Mesenchymal subtype, resulting in 53% of samples with NF1 abnormalities.


Table 2. Frequently mutated genes in Glioblastoma multiforme and their distribution among GBM subtypes according to Verhaak et al (2010). Outstanding frequencies are grayed out for comparison between subtypes. Modified from Verhaak et al. (2010).

III. Proneural subtype of GBM (31% of core samples):

The Proneural group showed high expression of oligodendrocytic genes, underlining its status as an atypical GBM subtype. The majority of TP53 mutations and TP53 loss of heterozygosity were found in Proneural samples. The classic GBM signature, chromosome 7 amplification associated with chromosome 10 loss was less prevalent and occurred in only 54% of the Proneural subtype. Focal amplifications of the locus at 4q12 harboring the PDGF Receptor A (PDGFRA) gene were seen in all subtypes of GBM but at a much higher rate

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 109

NFKBIA deletion **6**% 30% 39% 22%

EGFR amplification **80**% 20% 11% 46%

Table 4. Relationship of four molecular subtypes of glioblastoma to gene-dosage profiles for NFKBIA and EGFR across 188 glioblastomas. NFKBIA deletions are rare in classical (6%) and

Irrespective of subtype a degree of mutual exclusivity between NFKBIA deletion and EGFR amplification was suggested: NFKBIA deletion or EGFR amplification were observed in 53%, whereas concomitant occurrence (NFKBIA deletion together with EGFR amplification) was observed only in 5%. All data and conclusions are from Bredel et al. (2010).

> NFKBIA Expression and MGMT Promoter Methylation Status

44 Low NFKBIA, Unmeth. MGMT

59 Low NFKBIA, Meth. MGMT or High NFKBIA, Unmeth. MGMT

92 High NFKBIA, Meth. MGMT

Table 5. The strong association of the clinical course of GBM with expression of NFKBIA and expression/methylation status of the promoter of O6-methylguanine-DNA methyltrans-

derived from one GBM revealed area-specific genomic imbalances (see chapter 5).

To add an additional level of complexity, gene dosage analysis of separate tumor areas

ferase (MGMT). All data and conclusions are from Bredel et al. (2010).

Media Survival

(Weeks)

Glioblastoma subtypes were classified according to Verhaak et al. (2010).

Median Survival

Mesenchymal Subtype

Nonclassical Glioblastomas

Proneural Subtype

Neural Subtype

With Radiotherapie and Temozolomide

Median Survival

(Weeks)

35

71

122

NFKBIA Expression and MGMT Promoter Methylation Status

45 Low NFKBIA, Unmeth. MGMT

63 Low NFKBIA, Meth. MGMT or High NFKBIA, Unmeth. MGMT

91 High NFKBIA, Meth. MGMT

Genetic Alteration Classical

more common in non-classical (32%) glioblastomas.

NFKBIA and MGMT Expression

High MGMT

Low NFKBIA, Low MGMT or High NFKBIA, High MGMT

Low MGMT

High-risk Low NFKBIA,

Low-risk High NFKBIA,

Risk Groups

Intermediaterisk

Subtype

(35%) in Proneural samples. 11 of the 12 observed mutations in the isocitrate dehydrogenase 1 gene (IDH1) were found in this class.

IV. Neural subtype of GBM (16% of core samples):

The Neural subtype was typified by the expression of neuron markers. The two normal brain tissues samples examined in this data set were both classified as Neural subtype. Chomosome 7 amplification associated with chromosome 10 loss was prevalent in the Neural subtype.


Table 3. Frequency of copy number alterations in Glioblastoma subtypes according to gene expression. Modified from Verhaak et al. (2010).

#### **2.2.1 Subtypes and clinical correlations**

Three of four tumors classified as secondary GBMs were found in the Proneural group. The Proneural subtype was associated with younger age, PDGFRA abnormalities, IDH1 and TP53 mutations, all of which have been associated with secondary GBM in earlier studies (Arjona et al., 2006; Furnari et al., 2007; Kleihues and Ohgaki, 1999; Watanabe et al., 1996; Yan et al., 2009). Verhaak et al. (2010) concluded that tumors did not change class at recurrence, because recurrent tumors were found in all subtypes (Murat et al., 2008). Although statistically not significant, there was a trend towards longer survival for patients with a Proneural signature. Aggressive treatment significantly reduced mortality in Classical and Mesenchymal subtypes, had a less pronounced effect in the Neural subtype and did not alter survival in the Proneural subtype. There was no association of GBM subtype with methylation status of the DNA repair gene MGMT, which has been positively linked to therapy response (all data and conclusions from Verhaak et al., 2010).

Bredel et al. (2010) reported that NFKBIA (nuclear factor of κ-light polypeptide gene enhancer in B-cells inhibitor-α), an inhibitor of EGFR signaling pathway, is often deleted in GBM (Table 4). Most deletions occur in non-classical subtypes of GBM. Deletion and low expression of NFKBIA were reported to be associated with unfavorable outcomes. The authors present a two-gene model based on the expression of NFKBIA and MGMT that is strongly associated with the clinical course of GBM (Table 5).

(35%) in Proneural samples. 11 of the 12 observed mutations in the isocitrate dehydrogenase

The Neural subtype was typified by the expression of neuron markers. The two normal brain tissues samples examined in this data set were both classified as Neural subtype. Chomosome 7 amplification associated with chromosome 10 loss was prevalent in the

> Classical Subtype

7p11.2 EGFR 100% 95% 54% 96% 7q21.2 CDK6 92% 89% 46% 96% 7q31.2 MET 86% 91% 54% 92% 7q34 86% 91% 52% 92% 4q12 PDGFRA 5% 9% 35% 13%

17q11.2 NF1 5% 38% 6% 17% 10q23 PTEN 100% 87% 69% 96%

13q14 RB1 16% 53% 52% 46%

Table 3. Frequency of copy number alterations in Glioblastoma subtypes according to gene

Three of four tumors classified as secondary GBMs were found in the Proneural group. The Proneural subtype was associated with younger age, PDGFRA abnormalities, IDH1 and TP53 mutations, all of which have been associated with secondary GBM in earlier studies (Arjona et al., 2006; Furnari et al., 2007; Kleihues and Ohgaki, 1999; Watanabe et al., 1996; Yan et al., 2009). Verhaak et al. (2010) concluded that tumors did not change class at recurrence, because recurrent tumors were found in all subtypes (Murat et al., 2008). Although statistically not significant, there was a trend towards longer survival for patients with a Proneural signature. Aggressive treatment significantly reduced mortality in Classical and Mesenchymal subtypes, had a less pronounced effect in the Neural subtype and did not alter survival in the Proneural subtype. There was no association of GBM subtype with methylation status of the DNA repair gene MGMT, which has been positively linked to

Bredel et al. (2010) reported that NFKBIA (nuclear factor of κ-light polypeptide gene enhancer in B-cells inhibitor-α), an inhibitor of EGFR signaling pathway, is often deleted in GBM (Table 4). Most deletions occur in non-classical subtypes of GBM. Deletion and low expression of NFKBIA were reported to be associated with unfavorable outcomes. The authors present a two-gene model based on the expression of NFKBIA and MGMT that is

therapy response (all data and conclusions from Verhaak et al., 2010).

strongly associated with the clinical course of GBM (Table 5).

DKN2B 95% 67% 56% 71%

Mesenchymal Subtype

Proneural Subtype

Neural Subtype

1 gene (IDH1) were found in this class.

Known

Neural subtype.

Amplification

Homo- and

Hemizygous

Deletion Events

Events

IV. Neural subtype of GBM (16% of core samples):

9p21.3 CDKN2A/C

expression. Modified from Verhaak et al. (2010).

**2.2.1 Subtypes and clinical correlations**

Cancer Gene in Region


Table 4. Relationship of four molecular subtypes of glioblastoma to gene-dosage profiles for NFKBIA and EGFR across 188 glioblastomas. NFKBIA deletions are rare in classical (6%) and more common in non-classical (32%) glioblastomas.

Irrespective of subtype a degree of mutual exclusivity between NFKBIA deletion and EGFR amplification was suggested: NFKBIA deletion or EGFR amplification were observed in 53%, whereas concomitant occurrence (NFKBIA deletion together with EGFR amplification) was observed only in 5%. All data and conclusions are from Bredel et al. (2010). Glioblastoma subtypes were classified according to Verhaak et al. (2010).


Table 5. The strong association of the clinical course of GBM with expression of NFKBIA and expression/methylation status of the promoter of O6-methylguanine-DNA methyltransferase (MGMT). All data and conclusions are from Bredel et al. (2010).

To add an additional level of complexity, gene dosage analysis of separate tumor areas derived from one GBM revealed area-specific genomic imbalances (see chapter 5).

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 111

tumor masses are typically well-circumscribed. It occurs in younger patients (fifth decade)

The molecular genetic features include relatively high frequencies of TP53 mutations (59% to 90%) and PTEN deletion (up to 33%), whereas EGFR amplification/overexpression and homozygous p16 deletion (p16INK4a gene at the CDKN2A locus, 9p21) are lacking in comparison to conventional glioblastoma (Meyer-Puttlitz et al., 1997; Peraud et al., 1997; Peraud et al. 1999; Temme et al. 2010). Therefore, giant cell glioblastomas contain clinical and molecular genetic features of both primary and secondary glioblastomas. Giant cell glioblastomas have an increased expression of Aurora Kinase B; combined with TP53 mutations this may be responsible in induce cytokinesis defects and the development of

glioblastoma

5% 8% 0% 0%

Giant cell glioblastoma

Secondary glioblastoma

Gliosarcoma Primary

PTEN mutation 38% 32% 33% 4% EGFR amplification 0% 39% 5% 0% TP53 mutation 23% 11% 84% 67% p16INK4a deletion 37% 36% 0% 4%

Table 6. Genetic profile of the common histopathological glioblastoma subtypes. Similar tendencies are indicated by grayscale. Modified from Kleihues et al., 2007; Peraud et al.,

Despite showing a very poor prognosis giant cell glioblastoma appears to carry a slightly better prognosis than conventional glioblastoma (Burger and Vollmer, 1980; Margetts and Kalyan-Raman, 1989; Shinojima et al., 2004), perhaps because of a less infiltrative behaviour. *Gliosarcoma* constitutes roughly 2% of GBMs and is also recognized as a distinct clinicopathologic entity in the WHO 2007 classification. These tumors are characterized by their well-circumscribed, biphasic tissue pattern with clearly distinguishable areas of glial and mesenchymal differentiation. The glial component of gliosarcoma may display any of the aforementioned cytologic attributes and is typically immunoreactive for GFAP. The mesenchymal component is GFAP-negative and may also carry a wide variety of morphologic appearances, with evidence of differentiation along fibroblastic, cartilaginous, osseous, smooth and striated muscle, and adipose lines (Kleihues et al., 2007). There is a cytogenetic and molecular evidence for a monoclonal origin of both components (Actor et

Exept for the infrequent EGFR amplification, gliosarcomas are genetically similar to primary glioblastomas: they harbor likewise low frequency of TP53 mutations (up to 24%) and similar rates of PTEN deletions (38%) as well as deletions of p16INK4a gene (at the CDKN2A

Comparative genomic hybridization analysis in 20 gliosarcomas by Actor et al. (2002) revealed such common chromosomal imbalances as gains on chromosomes 7 (75%), X (20%), 9q and 20q (15% each) as well as losses on chromosomes 13q (15%), 10 and 9p (35%

(Kleihues et al., 2007).

MDM2 amplification

each).

multinucleated cells (Temme et al., 2010).

1997; Peraud et al., 1999 and Reis et al., 2000.

al., 2002; Paulus et al., 1994; Reis et al., 2000).

locus, 9p21) in roughly 37% (Actor et al., 2002; Reis et al., 2000).

#### **2.3 Correlation between genetic and histopathologic diversity in GBM**

Glioblastomas are morphologically highly heterogeneous and in addition the histological features often vary in different areas of one tumor. Currently three distinct common histopathological variants of GBM are recognized by the actual World Health Organization classification scheme, including conventional glioblastoma, giant cell glioblastoma, and gliosarcoma.

Despite of lack of any histopathological difference, *primary* (de novo) and *secondary* (with an evidence of a lower-grade precursor) *conventional glioblastomas* harbor distinct molecular genetic abnormalities: Primary glioblastomas are characterized by relatively high frequencies of EGFR amplification, PTEN deletion, and CDKN2A (p16) loss, whereas secondary glioblastomas often contain TP53 mutations, especially those involving codons 248 and 273 or G:C->A:T mutations at CpG sites (Ohgaki et al., 2004).

Even within the conventional glioblastoma category, the cellular composition is heterogeneous and may include small or fibrillary, gemistocytic, granular, lipidized and occasional giant cells or oligodendroglial components. According to the predomination of one of these cell types indicating patterns of differentiation, the WHO distinguishes respective subtypes of glioblastoma such as small cell glioblastoma, glioblastoma with granular cell astrocytoma features, glioblastoma with lipidized cells; whereas giant cell glioblastoma is recognized as a distinct clinicopathologic entity (Kleihues et al., 2007; Miller and Perry, 2007).

*Small cell astrocytoma* is an aggressive histologic variant being often misdiagnosed as anaplastic oligodendroglioma because of considerable morphologic similarities. Despite of histological overlap clinicopathologic and genetic features are distinct: there are no small cell astrocytomas harboring 1p/19q codeletions, whereas vIII mutant form of EGFR, EGFR amplification and 10q deletions are present in 50%, 69% and 97% of small cell astrocytomas, respectively (Perry et al., 2004).

Once thought to represent a reactive component, *gemistocytes* have been found to harbor TP53 mutations and cytogenetic abnormalities (chromosome 7p gains and 10q losses); therefore, they are now thought to represent a true neoplastic component (Kros et al., 2000).

In rare cases *granular cells* may predominate and create the impression of a granular cell tumor. Similar to astrocytomas with non-granular cytology, these tumors may also harbor TP53 mutations, high-frequency loss of heterozygosity at 9p, 10q, and 17p, and less frequent loss of heterozygosity at 1p and 19q (Castellano-Sanchez et al., 2003). Brat et al. (2002) reported the largest series of such tumors to date (22 cases, including 4 grade II, 7 grade III, and 11 grade IV tumors) and found that these tumors were more aggressive than nongranular cell astrocytomas of the same grade.

*Glioblastoma with oligodendroglioma component* is an astrocytoma WHO-grade IV containing oligodendroglial areas varying in size and frequency (Kleihues et al., 2007). Despite of oligodendroglial component and in contrast to rather frequent codeletions in WHO grade III anaplastic oligodendroglioma (approximately 85%), deletion of either 1p (24%), 19q (43%), or combined 1p/19q (22%) is relatively infrequent in glioblastoma with oligodendroglioma component (Miller and Perry, 2007).

*Giant cell glioblastoma* is a rare variant that constitutes up to 5% of glioblastoma and is recognized as a distinct clinicopathologic entity in the WHO 2007 classification. Although occasional giant cells may be found in conventional glioblastoma, these cells are a predominating cytologic component in giant cell glioblastoma. As the name implies, the tumor cells are markedly enlarged and bizarre, often appear often multi-nucleated and

Glioblastomas are morphologically highly heterogeneous and in addition the histological features often vary in different areas of one tumor. Currently three distinct common histopathological variants of GBM are recognized by the actual World Health Organization classification scheme, including conventional glioblastoma, giant cell glioblastoma, and

Despite of lack of any histopathological difference, *primary* (de novo) and *secondary* (with an evidence of a lower-grade precursor) *conventional glioblastomas* harbor distinct molecular genetic abnormalities: Primary glioblastomas are characterized by relatively high frequencies of EGFR amplification, PTEN deletion, and CDKN2A (p16) loss, whereas secondary glioblastomas often contain TP53 mutations, especially those involving codons 248 and

Even within the conventional glioblastoma category, the cellular composition is heterogeneous and may include small or fibrillary, gemistocytic, granular, lipidized and occasional giant cells or oligodendroglial components. According to the predomination of one of these cell types indicating patterns of differentiation, the WHO distinguishes respective subtypes of glioblastoma such as small cell glioblastoma, glioblastoma with granular cell astrocytoma features, glioblastoma with lipidized cells; whereas giant cell glioblastoma is recognized as a distinct clinicopathologic entity (Kleihues et al., 2007; Miller

*Small cell astrocytoma* is an aggressive histologic variant being often misdiagnosed as anaplastic oligodendroglioma because of considerable morphologic similarities. Despite of histological overlap clinicopathologic and genetic features are distinct: there are no small cell astrocytomas harboring 1p/19q codeletions, whereas vIII mutant form of EGFR, EGFR amplification and 10q deletions are present in 50%, 69% and 97% of small cell astrocytomas,

Once thought to represent a reactive component, *gemistocytes* have been found to harbor TP53 mutations and cytogenetic abnormalities (chromosome 7p gains and 10q losses); therefore, they are now thought to represent a true neoplastic component (Kros et al., 2000). In rare cases *granular cells* may predominate and create the impression of a granular cell tumor. Similar to astrocytomas with non-granular cytology, these tumors may also harbor TP53 mutations, high-frequency loss of heterozygosity at 9p, 10q, and 17p, and less frequent loss of heterozygosity at 1p and 19q (Castellano-Sanchez et al., 2003). Brat et al. (2002) reported the largest series of such tumors to date (22 cases, including 4 grade II, 7 grade III, and 11 grade IV tumors) and found that these tumors were more aggressive than non-

*Glioblastoma with oligodendroglioma component* is an astrocytoma WHO-grade IV containing oligodendroglial areas varying in size and frequency (Kleihues et al., 2007). Despite of oligodendroglial component and in contrast to rather frequent codeletions in WHO grade III anaplastic oligodendroglioma (approximately 85%), deletion of either 1p (24%), 19q (43%), or combined 1p/19q (22%) is relatively infrequent in glioblastoma with oligodendroglioma

*Giant cell glioblastoma* is a rare variant that constitutes up to 5% of glioblastoma and is recognized as a distinct clinicopathologic entity in the WHO 2007 classification. Although occasional giant cells may be found in conventional glioblastoma, these cells are a predominating cytologic component in giant cell glioblastoma. As the name implies, the tumor cells are markedly enlarged and bizarre, often appear often multi-nucleated and

**2.3 Correlation between genetic and histopathologic diversity in GBM** 

273 or G:C->A:T mutations at CpG sites (Ohgaki et al., 2004).

gliosarcoma.

and Perry, 2007).

respectively (Perry et al., 2004).

granular cell astrocytomas of the same grade.

component (Miller and Perry, 2007).

tumor masses are typically well-circumscribed. It occurs in younger patients (fifth decade) (Kleihues et al., 2007).

The molecular genetic features include relatively high frequencies of TP53 mutations (59% to 90%) and PTEN deletion (up to 33%), whereas EGFR amplification/overexpression and homozygous p16 deletion (p16INK4a gene at the CDKN2A locus, 9p21) are lacking in comparison to conventional glioblastoma (Meyer-Puttlitz et al., 1997; Peraud et al., 1997; Peraud et al. 1999; Temme et al. 2010). Therefore, giant cell glioblastomas contain clinical and molecular genetic features of both primary and secondary glioblastomas. Giant cell glioblastomas have an increased expression of Aurora Kinase B; combined with TP53 mutations this may be responsible in induce cytokinesis defects and the development of multinucleated cells (Temme et al., 2010).


Table 6. Genetic profile of the common histopathological glioblastoma subtypes. Similar tendencies are indicated by grayscale. Modified from Kleihues et al., 2007; Peraud et al., 1997; Peraud et al., 1999 and Reis et al., 2000.

Despite showing a very poor prognosis giant cell glioblastoma appears to carry a slightly better prognosis than conventional glioblastoma (Burger and Vollmer, 1980; Margetts and Kalyan-Raman, 1989; Shinojima et al., 2004), perhaps because of a less infiltrative behaviour. *Gliosarcoma* constitutes roughly 2% of GBMs and is also recognized as a distinct clinicopathologic entity in the WHO 2007 classification. These tumors are characterized by their well-circumscribed, biphasic tissue pattern with clearly distinguishable areas of glial and mesenchymal differentiation. The glial component of gliosarcoma may display any of the aforementioned cytologic attributes and is typically immunoreactive for GFAP. The mesenchymal component is GFAP-negative and may also carry a wide variety of morphologic appearances, with evidence of differentiation along fibroblastic, cartilaginous, osseous, smooth and striated muscle, and adipose lines (Kleihues et al., 2007). There is a cytogenetic and molecular evidence for a monoclonal origin of both components (Actor et al., 2002; Paulus et al., 1994; Reis et al., 2000).

Exept for the infrequent EGFR amplification, gliosarcomas are genetically similar to primary glioblastomas: they harbor likewise low frequency of TP53 mutations (up to 24%) and similar rates of PTEN deletions (38%) as well as deletions of p16INK4a gene (at the CDKN2A locus, 9p21) in roughly 37% (Actor et al., 2002; Reis et al., 2000).

Comparative genomic hybridization analysis in 20 gliosarcomas by Actor et al. (2002) revealed such common chromosomal imbalances as gains on chromosomes 7 (75%), X (20%), 9q and 20q (15% each) as well as losses on chromosomes 13q (15%), 10 and 9p (35% each).

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 113

Analysis of copy number alterations showed an average of 7 amplifications and 6 homozygous deletions per GBM. In addition, an average of 47 mutations was reported

A characteristic feature of GBM is a chromosomal instability (CIN) phenotype distinguished by the loss or gain of complete chromosomes, for example by the gain of chromosome 7 and/or loss of chromosome 10. These chromosome copy number changes can be explained by merotelic spindle attachment that is associated with bipolar but more often with multipolar mitosis. Multipolar spindle pole coalescence in cells with supernumerary centrosomes has been reported as a major source of chromosomal misattachment and chromosome missegregation in colorectal cancer cell lines (Silkworth et al., 2009). Obviously, specific chromosome aberrations may be associated with growth advantage for clonal populations of cancer cells (for example by the loss of tumor suppressor genes). In addition to its well-defined role in signal transduction at the plasma membrane, recent results have identified PTEN as a new guardian of the genome (for review see: Yin and Shen, 2008). Pten-deficient mouse embryo fibroblasts revealed an increased frequency of mitotic centromere-associated chromosomal instability as well as spontaneous DNA doublestrand breaks (Shen et al., 2007). Li Li et al. (2008) developed a mouse model by infecting PTEN-/- neural precursor cells with an EGFRvIII expressing retrovirus and found that EGFRvIII expression and PTEN loss synergistically induced chromosomal instability and

Interestingly, polyploidization of mammalian hepatocytes occurs through failed cytokinesis and is followed by a process that was called reductive mitoses (Duncan et al. 2010). The authors postulate a dynamic model of hepatocyte polyploidization, ploidy reversal and aneuploidy (ploidy conveyor) and propose that this mechanism evolved to generate genetic

Several studies point to a link between centrosome amplification, chromosomal instability and the development of cancer (for review see: D´Assoro et al., 2002). Cells in resected high grade gliomas and cultured glioblastoma cells have been reported to exhibit often centrosome amplifications (Loh et al., 2010) and the centrosomal protein γ-tubulin is overexpressed and shows altered subcellular localization in GBM (Katsetos et al., 2006; Loh et al., 2010). Multipolar mitoses were occasionally observed in time lapse recordings of cultured glioblastoma cells (Hegedüs et al., 2000). Our laboratory used long term life cell imaging to study mitoses in a newly established glioblastoma cell line and found that cytokinesis defects followed by multipolar mitosis may be an important mechanism that is used by glioblastoma cells to reduce ploidy and generate viable daughter cells (our unpublished

To add another level of complexity, many types of cancer cells carry aberrant epigenetic modifications. Changes in epigenetic marks (caused or not caused by genetic alterations) may have an fundamental impact on tumor development and/or tumor progression. Epigenetic markers in human gliomas have been reviewed by Hesson et al. (2008). Two groups have studied in detail DNA methylation profiles in GBM (Etcheverry et al. 2010; Nousmehr et al., 2010). Hypermethylation at a large number of genetic loci occurred in a subgroup (proneural group) of glioblastoma patients and was associated with improved

diversity and permits adaptation of hepatocytes to xenobiotic and nutritional injury.

**2.5 Mechanisms leading to genetic alterations in glioblastoma multiforme** 

(Parsons et al., 2008).

glial tumors.

results).

**2.6 Epigenetics in glioblastoma multiforme** 

outcome (Nousmehr et al., 2010).

#### **2.4 Area-specific genomic Imbalances in glioblastoma multiforme**

Using flow cytometry data analysis Hoshino et al. (1978) reported that different tumor regions of one glioblastoma showed a highly variable distribution of ploidy. By use of a DNA fingerprinting technique Misra et al. (2000) analysed genetic alterations within two or three tumor areas from seven glioblastomas. In all cases except one, different areas of one tumor displayed different fingerprints, indicating a striking extent of intratumoral genetic heterogeneity. Conventional comparative genomic hybridization (CGH) was used to study the intratumoral patterns of genomic imbalance in Glioblastoma multiforme (Harada et al., 1998; Jung et al., 1999). Array comparative genomic hybridization was utilized by Nobusawa et al. (2010) to study in detail tumor area-specific genomic imbalances. Genetic alterations common to all the areas analyzed within a single tumor included gains at chromosomes 1q32.1 (PIK3C2B, MDM4), 4q11-q12 (KIT, PDGFRA), 7p12.1-11.2 (EGFR), 12q13.3-12q14.1 (GLI1, CDK4), and 12q15 (MDM2), and loss of chromosomes at 9p21.1-24.3 (p16INK4a/p14ARF = CDKN2a), 10p15.3-q26.3 (PTEN, etc.), and 13q12.11-q34 (SPRY2, RB1). These alterations are likely to be causative in the pathogenesis of glioblastomas (driver mutations). Additionally, the authors reported numerous tumor area-specific genomic imbalances, which may be either nonfunctional (passenger mutations) or functional, but constitute secondary events reflecting clonal selection and/or progressive genomic instability, a hallmark of glioblastomas. Area specific-evolution of genomic imbalances in GBM may be comparable to the genetic evolution and genomic instability of metastatic pancreas cancer that has been studied in detail recently (Campbell et al., 2010; Yachida et al., 2010).

Loeper et al. (2001) reported that frequent mitotic errors occur in genetically microheterogenous glioblastomas. The authors used fluorescent in situ hybridization (FISH) to study chromosome numbers in a series of 24 glioblastomas. All examined chromosomes showed mitotic instability indicated by numerical aberrations within significant amounts of tumor cells. For chromosomes 10 and 17 only monosomy was observed, whereas chromosome 7 showed trisomy/polysomy. In contrast to other chromosomes displaying monosomy as well as trisomy, copy number changes of chromosomes 7, 10 and 17 seem to be the result of selection in favor of the respective aberration (Loeper et al., 2001). In this context it is interesting to note that neural stem and progenitor cells in the subventricular zone of mouse postnatal brain are frequently aneuploid (Kaushal et al., 2003) and that chromosome segregation defects contribute to aneuploidy in normal neural progenitor cells of the mouse cerebral cortex (Yang et al., 2003). Studies in mice and human demonstrate that chromosomal mosaicism is a prominent feature of neural stem cells, whereas interchromosomal translocations or partial chromosomal deletions or insertions are extremely rare (for review see: Peterson et al., 2008). Glioblastoma stem cells share several properties with neural stem cells, i.e. the growth in floating spheres under serum-free conditions, the expression of the stem cell marker nestin and the differentiation into neural cells like astrocytes or neurons. This similarity in marker expression and behaviour has led to the hypothesis that glioblastoma stem cells may be derived from NSCs (Berger et al., 2004; Sanai et al., 2005).

Recent research makes clear that GBMs do not behave as a whole; local heterogeneity may arise because the tumor regionally adapts to the microenvironment. The influence of microenvironment-induced stimuli may be the force behind clonal selection and acquisition of area specific genomic imbalances in GBM. In addition, regional genomic alterations may be associated with the development of resistance to irradiation and/or chemotherapy, resulting in tumor recurrence and/or progression.

Using flow cytometry data analysis Hoshino et al. (1978) reported that different tumor regions of one glioblastoma showed a highly variable distribution of ploidy. By use of a DNA fingerprinting technique Misra et al. (2000) analysed genetic alterations within two or three tumor areas from seven glioblastomas. In all cases except one, different areas of one tumor displayed different fingerprints, indicating a striking extent of intratumoral genetic heterogeneity. Conventional comparative genomic hybridization (CGH) was used to study the intratumoral patterns of genomic imbalance in Glioblastoma multiforme (Harada et al., 1998; Jung et al., 1999). Array comparative genomic hybridization was utilized by Nobusawa et al. (2010) to study in detail tumor area-specific genomic imbalances. Genetic alterations common to all the areas analyzed within a single tumor included gains at chromosomes 1q32.1 (PIK3C2B, MDM4), 4q11-q12 (KIT, PDGFRA), 7p12.1-11.2 (EGFR), 12q13.3-12q14.1 (GLI1, CDK4), and 12q15 (MDM2), and loss of chromosomes at 9p21.1-24.3 (p16INK4a/p14ARF = CDKN2a), 10p15.3-q26.3 (PTEN, etc.), and 13q12.11-q34 (SPRY2, RB1). These alterations are likely to be causative in the pathogenesis of glioblastomas (driver mutations). Additionally, the authors reported numerous tumor area-specific genomic imbalances, which may be either nonfunctional (passenger mutations) or functional, but constitute secondary events reflecting clonal selection and/or progressive genomic instability, a hallmark of glioblastomas. Area specific-evolution of genomic imbalances in GBM may be comparable to the genetic evolution and genomic instability of metastatic pancreas cancer that has been studied in detail recently (Campbell et al., 2010; Yachida et al.,

Loeper et al. (2001) reported that frequent mitotic errors occur in genetically microheterogenous glioblastomas. The authors used fluorescent in situ hybridization (FISH) to study chromosome numbers in a series of 24 glioblastomas. All examined chromosomes showed mitotic instability indicated by numerical aberrations within significant amounts of tumor cells. For chromosomes 10 and 17 only monosomy was observed, whereas chromosome 7 showed trisomy/polysomy. In contrast to other chromosomes displaying monosomy as well as trisomy, copy number changes of chromosomes 7, 10 and 17 seem to be the result of selection in favor of the respective aberration (Loeper et al., 2001). In this context it is interesting to note that neural stem and progenitor cells in the subventricular zone of mouse postnatal brain are frequently aneuploid (Kaushal et al., 2003) and that chromosome segregation defects contribute to aneuploidy in normal neural progenitor cells of the mouse cerebral cortex (Yang et al., 2003). Studies in mice and human demonstrate that chromosomal mosaicism is a prominent feature of neural stem cells, whereas interchromosomal translocations or partial chromosomal deletions or insertions are extremely rare (for review see: Peterson et al., 2008). Glioblastoma stem cells share several properties with neural stem cells, i.e. the growth in floating spheres under serum-free conditions, the expression of the stem cell marker nestin and the differentiation into neural cells like astrocytes or neurons. This similarity in marker expression and behaviour has led to the hypothesis that glioblastoma stem cells may be derived from NSCs (Berger et al., 2004;

Recent research makes clear that GBMs do not behave as a whole; local heterogeneity may arise because the tumor regionally adapts to the microenvironment. The influence of microenvironment-induced stimuli may be the force behind clonal selection and acquisition of area specific genomic imbalances in GBM. In addition, regional genomic alterations may be associated with the development of resistance to irradiation and/or chemotherapy,

**2.4 Area-specific genomic Imbalances in glioblastoma multiforme** 

2010).

Sanai et al., 2005).

resulting in tumor recurrence and/or progression.

#### **2.5 Mechanisms leading to genetic alterations in glioblastoma multiforme**

Analysis of copy number alterations showed an average of 7 amplifications and 6 homozygous deletions per GBM. In addition, an average of 47 mutations was reported (Parsons et al., 2008).

A characteristic feature of GBM is a chromosomal instability (CIN) phenotype distinguished by the loss or gain of complete chromosomes, for example by the gain of chromosome 7 and/or loss of chromosome 10. These chromosome copy number changes can be explained by merotelic spindle attachment that is associated with bipolar but more often with multipolar mitosis. Multipolar spindle pole coalescence in cells with supernumerary centrosomes has been reported as a major source of chromosomal misattachment and chromosome missegregation in colorectal cancer cell lines (Silkworth et al., 2009). Obviously, specific chromosome aberrations may be associated with growth advantage for clonal populations of cancer cells (for example by the loss of tumor suppressor genes).

In addition to its well-defined role in signal transduction at the plasma membrane, recent results have identified PTEN as a new guardian of the genome (for review see: Yin and Shen, 2008). Pten-deficient mouse embryo fibroblasts revealed an increased frequency of mitotic centromere-associated chromosomal instability as well as spontaneous DNA doublestrand breaks (Shen et al., 2007). Li Li et al. (2008) developed a mouse model by infecting PTEN-/- neural precursor cells with an EGFRvIII expressing retrovirus and found that EGFRvIII expression and PTEN loss synergistically induced chromosomal instability and glial tumors.

Interestingly, polyploidization of mammalian hepatocytes occurs through failed cytokinesis and is followed by a process that was called reductive mitoses (Duncan et al. 2010). The authors postulate a dynamic model of hepatocyte polyploidization, ploidy reversal and aneuploidy (ploidy conveyor) and propose that this mechanism evolved to generate genetic diversity and permits adaptation of hepatocytes to xenobiotic and nutritional injury.

Several studies point to a link between centrosome amplification, chromosomal instability and the development of cancer (for review see: D´Assoro et al., 2002). Cells in resected high grade gliomas and cultured glioblastoma cells have been reported to exhibit often centrosome amplifications (Loh et al., 2010) and the centrosomal protein γ-tubulin is overexpressed and shows altered subcellular localization in GBM (Katsetos et al., 2006; Loh et al., 2010). Multipolar mitoses were occasionally observed in time lapse recordings of cultured glioblastoma cells (Hegedüs et al., 2000). Our laboratory used long term life cell imaging to study mitoses in a newly established glioblastoma cell line and found that cytokinesis defects followed by multipolar mitosis may be an important mechanism that is used by glioblastoma cells to reduce ploidy and generate viable daughter cells (our unpublished results).

#### **2.6 Epigenetics in glioblastoma multiforme**

To add another level of complexity, many types of cancer cells carry aberrant epigenetic modifications. Changes in epigenetic marks (caused or not caused by genetic alterations) may have an fundamental impact on tumor development and/or tumor progression. Epigenetic markers in human gliomas have been reviewed by Hesson et al. (2008). Two groups have studied in detail DNA methylation profiles in GBM (Etcheverry et al. 2010; Nousmehr et al., 2010). Hypermethylation at a large number of genetic loci occurred in a subgroup (proneural group) of glioblastoma patients and was associated with improved outcome (Nousmehr et al., 2010).

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 115

predictive for prolonged time to progression, treatment response, and length of survival. Furthermore, the authors found that in case of discordance the patients with methylated tumors combined with high MGMT mRNA expression did significantly worse than those with low transcriptional activity or unmethylated tumors with low MGMT mRNA expression. Finally Kreth et al. (2011) assume methylation-independent pathways of MGMT expression regulation; however, the exact role of DNA-methyltransferases DNMT1 and DNMT3b that are likely to be involved in methylation of CpG islands of MGMT gene promoter remains unclear. In the Cancer Genome Atlas Research Network (2008) study, GBMs from patients treated with temozolomide and/or lomustine were analysed for mutations. Treatment with alkylating agents resulted in a more than tenfold increase in the number of mutations that was dependent on the methylation status of the MGMT gene. This phenotype seems to be caused by mutations in the MSH6 gene (Cahill et al., 2007; Hunter et al., 2006; Yip et al., 2009) and other genes of the DNA mismatch repair pathway (Cancer Genome Atlas Research Network, 2008). The loss of the mismatch repair protein MSH6 in GBM is associated with tumor progression during temozolomide treatment (Cahill et al., 2007;

The cancer stem cell concept that is of importance for the genesis of many types of cancer receives increasing credit also in the field of GBM. A minor population of GBM cancer stem cells, which may be derived from genetically altered neural stem cells, is presumed to generate transit amplifying cells with high mitotic activity. Because these stem cells appear to have a low mitotic activity, they are difficult to target by radiotherapy and conventional

For recent reviews on glioblastoma stem cells the reader is referred to Huang et al. (2010) and McLendon and Rich (2010). Ignatova et al. (2002) firstly described cells with stem-like properties in human cortical glial tumors. Singh et al. (2003) used the cell surface marker CD133 to isolate a clonogenic population of cells showing stem-like features in medulloblastomas and pilocytic astrocytomas. These cells were declared as tumor stem cells based on their capabilities of self-renewal and multilineage differentiation. Galli et al. (2004) and Yuan et al. (2004) confirmed these findings for glioblastomas. Bao et al. (2006a) selected CD133+ cells from glioblastoma biopsies that were capable of forming tumorspheres in vitro, demonstrated self-renewal and multilineage differentiation and resulted in tumours after transplantation into nude mice. In contrast, CD133- cells did not form tumorspheres in vitro und were not tumorigenic in nude mice. CD133+ cells proved to be a minor population of cells in GBM biopsies. Clinical studies suggested that the percentage of CD133+ cells (Zhang et al., 2008; Zeppernick et al., 2008) or the rate of tumorsphere formation in vitro (Laks et al., 2009; Panosyan et al., 2010) can be used to predict overall survival time of patients. However, it should be noted, that contrary results also exist (Phi et al., 2009; Kim et al., 2011). In recurrent glioblastomas the percentage of CD133+ cells is increased strongly when compared with primary glioblastomas (Pallini et al., 2010). Surprisingly, the increase in expression of CD133 after tumor recurrence was associated significantly with longer survival. Thon et al. (2008) described a correlation between the amount of CD133+ cells within the tumor mass and the WHO grade of glioma (WHO grade II, III and IV). Bao et al. (2006a) demonstrated that CD133+ cells constitutively expressed DNA repair genes at much

higher levels that CD133- cells, mediating resistance to X-irradiation in CD133+ cells.

Hunter et al., 2006; Yip et al., 2009).

chemotherapy.

**2.7 Stem cells in glioblastoma multiforme** 

Epigenetic mechanisms like methylation of DNA have already an impact on chemotheraypy of GBM. Temozolomide (TMZ, Temodal®) is an orally administered alkylating drug that is often used for chemotherapy of GBM. O6-Methylguanine-DNA methyltransferase (MGMT) is a DNA repair enzyme that specifically removes promutagenic alkyl DNA adducts from the O6 position of guanine residues in DNA which are induced by alkylating agents like temozolomide (Goth and Rajewsky, 1974; Margison and Kleihues, 1975). Loss of MGMT expression may be caused by transcriptional silencing through hypermethylation of its CpG islands (Esteller et al., 1999; Qian & Brent, 1997), is frequently (45% to 75%) present in glioblastomas (Bello et al., 2004; Kamiryo et al., 2004; Nakamura et al., 2001) and results in improved survival of glioblastoma patients treated with the alkylating agent temozolomide (Fukushima et al., 2009; Hegi et al, 2005; Hegi et al., 2008). On the other hand not all glioblastoma patients with MGMT promoter methylation respond to alkylating agents and in addition responding GBMs cannot avoid eventual recurrence (Fukushima et al., 2009; Hegi et al., 2008). MGMT promoter methylation appears to occur with a higher frequency in secondary than in primary glioblastoma (Bello et al., 2004; Nakamura et al., 2001) but there is no evidence about its correlation with other histopathologic subtypes.

However, prospective randomized studies of EORTC (European Organisation for Research and Treatment of Cancer) and NCIC (National Cancer Institute of Canada) trial have revealed a significant prolongation of progression free and overall survival for patients with newly diagnosed glioblastoma treated by the concomitant and adjuvant temozolomide and irradiation. By this means median survival has been increased over one year (Stupp et al., 2005, 2009).

The methylation status of the MGMT gene promoter is being used as a biomarker for the potential benefit of the addition of temozolomide to the therapy because its epigenetic silencing has been identified as a strong and independent predictive factor of treatment response for anaplastic glioma patients undergoing chemotherapy with alkylating agents (Hegi et al., 2005; Wick et al., 2009). 3 to 5% of the GBM patients survive for more than 3 years. MGMT hypermethylation was reported to be significantly more frequent in the longterm survivor group (Krex et al., 2007).

The assumption that DNA methylation of CpG island on the MGMT promoter represses consecutively transcriptional activity of the MGMT gene and expression of MGMT protein has been used to explain the correlation between the positive promoter methylation status and favorable treatment response after chemotherapy with temozolomide (Kaina et al., 2007).

However, studies that were performed to validate a relationship between MGMT promoter methylation and protein expression have yielded contradictory results in brain tumors as well as in other neoplasms (Brell et al., 2011). While some studies report a significant correlation between MGMT protein expression analyzed by immunohistochemistry (IHC) and MGMT promoter status measured by methylation-specific polymerase chain reaction (MSP) in glioblastoma and brain metastases of various origin (Ingold et al., 2009; Spiegl-Kreinecker et al., 2009; Tang et al., 2011), other studies failed to detect correlations between both parameters (Brell et al., 2005, 2011; Christmann et al., 2010; Preusser et al., 2008).

In addition, there is increasing evidence that MGMT mRNA expression, unlike MGMT protein expression, could be a better predictor for tumor sensitivity to alkylating agents than MGMT methylation status (Everhard et al., 2009; Kreth et al., 2011). Kreth et al. (2011) provide not only evidence that the degree of MGMT mRNA expression is highly correlated with the MGMT promoter methylation status, but also that low MGMT mRNA expression is strongly

Epigenetic mechanisms like methylation of DNA have already an impact on chemotheraypy of GBM. Temozolomide (TMZ, Temodal®) is an orally administered alkylating drug that is often used for chemotherapy of GBM. O6-Methylguanine-DNA methyltransferase (MGMT) is a DNA repair enzyme that specifically removes promutagenic alkyl DNA adducts from the O6 position of guanine residues in DNA which are induced by alkylating agents like temozolomide (Goth and Rajewsky, 1974; Margison and Kleihues, 1975). Loss of MGMT expression may be caused by transcriptional silencing through hypermethylation of its CpG islands (Esteller et al., 1999; Qian & Brent, 1997), is frequently (45% to 75%) present in glioblastomas (Bello et al., 2004; Kamiryo et al., 2004; Nakamura et al., 2001) and results in improved survival of glioblastoma patients treated with the alkylating agent temozolomide (Fukushima et al., 2009; Hegi et al, 2005; Hegi et al., 2008). On the other hand not all glioblastoma patients with MGMT promoter methylation respond to alkylating agents and in addition responding GBMs cannot avoid eventual recurrence (Fukushima et al., 2009; Hegi et al., 2008). MGMT promoter methylation appears to occur with a higher frequency in secondary than in primary glioblastoma (Bello et al., 2004; Nakamura et al., 2001) but there

However, prospective randomized studies of EORTC (European Organisation for Research and Treatment of Cancer) and NCIC (National Cancer Institute of Canada) trial have revealed a significant prolongation of progression free and overall survival for patients with newly diagnosed glioblastoma treated by the concomitant and adjuvant temozolomide and irradiation. By this means median survival has been increased over one year (Stupp et al.,

The methylation status of the MGMT gene promoter is being used as a biomarker for the potential benefit of the addition of temozolomide to the therapy because its epigenetic silencing has been identified as a strong and independent predictive factor of treatment response for anaplastic glioma patients undergoing chemotherapy with alkylating agents (Hegi et al., 2005; Wick et al., 2009). 3 to 5% of the GBM patients survive for more than 3 years. MGMT hypermethylation was reported to be significantly more frequent in the long-

The assumption that DNA methylation of CpG island on the MGMT promoter represses consecutively transcriptional activity of the MGMT gene and expression of MGMT protein has been used to explain the correlation between the positive promoter methylation status and favorable treatment response after chemotherapy with temozolomide (Kaina et al.,

However, studies that were performed to validate a relationship between MGMT promoter methylation and protein expression have yielded contradictory results in brain tumors as well as in other neoplasms (Brell et al., 2011). While some studies report a significant correlation between MGMT protein expression analyzed by immunohistochemistry (IHC) and MGMT promoter status measured by methylation-specific polymerase chain reaction (MSP) in glioblastoma and brain metastases of various origin (Ingold et al., 2009; Spiegl-Kreinecker et al., 2009; Tang et al., 2011), other studies failed to detect correlations between both parameters (Brell et al., 2005, 2011; Christmann et al., 2010; Preusser et al., 2008).

In addition, there is increasing evidence that MGMT mRNA expression, unlike MGMT protein expression, could be a better predictor for tumor sensitivity to alkylating agents than MGMT methylation status (Everhard et al., 2009; Kreth et al., 2011). Kreth et al. (2011) provide not only evidence that the degree of MGMT mRNA expression is highly correlated with the MGMT promoter methylation status, but also that low MGMT mRNA expression is strongly

is no evidence about its correlation with other histopathologic subtypes.

2005, 2009).

2007).

term survivor group (Krex et al., 2007).

predictive for prolonged time to progression, treatment response, and length of survival. Furthermore, the authors found that in case of discordance the patients with methylated tumors combined with high MGMT mRNA expression did significantly worse than those with low transcriptional activity or unmethylated tumors with low MGMT mRNA expression. Finally Kreth et al. (2011) assume methylation-independent pathways of MGMT expression regulation; however, the exact role of DNA-methyltransferases DNMT1 and DNMT3b that are likely to be involved in methylation of CpG islands of MGMT gene promoter remains unclear. In the Cancer Genome Atlas Research Network (2008) study, GBMs from patients treated with temozolomide and/or lomustine were analysed for mutations. Treatment with alkylating agents resulted in a more than tenfold increase in the number of mutations that was dependent on the methylation status of the MGMT gene. This phenotype seems to be caused by mutations in the MSH6 gene (Cahill et al., 2007; Hunter et al., 2006; Yip et al., 2009) and other genes of the DNA mismatch repair pathway (Cancer Genome Atlas Research Network, 2008). The loss of the mismatch repair protein MSH6 in GBM is associated with tumor progression during temozolomide treatment (Cahill et al., 2007; Hunter et al., 2006; Yip et al., 2009).

#### **2.7 Stem cells in glioblastoma multiforme**

The cancer stem cell concept that is of importance for the genesis of many types of cancer receives increasing credit also in the field of GBM. A minor population of GBM cancer stem cells, which may be derived from genetically altered neural stem cells, is presumed to generate transit amplifying cells with high mitotic activity. Because these stem cells appear to have a low mitotic activity, they are difficult to target by radiotherapy and conventional chemotherapy.

For recent reviews on glioblastoma stem cells the reader is referred to Huang et al. (2010) and McLendon and Rich (2010). Ignatova et al. (2002) firstly described cells with stem-like properties in human cortical glial tumors. Singh et al. (2003) used the cell surface marker CD133 to isolate a clonogenic population of cells showing stem-like features in medulloblastomas and pilocytic astrocytomas. These cells were declared as tumor stem cells based on their capabilities of self-renewal and multilineage differentiation. Galli et al. (2004) and Yuan et al. (2004) confirmed these findings for glioblastomas. Bao et al. (2006a) selected CD133+ cells from glioblastoma biopsies that were capable of forming tumorspheres in vitro, demonstrated self-renewal and multilineage differentiation and resulted in tumours after transplantation into nude mice. In contrast, CD133- cells did not form tumorspheres in vitro und were not tumorigenic in nude mice. CD133+ cells proved to be a minor population of cells in GBM biopsies. Clinical studies suggested that the percentage of CD133+ cells (Zhang et al., 2008; Zeppernick et al., 2008) or the rate of tumorsphere formation in vitro (Laks et al., 2009; Panosyan et al., 2010) can be used to predict overall survival time of patients. However, it should be noted, that contrary results also exist (Phi et al., 2009; Kim et al., 2011). In recurrent glioblastomas the percentage of CD133+ cells is increased strongly when compared with primary glioblastomas (Pallini et al., 2010). Surprisingly, the increase in expression of CD133 after tumor recurrence was associated significantly with longer survival. Thon et al. (2008) described a correlation between the amount of CD133+ cells within the tumor mass and the WHO grade of glioma (WHO grade II, III and IV). Bao et al. (2006a) demonstrated that CD133+ cells constitutively expressed DNA repair genes at much higher levels that CD133- cells, mediating resistance to X-irradiation in CD133+ cells.

Genetic Diversity of Glioblastoma Multiforme: Impact on Future Therapies 117

Potential targets for directed therapy of GBM may include extracellular matrix proteins of the perivascular niche that influence proliferation and/or migration of cancer stem cells. Targeting integrin α6 has recently been shown to inhibit self-renewal, proliferation, and tumor formation capacity of glioblastoma stem cells (Lathia et al., 2010). Cilengitide (Impetreve®) is a cyclic pentapeptide harboring a RGD sequence. RGD sequences present on extracellular matrix proteins mediate the binding to integrins, a class of cell surface receptors. Cilengitide is a selective inhibitor of ανβ3/5 integrins and currently under study as an inhibitor of angiogenesis in several types of solid cancer. Cilengitide monotherapy was well tolerated and exhibited modest antitumor activity among patients with recurrent GBM in a randomized phase II study (Reardon et al., 2008). Also targeting glioma stem cells through the neural cell adhesion molecule L1CAM has been reported to suppress glioma growth (Bao et al., 2008). Glioblastoma cells display complex surface structures with numerous microvilli and filopodia that resist the actions of cytolytic effector lymphocytes (Hoa et al., 2010). It should also be noted that gliomas are accompanied by numerous microglia/macrophages. As was recently reported, inhibition of microglia/macrophage activation may represent a new and effective strategy to suppress proliferation of glioma

Subtypes of breast cancer or leukemia can be efficiently treated by inhibiting the one excessively activated signal transduction pathway that is linked to malignancy. For GBM a monocausal therapy by inhibition of a single overactivated signaling pathway seems to be less promising, because cells or even regions with different genetic defects coexist in one tumor. A personalized therapy based on analysis of the individual genetic defects is not yet

Many types of cancer cells evolve through a multistep process in which genetic aberrations accumulate and finally lead to cells exhibiting aberrant gene expression programs. GBM has been considered as a system/network disease (Fathallah-Shaykh, 2010), because its phenotypes appear to be generated by several interconnected aberrant signal transduction pathways as well as numerous molecular abnormalities, thereby resulting in uncontrolled mitosis and migration of GBM cancer cells. In GBM local heterogeneity arises as the tumor regionally adapts to microenvironmental cues. Future molecular therapies of GBM should target its Achilles' heels: the elimination of the small intratumoral subpopulation of cells that exert stem cell properties and the inhibition of mitosis within the population of transit

Actor, B.; Cobbers, J.M., Buschges, R., Wolter, M., Knobbe, C.B., Lichter, P., Reifenberger, G.

& Weber, R.G. (2002). Comprehensive analysis of genomic alterations in gliosarcoma and its two tissue components. *Genes Chromosomes Cancer,* Vol.34,

amplifying cells, which is responsible for forming the tumor mass.

We thank the Maria-Pesch Stiftung and the Nolting-Stiftung for support.

No.4, (December 2002), pp. 416–427, ISSN 1045-2257

cells (Zhai et al., 2011).

in sight for GBM.

**3. Summary and perspective** 

**4. Acknowledgments** 

**5. References** 

Brain tumor stem cells seem to be localized in a perivascular niche (Bao et al., 2006b; Calabrese et al., 2007; Shen et al., 2008) and low oxygen tension (hypoxia) is associated with its undifferentiated state. In glioblastomas, cancer stem cells express much higher levels of VEGF than non-stem cancer cells and show increased angiogenic potential in vivo (Bao et al., 2006b; Li et al., 2009). Because VEGF expression is under control of transcription factors of the hypoxia inducible factor (HIF) family, one should note that expression of HIF2α is unique to glioma stem cells and correlated with poor patient survival, whereas HIF1α is found in all malignant cells (Li et al., 2009). It has been reported that different human cancers (GBM, colorectal carcinoma, and NSCL carcinoma) converge at the HIF2α oncogenic axis (Franovic et al., 2009). The authors propose that inhibition of HIF2α may be of broad clinical interest in the treatment of cancers with different genetic signatures. Hjelmeland et al. (2010) published recently that acidic stress promotes a glioma stem cell phenotype by induction of HIF2α and other glioma stem cell markers. The authors suggest that an increase in intratumoral pH may be of benefit for targeting the stem cell phenotype.

Three recent papers demonstrate that stem-like cells in GBM are able to differentiate into endothelial cells and may give rise to tumor endothelium (Ricci-Vitiani et al., 2010; Thon et al., 2008; Wang et al., 2010). These results define a novel mechanism for cancer vasculogenesis and may help to explain the failure of currently used inhibitors of angiogenesis. Glioma stem cells as targets for novel strategies of treatment have been recently reviewed (Dietrich et al., 2010; Gilbert & Ross, 2011).

#### **2.8 Promising targets for chemotherapy of glioblastoma multiforme**

GBMs are highly infiltrative tumors that show resistance to conventional chemotherapy. Many chemotherapeutic agents are not able to reach the tumor in sufficient doses, because the blood brain barrier is at least partially intact in these tumors.

Most mitotic inhibitors used in clinic impair the function of mitotic spindles by targeting tubulins that are basic components of microtubules. Because microtubules in non-mitotic cells are also affected, these compounds often exhibit significant side effects (for example neurotoxicity). Future therapies of GBM may involve small molecules that inhibit the activity of aurora kinases A or B, polo kinases or the mitotic kinesin Eg5, all proteins that have specific functions in different phases of mitosis (for review see: Kaestner and Bastians, 2010; Sudakin and Yen, 2007). Pharmaceutical companies are on the way to develop selective inhibitors that target these proteins. Phase I and II studies on different forms of solid cancers are currently underway to study newly developed mitosis inhibitors and may also open the way for a more efficient therapy of GBM. Interestingly, it has been reported that in glioblastoma expression of aurora kinases A (Barton et al., 2010) and B (Zeng et al., 2007) were both associated with poor prognosis and may be targets for therapy. Among several other proteins also histone deacetylases (HDACs) may be promising targets for future therapy of GBM (Argyriou and Kalofonos, 2009). ABC transporters play an important role in the development of multidrug resistance. The role of ABC transporters in the resistance network of glioblastoma was reviewed by Bleau et al. (2009).

The humanized monoclonal antibody against vascular endothelial growth factor (Bevacizumab, Avastin®) has been approved by the FDA for treatment of GBM. Although targeting the tumor vasculature with Bevacizumab reduced the number of cancer-like stem cells in orthotopic brain tumor xenografts (Calabrese et al., 2007), a recent phase II study indicates that bevacizumab does not affect median survival of patients with recurrent GBM (Pope et al, 2011).

Potential targets for directed therapy of GBM may include extracellular matrix proteins of the perivascular niche that influence proliferation and/or migration of cancer stem cells. Targeting integrin α6 has recently been shown to inhibit self-renewal, proliferation, and tumor formation capacity of glioblastoma stem cells (Lathia et al., 2010). Cilengitide (Impetreve®) is a cyclic pentapeptide harboring a RGD sequence. RGD sequences present on extracellular matrix proteins mediate the binding to integrins, a class of cell surface receptors. Cilengitide is a selective inhibitor of ανβ3/5 integrins and currently under study as an inhibitor of angiogenesis in several types of solid cancer. Cilengitide monotherapy was well tolerated and exhibited modest antitumor activity among patients with recurrent GBM in a randomized phase II study (Reardon et al., 2008). Also targeting glioma stem cells through the neural cell adhesion molecule L1CAM has been reported to suppress glioma growth (Bao et al., 2008). Glioblastoma cells display complex surface structures with numerous microvilli and filopodia that resist the actions of cytolytic effector lymphocytes (Hoa et al., 2010). It should also be noted that gliomas are accompanied by numerous microglia/macrophages. As was recently reported, inhibition of microglia/macrophage activation may represent a new and effective strategy to suppress proliferation of glioma cells (Zhai et al., 2011).

Subtypes of breast cancer or leukemia can be efficiently treated by inhibiting the one excessively activated signal transduction pathway that is linked to malignancy. For GBM a monocausal therapy by inhibition of a single overactivated signaling pathway seems to be less promising, because cells or even regions with different genetic defects coexist in one tumor. A personalized therapy based on analysis of the individual genetic defects is not yet in sight for GBM.

#### **3. Summary and perspective**

116 Glioma – Exploring Its Biology and Practical Relevance

Brain tumor stem cells seem to be localized in a perivascular niche (Bao et al., 2006b; Calabrese et al., 2007; Shen et al., 2008) and low oxygen tension (hypoxia) is associated with its undifferentiated state. In glioblastomas, cancer stem cells express much higher levels of VEGF than non-stem cancer cells and show increased angiogenic potential in vivo (Bao et al., 2006b; Li et al., 2009). Because VEGF expression is under control of transcription factors of the hypoxia inducible factor (HIF) family, one should note that expression of HIF2α is unique to glioma stem cells and correlated with poor patient survival, whereas HIF1α is found in all malignant cells (Li et al., 2009). It has been reported that different human cancers (GBM, colorectal carcinoma, and NSCL carcinoma) converge at the HIF2α oncogenic axis (Franovic et al., 2009). The authors propose that inhibition of HIF2α may be of broad clinical interest in the treatment of cancers with different genetic signatures. Hjelmeland et al. (2010) published recently that acidic stress promotes a glioma stem cell phenotype by induction of HIF2α and other glioma stem cell markers. The authors suggest that an increase

Three recent papers demonstrate that stem-like cells in GBM are able to differentiate into endothelial cells and may give rise to tumor endothelium (Ricci-Vitiani et al., 2010; Thon et al., 2008; Wang et al., 2010). These results define a novel mechanism for cancer vasculogenesis and may help to explain the failure of currently used inhibitors of angiogenesis. Glioma stem cells as targets for novel strategies of treatment have been

GBMs are highly infiltrative tumors that show resistance to conventional chemotherapy. Many chemotherapeutic agents are not able to reach the tumor in sufficient doses, because

Most mitotic inhibitors used in clinic impair the function of mitotic spindles by targeting tubulins that are basic components of microtubules. Because microtubules in non-mitotic cells are also affected, these compounds often exhibit significant side effects (for example neurotoxicity). Future therapies of GBM may involve small molecules that inhibit the activity of aurora kinases A or B, polo kinases or the mitotic kinesin Eg5, all proteins that have specific functions in different phases of mitosis (for review see: Kaestner and Bastians, 2010; Sudakin and Yen, 2007). Pharmaceutical companies are on the way to develop selective inhibitors that target these proteins. Phase I and II studies on different forms of solid cancers are currently underway to study newly developed mitosis inhibitors and may also open the way for a more efficient therapy of GBM. Interestingly, it has been reported that in glioblastoma expression of aurora kinases A (Barton et al., 2010) and B (Zeng et al., 2007) were both associated with poor prognosis and may be targets for therapy. Among several other proteins also histone deacetylases (HDACs) may be promising targets for future therapy of GBM (Argyriou and Kalofonos, 2009). ABC transporters play an important role in the development of multidrug resistance. The role of ABC transporters in the

The humanized monoclonal antibody against vascular endothelial growth factor (Bevacizumab, Avastin®) has been approved by the FDA for treatment of GBM. Although targeting the tumor vasculature with Bevacizumab reduced the number of cancer-like stem cells in orthotopic brain tumor xenografts (Calabrese et al., 2007), a recent phase II study indicates that bevacizumab does not affect median survival of patients with recurrent GBM

in intratumoral pH may be of benefit for targeting the stem cell phenotype.

**2.8 Promising targets for chemotherapy of glioblastoma multiforme**

resistance network of glioblastoma was reviewed by Bleau et al. (2009).

(Pope et al, 2011).

recently reviewed (Dietrich et al., 2010; Gilbert & Ross, 2011).

the blood brain barrier is at least partially intact in these tumors.

Many types of cancer cells evolve through a multistep process in which genetic aberrations accumulate and finally lead to cells exhibiting aberrant gene expression programs. GBM has been considered as a system/network disease (Fathallah-Shaykh, 2010), because its phenotypes appear to be generated by several interconnected aberrant signal transduction pathways as well as numerous molecular abnormalities, thereby resulting in uncontrolled mitosis and migration of GBM cancer cells. In GBM local heterogeneity arises as the tumor regionally adapts to microenvironmental cues. Future molecular therapies of GBM should target its Achilles' heels: the elimination of the small intratumoral subpopulation of cells that exert stem cell properties and the inhibition of mitosis within the population of transit amplifying cells, which is responsible for forming the tumor mass.

### **4. Acknowledgments**

We thank the Maria-Pesch Stiftung and the Nolting-Stiftung for support.

#### **5. References**

Actor, B.; Cobbers, J.M., Buschges, R., Wolter, M., Knobbe, C.B., Lichter, P., Reifenberger, G. & Weber, R.G. (2002). Comprehensive analysis of genomic alterations in gliosarcoma and its two tissue components. *Genes Chromosomes Cancer,* Vol.34, No.4, (December 2002), pp. 416–427, ISSN 1045-2257

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**7** 

*Italy* 

**Role of the Centrosomal MARK4** 

Ivana Magnani, Chiara Novielli and Lidia Larizza

Human gliomas are the most frequent tumours of the central nervous system (Kleihues & Cavenee, 2000). They are of neuroectodermal origin and present as different histological

According to the WHO (world health organization) system, astrocytoma, oligodendroglioma and mixed oligoastrocytoma are classified as differentiated gliomas, while anaplastic glioma and glioblastoma show increasing grades of malignancy (Box 1).

Gliomas are composed of different cell types displaying, even within low-grade tumours, a wide spectrum of heterogeneity regarding morphology, genotype, invasive potentiality, and treatment sensitivity (Noble & Dietrich, 2004). The development and progression of glioma malignancies is driven by accumulation of genomic alterations, including both mutations

CIN refers to the rate of lost or gained chromosomes and/or structural chromosome anomalies and ploidy changes during cell divisions (Geigl et al., 2008; Lengauer et al., 1998). Structural chromosome anomalies (translocations, deletions, insertions, inversion and additions) may be balanced or unbalanced and involve one or more chromosomes (Bayani et al., 2007). Chromosomal instability in glioma is mainly characterized by aneuploidy (Bigner et al., 1988; Hecht et al., 1995; Jenkins et al., 1989; Lindstrom et al., 1991; Magnani et al., 1994; Park et al., 1995; Thiel et al., 1992) affecting in particular glioblastoma, the most

**1. Introduction** 

Box 1.

types and malignancy grades (Louis et al., 2007).

and chromosomal instability (CIN).

**2. Chromosomal instability (CIN) in glioma** 

**Protein in Gliomagenesis** 

*Università degli Studi di Milano* 

