**Plasminogen Activator System — Diagnostic, Prognostic and Therapeutic Implications in Breast Cancer**

Catherine Leurer and Shafaat Ahmed Rabbani

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59429

## **1. Introduction**

As tumor metastasis to distant organs (lungs, liver, brain, bone) continues to be the leading cause of cancer associated morbidity and mortality, including breast cancer patients, therapies targeting genes involved in the metastatic cascade are a potentially effective strategy for blocking breast cancer progression and improving survival [1]. Previous 'one size fits all' cancer therapies, which have been used to treat a wide variety of cancers, are inefficient and often cause much unnecessary treatment-related toxicity. Thus, there is a huge unmet need in the research and medical community towards the characterization of cancers into more specific subcategories, which can then be used for prognosis and identifying potential therapies. However, this process requires the use of specific biomarkers to act as signatures for the different subcategories [2,3]. In breast cancer, the most commonly used biomarkers are the estrogen receptor (ER), the progesterone receptor (PR), and the epidermal growth factor 2 (HER2) oncogene [4]. More recently, the plasminogen activator (PA) system and its associated genes are being used as biomarkers to identify potential aggressive cancers, including in breast cancer. The urokinase-type plasminogen activator (uPA) and its inhibitor, the plasminogen activator inhibitor 1 (PAI-1), are proteins of the PA system which are distinguished among cancer biomarkers as being the first to attain level-of-evidence 1 (LOE-1). Thus, assessment of uPA and PAI-1 levels by ELISA assay has been a recommendation of the American Society of Clinical Oncology (ASCO) for assessment of the risk of reoccurrence in breast cancer patients since 2007 [5]. Elevated expression of uPA and its receptor (uPAR) are correlated with poor prognosis and are associated with advanced cancers, including occurrence of metastasis [6]. uPAR is unique as it is rarely expressed in normal quiescent tissue whereas its expression is uniformly high in several tumor tissues, identifying it as a good indicator of malignancy [7].

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These characteristics and many more make the PA system an excellent biomarker for breast cancer diagnosis, and a promising target for future breast cancer therapies.

In this chapter, we will discuss the current state of knowledge and ongoing efforts to establish uPA-uPAR system as a diagnostic, prognostic and therapeutic target in breast cancer.

#### **2. Molecular characterization of breast cancer**

The wide variety of breast cancer-targeting therapies which exists is due in large part to the diversity in the manifestations of breast cancer. When characterizing these cancers into subtypes, in order to identify patterns, morphology remains the cornerstone for diagnosis [4]. However, molecular classification of breast cancers is being used more and more as an additional tool for prognosis and prediction of disease progression. Prognostic factors identify the severity of the disease, forecasting the outcome of the cancer in an untreated individual. Predictive factors are used to identify treatment options, given the characteristics of the cancer, and predict how beneficial a given treatment might be [8]. The most commonly used bio‐ markers for molecular classification of breast cancer are ER, PR, and HER 2, levels of expression of which are routinely determined by immunohistochemistry [4]. In addition to these, the nuclear protein Ki-67 is a good indicator of cell proliferation; higher levels of Ki-67 expression are associated with poor prognosis and identifies a point at which a patient is at an increased risk of developing distant metastases [9]. In order to establish a stronger prognostic test which takes into account breast cancer cell proliferation, the percentage of Ki-67-positive tumor cells has been combined with the HER2, ER, and PR scores to form the "IHC4". This prognostic test is powerful when used for ER-positive breast cancers [10]. In addition to immunohistochemical studies identifying key biomarker proteins, newer assays have been developed which use expression levels of mRNA to characterize breast cancers into different subsets [4,11-15].

#### **3. Skeletal metastasis in breast cancer**

Metastasis accounts for 90% of deaths in cancer patients [16]. In breast cancer specifically, 70% of patients dying of the disease show presence of bone metastases in their post mortem examination [17]. Cancer metastasis is the spread of cancerous cells to distant tissues, where the cells then go on to form colonies independent of the original source. The original source could be the primary tumor, or the circulating tumor cells could have originated from another metastatic tumor [18]. The process of metastasis is not a spontaneous event, but rather a concerted evolution, in which one cell or population of cells undergoes a series of alteration or mutations which render the cells their invasive and metastatic phenotype [19]. Breast cancer metastasis to the skeleton is a non-random metastatic process; the location of distant metastasis is not based on vasculature or blood circulation. Rather, it is known that certain tumors have an increased 'preference' towards metastasis in certain organs as first describe in the "seed and soil hypothesis" by Paget in 1889 [20]. In addition to breast cancer, cancers of the prostate, lungs, kidney, liver, and thyroid, all show predilections towards skeletal metastasis [1,21]. Thus, there is a continuous search to identify genes and proteins which are involved in initiation and progression of skeletal metastasis in breast cancer and which can be targeted to develop innovative therapies. Bisphosphonates are analogs of pyrophosphate, with a carbon atom replacing the central oxygen atom of the pyrophosphate molecule [22]. Bisphosphonates are rapidly deposited on the bone surface, where they are subsequently ingested by osteoclasts as the cells degrade the bone matrix. Once inside the osteoclast, they interfere with the resorption process by inducing a toxic apoptotic effect. Bisphosphonates can also inhibit osteoclast differentiation and maturation [22]. Due to these effects on bone remodeling they are routinely used in patient with osteoporosis. Bisphosphonates have also been shown to be effective in reducing the incidence and number of skeletal metastases in women with breast cancer who were seen as at-risk of developing distant metastases [23]. Phase II clinical trials have shown that the use of bisphosphonate therapy in conjunction with standard anti-cancer therapy is more effective in reducing the number and persistence of disseminated tumor cells than standard therapy alone [24]. There is also evidence which points to antiangiogenic activity of zoledronic acid, a commonly used bisphosphonate, supporting the rationale for its use in breast cancer therapy [25].

Another drug which targets osteoclast activity is Denosumab, an inhibitor of the receptor activator for nuclear factor kappa-b ligand (RANKL). RANKL is a key regulator of bone resorption which is secreted by osteoblasts and binds to the receptor activator for nuclear factor kappa-b (RANK) on osteoclast progenitor cells, thereby stimulating osteoclast activation and maturation [26]. Osteoblasts also secrete osteoprotogerin (OPG), which can bind to RANKL, acting as a soluble decoy receptor and preventing RANKL-induced osteoclast activation. Thus, osteoblasts have the ability to regulate the rate of bone resorption through the control of osteoclast activity [27]. RANKL levels have been found to be elevated in breast cancer cells, which results in excessive bone resorption [1]. It has also been shown that RANKL promotes the migration of RANK-expressing tumor cells to bone [28]. Denosumab is a fully humanized anti-RANKL monoclonal antibody, acting like OPG to block RANKL binding to RANK and thus preventing osteoclast activation and maturation [29]. Denosumab was originally devel‐ oped as a treatment against osteoporosis in postmenopausal women, although it is now approved to treat skeletal related events in cancer patients as well [30]. Integrin αvβ3 is a cell surface receptor found on osteoclasts which stimulates intracellular signaling of the c-Src cascade [31]. Preclinical studies have demonstrated that αvβ3 integrin-inhibiting drugs can successfully blocked tumor growth and osteolysis [32,33]. Members of the integrin family including αvβ3, are significant due to their interaction with the uPA-uPAR system.

#### **4. Proteases and breast cancer**

These characteristics and many more make the PA system an excellent biomarker for breast

In this chapter, we will discuss the current state of knowledge and ongoing efforts to establish uPA-uPAR system as a diagnostic, prognostic and therapeutic target in breast cancer.

The wide variety of breast cancer-targeting therapies which exists is due in large part to the diversity in the manifestations of breast cancer. When characterizing these cancers into subtypes, in order to identify patterns, morphology remains the cornerstone for diagnosis [4]. However, molecular classification of breast cancers is being used more and more as an additional tool for prognosis and prediction of disease progression. Prognostic factors identify the severity of the disease, forecasting the outcome of the cancer in an untreated individual. Predictive factors are used to identify treatment options, given the characteristics of the cancer, and predict how beneficial a given treatment might be [8]. The most commonly used bio‐ markers for molecular classification of breast cancer are ER, PR, and HER 2, levels of expression of which are routinely determined by immunohistochemistry [4]. In addition to these, the nuclear protein Ki-67 is a good indicator of cell proliferation; higher levels of Ki-67 expression are associated with poor prognosis and identifies a point at which a patient is at an increased risk of developing distant metastases [9]. In order to establish a stronger prognostic test which takes into account breast cancer cell proliferation, the percentage of Ki-67-positive tumor cells has been combined with the HER2, ER, and PR scores to form the "IHC4". This prognostic test is powerful when used for ER-positive breast cancers [10]. In addition to immunohistochemical studies identifying key biomarker proteins, newer assays have been developed which use expression levels of mRNA to characterize breast cancers into different subsets [4,11-15].

Metastasis accounts for 90% of deaths in cancer patients [16]. In breast cancer specifically, 70% of patients dying of the disease show presence of bone metastases in their post mortem examination [17]. Cancer metastasis is the spread of cancerous cells to distant tissues, where the cells then go on to form colonies independent of the original source. The original source could be the primary tumor, or the circulating tumor cells could have originated from another metastatic tumor [18]. The process of metastasis is not a spontaneous event, but rather a concerted evolution, in which one cell or population of cells undergoes a series of alteration or mutations which render the cells their invasive and metastatic phenotype [19]. Breast cancer metastasis to the skeleton is a non-random metastatic process; the location of distant metastasis is not based on vasculature or blood circulation. Rather, it is known that certain tumors have an increased 'preference' towards metastasis in certain organs as first describe in the "seed and soil hypothesis" by Paget in 1889 [20]. In addition to breast cancer, cancers of the prostate,

cancer diagnosis, and a promising target for future breast cancer therapies.

**2. Molecular characterization of breast cancer**

140 A Concise Review of Molecular Pathology of Breast Cancer

**3. Skeletal metastasis in breast cancer**

Cancer mortality is usually a result of the metastatic spread of the cancerto distant vital organs, as opposed to growth of the original tumor [34]. As such, it is crucial to understand the progression from the localized to an invasive cancer, and eventually a metastatic cancer. Along with growth factors and cytokines, proteases play a major role in this progression, causing the

degradation of the basement membrane and surrounding extracellular matrix. Proteases play a crucial role in this first step, as they digest the basal lamina components, and allow for cell movement through the extracellular matrix (ECM)[34]. Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases whose primary role is the degradation of ECM proteins, dissolving connective tissue [35]. There are a total of 28 identified MMPs, of which 14 have been implicated in breast cancer development and progression [36]. MMPs are synthe‐ sized by the tumor itself as well as the surrounding peritumoral stromal cells [37]. In the area surrounding a tumor,the major source of MMP activity is the stromal cells, with the tumor cells likely stimulating production of MMPs via the local fibroblasts [38]. In order for the cancer to move beyond its original location and invade into a nearby duct, MMP activity must break down the basement membrane and stromal matrix, facilitating ECM remodeling [34].

The PA system in general and uPAR in particular play a significant due to its ability to localize the proteolytic effects of uPA which can activate latent growth factors and proteases to effect angiogenesis, matrix degradation, adhesion, activation intracellular signalling pathways, tumor cell invasion and metastasis depicted in Figure 1.

**Figure 1. Central role of uPA and uPAR in tumor progression.** uPA is localized to the tumor cells via its binding to domain 1 of uPAR. uPA can activate inactive zymogen plasminogen to plasmin, which can activate matrix metallopro‐ teases (MMPs) and activate or release growth factors. Via its domains 2 and 3, uPAR can interact with integrins (αvβ3, αvβ5) and vitronectin. PAI-1 binding to the uPA-uPAR complex inhibits the activation of plasminogen by uPA, and promoted internalization of the uPA-uPAR-PAI-1 complex and recycling of uPAR back to the cell surface. Collectively, the uPA/uPAR system plays a central role in matrix degradation, angiogenesis, adhesion, intracellular signalling, tu‐ mor invasion and metastasis.

## **5. Plasminogen Activator (PA) system**

degradation of the basement membrane and surrounding extracellular matrix. Proteases play a crucial role in this first step, as they digest the basal lamina components, and allow for cell movement through the extracellular matrix (ECM)[34]. Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases whose primary role is the degradation of ECM proteins, dissolving connective tissue [35]. There are a total of 28 identified MMPs, of which 14 have been implicated in breast cancer development and progression [36]. MMPs are synthe‐ sized by the tumor itself as well as the surrounding peritumoral stromal cells [37]. In the area surrounding a tumor,the major source of MMP activity is the stromal cells, with the tumor cells likely stimulating production of MMPs via the local fibroblasts [38]. In order for the cancer to move beyond its original location and invade into a nearby duct, MMP activity must break

down the basement membrane and stromal matrix, facilitating ECM remodeling [34].

tumor cell invasion and metastasis depicted in Figure 1.

142 A Concise Review of Molecular Pathology of Breast Cancer

mor invasion and metastasis.

The PA system in general and uPAR in particular play a significant due to its ability to localize the proteolytic effects of uPA which can activate latent growth factors and proteases to effect angiogenesis, matrix degradation, adhesion, activation intracellular signalling pathways,

**Figure 1. Central role of uPA and uPAR in tumor progression.** uPA is localized to the tumor cells via its binding to domain 1 of uPAR. uPA can activate inactive zymogen plasminogen to plasmin, which can activate matrix metallopro‐ teases (MMPs) and activate or release growth factors. Via its domains 2 and 3, uPAR can interact with integrins (αvβ3, αvβ5) and vitronectin. PAI-1 binding to the uPA-uPAR complex inhibits the activation of plasminogen by uPA, and promoted internalization of the uPA-uPAR-PAI-1 complex and recycling of uPAR back to the cell surface. Collectively, the uPA/uPAR system plays a central role in matrix degradation, angiogenesis, adhesion, intracellular signalling, tu‐

The plasminogen activator (PA) system is a key regulator of the tumor microenvironment, and is heavily implicated in the metastatic process in breast and other common cancers. It is involved in tumor recruitment of inflammatory cells, tumor cell growth and survival, angio‐ genesis, and tumor invasion and migration [39,40]. The PA system of enzymes comprises two plasminogen activators, tissue type plasminogen activator (tPA) which converts plasminogen to plasmin during clot lysis, and uPA which is used therapeutically as a fibrinolytic agent. tPA is present in normal and some malignant tissues, whereas uPA is more commonly associated with malignancies and plays a major role in pericellular proteolysis during cell migration and tissue remodelling (Figure 1) [41]. Within the PA system three key peptide members: uPA, uPAR and PAI-1 and 2 have now emerged as a viable and effective diagnostic, prognostic and therapeutic target in breast cancer patients [6]. uPA and uPAR expression have been shown to enhance tumor growth and metastasis [42,43]. Expression of uPA and uPAR is also corre‐ lated with poor prognosis, being associated with late stage disease, including metastasis [6]. This section will examine the members of the PA system, discussing their structures and functions, and will describe the important role this system plays in the progression of breast cancer.

#### **5.1. Urokinase-type Plasminogen Activator (uPA) and plasmin**

uPA is a serine protease expressed as a single chain zymogen, pro-uPA, which under‐ goes cleavage to form two-chain high molecular weight uPA (HMW uPA) [44]. After an additional proteolytic step, HMW-uPA is converted into an amino terminal fragment (ATF) containing the receptor-binding growth factor domain (GFD), and a proteolytically-active low molecular weight uPA (LMW-uPA) which retains its plasminogen activator (PA) function [45]. In previous studies, we identified the ATF of uPA as a selective mitogen for cells of the osteoblast phenotype [46-49]. uPA is composed of three domains: a kringle domain, a growth factor-like domain, and a serine protease domain [50]. The serine protease domain of uPA shows high specificity for its substrate, the inactive zymogen plasmino‐ gen, which it cleaves to form the activated protease plasmin; plasmin is responsible for the breakdown of various component of the ECM, exerting uPA's pro-invasive and prometastatic effects [51,52]. Plasmin is also a serine protease, and catalyzes the process of fibrinolysis, in which fibrin and other components of the ECM are degraded to allow for cell invasion, migration, and dissemination [52]. Plasmin promotes further tumor cell invasion through the conversion of pro-MMPs to enzymatically active MMPs. Plasmin can also promote tumor cell proliferation by activating latent growth factors. Thus, plasmin can also activate ECM degradation both directly and indirectly [53]. Interestingly, plasmin promotes a positive feedback loop in the ECM degradation process, as plasmin also cleaves pro-uPA to create HMW-uPA [52]. uPA synthesis and/or release can be induced by a variety of cytokines and growth factors, including EGF, VEGF, and TNF-α [54,55].

There is speculation regarding which enzyme is responsible for the cleaved activation of prouPA into uPA. It is hypothesized that plasmin may be the activator, however, this theory results in ambiguity concerning whether uPA or plasmin is first activated and how [56]. Other enzymes, such as kallikreins, cathepsins, and matriprase, have been shown to be capable of cleaving single chain uPA (scuPA) *in vitro* and are speculated as potential 'first activators' [57]. Interestingly, *in vitro* experiments have shown that binding of pro-uPA to uPAR allows for activation of plasminogen into plasmin, despite pro-uPA not having been converted into it active form. It is thus believed that binding of pro-uPA to uPAR causes a conformational change that confers protease abilities to the single-chain molecule [58]. This is not entirely surprising, as a known role of uPAR is increasing the catalytic efficiency of uPA; in vivo, binding of uPA to uPAR greatly increases the efficiency of plasminogen conversion by as much as 50-fold [59].

Elevated expression levels of uPA in tumor tissue as compared with normal tissue have long been noted [60-62]. In both primary and metastatic tumors, uPA is localized to the invading front, which supports the theory that uPA plays an important role in tumor cell invasion and migration [63]. In breast cancer, increased levels of uPA are correlated with poor relapse-free and overall survival [64]. Increased expression of uPA is seen in patients several common cancers (breast, prostate, lung, colon, thyroid, glioma) where it promotes metastasis and indicates poor prognosis [65-70].

#### **5.2. Plasminogen Activator Inhibitors (PAI)**

The effects of uPA are neutralized by plasminogen activator inhibitors 1 and 2 (PAI-1 and 2), produced by stromal cells surrounding the tumor cells. PAI-1 and PAI-2 are involved in the tight control of proteolysis, causing the uPA-uPAR complex to be internalized [71]. Increased PAI-1 expression is associated with higher metastasis whereas PAI-2 has a protective role [72]. PAI-1 binding maintains the active conformation of the uPA-uPAR-vitronectin (VN) complex, interferes with cell matrix interactions, and acts as a detachment factor to promote tumor metastasis [73]. The uPA-PAI-1-uPAR complex is internalized via clathrin-mediated endocy‐ tosis, with help from the very low-density lipoprotein receptor (VLDLR) related protein LRP. Inside the cell, the uPA-PAI-1 complex dissociated from uPAR, and is trafficked to the lysosome for degradation. The unbound uPAR is then recycled to the cell surface [71,74]. Interest in PAI-1 as a target in malignancy was revealed in studies where an anti-PAI-1 antibody showed anti-invasive effects on melanoma and fibrosarcoma cells [75]. Highthroughput screening led to the identification of small molecule inhibitors of PAI-1 with antiangiogenic and polyp-formation inhibition activities, thereby identifying PAI-1 as a viable novel target for cancer [76,77].

#### **5.3. uPA Receptor (uPAR)**

The role of uPAR within the PA system goes beyond localizing the proteolytic activity of uPA. Rather, uPAR itself plays an important role in tumor progression, interacting with many key signaling molecules, a surprising discovery as uPAR is devoid of a transmem‐ brane domain. Rather, uPAR is a three-domain protein covalently linked to the outer layer of the cell membrane by a glysocylphosphatidylinositol (GPI) anchor [6]. uPAR is impor‐ tant in localizing uPA to the cell surface, which is necessary for uPA's activation of

plasminogen to plasmin [59]. All three domains (D1, D2, D3) are involved in the binding of uPA to uPAR, however only domains D2 and D3 are thought to play a role in uPAR's interactions with other cell surface proteins [6]. uPAR alters cell adhesion and signaling through the interaction with various cell surface proteins, such as integrins (including αvβ3, αvβ, α5β1, and α3β1), G-protein coupled receptors (GPCR), VLDLR, and receptor tyro‐ sine kinases (including epithelial growth factor receptor (EGFR) and platelet-derived growth factor receptor (PDGFR)) [7,78-80]. It is hypothesized that uPAR is part of a larger complex of signaling molecules, called a 'signalosome', which uses signaling effectors such as Src, Akt, and focal adhesion kinase (FAK) [81]. Many of these signaling effectors have been implicated in breast cancer progression, including Src, integrins/FAK, Ras/ERK, and Akt as depicted in Figure 2 [82]. As discussed in a later section, these effectors have become important drug targets for the inhibition of uPA/uPAR-induced breast cancer progres‐ sion. uPAR is rarely expressed in physiologically normal tissue, although its expression can be up regulated during some pathological processes, such as wound healing or inflamma‐ tory response to infection [83,84]. It is involved in normal hemostasis, as plasmin plays an important role in fibrin clot lysis. Under those circumstances, plasmin proteolyzes ECM components either directly or through the activation of MMPs [85,86]. Importantly, uPAR is highly expressed in cancers, and can be expressed by the tumor cells themselves, as well as by tumor-associated cells such as stromal cells, endothelial cells, and infiltrating inflammatory cells [56]. uPAR-expressing tumors generally fall into two categories: those in which both tumor cells and tumor-associated cells express uPA and uPAR, and those in which only the tumor-associated cells express uPAR [56].

results in ambiguity concerning whether uPA or plasmin is first activated and how [56]. Other enzymes, such as kallikreins, cathepsins, and matriprase, have been shown to be capable of cleaving single chain uPA (scuPA) *in vitro* and are speculated as potential 'first activators' [57]. Interestingly, *in vitro* experiments have shown that binding of pro-uPA to uPAR allows for activation of plasminogen into plasmin, despite pro-uPA not having been converted into it active form. It is thus believed that binding of pro-uPA to uPAR causes a conformational change that confers protease abilities to the single-chain molecule [58]. This is not entirely surprising, as a known role of uPAR is increasing the catalytic efficiency of uPA; in vivo, binding of uPA to uPAR greatly increases the efficiency of plasminogen conversion by as much

Elevated expression levels of uPA in tumor tissue as compared with normal tissue have long been noted [60-62]. In both primary and metastatic tumors, uPA is localized to the invading front, which supports the theory that uPA plays an important role in tumor cell invasion and migration [63]. In breast cancer, increased levels of uPA are correlated with poor relapse-free and overall survival [64]. Increased expression of uPA is seen in patients several common cancers (breast, prostate, lung, colon, thyroid, glioma) where it promotes metastasis and

The effects of uPA are neutralized by plasminogen activator inhibitors 1 and 2 (PAI-1 and 2), produced by stromal cells surrounding the tumor cells. PAI-1 and PAI-2 are involved in the tight control of proteolysis, causing the uPA-uPAR complex to be internalized [71]. Increased PAI-1 expression is associated with higher metastasis whereas PAI-2 has a protective role [72]. PAI-1 binding maintains the active conformation of the uPA-uPAR-vitronectin (VN) complex, interferes with cell matrix interactions, and acts as a detachment factor to promote tumor metastasis [73]. The uPA-PAI-1-uPAR complex is internalized via clathrin-mediated endocy‐ tosis, with help from the very low-density lipoprotein receptor (VLDLR) related protein LRP. Inside the cell, the uPA-PAI-1 complex dissociated from uPAR, and is trafficked to the lysosome for degradation. The unbound uPAR is then recycled to the cell surface [71,74]. Interest in PAI-1 as a target in malignancy was revealed in studies where an anti-PAI-1 antibody showed anti-invasive effects on melanoma and fibrosarcoma cells [75]. Highthroughput screening led to the identification of small molecule inhibitors of PAI-1 with antiangiogenic and polyp-formation inhibition activities, thereby identifying PAI-1 as a viable

The role of uPAR within the PA system goes beyond localizing the proteolytic activity of uPA. Rather, uPAR itself plays an important role in tumor progression, interacting with many key signaling molecules, a surprising discovery as uPAR is devoid of a transmem‐ brane domain. Rather, uPAR is a three-domain protein covalently linked to the outer layer of the cell membrane by a glysocylphosphatidylinositol (GPI) anchor [6]. uPAR is impor‐ tant in localizing uPA to the cell surface, which is necessary for uPA's activation of

as 50-fold [59].

indicates poor prognosis [65-70].

novel target for cancer [76,77].

**5.3. uPA Receptor (uPAR)**

**5.2. Plasminogen Activator Inhibitors (PAI)**

144 A Concise Review of Molecular Pathology of Breast Cancer

uPA and uPAR are not expressed homogeneously throughout the tumor, but instead are generally associated with the interface of tumor tissue-benign tissue or tumor and vascular tissue [87]. uPAR is generally expressed on the migrating or invading edge of cancer cells, restricting the region of proteolytic activity and providing directionality. Thus, a path is created through the ECM, in the direction of movement. A chemical gradient is also created for the invading cancer cells to follow, as chemotactic ECM fragments and latent growth factors are released in the path of ECM destruction [88]. The PA system is responsible for not only the migration of tumor cells, but is also implicated in the migration of tumor-associated macro‐ phages. Binding of uPA to uPAR has different effects depending on the state of maturation of the monocytic cells. uPA-uPAR binding stimulates migration in less mature, more monocytelike cells; this is would induce the cells to follow the uPA gradient towards the tumor site. On more mature, more macrophage-like cells, uPA-uPAR binding instead induces adhering; thus, a macrophage which arrives at the tumor site will remain [89,90]. uPA has also been implicated in angiogenesis, initially observed in models of corneal vascularization [91]. uPA proteolytic activity is required for endothelial cell migration, one of the earliest steps in angiogenesis, and is also required for the earliest stages in tube formation [92,93]. Thus, the PA system plays an important role in the progression of breast cancer, promoting proliferation through angiogen‐ esis, and enabling metastasis through the induction of tumor cell invasion and migration.

**Figure 2. Schematic diagram of pathway involved in the uPA/uPAR signalling.** Through its amino terminal fragment (ATF), uPA can bind to domain (D) 1 of its receptor uPAR. Via D2, D3, uPAR can interact vitronectin and members of the integrin family. Through its glycophosphatidyl inositol (GPI) anchor on D3, uPAR is associated to cell membrane. Collectively uPA/uPAR interaction can activate a number of key intracellular signalling pathways to 1) activate latent growth factors, 2) activate proteases, 3) promote tumor cell invasion, adhesion and migration, 4) facilitate matrix deg‐ radation and 5) promote angiogenesis.

## **6. Transcriptional regulation of uPA**

Cancer development and progression to the metastatic stage involve the coordinated activa‐ tion and deactivation of many specific genes. For a long time, cancer was regarded as primarily a genetic disease, with mutation in the DNA sequence being ascribed as the cause for the change in gene expression throughout cancer progression. However, it has now been estab‐ lished that epigenetic changes may also play a key role in the differential gene expression in cancer [94]. The epigenome is dynamic, with some parts of the epigenome being inherited or established during embryonic development, while other aspects are in a state of flux through‐ out life [95,96].

Epigenetic modifications can be made through various methods, including DNA methylation, nucleosome positioning, post-translational modification of histone tails, and non-coding RNA [97]. The protein machinery which is responsible for implementing these modifications consists of methyl-DNA binding proteins (MBDs), DNA methyltransferases (DNMTs), chromatin remodeling complexes, histone modifiers, and proteins which interact with histone modifications [95]. One of the most closely studied aspects of epigenetics is DNA methylation.

We were the first to identify the epigenetic regulation of uPA by examining the correlation between hormone (estrogen) sensitivity and expression of uPA in normal human mammary epithelial cells (HMEC), early stage hormone-responsive breast cancer cells lines (MCF-7 and T-47D), and late stage hormone-insensitive breast cancer cells (MDA-MB-231). uPA expression was only observed in the highly invasive MDA-MB-231 cells. Expression of various members of the PA system is shown in different human breast cancer cell lines in Table 1. Upon examination of the DNA methylation status of the uPA gene via Southern blot analysis using methylation sensitive enzymes, it was observed that CpG islands within the uPA gene are methylated in normal breast cells and early stage breast cancer cells. Conversely, the CpG islands of the uPA gene are hypomethylated in the highly invasive breast cancer cell line. Treatment of early stage MCF-7 cells with 5' azacytidine (5-aza-C), a cytosine DNA methyl‐ transferase inhibitor, caused demethylation of the uPA CpG islands and a dose-dependent expression of uPA mRNA [98]. Thus, this study was the first to demonstrate that expression of uPA in invasive vs. non-invasive breast cancers is regulated by DNA methylation of CpG islands within the gene and that this regulation is reversible. In another study conducted by us, methylation-sensitive PCR was used to quantify the methylation status of the CpG islands in the uPA promoter, comparing non-invasive hormone-sensitive MCF-7 cells to highlyinvasive hormone-insensitive MDA-MB-231 cells. 90% of the CpG islands in the uPA promoter were found to be methylated in the MCF-7 cells, whereas the MDA-MB-231 cells had fully demethylated CpGs. Luciferase reporter assays demonstrated that the Ets-1 transcription factor binding, which regulates uPA promoter activity, was inhibited by methylation [99]. In order to determine the cause of the differences in the methylation status of the uPA promoter between MCF-7 and MDA-MB-231 cells, our group examined the levels of DNA methylation machinery. Both maintenance DNMT (DNMT1) and DNA demethylase (DMase) activities were shown to correlate with the methylation status of the uPA gene. Thus, MCF-7 cells show high DNMT1 activity and low DMase activity, resulting in a methylated uPA promoter, whereas MDA-MB-231 cells show increased DMase activity and reduced DNMT1 activity, resulting in a demethylated uPA promoter. DNA methylation was confirmed as the dominant mechanism in the silencing of the uPA gene, as histone deacetylase inhibitor Trichostatin A induced uPA expression in MDA-MB-231 cells but not in MCF-7 cell [99]. Thus, this study collectively demonstrated that DNA methylation is critical in the regulation of uPA expression in breast cancer cells.

**6. Transcriptional regulation of uPA**

146 A Concise Review of Molecular Pathology of Breast Cancer

radation and 5) promote angiogenesis.

Cancer development and progression to the metastatic stage involve the coordinated activa‐ tion and deactivation of many specific genes. For a long time, cancer was regarded as primarily a genetic disease, with mutation in the DNA sequence being ascribed as the cause for the change in gene expression throughout cancer progression. However, it has now been estab‐ lished that epigenetic changes may also play a key role in the differential gene expression in

**Figure 2. Schematic diagram of pathway involved in the uPA/uPAR signalling.** Through its amino terminal fragment (ATF), uPA can bind to domain (D) 1 of its receptor uPAR. Via D2, D3, uPAR can interact vitronectin and members of the integrin family. Through its glycophosphatidyl inositol (GPI) anchor on D3, uPAR is associated to cell membrane. Collectively uPA/uPAR interaction can activate a number of key intracellular signalling pathways to 1) activate latent growth factors, 2) activate proteases, 3) promote tumor cell invasion, adhesion and migration, 4) facilitate matrix deg‐


Expression of members of the plasminogen activator (PA) system, urokinase-type plasminogen activator (uPA), its receptor (uPAR), PA inhibitor 1 (PAI-1] and 2 (PAI-2] in human breast cancer cell lines (MCF-7, BT-474, ZR-75-1, T-47-D, MDA-MB-231, BT-549, HS-578T). uPA and PAI-1 are only detectable in highly invasive, estrogen (ER), progesterone (PR) receptor and Her-2 negative human breast (MDA-MB-231, BT-549, HS-578T) cancer cell lines.

N/D: None detected

**Table 1.** Expression of members of the plasminogen activator (PA) system in human breast cancer cells.

In a later study, our group set out to test the hypothesis that hypomethylation of the uPA promoter plays a causal role in breast cancer metastasis. In order to test this hypothesis, highly invasive MDA-MB-231 breast cancer cells were treated with different doses of the methyl donor S-adenosyl-methionine (SAM) for six days. SAM has been shown to inhibit hypome‐ thylation, either through the inhibition of active demethylation or through the enhancement of DNMT activity [100]. Treatment with SAM resulted in a marked inhibition of uPA mRNA expression, accompanied by the expected decrease in uPA enzymatic activity [101]. Reduction in uPA production was accompanied by a significant decrease in tumor cell invasive capacity as determined by Matrigel invasion assay. The methylating capacity of SAM in breast cancer cells was confirmed, as the SAM-treated cells showed hypermethylation of the uPA promoter. Subsequent treatment of the SAM-treated cells with demethylating agent 5-aza-C caused a reversal of the observed uPA silencing, demonstrating that the effect of SAM on uPA expres‐ sion is mediated through promoter hypermethylation. In *in vivo* studies carried out in immune deficient mice, animals were injected with MDA-MB-231 cells treated with vehicle or SAM via mammary fat pad. Experimental animals inoculated with MDA-MB-231 cells treated with SAM showed the development tumors which were significantly smaller in volume as com‐ pared to control animals. These anti-tumors effects of SAM were accompanied by a significant decrease in the development of tumor cells metastatic ability, resulting in significantly fewer metastatic foci in lungs, liver, kidney, spleen and kidneys as compared to animals inoculated with control cells (Figure 3). Analyses of tumoral RNA demonstrated that the tumors derived from SAM-treated breast cancer cells expressed no detectable levels of uPA, while uPA mRNA was highly expressed in tumors derived from control breast cancer cells. Thus, this was the first report to describe a potential epigenetic based strategy to block the expression of prometastatic genes like uPA which resulted in decreased tumor growth and metastasis [101].

Expression of members of the plasminogen activator (PA) system, urokinase-type plasminogen activator (uPA), its receptor (uPAR), PA inhibitor 1 (PAI-1] and 2 (PAI-2] in human breast cancer cell lines (MCF-7, BT-474, ZR-75-1, T-47-D, MDA-MB-231, BT-549, HS-578T). uPA and PAI-1 are only detectable in highly invasive, estrogen (ER), progesterone (PR)

In a later study, our group set out to test the hypothesis that hypomethylation of the uPA promoter plays a causal role in breast cancer metastasis. In order to test this hypothesis, highly invasive MDA-MB-231 breast cancer cells were treated with different doses of the methyl donor S-adenosyl-methionine (SAM) for six days. SAM has been shown to inhibit hypome‐ thylation, either through the inhibition of active demethylation or through the enhancement of DNMT activity [100]. Treatment with SAM resulted in a marked inhibition of uPA mRNA expression, accompanied by the expected decrease in uPA enzymatic activity [101]. Reduction in uPA production was accompanied by a significant decrease in tumor cell invasive capacity as determined by Matrigel invasion assay. The methylating capacity of SAM in breast cancer cells was confirmed, as the SAM-treated cells showed hypermethylation of the uPA promoter. Subsequent treatment of the SAM-treated cells with demethylating agent 5-aza-C caused a reversal of the observed uPA silencing, demonstrating that the effect of SAM on uPA expres‐ sion is mediated through promoter hypermethylation. In *in vivo* studies carried out in immune deficient mice, animals were injected with MDA-MB-231 cells treated with vehicle or SAM via mammary fat pad. Experimental animals inoculated with MDA-MB-231 cells treated with SAM showed the development tumors which were significantly smaller in volume as com‐ pared to control animals. These anti-tumors effects of SAM were accompanied by a significant decrease in the development of tumor cells metastatic ability, resulting in significantly fewer

receptor and Her-2 negative human breast (MDA-MB-231, BT-549, HS-578T) cancer cell lines.

**Table 1.** Expression of members of the plasminogen activator (PA) system in human breast cancer cells.

N/D: None detected

148 A Concise Review of Molecular Pathology of Breast Cancer

**Figure 3. Effect of SAM on MDA-MB-231 tumor volume and metastasis. A**: MDA-MB-231 cells treated with vehicle alone as control (CTL) or SAM were introduced into the mammary fat pad of female BALB/c nude mice. Tumor vol‐ umes were determined at weekly interval. **B**: At the end of these studies animals were sacrificed and fluorescent mi‐ croscopic tumor foci in lungs, liver, spleen and kidneys were counted and compared with control group of animals. Significant difference from control is shown by an asterisk (P <0.05). (Adapted from Pakneshan P et al; Ref. 101)

Demethylation results in the activation of tumor suppressor genes, which has led to develop‐ ment of demethylating agent 5-aza-C (Vidaza) for myelodysplastic syndromes, and which is now being tested for its beneficial effects in solid tumors [102,103]. The anti-tumor effects of SAM led us to investigate whether combining 5-aza-C and SAM can have additive or syner‐ getic effects by activating tumor suppressor genes and suppressing pro-metastatic genes. Using several human breast cancer cell lines we have recently shown that SAM inhibits global and gene specific demethylation, prevents potential activation of pro-metastatic genes like uPA and MMPs, and potentiates the activation of tumor suppressor genes by 5-aza-C. These results have led us to propose epigenetic based demethylation (5-aza-C) and methylation (SAM) based therapies at different stage of tumor progression [104].

While a large number of these studies were carried out in breast cancer, DNA methylation has also been shown to regulate uPA and PAI-1 expression in prostate cancer, laryngeal squamous cell carcinoma, meningioma, and gastric cancer, where these genes are also identified as epigenetic based prognostic and therapeutic targets [105,106]. However, large scale clinical studies still remain to be carried out to demonstrate the impact of uPA-PAI-1 methylation in cancer. These epigenetic based therapies can also influence the effects of radiotherapy and chemotherapeutic agents to alter metastatic behaviour [107,108].

### **7. Diagnostic approaches**

The field of cancer research has moved away from the development of broad drug classes which aim to target all cancers, and is instead moving towards personalized medicine. The current goal is to subdivide patients into groups based on molecular characteristics, which then allows therapy options to be assessed and administered based on the molecular charac‐ teristics within that particular group [109]. The proteins uPA and PAI-1 are now clinically used biomarkers which are unique among cancer biomarkers because of the lack of contradictory evidence which exists. This is especially surprising, given the variety of demographics which are covered by uPA/PAI-1 diagnostic studies [110]. Notably, uPA and PAI-1 have achieved the highest LOE-1 score attainable according the Tumor Marker Utility Grading System. uPA/ PAI-1 are the only breast cancer biomarkers to reach LOE-1 [111].

In 1985, the first comprehensive report examining uPA expression in breast cancer was published. O'Grady *et al.* measured uPA proteolytic activity in both benign tumors and primary breast cancer tissue. Although no measurement was made of actual uPA antigen levels, the study demonstrated significantly elevated levels of uPA enzymatic activity in malignant tumors as compared with benign tumors [112]. In 1988, Duffy *et al.* added further to this area of research, showing that elevated levels of uPA proteolytic activity in primary cancer tissue was correlated with shorter disease-free intervals [113]. Later on, Jänicke *et al.* were first to examine actual proteins levels of uPA in breast cancer tissue, and in 1989 published a study which used the immunoenzymometric test ELISA, showing significant correlation between elevated expression of the uPA antigen in primary tumor tissues and poor prognosis of breast cancer patients [114]. Later on, the same group found a similar correlation existing for the uPA inhibitor PAI-1 [115]. In 2007, uPA and PAI-1 were added to the Breast Cancer Treatment Guidelines of the ASCO as novel cancer biomarkers. They are now used to help determine appropriate adjuvant systemic therapies in primary breast cancers [116].

Today, ELISA remains the gold-standard for assessment of uPA/PAI-1 correlation with breast cancer outcomes. It is the only system examining uPA/PAI-1 in which clinically relevant, validated data have been obtained. When conducting ELISA analysis, either detergentreleased tumor-tissue fractions or tumor-tissue cytosolic fractions can be used [117]. Analysis can be conducted on core needle biopsies, primary tumor biopsies, and cryostat sections [118]. Therefore, a major advantage of the use of ELISA tests is the requirement for only very small tissue extract samples [119]. Currently, there is a commercially available ELISA-based assay called FEMTELLE® which is used to assess the probability of breast cancer reoccurrence in newly diagnosed women with node-negative breast cancer. FEMTELLE classifies women into categories of high or low risk of reoccurrence, based on the quantitatively-determined levels of uPA and PAI-1 found in tumor-tissue extracts [52].

While a large number of these studies were carried out in breast cancer, DNA methylation has also been shown to regulate uPA and PAI-1 expression in prostate cancer, laryngeal squamous cell carcinoma, meningioma, and gastric cancer, where these genes are also identified as epigenetic based prognostic and therapeutic targets [105,106]. However, large scale clinical studies still remain to be carried out to demonstrate the impact of uPA-PAI-1 methylation in cancer. These epigenetic based therapies can also influence the effects of radiotherapy and

The field of cancer research has moved away from the development of broad drug classes which aim to target all cancers, and is instead moving towards personalized medicine. The current goal is to subdivide patients into groups based on molecular characteristics, which then allows therapy options to be assessed and administered based on the molecular charac‐ teristics within that particular group [109]. The proteins uPA and PAI-1 are now clinically used biomarkers which are unique among cancer biomarkers because of the lack of contradictory evidence which exists. This is especially surprising, given the variety of demographics which are covered by uPA/PAI-1 diagnostic studies [110]. Notably, uPA and PAI-1 have achieved the highest LOE-1 score attainable according the Tumor Marker Utility Grading System. uPA/

In 1985, the first comprehensive report examining uPA expression in breast cancer was published. O'Grady *et al.* measured uPA proteolytic activity in both benign tumors and primary breast cancer tissue. Although no measurement was made of actual uPA antigen levels, the study demonstrated significantly elevated levels of uPA enzymatic activity in malignant tumors as compared with benign tumors [112]. In 1988, Duffy *et al.* added further to this area of research, showing that elevated levels of uPA proteolytic activity in primary cancer tissue was correlated with shorter disease-free intervals [113]. Later on, Jänicke *et al.* were first to examine actual proteins levels of uPA in breast cancer tissue, and in 1989 published a study which used the immunoenzymometric test ELISA, showing significant correlation between elevated expression of the uPA antigen in primary tumor tissues and poor prognosis of breast cancer patients [114]. Later on, the same group found a similar correlation existing for the uPA inhibitor PAI-1 [115]. In 2007, uPA and PAI-1 were added to the Breast Cancer Treatment Guidelines of the ASCO as novel cancer biomarkers. They are now used to help

determine appropriate adjuvant systemic therapies in primary breast cancers [116].

Today, ELISA remains the gold-standard for assessment of uPA/PAI-1 correlation with breast cancer outcomes. It is the only system examining uPA/PAI-1 in which clinically relevant, validated data have been obtained. When conducting ELISA analysis, either detergentreleased tumor-tissue fractions or tumor-tissue cytosolic fractions can be used [117]. Analysis can be conducted on core needle biopsies, primary tumor biopsies, and cryostat sections [118]. Therefore, a major advantage of the use of ELISA tests is the requirement for only very small tissue extract samples [119]. Currently, there is a commercially available ELISA-based assay

chemotherapeutic agents to alter metastatic behaviour [107,108].

PAI-1 are the only breast cancer biomarkers to reach LOE-1 [111].

**7. Diagnostic approaches**

150 A Concise Review of Molecular Pathology of Breast Cancer

A major disadvantage of FEMTELLE, and other ELISA-based assays, is the requirement of fresh or fresh-frozen tissue samples [109]. Thus, other methods of uPA/PAI-1 quantification are under investigation for validation. Immunohistochemistry allows the use of fixed, archived, paraffin-embedded tissue samples for analysis. A roadblock in the development of this assay is that uPA and PAI-1 are present in both tumor and stromal cells, as well as being released into the tissue. Thus, it is extremely difficult to develop a reliable scoring system for uPA/PAI-1 in immunohistochemical analysis. Nevertheless, in 1990 Jänicke *et al.* published a comparison of uPA levels obtained using immunohistochemical scoring and ELISA. The study showed a statistically significant increase in staining intensity for uPA in immunohistochem‐ istry which correlated with an increase in ELISA uPA values [120]. Reilly *et al.* later published the same correlation for PAI-1 [121]. Thus, much work is being done to develop immunohis‐ tochemistry as a validated, clinically relevant method of quantifying uPA/PAI-1 expression in breast cancer samples. It is important to note that significant correlation is yet to be established between plasma levels of uPA/PAI-1 with tissue expression of these proteins. Thus, expression of uPA/PAI-1 must be measured directly in the breast cancer tissue sample, and cannot be extrapolated from any plasma measurements [122].

Rather than measuring protein expression levels of uPA and PAI-1 in breast cancer tissue, much research is also invested in the assessment of uPA and PAI-1 biomarker expression at the transcriptional level. The highly sensitive quantitative reverse transcription-polymerase chain reaction (RT-PCR) does not require fresh or fresh-frozen tissue samples, as it can use formalin-fixed tissue specimens and only requires minute amount of mRNA for assessment [123]. Significant correlation between transcript and protein levels for uPA and PAI-1 have been found in breast cancer cell lines [123]. Unfortunately, no correlation was found when examining breast cancer tissue specimens. Spyratos *et al.* found no significant correlation when examining uPA expression, and found only a weak correlation in the case of PAI-1 [124]. Conversely, Lamy *et al.* was able to show high concordance between uPA/PAI-1 antigen expression, as assessed by ELISA, and mRNA expression as assessed by the novel technique nuclei acid sequence-based amplification (NASBA) [125]. However, the results of this study require future validation.

The final area of study which examines the correlation between uPA/PAI-1 expression and breast cancer prognosis is the examination of DNA methylation. As this is a DNA-based assessment, this form of analysis can be easily carried out in formalin-fixed, paraffin-embed‐ ded samples, using PCR-based or DNA array technology [109]. As described above, our lab demonstrated the correlation between uPA promoter methylation status in breast cancer [98]. In this study uPA promoter was methylated in normal mammary epithelial cells and in low invasive breast cancer cell lines. In contrast the uPA promoter was demethylated resulting in high levels of uPA expression. Using surgical biopsy specimens, uPA promoter demethylation was associated with advanced disease stage (Figure 4). This effect was independent of the hormone receptor status and results from this study demonstrated the determination of uPA promoter methylation can be developed as a reliable and early marker for uPA expression in breast cancer patents [126]. A similar correlation has also been demonstrated for the PAI-1 promoter [105]. Using surgical biopsy specimens from breast cancer patients, we demonstrated a correlation between uPA promoter methylation status and disease stage correlating with uPA mRNA expression which can serve as an early and reliable diagnostic and prognostic marker for breast cancer [126].

**Figure 4. Reverse correlation between percentage of methylation of the urokinase promoter (uPA) and uPA mRNA expression in breast cancer**. Percentage of methylation of the uPA promoter (A) and the uPA mRNA expression (B) in the biopsy samples of breast cancer patients were analyzed and graphed. Results are the mean ± SE of at least three independent analyses. Significant difference from grade 1 is shown by an asterisk, and significant difference from both grade 1 and 2 is shown by two asterisks (P <0.05). (Adapted from Pakneshan P et al; Ref. 126)

#### **8. uPAR as an imaging target in breast cancer**

Continued development of novel targeted therapies and the effective use of current ap‐ proaches for breast cancer are still not yielding optimum benefit due to poor strategies to monitor therapeutic efficacy. While diagnostic imaging is extensively used to stage cancers and assess therapy effectiveness, development of highly sensitive non-invasive imaging agents which can identify aggressive lesions while also identifying residual disease will prove to be highly beneficial. High levels of uPAR in cancer lesions as compared to adjacent tissue and normal hemostatic tissues provide a unique opportunity to target uPAR as an imaging target in several common malignancies [127-129]. These unique characteristics allowed the develop‐ ment of non-invasive approaches to detect invasive cancers and detect the presence of occult tumor metastases [130-132]. Our group was first to identify uPAR as an imaging target in cancer and towards these goals we used our well established syngeneic model of breast cancer, which led to the validation of uPAR as a viable target to detect the presence and progression of cancer [133]. In a series of studies, a species specific (rat) antibody directed against the rat (r)-uPAR was developed and characterized by immunofluorescence and Western blot analysis. Following 125I-labelling of the antibody, the binding of r-uPAR-IgG was confirmed in rat prostate cancer cells (Dunning R3227 Mat Ly Lu) and breast cancer cells (Mat B-III) overex‐ pressing (r)-uPAR (Mat B-III-uPAR). In *in vivo* studies, 125I-rat (r)-PAR-IgG was injected on to rat breast and prostate cancer tumor-bearing animals. Uptake of this radiolabel was seen in primary tumors and in liver, spleen, lungs, and lymph nodes, which are common sites of tumor metastasis in these models. Minimal levels of radioactivity were seen in these organs in normal animals and tumor-bearing animals injected with 125I-labeled pre-immune IgG. This study not only further confirmed uPAR as a therapeutic target but also validated it as an imaging target to monitor tumor progression and metastasis.

hormone receptor status and results from this study demonstrated the determination of uPA promoter methylation can be developed as a reliable and early marker for uPA expression in breast cancer patents [126]. A similar correlation has also been demonstrated for the PAI-1 promoter [105]. Using surgical biopsy specimens from breast cancer patients, we demonstrated a correlation between uPA promoter methylation status and disease stage correlating with uPA mRNA expression which can serve as an early and reliable diagnostic and prognostic

**Figure 4. Reverse correlation between percentage of methylation of the urokinase promoter (uPA) and uPA mRNA expression in breast cancer**. Percentage of methylation of the uPA promoter (A) and the uPA mRNA expression (B) in the biopsy samples of breast cancer patients were analyzed and graphed. Results are the mean ± SE of at least three independent analyses. Significant difference from grade 1 is shown by an asterisk, and significant difference from both

Continued development of novel targeted therapies and the effective use of current ap‐ proaches for breast cancer are still not yielding optimum benefit due to poor strategies to monitor therapeutic efficacy. While diagnostic imaging is extensively used to stage cancers and assess therapy effectiveness, development of highly sensitive non-invasive imaging agents which can identify aggressive lesions while also identifying residual disease will prove to be highly beneficial. High levels of uPAR in cancer lesions as compared to adjacent tissue and normal hemostatic tissues provide a unique opportunity to target uPAR as an imaging target in several common malignancies [127-129]. These unique characteristics allowed the develop‐ ment of non-invasive approaches to detect invasive cancers and detect the presence of occult tumor metastases [130-132]. Our group was first to identify uPAR as an imaging target in cancer and towards these goals we used our well established syngeneic model of breast cancer, which led to the validation of uPAR as a viable target to detect the presence and progression of cancer [133]. In a series of studies, a species specific (rat) antibody directed against the rat (r)-uPAR was developed and characterized by immunofluorescence and Western blot analysis. Following 125I-labelling of the antibody, the binding of r-uPAR-IgG was confirmed in rat

grade 1 and 2 is shown by two asterisks (P <0.05). (Adapted from Pakneshan P et al; Ref. 126)

**8. uPAR as an imaging target in breast cancer**

marker for breast cancer [126].

152 A Concise Review of Molecular Pathology of Breast Cancer

Following our report, a number of groups have actively pursued these goals; uPAR is now established as an excellent imaging target in cancer. Studies in this regard include the use of dual labelled nanoparticles conjugated to the ATF of uPA, which allowed the accumulation of dye in a xenograft model of pancreatic cancer [134]. Following its internalization, the use of nanoparticles was shown to increase dye retention in the primary tumor and metastatic sites.

The organic compound, 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (also known as DOTA) has medical application including its use as an imaging agent. DOTA was conjugated to the lead uPAR-targeted peptide (AE-105) and labelled with 64Cu [135-137]. It was successfully shown to monitor the levels of uPAR-expressing tumor cells using positron emission tomography (PET) in a human glioma xenograft model. In this study, solidbased synthesis was carried out via Fmoc approach, followed by the elution and concentra‐ tion of chelator used for labelling. The labelled reagent was characterized in a series of *in vitro* studies to determine its uptake followed by dynamic ET imaging in tumor-bearing mice. Use of gallium (Ga) based tracers and PET imaging with targeting peptide was shown to be highly effective due to its high radiochemical yield, purity, stability, cellular uptake and good tumor to background ratio using non-invasive PET-based imaging which will be highly useful in a clinical setting [135]. These investigators followed up by combining their findings with a therapeutic approach as well where AE105 was first labelled with 64Cu and 177Lu for its uses in PET-based imaging as well as radionuclide therapy in a xenograft model of colorectal cancer [136].

Various imaging modalities like plane film X-ray, bone scan, ultrasound, computed tomogra‐ phy (CT), magnetic resonance imaging (MRI), and PET are used alone or in combination. PET is a non-invasive imaging technique that offers substantial advantages over anatomic imaging modalities in oncology. Additionally, PET can often distinguish between benign and malig‐ nant lesions. Given that highly expressed receptors like uPAR or enzymes can be linked to prognosis in many cases, targeted imaging with highly specific probes may provide prognostic information concerning the level of differentiation of breast cancer, both at primary and metastatic sites.

Over the past few years, there has been a significant growth in the development of radiolabeled monoclonal antibodies (mAbs), which bind with high affinity to receptors frequently highly overexpressed on diverse human cancer cells, for diagnostic and therapeutic applications [138,139]. Characterization of the structure of ATN-658 and its demonstrated efficacy in several xenograft models has led to the initiation of clinical trials using ATN-658 as a therapeutic agent [140]. Availability of this selective anti-uPAR antibody provides us with the opportunity to evaluate it as an imaging agent using multiple radiolabels which can be effectively used to develop PET tracers.

Collectively, evidence continues to accumulate in multiple models, validating uPAR as a viable imaging target for future translational studies for the use of uPAR imaging agents in patients with various malignancies, where overexpression of uPA-uPAR system plays a major role in tumor progression.

## **9. Targeting the PA system in breast cancer**

Since first identifying the PA system as an important player in breast cancer progression and metastasis, there have been many attempts made to target this system specifically. Early development focused on the inhibition of plasminogen activation, looking to inhibit uPA enzymatic activity. This could be accomplished either through the use of small molecules to block the active site of uPA, or by attempting to block the binding of uPA or scuPA to uPAR. Blocking the binding of uPA to uPAR proved to be a more challenging method, as uPAR's binding pocket is much larger than the enzymatic active site of uPA [56]. Many studies have been published which show early attempts at blocking proteolytic activation of plasminogen by uPA.

A common approach was to use small-molecule inhibitors of uPA to block its enzymatic activity, thereby reducing proliferation, invasion, and metastasis. Using this strategy we showed the use of one such uPA inhibitor (B-428) for its ability to block tumor metastases in a xenograft model of prostate cancer. Infusion of B-428 into syngeneic rats inoculated with rat (r) prostate cancer cells Mat LyLu which overexpressed r-uPA resulted in a significantly decreased tumor volume and smaller metastatic foci, as compared with control tumor bearing animals receiving vehicle alone [141]. Other serine protease inhibitors have also been used, and have even been advanced into clinical trials. Promising results have recently been reported with regard to a Phase Ib clinical trial using serine protease inhibitor WX-UK1 for treatment of breast cancer, as well as other solid tumors [142]. A similar agent, known as WX-671 (MESUPRON®), which is a pro-drug of WX-UK1 has also completed a Phase Ib trial for treatment of patients with head and neck cancer [143]. MESUPRON has now moved on to two Phase II clinical trials, currently underway, in which it is being given patients with advanced breast or pancreatic cancer. In both trials, patients are receiving MESUPRON alongside a traditional chemotherapy drug, Capecitabine and Gemcitabine for breast and pancreatic cancer, respectively [5].

Other methods which have been used to successfully block plasminogen activation through inhibition of the uPA system include peptide inhibitors of the uPA-uPAR interaction and anti uPA-uPAR antibodies [144,145]. A non-competitive antagonist of the uPA-uPAR interaction corresponding to the amino acid 136-143 was identified and this peptide (A6) was shown to inhibit endothelial cell migration and breast cancels invasion *in vitro* [146]. Treatment of breast cancer cells MDA-MB-231 tumor-bearing mice resulted in significant inhibition of tumor volume and metastasis (Figure 5). These experimental tumors also showed decreased factor VIII-positive tumor micro vessel hot-spots, establishing the anti-angiogenic effects of A6. In studies carried out by Mishima *et al.* the antitumor and anti angiogenic effects of A6 were shown alone and in combination with chemotherapeutic agent Cisplatin in a glioblastoma model which led to the clinical evaluation of A6 [147,148]. Use of antibody based therapies has been established during the last decade, resulting in highly beneficial therapeutic approaches for various cancers [149]. The use of antibodies to block uPA-induced metastasis has met with some success, as described below. Using a polyclonal anti-rat uPAR antibody we targeted the ligand binding NH2-terminal domain of rat uPAR we showed its ability to block breast cancer growth and metastasis *in vivo* [133]. More recently, we evaluated the potential of a highly selective monoclonal antibody against human uPAR (ATN-658). First we examined the efficacy of ATN-658 in blocking prostate cancer growth, invasion, migration, and skeletal metastasis. Examination of the effects of ATN-658 administration *in vitro* using human prostate cancer PC-3 cells showed its ability to cause a decrease in tumor cell invasion and migration by interference with downstream signaling molecules involved in mediating the effects of uPAR (Figure 6). In *in vivo* studies ATN-658 administration caused a significant decrease in tumor volume and number of skeletal metastatic foci [150]. Using ATN-658, Larengyl *et al.* showed its ability to block ovarian cancer metastasis by inducing apoptosis and u-PAR-α5 integrin interaction [151]. Recently, we have examined the effect of ATN-658 alone and in combination with the bisphosphonate Zometa on skeletal metastasis associated with breast cancer. ATN-658 had a significant effect on reducing the number and area of skeletal lesions as determined by X-ray, however these effects were more pronounced when ATN-658 and Zometa were administered in combination (Rabbani *et al*., unpublished observations).

evaluate it as an imaging agent using multiple radiolabels which can be effectively used to

Collectively, evidence continues to accumulate in multiple models, validating uPAR as a viable imaging target for future translational studies for the use of uPAR imaging agents in patients with various malignancies, where overexpression of uPA-uPAR system plays a major role in

Since first identifying the PA system as an important player in breast cancer progression and metastasis, there have been many attempts made to target this system specifically. Early development focused on the inhibition of plasminogen activation, looking to inhibit uPA enzymatic activity. This could be accomplished either through the use of small molecules to block the active site of uPA, or by attempting to block the binding of uPA or scuPA to uPAR. Blocking the binding of uPA to uPAR proved to be a more challenging method, as uPAR's binding pocket is much larger than the enzymatic active site of uPA [56]. Many studies have been published which show early attempts at blocking proteolytic activation of plasminogen

A common approach was to use small-molecule inhibitors of uPA to block its enzymatic activity, thereby reducing proliferation, invasion, and metastasis. Using this strategy we showed the use of one such uPA inhibitor (B-428) for its ability to block tumor metastases in a xenograft model of prostate cancer. Infusion of B-428 into syngeneic rats inoculated with rat (r) prostate cancer cells Mat LyLu which overexpressed r-uPA resulted in a significantly decreased tumor volume and smaller metastatic foci, as compared with control tumor bearing animals receiving vehicle alone [141]. Other serine protease inhibitors have also been used, and have even been advanced into clinical trials. Promising results have recently been reported with regard to a Phase Ib clinical trial using serine protease inhibitor WX-UK1 for treatment of breast cancer, as well as other solid tumors [142]. A similar agent, known as WX-671 (MESUPRON®), which is a pro-drug of WX-UK1 has also completed a Phase Ib trial for treatment of patients with head and neck cancer [143]. MESUPRON has now moved on to two Phase II clinical trials, currently underway, in which it is being given patients with advanced breast or pancreatic cancer. In both trials, patients are receiving MESUPRON alongside a traditional chemotherapy drug, Capecitabine and Gemcitabine for breast and pancreatic

Other methods which have been used to successfully block plasminogen activation through inhibition of the uPA system include peptide inhibitors of the uPA-uPAR interaction and anti uPA-uPAR antibodies [144,145]. A non-competitive antagonist of the uPA-uPAR interaction corresponding to the amino acid 136-143 was identified and this peptide (A6) was shown to inhibit endothelial cell migration and breast cancels invasion *in vitro* [146]. Treatment of breast cancer cells MDA-MB-231 tumor-bearing mice resulted in significant inhibition of tumor volume and metastasis (Figure 5). These experimental tumors also showed decreased factor

develop PET tracers.

154 A Concise Review of Molecular Pathology of Breast Cancer

tumor progression.

by uPA.

cancer, respectively [5].

**9. Targeting the PA system in breast cancer**

**Figure 5. Effect of Å6 on tumor growth and metastases. A:** MDA-MB-231-GFP tumor-bearing BALB/c (nu/nu) mice were injected i.p. with Å6 or vehicle alone (CTL) and tumor volume was determined at weekly intervals. **B**: At the end of this study, control and experimental mice were sacrificed to count the number of macroscopic and microscopic fluo‐ rescent tumor foci in different organs. Significant difference from control tumor-bearing animals after treatment with Å6 is denoted by asterisks (P<0.05). (Adapted from Guo Y et al; Ref. 146)

Additional efforts towards therapeutic targeting of the PA system in breast cancer have focused on either decreasing uPA/uPAR/PAI-1 expression, or have focused on using uPA/

**Figure 6. Effect of ATN-658 on tumor cells invasion in vitro and intracellular signaling pathways** *in vivo***. A:** Human prostate cancer cells PC-3 cell invasive capacity was evaluated after treating with control IgG or ATN-658 using a Boy‐ den chamber Matrigel invasion assay. Number of cells invading is shown as bar diagram ± SEM. B: Male Fox chase SCID mice were inoculated with PC-3 cells through the intra tibial route of injection. Animals were treated with 10.0 mg/kg of control IgG (CTL) or ATN-658. At the end of these studies, animals were sacrificed, and tibias were removed, formalin-fixed, and subjected to immunohistochemical analysis to determine the effect on various intracellular signal‐ ing pathways. (Adapted from Rabbani SA et al; Ref. 150)

uPAR as homing mechanisms for cytotoxic drugs. Techniques which aim to reduce or block the expression of uPA/uPAR/PAI-1 include the use of antisense oligonucleotides, interference (RNAi), ribozymes, or DNAzymes [55,152-155]. Experiments using these techniques have shown significant effects on uPAR signaling and tumor behaviour. Anti-uPAR antisense oligonucleotides have been used to inhibit cancer cell proliferation and invasion *in vitro* using melanoma cells, while *in vivo* experiments also showed inhibition of tumor growth and metastasis [156]. Down regulation of uPA and uPAR expression using RNAi has also shown promise, and *in vitro* experiments using human glioma cells showed inhibition of pro-cancer signaling molecules, such as RAS-and MEK-mediated signaling, and resulted in activation of apoptosis [157]. As mentioned above, Pakneshan *et al.* have shown that treatment of highly invasive breast cancer MDA-MB-231 cells with SAM results in decreased expression of uPA, as well as decreased tumor proliferation, invasion, and metastasis [101]. While the exact mechanism through which SAM exerts its methylating actions is still being debated, SAM is a methyl donor and thus may increase the number of methyl groups available for the meth‐ yltransferase reaction [94]. SAM has also been shown to inhibit DNA demethylase activity, including MBD2 [100]. Thus, uPA/uPAR expression can be targeted at the transcriptional or at the translational level as well.

Not only is the PA system an excellent therapeutic target because of its pro-metastatic effects, but it is also an exciting group of proteins because of the specificity through which it is highly expressed in tumor cells and the surrounding stroma. This allows for therapeutic targeting of cytotoxic drugs to the tumor compartment through the use of uPA-derived or other uPARbinding peptides. One example is the conjugation of the growth factor domain (GFD) of uPA to the chelator DOTA and 213-Bi, an α-emitter. With the GFD portion binding to uPAR, this combination has been shown to be cytotoxic to uPAR-expressing ovarian cancer cells *in vitro* [158]. It is also possible to use the amino terminal fragment (ATF) of uPA to deliver drugs to the tumor compartment. ATF binds uPAR with an affinity similar to that of the full sized uPA peptide, resulting in extremely effective delivery of the ATF-conjugated therapeutic payload. Many ATF-toxin fusions have been made, including a ATF-pseudomonas exotoxin (PE), which has been shown to be effective against a number of cancerous cell lines, and ATF-diphtheria toxin (DTAT), which has shown efficacy both *in vitro* and *in vivo* [159-161].

Another recent area of exploration is the use of nanobins, a novel liposomal nanoparticle drug encapsulation and formulation system. Nanobins take advantage of the 'enhanced permea‐ bility and retention effect' (EPR effect), in which molecules of certain sizes tend to accumulate in tumor tissue more so than in normal tissue [162]. Although nanobins were already designed to target the tumor environment, relying either entirely on the EPR effect or in conjunction with the use of a pH-responsive cross-linked polymer shell, it is also possible to conjugate nanobin technology with uPA/uPAR-targeting techniques. O'Halloran *et al.* describe their current efforts to combine the monoclonal anti-uPA antibody ATN-291 with nanobins, creating a product which can be internalized into tumor and tumor-associated cells for greater therapeutic strength. ATN-291 binds to the kringle domain of uPA and is able to bind uPA which is already bound to uPAR. Interestingly, the internalization of the ATN-291-uPA-uPAR complex is not dependent on the presence of PAI-1. The efficacy of this system is currently being evaluated in several xenograft models, with hopes of advancing this technology into clinical development sometime in the near future [6].

One caveat when studying any uPA/uPAR-targeted therapy is the high degree of species specificity of uPA and uPAR, such that human uPA has an extremely low binding capacity towards murine uPAR, and vice versa. This is especially relevant to the use of xenograft models, in which therapies which target human uPA/uPAR will only have an effect on tumor cells, and not on the surrounding stromal cells [56]. One result of this issue is that the efficacy of potential uPA/uPAR-targeted therapies may be underestimated in xenograft models. The second implication is that the toxicity profiles of these drugs may also be underestimated in xenograft models. However, toxicity concerns can be somewhat put to rest, as analysis of cadaveric human tissue has demonstrated very little tissue expression of uPAR [7].

uPAR as homing mechanisms for cytotoxic drugs. Techniques which aim to reduce or block the expression of uPA/uPAR/PAI-1 include the use of antisense oligonucleotides, interference (RNAi), ribozymes, or DNAzymes [55,152-155]. Experiments using these techniques have shown significant effects on uPAR signaling and tumor behaviour. Anti-uPAR antisense oligonucleotides have been used to inhibit cancer cell proliferation and invasion *in vitro* using melanoma cells, while *in vivo* experiments also showed inhibition of tumor growth and metastasis [156]. Down regulation of uPA and uPAR expression using RNAi has also shown promise, and *in vitro* experiments using human glioma cells showed inhibition of pro-cancer signaling molecules, such as RAS-and MEK-mediated signaling, and resulted in activation of apoptosis [157]. As mentioned above, Pakneshan *et al.* have shown that treatment of highly invasive breast cancer MDA-MB-231 cells with SAM results in decreased expression of uPA, as well as decreased tumor proliferation, invasion, and metastasis [101]. While the exact mechanism through which SAM exerts its methylating actions is still being debated, SAM is a methyl donor and thus may increase the number of methyl groups available for the meth‐ yltransferase reaction [94]. SAM has also been shown to inhibit DNA demethylase activity, including MBD2 [100]. Thus, uPA/uPAR expression can be targeted at the transcriptional or

**Figure 6. Effect of ATN-658 on tumor cells invasion in vitro and intracellular signaling pathways** *in vivo***. A:** Human prostate cancer cells PC-3 cell invasive capacity was evaluated after treating with control IgG or ATN-658 using a Boy‐ den chamber Matrigel invasion assay. Number of cells invading is shown as bar diagram ± SEM. B: Male Fox chase SCID mice were inoculated with PC-3 cells through the intra tibial route of injection. Animals were treated with 10.0 mg/kg of control IgG (CTL) or ATN-658. At the end of these studies, animals were sacrificed, and tibias were removed, formalin-fixed, and subjected to immunohistochemical analysis to determine the effect on various intracellular signal‐

at the translational level as well.

ing pathways. (Adapted from Rabbani SA et al; Ref. 150)

156 A Concise Review of Molecular Pathology of Breast Cancer

Like uPA, several studies have been carried out targeting the PAI-1 as an anti-cancer therapy. Elevated levels of PAI-1 are a predictor of aggressive cancers, although that fact seems contradictory, given that PAI-1 is an inhibitor of uPA activity. However, it is now believed that PAI-1 may possess functions independent of uPA inhibition [163]. For example, expres‐ sion of PAI-1 is necessary for cancer-induced angiogenesis in preclinical models [164]. In addition, PAI-1 is associated with insensitivity to chemotherapy treatment, while PAI-1 deficiency causes increased chemotherapy sensitivity [165]. A way of targeting these actions is to inactivate PAI-1, forcing the conversion of PAI-1 into its latent form. This can be done using the small peptide paionin-4-D1D2 or small-molecule inhibitor PAI-039 [166,167]. Another method under examination is the interference of the interaction between PAI-1 and vitronectin, an interaction which has been shown to cause detachment of tumor cells from the ECM, promoting the metastatic process [168]. RNA-aptamers SM-20 and WT-15 are effective in inhibiting this interaction without affecting the uPA-inhibiting activity of PAI-1 [155, 169].

Thus, the PA system represents a promising area of research for the development of targeted anti-cancer therapies. There are a wide variety of methods being examined, targeting any of the three key players within the PA system, and using several molecular, chemical, and immunological approaches which have already shown highly promising results, paving the way for their clinical evaluation.

## **10. Summary and future goals**

Within the last 20 years, the PA system has been established as an important regulator of breast cancer progress, being directly involved in proliferation, invasion, and migration of tumor cells. As such, it has become a key target for clinical use in diagnostics, imaging, and thera‐ peutics. Over the next few years, there will likely be many more important developments in this field of study. The exact nature of the signalosome relationship is still being elucidated, and several studies are underway to identify which proteins are directly bound to uPAR and are involved in its intracellular signaling. Although ELISA is currently being used as the goldstandard in measuring uPA/uPAR for diagnostic purposes, much work is being done to establish immunohistochemical protocols, so that fresh or fresh-frozen tissue samples are no longer required. Much research is being conducted to evaluate the potential regulation of uPA/ uPAR/PAI-1 expression via epigenetics as well as antisense oligonucleotides and RNAi. In addition, technologies which use uPA and uPAR to target cytotoxic drug to the tumor compartment are only now in their earliest stages of development, thus, there are many avenues to explore in that area of research. Collectively, results from these studies will drive the clinical development of several PA targeted diagnostic and therapeutic agents which are either already in clinical trials are expected to enter in the near future. There is great optimism in these studies using targeted approaches which will lead to reduced morbidity and mortality in several common malignancies, including breast cancer.

## **Acknowledgements**

This work was supported by a grant MOP 130410 from the Canadian Institutes for Health Research to SAR.

## **Author details**

deficiency causes increased chemotherapy sensitivity [165]. A way of targeting these actions is to inactivate PAI-1, forcing the conversion of PAI-1 into its latent form. This can be done using the small peptide paionin-4-D1D2 or small-molecule inhibitor PAI-039 [166,167]. Another method under examination is the interference of the interaction between PAI-1 and vitronectin, an interaction which has been shown to cause detachment of tumor cells from the ECM, promoting the metastatic process [168]. RNA-aptamers SM-20 and WT-15 are effective in inhibiting this interaction without affecting the uPA-inhibiting activity of PAI-1 [155, 169].

Thus, the PA system represents a promising area of research for the development of targeted anti-cancer therapies. There are a wide variety of methods being examined, targeting any of the three key players within the PA system, and using several molecular, chemical, and immunological approaches which have already shown highly promising results, paving the

Within the last 20 years, the PA system has been established as an important regulator of breast cancer progress, being directly involved in proliferation, invasion, and migration of tumor cells. As such, it has become a key target for clinical use in diagnostics, imaging, and thera‐ peutics. Over the next few years, there will likely be many more important developments in this field of study. The exact nature of the signalosome relationship is still being elucidated, and several studies are underway to identify which proteins are directly bound to uPAR and are involved in its intracellular signaling. Although ELISA is currently being used as the goldstandard in measuring uPA/uPAR for diagnostic purposes, much work is being done to establish immunohistochemical protocols, so that fresh or fresh-frozen tissue samples are no longer required. Much research is being conducted to evaluate the potential regulation of uPA/ uPAR/PAI-1 expression via epigenetics as well as antisense oligonucleotides and RNAi. In addition, technologies which use uPA and uPAR to target cytotoxic drug to the tumor compartment are only now in their earliest stages of development, thus, there are many avenues to explore in that area of research. Collectively, results from these studies will drive the clinical development of several PA targeted diagnostic and therapeutic agents which are either already in clinical trials are expected to enter in the near future. There is great optimism in these studies using targeted approaches which will lead to reduced morbidity and mortality

This work was supported by a grant MOP 130410 from the Canadian Institutes for Health

way for their clinical evaluation.

**10. Summary and future goals**

158 A Concise Review of Molecular Pathology of Breast Cancer

in several common malignancies, including breast cancer.

**Acknowledgements**

Research to SAR.

Catherine Leurer and Shafaat Ahmed Rabbani\*

\*Address all correspondence to: shafaat.rabbani@mcgill.ca

Department of Medicine, McGill University Health Center, Canada

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## **Bioinformatics in Breast Cancer Research**

Beyzanur Yigitoglu, Eyyup Uctepe, Ramazan Yigitoglu, Esra Gunduz and Mehmet Gunduz

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59519

## **1. Introduction**

Developments both in computer hardware and software allowed for storing, distributing, and analyzing data obtained from biological experimentation, the very definition of bioinformatics. From this standpoint, bioinformatics can be narrowly defined as a field at the crossroads of biology and computer engineering, responsible for the storage, distribution, and analysis of biological information.[1] The term of bioinformatics relatively refers to the formation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems posed by or inspired from the management and analysis of biological data.[2,3]

Since its emergence as an independent discipline in the 1980s, bioinformatics has been rapidly developing, keeping up with the expansion of genome sequence data. Whereas it is safe to say that 20 years ago, publishing computationally-derived results was a challenge and experi‐ mental observations were considered the only way of making progress[1]; after the famous Clinton-Blair handshake for the completion of the human genome in April 2003 [4], headlines such as ''the laboratory rat is giving way to the computer mouse'' arose.[5] The importance of bioinformatics methods has further increased following the technological improvement of large-scale gene expression analysis using DNA microarrays and proteomics experiments. Wet experiments and the use of bioinformatics analyses go hand in hand in today's biological and clinical research.[6] Undeniably, it is almost inconceivable that a high-impact research publication in biology does not contain some elements of computing.[1]

To date, the genome, transcriptome and proteome are investigated with large-scale and highthroughput techniques to suggest treatment and predict outcomes. With the availability of high-throughput sequencing in hypothesis driven science, various sequence-based techniques

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

are originated, namely expressed sequence tags (ESTs)[7], serial analysis of gene expression (SAGE)[8], massively parallel signature sequencing (MPSS)[9], the 'HapMap' project proceed‐ ing by means of individual SNPs (single nucleotide polymorphisms) to link specific genotypes to diseases.[10,11] Aside from sequencing techniques, microarray technology is one of the high-throughput techniques, possibly the most promising one. As for protein analysis techniques, tissue arrays[12] and proteomics can be named.

On the one hand, microarrays are microscope slides or chips with immobilized probes, usually cDNA (complementary DNA), BAC (bacterial artificial chromosome), or oligo probes.[13] There are very large numbers of spots on an array, each containing a huge number of identical DNA molecules. Two important applications of microarray technology are gene expression monitoring and Single Nucleotide Polymorphisms (SNP) detection.[14] This technique is widely applicable because less RNA is used to analyze thousands of genes. Despite its increasing use around the world, microarray analysis has some limitations if used as a single method for exploring tumor biology. An obvious weakness is that a microarray represents a single snapshot of the patient.[15] But there are a large number of elements leading to disturbed gene function[16], such as large and small deletions or single base substitutions, mutations that affect promoter regions or splice-sites, as well as epigenetic silencing. Those factors may influence the result but may go undetected as well, depending on the exact type of lesion as well as its location with respect to the area hybridizing with the probe.[17] Furthermore, differentially expressed genes do not necessarily translate into varying protein levels with functional implications; so, it does not always show a correlation between the expression of a gene and the amount of translated protein.[18] Also, compared to RT-PCR (reverse transcrip‐ tion polymerase chain reaction), microarray signals are less sensitive, accurate and not able to resolve smaller differences in gene expression.[19] In addition to its comparative simplicity, microarray technology requires better understanding of the limitations and careful attention to experimental design and data analysis for meaningful results.

Bioinformatics applications are used in analysis of entire gene expression profiles to approach the disease at genome level and pose new hypotheses regarding certain mechanisms including but not limited to signaling pathways governing the process of formation, maintenance and expansion of tumor.[20] Bioinformatics analyses can also be applied to miRNA, DNA copynumber, SNPs, sequence, and methylation data[21] along with the field of medical sciences to know the pathways for diagnosing which genomic changes could give rise to each known inherited disease, i.e., identification of the gene causing disease, and also genetic therapies that can reverse disease phenotype.[14] Different Browser and Databases has been developed to analyze and process this huge quantity of data (Table 1.0 and Table 2.0).

Kept in mind that the discovery of complete protein classes is still in progress, e.g., the kinases of the human genome[22], the classification of proteins with related structure and function[23] will preserve its significance in the molecular dissection of human health and disease. In the future, bioinformatics is expected to continue its fascinating interplay with the field of genomics in cancer research, that is cancer bioinformatics and oncogenomics.[24]

## **2. Bioinformatics in various cancers**

are originated, namely expressed sequence tags (ESTs)[7], serial analysis of gene expression (SAGE)[8], massively parallel signature sequencing (MPSS)[9], the 'HapMap' project proceed‐ ing by means of individual SNPs (single nucleotide polymorphisms) to link specific genotypes to diseases.[10,11] Aside from sequencing techniques, microarray technology is one of the high-throughput techniques, possibly the most promising one. As for protein analysis

On the one hand, microarrays are microscope slides or chips with immobilized probes, usually cDNA (complementary DNA), BAC (bacterial artificial chromosome), or oligo probes.[13] There are very large numbers of spots on an array, each containing a huge number of identical DNA molecules. Two important applications of microarray technology are gene expression monitoring and Single Nucleotide Polymorphisms (SNP) detection.[14] This technique is widely applicable because less RNA is used to analyze thousands of genes. Despite its increasing use around the world, microarray analysis has some limitations if used as a single method for exploring tumor biology. An obvious weakness is that a microarray represents a single snapshot of the patient.[15] But there are a large number of elements leading to disturbed gene function[16], such as large and small deletions or single base substitutions, mutations that affect promoter regions or splice-sites, as well as epigenetic silencing. Those factors may influence the result but may go undetected as well, depending on the exact type of lesion as well as its location with respect to the area hybridizing with the probe.[17] Furthermore, differentially expressed genes do not necessarily translate into varying protein levels with functional implications; so, it does not always show a correlation between the expression of a gene and the amount of translated protein.[18] Also, compared to RT-PCR (reverse transcrip‐ tion polymerase chain reaction), microarray signals are less sensitive, accurate and not able to resolve smaller differences in gene expression.[19] In addition to its comparative simplicity, microarray technology requires better understanding of the limitations and careful attention

Bioinformatics applications are used in analysis of entire gene expression profiles to approach the disease at genome level and pose new hypotheses regarding certain mechanisms including but not limited to signaling pathways governing the process of formation, maintenance and expansion of tumor.[20] Bioinformatics analyses can also be applied to miRNA, DNA copynumber, SNPs, sequence, and methylation data[21] along with the field of medical sciences to know the pathways for diagnosing which genomic changes could give rise to each known inherited disease, i.e., identification of the gene causing disease, and also genetic therapies that can reverse disease phenotype.[14] Different Browser and Databases has been developed to

Kept in mind that the discovery of complete protein classes is still in progress, e.g., the kinases of the human genome[22], the classification of proteins with related structure and function[23] will preserve its significance in the molecular dissection of human health and disease. In the future, bioinformatics is expected to continue its fascinating interplay with the field of

techniques, tissue arrays[12] and proteomics can be named.

176 A Concise Review of Molecular Pathology of Breast Cancer

to experimental design and data analysis for meaningful results.

analyze and process this huge quantity of data (Table 1.0 and Table 2.0).

genomics in cancer research, that is cancer bioinformatics and oncogenomics.[24]

Cancer is one of the prevalent diseases that bring about death worldwide. Given that Scientists have sequenced the human genome[25], now it is time to use these genomic data, and the highthroughput technology developed to generate them, to tackle major health problems such as cancer.[24] Cancer molecular mechanisms are more successfully examined considering the genes and proteins interaction and network. Bioinformatics tools are vital for acquiring a more holistic view of cancer and analyzing the intricate data, speeding up the research process including biomarker discovery. Moreover, cancer clinical bioinformatics is critical to reach systems clinical medicine by combining clinical measurements and signs with human cancer tissue-generated bioinformatics, understanding clinical symptoms and signs, disease devel‐ opment and progress, and therapeutic strategy.[26,27,28]

The leading cause of cancer death is lung cancer but still awaits reliable molecular markers. Kim et al.[29] used multiple clinical samples and combined the bioinformatics analysis of the public gene expression data with clinical validation to identify biomarker genes for non–smallcell lung cancer, which shows poor prognosis and recurrence. They meta-analyzed the SAGE and EST data and chose 20 genes for experimental validation through semiquantitative RT-PCR. Then, applied quantitative RT-PCR to 7 genes (CBLC, CYP24A1, ALDH3A1, AKR1B10, S100P, PLUNC, and LOC147166) identified as potential diagnostic markers, leading to 2 highly probable novel biomarkers (CBLC and CYP24A1).

Liver cancer is the most common type, subsequent to lung cancer, responsible for cancerrelated deaths. Sawey et al.[30] performed a forward genetic screen, using a mouse hepatoblast model and RNAi, guided by human hepatocellular carcinoma amplification data. They found that the amplification led to the selective sensitivity to FGF19 inhibition. Hence, FGF19 is an equally important driver gene of 11q13.3 amplicon as CCND1 in liver cancer, which means 11q13.3 amplification could be an effective biomarker for patients predicted to respond to anti-FGF19 therapy.

In a recent study[31], an individualized bioinformatics analysis strategy was applied to previously-established transcriptome data for clear cell renal cell carcinoma (ccRCC) to identify and reposition 8 FDA-approved drugs with negative correlation and P-value <0.05 for anticancer therapy. Authors demonstrated that pentamidine is effective against RCC cells in culture, and slows tumor growth in a RCC xenograft mouse model so it might be a new therapeutic agent to be combined with current standard-of-care regimens for patients with metastatic RCC.

With regard to leukemia, diagnosis and subclassification is mostly based on the application of various techniques like cytomorphology, cytogenetics, fluorescence in situ hybridization, multiparameter flow cytometry, and PCR-based methods which are time-consuming and costintensive, also require expertise in central reference laboratories. Therefore, microarray analysis represents a novel promising method to be used as a diagnostic tool.[14] A key determinant in the prognosis of chronic lymphocytic leukemia (CLL) is the mutational status of the immunoglobulin heavy chain variable region (IGHV) genes.[32] For the correct delin‐ eation of the mutational status, the patient's leukemic cells and closest germline counterpart should be compared. Unfortunately, public web-based databases are commonly used instead of the patient's germline DNA sequence from non-leukemic cells. Several of these reference databases involve VBASE, GenBank/IgBLAST and the international ImMunoGeneTics information systems that employ different software types, amount of natural IGHV polymor‐ phism and criteria used to map the complementarity determining regions and framework regions. As a result, the correct interpretation of the IGHV mutational status in CLL may be affected.[33]

Because of the heterogeneity of many tumors, it is a very challenging work to identify good molecular targets. For instance, resistant subclones of overexpressed and mutated genes may prevent them from being good molecular targets. Therefore, best target is a 'red dot' gene whose mutation occurs early in oncogenesis and dysregulates a key pathway that drives tumor growth in all of the subclones. Examples include mutations in the genes ABL, HER-2, KIT, EGFR and probably BRAF, in chronic myelogenous leukemia, breast cancer, gastrointestinal stromal tumors, non-small-cell lung cancer and melanoma, respectively. For efficacious therapeutics; identification of red-dot targets, development of drugs that inhibit the red-dot targets, and diagnostic classification of the related pathways are a must.[34]

## **3. Bioinformatics and breast cancer**

Breast cancer occurs in both men and women, yet male breast cancer is less common. Although a cure for each stage of breast cancer has not yet been found, identifying the genetic mutations that cause the disease can play an important role and this is said by scientists to be like looking for needles in a haystack, and after finding the needles or coding regions, they must find disease-related sequences within them.[3,6] Bioinformatics sets the stage for searching 3 billion base pairs to detect genetic defects.

Allinen et al. described the comprehensive gene expression profiles of each cell type composing normal breast tissue and in situ and invasive breast carcinomas performing SAGE (serial analysis of gene expression) and utilizing cell-type specific cell surface markers and magnetic beads for the rapid sequential isolation. Their results suggest that considerable transcriptional alterations happen in all cell populations while genetic changes were detected only in epithelial cells among myoepithelial, endothelial and stromal cells, myofibroblasts and lymphocytes.[35] To continue with another study, based upon a systematic Sanger sequencing analysis of 13,023 genes in 11 human breast cancers, individual tumors accumulate an average of approximately 90 point mutations in gene coding regions, but only a tiny number of these were recurrent and were in significant genes of breast cancer, including p53 and PIK3CA. A much larger number of the genes do not necessarily contribute to the carcinogenesis.[36] Considering the genomic landscape of breast cancer, these more common mutations resemble "mountains" while the vast majority of genes reflect "hills" that are infrequently mutated. We need to elucidate mechanisms involved in the disease to understand the heterogeneity of human cancers and utilize personal genomics for tumor diagnosis and new therapeutic strategies.[37]

As widely accepted, early detection of breast cancer has an enormous impact on patient's survival. Seeing that genome-wide expression patterns of tumors mirror the biology of the tumors, relating gene expression patterns to clinical outcomes sheds light on the biological diversity of the tumors.[38] In the discovery of genes and pathways that are specifically activated or inactivated during tumor progression, high throughput genome-wide array based techniques like array comparative genomic hybridization (aCGH) and transcriptional profil‐ ing can be used.[13] A molecular classification of breast cancer, with more than five reprodu‐ cible subtypes (basal-like, ERBB2, normal-like, luminal A, luminal B) was defined through gene expression profiling and microarray analysis.[38,39,17] In addition, performing the gene set enrichment analysis (GSEA), a gene set linked to the growth factor (GF) signaling was observed to be significantly enriched in the luminal B tumors.[40] Another study states that multiple pathways were identified by mapping gene sets defined in Gene Ontology Biological Process (GOBP) for estrogen receptor positive (ER+) or estrogen receptor negative (ER-); and among them, in a separate set, pathways related to apoptosis and cell division or G-protein coupled receptor signal transduction are associated with the metastatic capability of ER+or ER-tumors, respectively.[41] Additionally, in a study, it is supported that breast cancer is initiated with mutated stem cells/progenitors, also called "breast cancer stem cells" because they are sufficient to sustain oncogenesis and tumor growth.[42] To identify genetic changes in the progression of breast carcinoma, Yao et al. [43] used aCGH and SAGE combined for ductal carcinoma in situ (DCIS), invasive breast carcinomas, and lymph node metastases. They identified 49 minimal commonly amplified regions and reported that the overall frequency of copy number alterations was more in invasive tumors than in DCIS, with several of them present only in invasive cancer. In breast cancer, gene amplification happens recurrently on some chromosomal locations (e.g. 1q, 8p12, 8q24, 11q13, 12p13, 12q13, 17q21-q23, 20q13) [43,44], which points to the activation of some oncogenes at high frequency during the growth of tumor. Amplification is a mechanism causing the gene expression constitutively enhanced above the level of physiologically normal variation, so the significance of oncogene amplifi‐ cation in tumorigenesis had originated from expression profiling of tumor cells by oncogene arrays.[45]

eation of the mutational status, the patient's leukemic cells and closest germline counterpart should be compared. Unfortunately, public web-based databases are commonly used instead of the patient's germline DNA sequence from non-leukemic cells. Several of these reference databases involve VBASE, GenBank/IgBLAST and the international ImMunoGeneTics information systems that employ different software types, amount of natural IGHV polymor‐ phism and criteria used to map the complementarity determining regions and framework regions. As a result, the correct interpretation of the IGHV mutational status in CLL may be

Because of the heterogeneity of many tumors, it is a very challenging work to identify good molecular targets. For instance, resistant subclones of overexpressed and mutated genes may prevent them from being good molecular targets. Therefore, best target is a 'red dot' gene whose mutation occurs early in oncogenesis and dysregulates a key pathway that drives tumor growth in all of the subclones. Examples include mutations in the genes ABL, HER-2, KIT, EGFR and probably BRAF, in chronic myelogenous leukemia, breast cancer, gastrointestinal stromal tumors, non-small-cell lung cancer and melanoma, respectively. For efficacious therapeutics; identification of red-dot targets, development of drugs that inhibit the red-dot

Breast cancer occurs in both men and women, yet male breast cancer is less common. Although a cure for each stage of breast cancer has not yet been found, identifying the genetic mutations that cause the disease can play an important role and this is said by scientists to be like looking for needles in a haystack, and after finding the needles or coding regions, they must find disease-related sequences within them.[3,6] Bioinformatics sets the stage for searching 3 billion

Allinen et al. described the comprehensive gene expression profiles of each cell type composing normal breast tissue and in situ and invasive breast carcinomas performing SAGE (serial analysis of gene expression) and utilizing cell-type specific cell surface markers and magnetic beads for the rapid sequential isolation. Their results suggest that considerable transcriptional alterations happen in all cell populations while genetic changes were detected only in epithelial cells among myoepithelial, endothelial and stromal cells, myofibroblasts and lymphocytes.[35] To continue with another study, based upon a systematic Sanger sequencing analysis of 13,023 genes in 11 human breast cancers, individual tumors accumulate an average of approximately 90 point mutations in gene coding regions, but only a tiny number of these were recurrent and were in significant genes of breast cancer, including p53 and PIK3CA. A much larger number of the genes do not necessarily contribute to the carcinogenesis.[36] Considering the genomic landscape of breast cancer, these more common mutations resemble "mountains" while the vast majority of genes reflect "hills" that are infrequently mutated. We need to elucidate mechanisms involved in the disease to understand the heterogeneity of human cancers and

utilize personal genomics for tumor diagnosis and new therapeutic strategies.[37]

targets, and diagnostic classification of the related pathways are a must.[34]

**3. Bioinformatics and breast cancer**

178 A Concise Review of Molecular Pathology of Breast Cancer

base pairs to detect genetic defects.

affected.[33]

Bioinformatics is also crucial in the realm of pharmacogenomics. There became a need to develop accurate tools for the effective treatment relying on biological characterization of each patient's tumor. Gene-expression profiling of tumors with DNA microarrays is a powerful tool for pharmacogenomics targeting of treatments. Oncotype DX™ assay (Genomic Health) is a good example, which was described for identifying the subset of node-negative estrogenreceptor-positive breast cancer patients who do not require adjuvant chemotherapy.[46,34] A recent research demonstrated that microarray analysis with qRT-PCR validation reveals distinct pathways of resistance to bevacizumab (BEV) in xenograft models of human ER+breast cancer, showing Follistatin (FST) and NOTCH as the top signaling pathways associated with resistance in VEGF-driven tumors (P <0.05). According to the gene expression analysis, the level of VEGF expression affects the response to BEV therapy and gene pathways.[47] Using appropriate bioinformatics tools, such findings may elucidate the matter of resistance to drugs for individual patients and provide a deeper understanding of treatments and risk factors, opening the door from novel targets and disease-related biomarkers to right drugs.

Last but not least, the effect of epigenetic changes on breast cancer etiology is beyond doubt. In spite of quite a number of DNA methylation research manifesting diverse patterns including tumor suppressor genes and oncogenes, only a small fraction of them connect the epigenome data with the transcriptome. In a recent study by Minning and coworkers[48], DNA methyl‐ ation and gene expression profiling of primary breast tumor tissues and adjacent noncancerous breast tissues was carried out. They preferred MS-MLPA or MS-qPCR for validation of results. The overlapping genes between DNA methylation and gene expression datasets were further mapped to the KEGG database to identify the molecular pathways linking the used genes together and supervised hierarchical clustering was used for data analysis. The authors found that most of the overlapping genes belong to the focal adhesion and extracellular matrix-receptor interaction that play important roles in breast carcinogenesis. The more gene signature data is acquired by different studies, the better understanding of epigenetic regula‐ tion of gene expression and remedial intervention will be possible.

Advances in bioinformatics and its application are much possible by multidisciplinary teams pursuing focused research. The sensitivity, specificity and combination of tools, methodolo‐ gies, and databases should be evaluated in a complete matter. On top of that, findings must be confirmed with several molecular techniques before translation into clinical practice.


**Table 1.** Major electronic nucleotide and protein databases


**Table 2.** Commonly used genom browser and databases

## **Author details**

Last but not least, the effect of epigenetic changes on breast cancer etiology is beyond doubt. In spite of quite a number of DNA methylation research manifesting diverse patterns including tumor suppressor genes and oncogenes, only a small fraction of them connect the epigenome data with the transcriptome. In a recent study by Minning and coworkers[48], DNA methyl‐ ation and gene expression profiling of primary breast tumor tissues and adjacent noncancerous breast tissues was carried out. They preferred MS-MLPA or MS-qPCR for validation of results. The overlapping genes between DNA methylation and gene expression datasets were further mapped to the KEGG database to identify the molecular pathways linking the used genes together and supervised hierarchical clustering was used for data analysis. The authors found that most of the overlapping genes belong to the focal adhesion and extracellular matrix-receptor interaction that play important roles in breast carcinogenesis. The more gene signature data is acquired by different studies, the better understanding of epigenetic regula‐

Advances in bioinformatics and its application are much possible by multidisciplinary teams pursuing focused research. The sensitivity, specificity and combination of tools, methodolo‐ gies, and databases should be evaluated in a complete matter. On top of that, findings must be confirmed with several molecular techniques before translation into clinical practice.

> EMBL Europian Bioinformatics Institute www.ebi.ac.uk/ DDBJ National Institute of Genetic, Japan www.ddbj.nig.ac.jp/

> > EMBL database that have not yet been deposited

Institute of Bioinformatics (SIB) and the Protein

dbEST www.ncbi.nlm.nih.gov/dbEST

European Bioinformatics Institute www.ebi.ac.uk/swissprot/

SWISS-PROT Swiss Institute of Bioinformatics, Geneva web.expasy.org/docs/swiss-

www.ncbi.nlm.nih.gov/genbank

prot\_guideline.html

www.ebi.ac.uk/tremble

www.uniprot.org

pir.georgetown.edu

www.ddbj.nig.ac.jp

mips.gsf.de

tion of gene expression and remedial intervention will be possible.

180 A Concise Review of Molecular Pathology of Breast Cancer

**Database GroupDatabase Originator Web Adress**

TREMBLE EBI (translation of coding sequences from the

UniProt Bioinformatics Institute (EMBL-EBI), Swiss

Information Resource (PIR).

PIR US National Biomedical Research Foundation

Japan International Protein Information

Munich Information Center for Protein

in SWISS-PROT)

Database (JIPID)

Sequences (MIPS)

(NBRF)

**Table 1.** Major electronic nucleotide and protein databases

GenBank US National Center for Biotechnology Information (NCBI)

**Nucleotide Sequence**

**Protein Sequence** Beyzanur Yigitoglu1 , Eyyup Uctepe1 , Ramazan Yigitoglu2 , Esra Gunduz1\* and Mehmet Gunduz1

\*Address all correspondence to: mehmet.gunduz@gmail.com

1 Department of Medical Genetics, Faculty of Medicine, Turgut Ozal University, Ankara, Turkey

2 Medical Biochemistry, Faculty of Medicine, Turgut Ozal University, Ankara, Turkey

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## **Relationship of Breast Cancer with Ovarian Cancer**

Ayşe Çelik, Muradiye Acar, Catherine Moroski Erkul, Esra Gunduz and Mehmet Gunduz

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59682

## **1. Introduction**

Cancer is perhaps the cruelest of deadly diseases in our era. So many factors play a role in cancer and these features were characterized in 2011 as belonging to eight categories: evasion of apoptosis, excessive growth signalling, insensitivity to anti-growth signals, maintained angiogenesis, endless replicative potential, metastasis, reprogramming of energy metabolism and avoidance of immune destruction. Types of cancer may be put in different categories (or combinations of these) according to symptoms and pathogenesis, therefore revealing many relationships.

Breast cancer is the most commonly diagnosed cancer type among women. There are similar‐ ities between breast and ovarian cancer such as similar mutations (tumor suppressors, protooncoges), changes in hormone regulation and microenvironment, etc. In 2014, approximately 235,030 new cases are expected, and it is estimated that 40,430 deaths from breast cancer will occur. Also, an estimated 21,980 new cases of ovarian cancer will be diagnosed in 2014, with an estimated 14,270 deaths. Statistical results and similarities raise the question of whether metastasis of breast cancer is related to the occurrence of ovarian cancer.

Several mutations in growth control genes can trigger the development of tumors in the body. The specific causes of the mutations that lead to cancer are not fully known. Recent studies have tried to uncover these unknown relationships between breast and ovarian cancer. Understanding of the correlations between different types of cancers provide knowledge to us about the disease process. Recent studies focus on common mutations, tumor microenvironment, receptor inactivation, Trastuzumab resistance, etc. Thanks to these studies, new therapeutic techniques have been developed such as using miRNA as therapeutic targets or improvement of nanodrug delivery systems. Also, mathematical modeling has been used in attempts to understand changes in metabolic pathways and metastasis.

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

Briefly, understanding of the associations between breast and ovarian cancers provide opportunities for the prevention of metastasis and allow development of new ways to cure cancer.

## **2. Hereditary Breast and Ovarian Cancer (HBOC)**

Despite intense studies about breast and ovarian cancer, these cancer types are the most significant cause of death in women in our century. Recent studies have tried to identify different types of mutations for certain genes and determine changes in copy numbers, expression profiles, etc. by using high-throughput technologies [1]. Identifying variations among breast and ovarian cancers will hopefully uncover associations between them, thus possibly revealing methods for early disease screening and allow understanding of the mechanism(s) of metastasis between these two cancer types.

Several studies have continued to find a common point for breast and ovarian cancer; all studies have defined certain mutations in BRCA1/BRCA2 for these types of cancer. The statistics show that 60-80% of BRCA1/BRCA2 gene mutation carriers will develop breast cancer and 20-40% will develop ovarian cancer. Some cases of HBOC indicate a connection with constitutive epimutations or other susceptibility genes such as several gene clusters including the Fanconi anemia (FA) cluster (FANCD2, FANCA and FANCC), mismatch repair (MMR) cluster (MLH1, MSH2, PMS1, PMS2 and MSH6), NA repair cluster (ATM, ATR and CHK1/2), and tumor suppressor cluster (TP53, SKT11 and PTEN). If a patient does not have any mutations in the BRCA genes but their cancer has a phenotype characteristic of those with BRCA mutations and a dysfunction in a DNA repair system, it is known as 'BRCAness';[1]. In conclusion,mutations that occur in some DNA repair mechanisms can increase the risk of developing breast and ovarian cancer.

## **3. Identification of high penetrance of genes**

The inactivation of BRCA1 and BRCA2 genes are germline mutations and trigger breast and ovarian cancer. This phenomenon was confirmed by high throughput technologies used for molecular diagnostics such as next generation sequencing (NGS). By using NGS, the DNA of 59 patients harbouring SNVs that include indels or large genomic rearrangements of BRCA1 or BRCA2 was analyzed. Also, 168 patients were used as blind study to compare NGS versus Sanger sequencing or MLPA analyses of BRCA1 and BRCA2. Then, by using three different capture methods, 708 consecutive patients were monitored. A total of 69 deleterious germline alterations within BRCA1 and BRCA2, and 4 TP53 mutations were detected in 468 patients. In addition to this, 36 variations that include either a premature codon stop or a splicing defect among other genes were found (*5/708 in CHEK2, 3/708 in RAD51C, 1/708 in RAD50, 7/708 in PALB2, 3/708 in MRE11A, 5/708 in ATM, 3/708 in NBS1, 1/708 in CDH1, 3/468 in MSH2, 2/468 in PMS2, 1/708 in BARD1, 1/468 in PMS1 and 1/468 in MLH3)*. This study shows the efficiency of NGS in performing molecular diagnosis of HBOC [2].

In the past, full coding exon sequencing was challenging, because researchers had to analyse dozens of coding genes using the traditional method of Sanger sequencing. It is a very time consuming and labor intensive method. Thus, complicated genetic analysis was not possible. However, new techniques have made such research easy. Also, parallel sequencing allows for complicated genetic analysis in a short time. This technique is now reliable for genomic research, but applying this in the clinic is still difficult due to the requirement of complex equipment and highly trained staff [3]. In clinical applications, several library preparation methods have been used to demonstrate a novel capture method. Targeting coding sequences of genes have high coverage in every captured region. In order to streamline the number of germline mutation variants, further whole exon sequencing studies and confirmations are required in order to provide a gold standard for the investigation of germline variants.Nowa‐ days, clinical decisions that include molecular diagnoses have a significant impact on the determination of treatments such as chemotherapy and prophylactic surgery. The association between breast and ovarian cancer try to depend on high or low penetrance of genes that are observable in both cancer types. The most common susceptibility genes in this field are BRCA1/ BRCA2. If any mutations are present in either of these genes, it translates to a 60-85% lifetime risk of developing breast or ovarian cancer [4].

Briefly, understanding of the associations between breast and ovarian cancers provide opportunities for the prevention of metastasis and allow development of new ways to cure

Despite intense studies about breast and ovarian cancer, these cancer types are the most significant cause of death in women in our century. Recent studies have tried to identify different types of mutations for certain genes and determine changes in copy numbers, expression profiles, etc. by using high-throughput technologies [1]. Identifying variations among breast and ovarian cancers will hopefully uncover associations between them, thus possibly revealing methods for early disease screening and allow understanding of the

Several studies have continued to find a common point for breast and ovarian cancer; all studies have defined certain mutations in BRCA1/BRCA2 for these types of cancer. The statistics show that 60-80% of BRCA1/BRCA2 gene mutation carriers will develop breast cancer and 20-40% will develop ovarian cancer. Some cases of HBOC indicate a connection with constitutive epimutations or other susceptibility genes such as several gene clusters including the Fanconi anemia (FA) cluster (FANCD2, FANCA and FANCC), mismatch repair (MMR) cluster (MLH1, MSH2, PMS1, PMS2 and MSH6), NA repair cluster (ATM, ATR and CHK1/2), and tumor suppressor cluster (TP53, SKT11 and PTEN). If a patient does not have any mutations in the BRCA genes but their cancer has a phenotype characteristic of those with BRCA mutations and a dysfunction in a DNA repair system, it is known as 'BRCAness';[1]. In conclusion,mutations that occur in some DNA repair mechanisms can increase the risk of

The inactivation of BRCA1 and BRCA2 genes are germline mutations and trigger breast and ovarian cancer. This phenomenon was confirmed by high throughput technologies used for molecular diagnostics such as next generation sequencing (NGS). By using NGS, the DNA of 59 patients harbouring SNVs that include indels or large genomic rearrangements of BRCA1 or BRCA2 was analyzed. Also, 168 patients were used as blind study to compare NGS versus Sanger sequencing or MLPA analyses of BRCA1 and BRCA2. Then, by using three different capture methods, 708 consecutive patients were monitored. A total of 69 deleterious germline alterations within BRCA1 and BRCA2, and 4 TP53 mutations were detected in 468 patients. In addition to this, 36 variations that include either a premature codon stop or a splicing defect among other genes were found (*5/708 in CHEK2, 3/708 in RAD51C, 1/708 in RAD50, 7/708 in PALB2, 3/708 in MRE11A, 5/708 in ATM, 3/708 in NBS1, 1/708 in CDH1, 3/468 in MSH2, 2/468 in PMS2, 1/708 in BARD1, 1/468 in PMS1 and 1/468 in MLH3)*. This study shows the efficiency

**2. Hereditary Breast and Ovarian Cancer (HBOC)**

188 A Concise Review of Molecular Pathology of Breast Cancer

mechanism(s) of metastasis between these two cancer types.

developing breast and ovarian cancer.

**3. Identification of high penetrance of genes**

of NGS in performing molecular diagnosis of HBOC [2].

cancer.

Germline mutations in BRCA1 and BRCA2 can be inherited by offspring and thus are known as constitutional mutations. The mutations may have complete or partial gene deletions, large insertions, duplications, splicing, frameshifts, missense and nonsense mutations. Insertions and deletions may occur at the same position in the sequence and induce gene shuffling, which in turn leads to abnormal gene structure, function,etc. The rate of these mutations changes from population to population. According to data from the Breast Cancer Information Core website, approximately 3500 mutations have been reported for both genes. For instance, female breast cancer patients of Ashkenazi Jewish descent have a 10 – 12 % frequency of mutations in these genes. Frequency of this mutation is higher than in the rest of the Caucasian popula‐ tion, because the female Ashkenazi Jewish population harbors ancient BRCA1 / BRCA 2 mutant alleles. The 5266dup, BRCA2999del5 and BRCA1delexon17 mutations have been defined in some populations such as Slavic, Finnish, Icelandic and German [4].

In addition, the penetrance of mutations is important for genomic rearrangements to develop into a detectable trait. Detection of high penetrance genes is easier than lower ones, because they form symptoms and are always apparent in an individual carrying the allele. However, several variations in low penetrance alleles are more common, and these low penetrance alleles could increase risk to develop cancer and its progression [5]. Some researchers have focused on identification of new genes to explain the missing heritability in BRCA negative cancer patients, including targeted genes that may interact with BRCA pathways and proteins.

Nowadays, several studies have focused on finding these candidate genes and mutations using NGS technologies. According to these studies, additional high penetrance alleles have been found for breast/ovarian cancers; for instance, TP53, STK11,etc. Also, moderate penetrance alleles such as PALB2, BRIP1, RAD51C have a role in cancer via their alteration in pathways like Fanconi Anemia [6],[7]. In addition, ATM and CHEK2 have the same penetrance level and are involved in the homologous recombination repair pathway [8]. Detection of mutations and penetrance within genes other than BRCA1 and BRCA2 has shed light on the genetic hetero‐ geneity of HBOC.

#### **3.1. BRCA1 and BRCA2 genes**

BRCA1 and BRCA2 genes are expressed in epithelial cells of breast and ovarian tissues. They regulate the repair of some types of DNA damage and are involved in cell fate decision; if DNA damage is too excessive and cannot be repaired efficiently, the cell will be directed to be destroyed. Briefly, BRCA1 and BRCA2 genes are tumor supressor genes that are essential in homologous recombination repair of double strand breaks [9], [10]. If any mutations or damage occurs in BRCA1/BRCA2, DNA damage cannot be properly repaired and this increases the risk of developing breast cancer [11]. However, BRCA1/2 are not oncogenes.They are normal but their mutations are abnormal and cause formation of breast cancer. Chromosomal arrangements may result from errors in the DNA damage response mechanism. It might lead to genomic instability. If genomic rearrangements are large, they may escape detection. The problem is that standard genetic testing is not capable of identifying large rearrangements and therefore next generation and whole exon sequencing technologies must be used to detect these gene modifications/changes [12].

Some studies have focused on solving the mechanisms of BRCA1 and BRCA2. According to biochemical, genetic and cytological studies, the lack of BRCA1 results in cell death because BRCA1 regulates stem/progenitor cell proliferation and differentiation. Apicobasal polarity is regulated by BRCA1 and RHAMM (hyaluronan-mediated motility receptor), AURKA (aurora kinase A) and TPX2 (microtubule-associated, homolog). This gene complex can change the miotic spindle promoting activity of RHAMM which may control tumor progression. In addition to this, BRCA1 binds and regulates AURKA which plays a role in the cell cycle as a kinase and appears to be strongly involved in centrosome regulation. Therefore, variations of the AURKA gene may contribute to breast cancer progression [13]. BRCA1 causes an accu‐ mulation of TPX2 and is required for mitotic spindle- pole assembly. Not only DNA damage response and repair, but also cell differentiation requires the BRCA core complex proteins for functional integrity.



**Table 1.** BRCA interacting proteins

penetrance within genes other than BRCA1 and BRCA2 has shed light on the genetic hetero‐

BRCA1 and BRCA2 genes are expressed in epithelial cells of breast and ovarian tissues. They regulate the repair of some types of DNA damage and are involved in cell fate decision; if DNA damage is too excessive and cannot be repaired efficiently, the cell will be directed to be destroyed. Briefly, BRCA1 and BRCA2 genes are tumor supressor genes that are essential in homologous recombination repair of double strand breaks [9], [10]. If any mutations or damage occurs in BRCA1/BRCA2, DNA damage cannot be properly repaired and this increases the risk of developing breast cancer [11]. However, BRCA1/2 are not oncogenes.They are normal but their mutations are abnormal and cause formation of breast cancer. Chromosomal arrangements may result from errors in the DNA damage response mechanism. It might lead to genomic instability. If genomic rearrangements are large, they may escape detection. The problem is that standard genetic testing is not capable of identifying large rearrangements and therefore next generation and whole exon sequencing technologies must be used to detect these

Some studies have focused on solving the mechanisms of BRCA1 and BRCA2. According to biochemical, genetic and cytological studies, the lack of BRCA1 results in cell death because BRCA1 regulates stem/progenitor cell proliferation and differentiation. Apicobasal polarity is regulated by BRCA1 and RHAMM (hyaluronan-mediated motility receptor), AURKA (aurora kinase A) and TPX2 (microtubule-associated, homolog). This gene complex can change the miotic spindle promoting activity of RHAMM which may control tumor progression. In addition to this, BRCA1 binds and regulates AURKA which plays a role in the cell cycle as a kinase and appears to be strongly involved in centrosome regulation. Therefore, variations of the AURKA gene may contribute to breast cancer progression [13]. BRCA1 causes an accu‐ mulation of TPX2 and is required for mitotic spindle- pole assembly. Not only DNA damage response and repair, but also cell differentiation requires the BRCA core complex proteins for

**protein**

RAD51 DSB repair Exon 11 (758-1064) [14] RAD50 DSB repair Exon 11(341- 748) [15]

BASC (QTM,BLM,MSH2,MSH6,MLH1,RCF) Mismatch repair BRCA part of complex [16]

tumor supressor

**Interacting**

BRCT domain

Exon 11 and BRCT domain (224 – 500 and

1760-1863)

**domain(a.a. residues)**

(1314-1863) [14]

**Ref.**

[17], [18]

geneity of HBOC.

**3.1. BRCA1 and BRCA2 genes**

190 A Concise Review of Molecular Pathology of Breast Cancer

gene modifications/changes [12].

functional integrity.

**BRCA1 interacting protein or complex Function of interacting**

p53 Transcription Factor,

BRCA2 DSB repair

Many biochemical studies have shed light on a multitude of proteins with defined interactions with BRCA1 and BRCA2. These proteins are involved in control mechanisms of DNA double strand breaks. Within several minutes after damage, H2AX, a member of the histone H2A family of proteins, becomes phosphorylated and foci form at the site of DNA double strand breaks [42]. BRCA1 is recruited with this area within several hours. Subsequently, RAD50 and RAD51 interact with the strand breaks. This situation shows that BRCA1 and H2AX can initiate repair mechanisms of local chromatin structure, thus DNA repair proteins can access damaged sites.

If BRCA1 and BRCA2 genes are absent from the cell, chromosomal abnormalities, breaks, aneuploidy and centrosome amplification occurs. The pathogenic tumor formation in breast and ovarian tissue may depend on chromosomal instability that is the result of deficiency of BRCA1 and BRCA2 genes. In order to reveal this relation, researchers monitored sporadic breast and ovarian tumors. 50 – 70 % of them were found to have lost an BRCA1 allele and 30 – 50 % were found to have lost an BRCA2 allele [43],[44].

Genomic instability of BRCA1 and BRCA2 genes result from the repetitive DNA elements that are of high density. 42% of BRCA1 consists of Alu sequences and 5% non-Alu repeats. The genomic region of BRCA2 consists of 47% repetitive DNA [45]. BRCA1 and BRCA2 are rare genes that include high density repetitive DNA regions. Multiple diseases are mediated by genetic rearrangements of Alu sequences. According to the given density of repeat elements in BRCA1 and BRCA2, careful analysis of these genes can reveal the risk of breast and ovarian cancer due to these susceptibility genes.

The source of the large deletions depends on repetitive regions on genes. One mechanism that manages the large deletions observed around the BRCA1 and BRCA2 that are inherited and sporadic tumors in breast and ovarian cancer (Figure1). These repeat regions may be far apart from the linear DNA but physically close in the nucleus. For instance, if a chromosome break occurs near a replication fork during replication, it might be repaired by HR to a replication fork at a nearby anchorage point.

#### **3.2. Association between DNA damage and BRCA1-BRCA2 genes**

Double strand breaks such as exposure to ionizing radiation or certain kinds of DNAdamaging agents. Genetic defects in DNA damage response genes and/or down-regulation of the DNA repair mechanisms induces genomic instability, and this can lead to carcinogenesis [46]. Among the many DNA repair pathways available in mammalian cells are homologous repair, non-homologous end-joining and single-strand annealing [47]. There are several ways that cells can repair double strand breaks. A number of signaling pathways are involved in the detection of DSBs and regulate DNA repair or apoptotic cell death. The main DNA damage recognition molecule is ATM [48], a checkpoint kinase that phosphorylates a number of proteins in response to DNA damage, including p53 and BRCA1 [Figure2].

p53 plays a critical role in preventing cancer development. Generally, p53 gene is mutated in cancer tissue, so it cannot protect the genetic integrity of cells. In physiological conditions, p53 is activated when DNA damage occurs. The failure of DNA damage response results in p53

Many biochemical studies have shed light on a multitude of proteins with defined interactions with BRCA1 and BRCA2. These proteins are involved in control mechanisms of DNA double strand breaks. Within several minutes after damage, H2AX, a member of the histone H2A family of proteins, becomes phosphorylated and foci form at the site of DNA double strand breaks [42]. BRCA1 is recruited with this area within several hours. Subsequently, RAD50 and RAD51 interact with the strand breaks. This situation shows that BRCA1 and H2AX can initiate repair mechanisms of local chromatin structure, thus DNA repair proteins can access damaged

If BRCA1 and BRCA2 genes are absent from the cell, chromosomal abnormalities, breaks, aneuploidy and centrosome amplification occurs. The pathogenic tumor formation in breast and ovarian tissue may depend on chromosomal instability that is the result of deficiency of BRCA1 and BRCA2 genes. In order to reveal this relation, researchers monitored sporadic breast and ovarian tumors. 50 – 70 % of them were found to have lost an BRCA1 allele and 30

Genomic instability of BRCA1 and BRCA2 genes result from the repetitive DNA elements that are of high density. 42% of BRCA1 consists of Alu sequences and 5% non-Alu repeats. The genomic region of BRCA2 consists of 47% repetitive DNA [45]. BRCA1 and BRCA2 are rare genes that include high density repetitive DNA regions. Multiple diseases are mediated by genetic rearrangements of Alu sequences. According to the given density of repeat elements in BRCA1 and BRCA2, careful analysis of these genes can reveal the risk of breast and ovarian

The source of the large deletions depends on repetitive regions on genes. One mechanism that manages the large deletions observed around the BRCA1 and BRCA2 that are inherited and sporadic tumors in breast and ovarian cancer (Figure1). These repeat regions may be far apart from the linear DNA but physically close in the nucleus. For instance, if a chromosome break occurs near a replication fork during replication, it might be repaired by HR to a replication

Double strand breaks such as exposure to ionizing radiation or certain kinds of DNAdamaging agents. Genetic defects in DNA damage response genes and/or down-regulation of the DNA repair mechanisms induces genomic instability, and this can lead to carcinogenesis [46]. Among the many DNA repair pathways available in mammalian cells are homologous repair, non-homologous end-joining and single-strand annealing [47]. There are several ways that cells can repair double strand breaks. A number of signaling pathways are involved in the detection of DSBs and regulate DNA repair or apoptotic cell death. The main DNA damage recognition molecule is ATM [48], a checkpoint kinase that phosphorylates a number of

p53 plays a critical role in preventing cancer development. Generally, p53 gene is mutated in cancer tissue, so it cannot protect the genetic integrity of cells. In physiological conditions, p53 is activated when DNA damage occurs. The failure of DNA damage response results in p53

– 50 % were found to have lost an BRCA2 allele [43],[44].

**3.2. Association between DNA damage and BRCA1-BRCA2 genes**

proteins in response to DNA damage, including p53 and BRCA1 [Figure2].

cancer due to these susceptibility genes.

192 A Concise Review of Molecular Pathology of Breast Cancer

fork at a nearby anchorage point.

sites.

**Figure 1.** A mechanism for the formation of deletion by loss of a chromatin loop at different stages. Deletions of phase 1 occur in S phase, when the same repetitive sequences are physically brought together by MAR (blue ellipse). Breaks in DNA, and their repair, might lead to deletion of a chromatin loop (red). Deletions of type 2 and 3 occur by the same mechanism but occur later during DNA synthesis in the replication cycle. (Adapted from Piri et al [11])

mediated cell apoptosis [49]. Several mechanisms regulate p53 activity. p21WAF-1 has been shown to play an important role in both p53-dependent [50] and -independent pathways [51]. p21WAF-1 prevents cell cycle progression via interaction with the cyclin-dependent kinase (CDK) complex. Therefore, p53 plays a role in the most important part of providing stability to the genome by using cell cycle checkpoints, DNA repair and apoptosis.

BRCA1 also involves a gold standard for a tumor suppressor gene that is needed to prevent cancer development and progression. BRCA1 / BRCA2 related breast and ovarian cancers are have defects in a DNA repair pathway [52]. Studies have shed light on the functional roles of BRCA1/BRCA2 genes in DNA repair, cell cycle checkpoints and DNA damage signaling pathways [53]. BRCA1 interacts with several cyclins and CDKs, triggers the activation of the CDK inhibitor, p21WAF-1, and p53, thus it can control the cell cycle. The main function of BRCA1 depends on its phosphorylation status, so if the gene becomes hyper-phosphorylated following any damage or exposure to DNA damaging agents, it becomes non-functional[54].

Also, BRCA1 and BRCA2 genes are not only responsible for DNA damage response but also their proteins interact with the estrogen and androgen receptors [55]. These genes inhibit

**Figure 2.** Schematic representation and overview of the DNA repair and checkpoint regulation of cell cycle

estrogen receptor-α activity and stimulate androgen receptors. In this way, BRCA1 mutations are associated with hormone responsive cancer. In other words, the cancer risk of BRCA1 mutation carriers will increase via hormonal factors.

#### **3.3. Association of estrogens — Estrogen receptors with BRCA genes**

Estrogen, progesterone and androgen hormones control the initiation of carcinogenesis by using special hormone receptors. Moreover, hormonal therapies frequently regulate hormonemediated diseases such as cancer. A number of candidate genes have been identified as biomarkers for ovarian and breast cancers [56].

Frequently, damage in the DNA repair system induce growth arrest and cell death. BRCA deficient mice die in the early stages of embryogenesis. The first question that arises is why BRCA deficient breast or ovarian epithelial cells develop tumors instead of undergoing apoptosis? What is special to breast and ovarian epithelial cells that allows them to escape apoptosis or response to the DNA damage response system? Finally, how are BRCA1 and BRCA2 genes associated with estrogen levels?

The transition of the hormone independence induces the progression of breast and ovarian cancer because of DNA repair defects. The estrogen-bound receptor dimerizes and associates with chromatin. The estrogen response elements that are present on a DNA sequence motif bind directly to the receptor dimers. There are two kind of estrogen receptors:estrogen receptor-α and estrogen receptor-β. Estrogen receptor-α plays a role in proliferation, and the activation of estrogen receptor-β controls apoptosis [57]. An increase in estrogen receptor-β levels might be related with a reduction in breast cancer risk [58]. Estrogen receptor-β may prevent cellular proliferation by action opposite to that of estrogen receptor-α.

**Figure 3.** Schematic representation of interaction between BRCA1 and estrogen receptor (ER)-α

estrogen receptor-α activity and stimulate androgen receptors. In this way, BRCA1 mutations are associated with hormone responsive cancer. In other words, the cancer risk of BRCA1

**Figure 2.** Schematic representation and overview of the DNA repair and checkpoint regulation of cell cycle

Estrogen, progesterone and androgen hormones control the initiation of carcinogenesis by using special hormone receptors. Moreover, hormonal therapies frequently regulate hormonemediated diseases such as cancer. A number of candidate genes have been identified as

Frequently, damage in the DNA repair system induce growth arrest and cell death. BRCA deficient mice die in the early stages of embryogenesis. The first question that arises is why BRCA deficient breast or ovarian epithelial cells develop tumors instead of undergoing apoptosis? What is special to breast and ovarian epithelial cells that allows them to escape apoptosis or response to the DNA damage response system? Finally, how are BRCA1 and

The transition of the hormone independence induces the progression of breast and ovarian cancer because of DNA repair defects. The estrogen-bound receptor dimerizes and associates with chromatin. The estrogen response elements that are present on a DNA sequence motif bind directly to the receptor dimers. There are two kind of estrogen receptors:estrogen receptor-α and estrogen receptor-β. Estrogen receptor-α plays a role in proliferation, and the activation of estrogen receptor-β controls apoptosis [57]. An increase in estrogen receptor-β

mutation carriers will increase via hormonal factors.

194 A Concise Review of Molecular Pathology of Breast Cancer

biomarkers for ovarian and breast cancers [56].

BRCA2 genes associated with estrogen levels?

**3.3. Association of estrogens — Estrogen receptors with BRCA genes**

A woman exposed to estrogen either endogenously or exogenously, has an increased risk of developing breast or ovarian cancer. BRCA1 and BRCA2 expression levels are highest during pregnancy and puberty, when estrogen levels are increased [59].

If estrogens triggers cell proliferation [60], increased estrogens promotes the probability of developing random genetic rearrangements and errors. Metabolic processes produce reactive oxygen species (ROS) that cause oxidative damage to genomic DNA. In addition, some hormone oxidative metabolites catalyzed by cytochrome p450 enzymes can form unstable adducts in DNA which then leads to mutations [61].

**Figure 4.** Connection of the hormone endocrine, immune, DNA damage and DNA repair systems in cancer

A long period of exposure to estrogen is strongly associated with an increased risk of devel‐ oping breast and ovarian cancer. However, activation of DNA damage response mechanisms may be triggered via androgen signaling [62]. The estrogen receptor-mediated pathways are inhibited by BRCA1 and BRCA2 proteins which function as a suppressor in mammary epithelial cell proliferation. Also, the estrogen receptor complex regulates the transcription of BRCA1 and BRCA2 under the condition of estrogen stimulation. In addition, estrogens are not only essential for mammary growth and differentiation, but also enhance the activity of the p53 tumor suppressor protein [63].

## **4. Biomarkers in breast and ovarian cancer**

#### **4.1. The KRAS-variant (A germline microRNA binding site-disrupting variant)**

Cancer susceptibility genes increase the risk of malignancy as a result of mutations in tumor suppressor or oncogenes that control different pathways. The KRAS variants are active at the site of the 3'-untranslated region of the complementary site of let-7 miRNA. miRNAs are 22 nucleotide long noncoding RNAs that are conserved regions. They are a novel class of oncogenes and tumor supressors that are upregulated in cancers [64]. Recent studies showed that SNPs that are present in miRNA binding sites can be powerful markers of cancer risk [65]. Ratner et al. reported that KRAS is associated with 61% of cases of breast and ovarian cancer syndrome. In another study, KRAS variants were observed to be increased within women with triple-negative breast cancer [66]. A study at Yale University, involving 58 hereditary breast and ovarian syndrome patients tested for the presence of the KRAS variant. The KRAS-variant was identified in 60% of HBOC patients who lacked BRCA1 or BRCA2 mutations. These findings strongly support the hypothesis that the KRAS-variant is a genetic marker of an increased risk of developing ovarian cancer[67].

The KRAS variant might be a new biomarker for breast and ovarian cancer. Therefore, preventing or identifying cancer in early steps may be possible by using this biomarker.

#### **4.2. Flap Endonuclease 1 (FEN1) as a biomarker in breast and ovarian cancer**

FEN1 is a kind of flap structure endonuclease that is critical for DNA repair processing. It is involved in long patch base excision repair (LP-BER) and Okazaki fragment maturation during replication. In addition, it plays a role in rescue delayed in replication forks, managing of telomere stability and apoptotic formation of DNA [68] [69]. Fen1 is also a main actor in posttranslational modifications such as acetylation, phosphorylation, sumoylation, methyla‐ tion and ubiquitylation which control nuclease activities [68] [69].

FEN1 has a role in tumor formation. A FEN1 E160D mutant mouse model shows alteration in DNA repair [70] [71]. These changes trigger an increased frequency of cancer development. Polymorphic variations of FEN1 in humans may be associated with high frequency cancer susceptibility [72, 73].

FEN1 has an impact on breast tumors. It affects BRCA1, PARP1, XRCC1 and TOP2A genes. There is an association between high FEN1 and ATM expression. FEN1 may regulate the ERinduced transcriptional response with interaction of estrogen response elements [74]. There is a complex network between ER, FEN1 and ATM in breast cancer cells. Similarly, in ovarian cancer, FEN1 expression is linked to an aggressive phenotype and poor survival [75]. Abdel-Fatah et al. demonstrated that FEN1 overexpression is associated with an aggressive pheno‐ type and poor survival in breast and ovarian cancer.

## **5. Conclusion**

A long period of exposure to estrogen is strongly associated with an increased risk of devel‐ oping breast and ovarian cancer. However, activation of DNA damage response mechanisms may be triggered via androgen signaling [62]. The estrogen receptor-mediated pathways are inhibited by BRCA1 and BRCA2 proteins which function as a suppressor in mammary epithelial cell proliferation. Also, the estrogen receptor complex regulates the transcription of BRCA1 and BRCA2 under the condition of estrogen stimulation. In addition, estrogens are not only essential for mammary growth and differentiation, but also enhance the activity of the

**4.1. The KRAS-variant (A germline microRNA binding site-disrupting variant)**

Cancer susceptibility genes increase the risk of malignancy as a result of mutations in tumor suppressor or oncogenes that control different pathways. The KRAS variants are active at the site of the 3'-untranslated region of the complementary site of let-7 miRNA. miRNAs are 22 nucleotide long noncoding RNAs that are conserved regions. They are a novel class of oncogenes and tumor supressors that are upregulated in cancers [64]. Recent studies showed that SNPs that are present in miRNA binding sites can be powerful markers of cancer risk [65]. Ratner et al. reported that KRAS is associated with 61% of cases of breast and ovarian cancer syndrome. In another study, KRAS variants were observed to be increased within women with triple-negative breast cancer [66]. A study at Yale University, involving 58 hereditary breast and ovarian syndrome patients tested for the presence of the KRAS variant. The KRAS-variant was identified in 60% of HBOC patients who lacked BRCA1 or BRCA2 mutations. These findings strongly support the hypothesis that the KRAS-variant is a genetic marker of an

The KRAS variant might be a new biomarker for breast and ovarian cancer. Therefore, preventing or identifying cancer in early steps may be possible by using this biomarker.

FEN1 is a kind of flap structure endonuclease that is critical for DNA repair processing. It is involved in long patch base excision repair (LP-BER) and Okazaki fragment maturation during replication. In addition, it plays a role in rescue delayed in replication forks, managing of telomere stability and apoptotic formation of DNA [68] [69]. Fen1 is also a main actor in posttranslational modifications such as acetylation, phosphorylation, sumoylation, methyla‐

FEN1 has a role in tumor formation. A FEN1 E160D mutant mouse model shows alteration in DNA repair [70] [71]. These changes trigger an increased frequency of cancer development. Polymorphic variations of FEN1 in humans may be associated with high frequency cancer

**4.2. Flap Endonuclease 1 (FEN1) as a biomarker in breast and ovarian cancer**

tion and ubiquitylation which control nuclease activities [68] [69].

p53 tumor suppressor protein [63].

196 A Concise Review of Molecular Pathology of Breast Cancer

**4. Biomarkers in breast and ovarian cancer**

increased risk of developing ovarian cancer[67].

susceptibility [72, 73].

Despite the more intense studies about breast and ovarian cancer, these cancer types are the most significant cause of death in women in our century. Recent studies have tried to stream‐ line the number of mutations for specific genes and identify changes in copy number, expres‐ sion profiles, etc. by using high-throughput technologies for identification of variations. Identification of all kinds of variations will uncover associations between breast and ovarian cancer, and thus reveal potential disease screening methods and provide an understanding of the mechanism of metastasis between these two cancer types. In this chapter, we aimed to gather the current knowledge about susceptibility genes BRCA1 and BRCA2 which are highly connected with breast and ovarian cancer. Also, mechanisms and hormones (estrogen) that induce cancer associated with BRCA1/BRCA2 have been discussed. Finally, new biomarkers including FEN1 and KRAS for breast and ovarian cancer have been discussed.

## **Author details**

Ayşe Çelik, Muradiye Acar, Catherine Moroski Erkul, Esra Gunduz and Mehmet Gunduz\*

\*Address all correspondence to: mehmet.gunduz@gmail.com

Department of Medical Genetics, Faculty Of Medicine, Turgut Ozal University, Ankara, Turkey

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