Bridging Cell Biology and Genetics to the Cancer Clinic

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Bridging Cell Biology and Genetics to the Cancer Clinic Editor

Parvin Mehdipour Department of Medical Genetics, School of Medicine Tehran University of Medical Sciences Tehran, Iran

Transworld Research Network, T.C. 37/661 (2), Fort P.O., Trivandrum-695 023 Kerala, India


Published by Transworld Research Network 2011; Rights Reserved Transworld Research Network T.C. 37/661(2), Fort P.O., Trivandrum-695 023, Kerala, India Editor Parvin Mehdipour Managing Editor S.G. Pandalai Publication Manager A. Gayathri Transworld Research Network and the Editor assume no responsibility for the opinions and statements advanced by contributors ISBN: 978-81-7895-518-6


Preface Cell, is an atmosphere of life within the tissues which is supported by the surrounded neighboring partners, capable for initiating further events. Cancer, puzzling and questioning, is characterized with many undiscovered genes, facts, pathways and patterns. There is available knowledge in cancer, but we need to revise and edit them. Restoration is a dictating item for cancer research. The edition of this book was aimed to highlight the role and impact of “cell biology” and “genetics” in the cancer clinic. In addition, this endeavor was particularly aspired to provide the key and basic information for the clinicians who are interested in bridging paradigm, at a glance. Although the history of cancer is indicative of an appreciable efforts of clinicians and scientists in medical history, but still the lack of comprehensive insight towards cancer development and progression is obvious. An interaction between cell biology and genetics play a key role in cancer-diagnosis, prognosis, and prevention. However, to access the initial roots in cancer, and by considering the patients’ benefit the strong multi- bridging between the events in cell biology, genetics, and clinical characteristics are required. By considering the manner of multidisciplinary events in cancer development and progression, a trustable movement could lead the clinicians and/or scientists towards a knowledgeable, resolvable, effective, and appropriate strategy through which an early, and a rapid clinical management could emerge and be applied for cancer diagnosis and treatment. This book contains 6 chapters: Chapter 1, section 1 is focused on the importance of pedigree analysis, gene mutation, cell cycle genes, including cyclin D1, cyclin E, CDC25A; and ki67 as a proliferation index in breast cancer. Finally, the prognostic role of CDC25A expression was initially highlighted. In chapter 1, section 2, the three- hit hypothesis in ATM-gene, the tumourigenic role of three triggers at genomic- and somatic-level in astrocytoma, and the importance of pedigree analysis was included. In chapter 2, targeting signaling molecules for drug design and patient stratification is discussed with remarks on successes and challenges in this area. In chapter 3, nutritional facts about macronutrients in cancer genetics; importance of diet and nutrients in tumorigenesis are discussed. The anti-


tumourigenic effect of vitamin D3 in lung tumors and the expression of Ki67 proliferation index in animal is highlighted. Interaction between ER and PR downregulation, folate deficiency, and hypermethylation status of RARbeta2 and ERalpha genes in human breast tumours are also tinted. In chapter 4, the cancer-testis antigens with limited expression in male germ cells of the testis and different types of tumours; and the importance of blood-testis barrier in eliciting the immune response at other sites of body were discussed. In chapter 5, the ethical rules for protection of genetic information, genetic testing as a predicting tool in cancer clinic, and sharing the genomic test results are discussed as beneficial and preventive tools for the family members. In chapter 6, the cyclic Bridging programme for the Cancer Clinic is representative of modeling in cancer management, cyclic bridging programme, and the applicable examples of different chapters of this book in cancer clinic. It is important to keep the cancer paradigm at the “top of our thoughts” and “ deep in our heart”. Parvin Mehdipour


Contents

Chapter 1.1 Strategies in cell biology and genetics: Establishing priorities in the cancer clinic Parvin Mehdipour

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Chapter 1.2 Three-hit hypothesis in astrocytoma Parvin Mehdipour

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Chapter 2 Cell signaling in cancer treatment and prevention Mina Tabrizi and Leila Youssefian

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Chapter 3 Nutritional facts about macronutrients in cancer Saeed Pirouzpanah and Fariba Koohdani

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Chapter 4 Potential of cancer-testis antigens as targets for cancer immunotherapy Mohammad Hossein Modarressi and Soudeh Ghafouri-Fard

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Chapter 5 Ethics in the cancer clinic Javad Tavakkoly Bazzaz, Elahe Motevaseli Mahsa M. Amoli and Bagher Larijani Chapter 6 The final words :The cyclic bridging programme for the cancer clinic Parvin Mehdipour

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Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 1-20 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

1.1. Strategies in cell biology and genetics: Establishing priorities in the cancer clinic Parvin Mehdipour Department of Medical Genetics, School of Medicine,Tehran University of Medical Sciences Tehran, Iran

Abstract. An appropriate cooperation between cancer, genetics, and cell biology requires a clear frame of definitions at molecular – cellular level and an ideal targeted translation of the known facts to the clinic. The pedigree-based plan in cancer genetics may guarantee to select the relevant targets according to type of cancer distribution in different generations. Our findings in breast cancer patients could highlight the prognostic impact of cyclin E, CDC25A expression and a significant association between CDC25A with poor overall survival. At molecular level, the heterozygous carriers of ATM D1853N polymorphism showed a significant difference between patients affected with primary breast cancer and controls as well.

Introduction Cancer philosophy might be a frame of mind through which complementary insights could provide some avenues to reach a better understanding in this field. Classification of cancer mostly relied on different, but limited, categories including histopathology and clinical features based on specific parameters. Correspondence/Reprint request: Professor Parvin Mehdipour, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O.Box 14155-6447 Tehran, Iran E-mail: mehdipor@tums.ac.ir


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However, still traditional genetics and pathology retain their place in the clinic. These points give a wide spectrum of values in cancer and it could be considered as a “Medical Globe” with unlimited satellites for variety of studies, investigations, and combination of managements. Cancer is a biological, psycho-somatic, genetic, and environmental disease making it a“multifactorial complex”. In this chapter, it was aimed to include the selected targets including the protein expression assay at cellular level in cell biology and DNA mutation detection at molecular level in genetics, which play important roles through interaction between these two paradigms in cancer development and progression. It was also attempted, at a glance, to highlight these relevant behaviors in basic science which could be linked to the clinic.

Pedigree and gene mutation Since discovery of cells by Levan Hooke in 1666, it was automatically dictated to the scientific media that “cell” is the origin of life. This was significant date which initiated the pre-cytogenetic era. But, without a flowing pedigree, it could not facilitate and promote the future of life through inheritance. Pedigrees could be considered as key systematic packages in cancer research programming for diagnosis, prognosis, and prevention without which no optimal success could be achieved. The value and importance of pedigrees is unique, and regarding the selection of targeted genetic study, sometimes irrespective of the cancer type, we might reach the same decision for looking at the same specific gene(s) in cancer-prone families. This is due to the involvement of molecular and/or biological characteristics which many cancers have in common. Although the following examples are related to breast cancer, there are reasonable number of pedigrees in which there is the clustering of brain and breast cancers. For instance, the Li-Fraumeni syndrome (LFS) and also the pedigrees without any germline mutation of P53. A reliable database, together with pathological, para-clinical, and clinical outcome data during the follow-up study and data on the therapeutic protocol(s), rely on a standard consultation with a long follow-up period. This package of information could lead us to achieve a better understanding of cancer and choosing more complementary ways to solve this global disaster. Our previous work was conducted on the pedigree of 542 female patients affected with primary breast cancer (BC) and a total of 6,220 relatives [1]. The cancer distribution through four generations in different degrees of


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relatives and the maternal-paternal lines were also considered. Among the BC-probands, 29.9% and 53.9% had a positive family history (FH) of BC and other malignancies excluding BC, respectively. The occurrence of brain, uterine, and colorectal cancers was significantly higher in maternal-line relatives. A total of 477 affected relatives were reported, including 34 with brain tumours, mostly distributed in 3rd and 2nd generations but equally among 1st and 2nd degree relatives. Remaining cancer types were found to be gastric (n=63), lung (n=49), uterine (n=44), hematopoietic (n=40), and colorectal (n=30). We also did not find any relation between having a positive FH of BC and developing early onset BC. Cancer is a genetic disease and age dependent. Familial BC could be associated with early age of onset, however, it was reported that contrary to what was expected, the early-onset BC cases in Iranian population tended to be associated with a negative FH of the disease in comparison with the non-early-onset cases (P = 0.083) [2]. By considering a specific race and population, the original and fundamental genetic make up of individuals is relatively same, and they have normal traits in common, but the people who are affected with cancer could have diversity in the required/acquired nature of some genes which could be de novo, or inherited from their ancestral lines. The known genes could be detected and defined through the pedigrees, but an important and very attractive corner in cancer research is known as “predisposing genes�, very general name with specific aim, but mostly undiscovered. The people who carry such gene(s) could have an increased risk and might be half - way to being affected with cancer or multi-cancers during their lifetime. Therefore, the pedigree- based research may assist to find these genes. According to another report, it was shown that amongst cancer-prone families, only 0.1% have cancer family syndromes, but hereditary cancer is found to be 5-10% [3]. The important insight is to identify the characteristics of inherited and sporadic cancers through which researchers and clinicians might be able to illuminate the involved mechanisms including the cellular biology and genetic of cancer. Cancer-prone families, clustering cancer with an inherited pattern, were initially known in the 19th century. Since then, it has been considered as a Mendelian autosomal dominant trait [4]. In previous review articles, the core discussion was focused on the importance of hereditary cancers, germ line mutations, and protein expression. They have stated that Knudson’s two-hit model of tumourigenesis is the simplest mechanism and is probably operating in most of retinoblastoma (RB), LFS, familial breast/ovarian cancer, MEN1, NF2 tumours, some NFl component tumours and RCCs in VHL. In these cases, the germ line alteration of a single allele of the susceptibility gene is sufficient to cause an altered phenotype, but


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not in ATM. The heterozygosity in ATM mutation was also reported [5]. Carriers are common in the population (about 0.5%-1%), leading them to have an increased risk of breast cancer [6]. The contribution of ATM-heterozygosity for elevating the relative risk in breast cancer patients was supported by some studies but not confirmed by others. In view of this discrepancy, the frequency of ATM germline mutations in a selected group of Dutch patients with breast cancer was examined and revealed to be 8.5% [7]. The informative and updated pedigrees during the follow-up studies could be considered as a director for our plan in diagnosis, prognosis, and prevention for the probands and their affected or healthy relatives. A pedigree- based research in cancer genetics would guarantee an appropriate planning through which the cell biological and genetic targets could be relevantly selected according to the type of cancer distribution in different generations and within different degree of affected relatives. In the following cancer-prone pedigree, breast cancer was distributed in generations III, and IV with different age of onset varying between 31 and 62 years (Fig.1). However, the tracing strategy of specific genetic targets could be applied in probands and their relatives.

Figure 1. Partial pedigree of a cancer-prone family (P. Mehdipour’s archive). The vertical numbers on the left: are indicative of generations. The numbers bellow of each symbol: present the horizontal distribution of family members. BC: breast cancer with age of onset on the right side. Uter: uterus cancer with age of onset on the right side. Arrow on individual 7 of generation 4 refers to the proband affected with BC at Deceased female; deceased male. age of 50 years.


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Cell cycle territory and cancer Cell cycle The ability of a cell to divide is vastly regulated, and when it is defective, cancer could develop. The temporal and physical progression of a cell through cell division by numerous genes is named the cell cycle. A critical phase is the transition from either a stationary (G0) or a growing cell (G1) into the phase of active DNA synthesis (S) immediately prior to cell division. Cell cycle plays a critical role in cancer and deregulation of involved genes is most relevant to the process of carcinogenesis. Our knowledge of the functional mechanism could facilitate understanding of how the genetic alterations cause an uncontrolled tumour cell growth. The global information in cellular territory will aid in developing avenues for appropriate therapy and prevention of cancer. The cellular protein factors regulate the forward succession of the cell cycle and are termed cyclins (8). The selected and investigated cell cycle targets in this chapter include cyclin D1, cyclin E, and CDC25A (Fig. 1).

Figure 2. The partial scheme of the selected targets involved in cell cycle regulation. Cell cycle phases: G1, G2: Gap1 and Gap2 S: DNA synthesis M: mitosis.


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Cyclin D1 Cyclin D1 plays a critical role in G1 to S transition and is considered as a putative proto-oncogene. It is a 36k Dalton protein encoded by the CCND1 (bcl1) gene located on chromosome 12q13. CCND1 amplification and/or Cyclin D1 overexpression have been found in variety of human tumours. It is reported to be useful for identification of mantle cell lymphoma and in the context of lymphoid tumours. Deregulation of cell cycle machinery is known to be key event in cancer leading to proliferation, tumourigenesis and progression (8). By considering the crucial role of cyclin D1, Rb, and CDK2 in breast cancers, they have developed a highly specific inhibitor of CDK4/6 activity (PD-0332991) that may have an impact on the therapeutic strategy in breast cancer. They have reported that the acquired resistance to PD03322991 was specifically associated with attenuation of CDK2 inhibitors, indicating that redundancy in CDK functions represents a determinant of therapeutic failure. Complementary definitions of cell-cycle regulatory pathways, may lead to utilization of inhibitors in the cancer clinic. However, the prognostic role of cyclin D1 in breast cancer was found to be controversial, but cyclin D1b overexpression is associated with poor prognosis. In addition, no definite statement could confirm the significant clinical benefits of these biomarkers (9). In addition, the mean Âą SD of cyclin D1 expression was found to be 53.3 Âą2.04 by flow-cytometry in our patients affected with primary breast cancer, which was also observed by immunofluorescence (Fig.3/a-2). Estrogens have attracted different paradigms in cancer research including breast cancer cells in vivo, and in vitro. Estrogens could influence cellular function in different tissues and rate of proliferation in breast cancer cells [10-12]. Estrogen receptor (ER)-positive breast cancer cell lines and antiestrogens functioning on specific cells through the G1-phase are also of concern in cancer [13, 14]. In G/S transition, the complex formation of cyclin-dependent kinases (Cdks) and regulatory cyclins are required. D-type cyclins participate in identifying extracellular growth stimuli and also in initiating the G1- transition [15]. There is an interesting cooperation between the overexpression at mRNA- and protein- level of cyclin D1 and estrogen induced proliferation in normal breast epithelium [16]. But, still there is great concern regarding the independent capacity of estrogen which could probably regulate the expression machinery of cell cycle, either in normal, or in malignant cells.


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Cyclin E The decisive moment in cell cycle through which DNA replication occurs is due to the protein kinase complex composed of cyclin E and Cdk2. Increased and prolonged production of cyclin E in human breast cancer is associated with poor prognosis[17]. The E-type cyclin includes cyclins E1 and E2 encoded by two different genes located on chromosomes 19q12 (CCNE1) and 8q22.1 (CCNE2) respectively in humans. The complex of cyclin E with cdk2 is considered as a key element which facilitates the transition from G1 to S phase [18, 19]. Deregulation, including overexpression of cyclin E could affect the G1/S transition. Cyclin E could be considered as a guard in which different degree of overexpression has been previously reported in variety of cancers leading to a poor prognosis [20-21]. However, deregulation of cyclin E was found to be 25% in patients affected with invasive carcinoma. The overexpression of cyclin E, by application of immunohistochemistry and western blot assays, has been previously observed. The oncogenic function is derived from genomic instability and might be originated from deregulation of cyclin E due to centrosome amplification, and through replication complex assembly [22-23]. This role of cyclin E has been suggested by considering the biological role of the protein [19,24,25] and overexpression in human breast cancer [26,27]. Elevated expression of cyclin E1 protein in breast cancer is reported to be correlated with high Ki67 proliferative index and an increased mitotic index [28]. Such a harmonic behavior indicates that cyclin E1 could promote proliferation of cells in neoplasia which could highlight its oncogenic ability. Previous reports have shown estrogen proliferative ability to cause breast cancer and facilitate the G1/S transition through Cdk2 activation. In addition, c-Myc and cyclin D1 play important roles by initiating pathways that diverge at cyclin E1-Cdk2 activation [29]. Although the upregulation of cyclin E2, primarily, depends on cyclin D1, the chromatin remodelling factor, “chromodomain” helicase, DNA binding protein 8 (CHD8), and E2F transcription factors are also required. However, cyclins E1 and E2, by having a distinct correlation with the positive status of estrogen receptor could pave the way for clinicians toward an endocrine therapy for breast cancer patients [30]. The mean ± SD of cyclin E expression in our patients affected with primary breast cancer was found to be 31.9 ± 12.9 of whole counted cells. Although deregulation of cyclin E could be considered as an early event in the oncogenic process, but additional biological behavior could affect and alter the manner of cyclin E expression. How does deregulation of cyclin E


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occur? The point is that assay of the overexpression at mRNA level could not definitely guarantee overexpression at protein level solely. However, by considering the clinical correlations during the follow-up study, and comparing degree of expression at cellular level this question provided the convincing outcome in our previous publication [31]. However, there was a harmonic expression of Cyclin D1 and cyclin E, either individually, or as coexpression of these two key factors of cell cycle in breast tumour cells (Fig. 3/a-3, 4). CDC25A The Cdc25 phosphates is considered as a candidate oncogene characterized by overexpression in variety of tumours and was found to be overexpressed in approximately 30% of breast carcinomas [32]. The available data on cdc25 was achieved in vivo. Cdc25A is a member of cell division cycle 25 (CDC25) phosphatase-families regulating the cell cycle progression and is a highlighted gene in the cell cycle. The overexpression of CDC25A speed ups the entrance to S phase and could also lead to genomic instability. In addition to its critical role in G1 to S transition, CDC25A is considered as a putative proto-oncogene as well. Checkpoint activation in G1 or S phase results in G1/S transition or S progression arrest via at least two potential factor inhibitors: the CDK inhibitor p21WAF1/CIPI and Cdc25A. The activity of both is essential for multiple S phase requirements [33]. It is active in G1 and through S phase and also plays a role in activating Cdk2 [34, 35]. Cdc25A expression is induced by Myc [36] and E2F [37]. Cdc25A is also reported to be phosphorylated and activated in vitro by cyclin E-Cdk2 [35]. Believing in the cooperation of genes in cancer, cyclin E and Cdc25A are overexpressed in breast carcinoma cells [32, 38]. The previous review has focused on in vivo roles of CDC25 phosphatases. It is known that CDC25 phosphatases are considered as ratelimiting activators of cyclin-dependent kinases (CDKs) and CHK1/CHK2mediated checkpoint pathway [39]. It regulates G1/S, and G2/M boundaries and is involved in the regulation of different events of mitosis and full activation of nuclear CDK1/Cyclin B complex. They have highlighted that high levels of CDC25A and CDC25B are detected in various human tumours. Deregulated expression of CDC25A may also lead to genomic instability in human and promotes RAS- or NEU-induced mammary tumour development in murine models. In this review, the authors have noted that the CDC25A controls the G1/S transition in human cell cultures, accompanied by an increase in CDK2/Cyclin E activity. But, the oncogenic function, as well as


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the mechanisms of cancer-associated overexpression of CDC25A, requires further definition. Moreover, the frequency of human CDC25A gene SNPs in metastatic and non-metastatic breast cancer patients has recently been reported [40]. They found an association between the 263C/T polymorphism with breast cancer and metastasic risk. In addition, -51C/G polymorphism was only associated with breast cancer risk. They have concluded that these two polymorphisms of CDC25A gene could be candidate markers for early diagnosis. Regarding the influence of environmental factors, CDC25A could be inferred to mediate G2/M cell cycle arrest by 3,3'-Diindolylmethane (DIM) in MCF-7 and MDA-MB-468 breast cells. It was shown that DIM could downregulate the expression of CDK 2 and 4, and Cdc25A, which plays an important role in G2/M phase [41]. DIM is a potential chemopreventive phytochemical derived from Brassica vegetables and is given here just as an example to highlight the interaction between nutrition and cancer cell biology which will be discussed in chapter three. Besides the available data in vivo and in vitro, we considered a reasonable clinical follow-up period and included three cell cycle genes to evaluate protein expression in patients affected with primary breast cancer [31]. In this attempt, the positive mean Âą SD of CDC25A expression was found to be 39.4 Âą 14% by flow-cytometry. This data could emphasize the prognostic role of CDC25A expression alone or in combination with Ki67. However, CDC25A was associated with poor overall survival. Ki-67 Ki-67 is an index for measuring the growth and proliferation of neoplasms. The gene is located on chromosome 10, and the size of the gene is approximately 300,000 base pairs organized into 15 exons. The ki-67 antigen is a nuclear non-histone protein and is expressed in proliferating cells during late G1, S, M, and G2 phases of the cell cycle, but it is absent in resting (G0) cells.Ki67 is a key index for cell proliferation which reflects how it is tightly controlled and regulated [33]. A recent review reflected an overview of ki67, in which the utilization of biomarkers has been considered in breast cancer patients [9]. They have focused on the applicable biomarkers including estrogen receptor (ER) and progesterone receptor (PR), HER2 and Ki67. It has been reported that Ki67 has been recognized as a poor prognostic index and a predictive factor for effective therapeutic response of positive cells treated with anti-hormonal and chemotherapy.


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They have also highlighted Ki67 as a proliferative and prognostic marker in early stage breast cancer, leading to a statistically significant correlation with clinical outcomes by considering nuclear grade, age, and mitotic rate. An overexpressed Ki67 in more than 20–50% of breast cancers was a high risk sign for developing recurrent disease. The Ki67 index was revealed to be correlated with survival. However, they have noted that Ki67 could be used as a reliable prognostic index in breast cancer. It is also concluded that, although ki67 is used as a marker, further complementary studies are required. However, in our patients affected with primary breast cancer, the mean ± SD of cells with positive expressions of Ki67was 10.08 ± 6.77 by flow-cytometry [31]. In addition, the protein expression at cellular level was also assayed by immunofluorescence (Fig.3/b-1).

Interaction of protein expression in cell cycle genes It is known that cyclin D1, cyclin E, CDC25A, and Ki67 are the key targets in cancer development and progression. Now, I would like to include our findings of these targets in the patients affected with primary breast cancer [31]. Cyclin E and CDC25A were analyzed in 44 breast carcinoma by flow cytometry. The expression for cyclin E or CDC25A was found among 34.1% of tumours. The expression of cyclin E and CDC25A was positive at 31.9 ± 12.9 and 39.4 ± 14% of whole counted cells, respectively. Normal breast tissues of healthy women who underwent breast cosmetic surgery (n = 11) were used as controls. The frequency of cells with positive expression of Ki67, CDC25A and cyclin E were 10.08 ± 6.77, 9.02 ± 4.22 and 7.16 ± 5.08%, respectively, which found to be significantly lower (P < 0.001). Considering the pedigree analysis, high expression of cyclin E and CDC25A proteins was observed in patients with a positive family history (P = 0.22 and P = 0.54, respectively). There was diverse cooperation and interaction between these cyclins together with ki67. Expression of Ki67 along with either of the cyclins was also analyzed in the patients. The average co-expression of CDC25A and Ki67 was 56.1± 17.2%. The expression of CDC25A in cells with negative Ki67 could be observed in 2.4±1.5%. Expression of both cyclin E and Ki67 was found in 27.7 ± 13.6% of the cells. The positive expression of cyclin E in cells with negative Ki67 (E+/K-) was 2.8 ± 3.7%. Cyclin E demonstrated significant expression in 27.3% (12/44) of patients who had high expression of Ki67 (P= 0.016). However, low and moderate levels of cyclin E were expressed in most cells with low Ki67 level. CDC25A was significantly expressed in 34.1% (15/44) of cases that concurrently expressed Ki67 at greater than 50% level (P = 0.001). There was


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significant association between the expression of Ki67 and either of the two cyclins (P < 0.001). As far as histopathological classification concerns, the low expression of cyclin E and CDC25A was frequently observed in invasive ductal carcinoma (IDC). Ki67 was significantly expressed in 48.8% of tumours with IDC (P= 0.033). The majority of patients with low expressions of Ki67 and cyclin E were not apparently associated with axillary lymph node metastasis. However, a high co-expression of cyclin E and CDC25A more frequently led to relapse. Regarding the clinical follow-up study, an overall survival rate in patients with high CDC25A expression versus low was significantly decreased (P = 0.028). In multivariate Cox regression analysis, the higher rate of CDC25A-expression in tumours was a significant independent predictor of overall survival with hazard ratio of 0.404 (95%CI: 0.175-0.935). In conclusion, cyclin E or CDC25A expression was correlated with Ki67 labeling. Apparently, there might be interactions between cellular cyclin E and CDC25A expression status in relation to the aggressive phenotype in human breast tumour. The available data include no frequency of protein translation in the experimental system by both flow cytometry and immunofluorescence with consideration to the evaluation of these biological targets for the clinical outcome. In addition, we have demonstrated that CDC25A was independently associated with poor outcome for overall survival. Patients with higher ratios of negative cyclin E-/positive Ki67 and negative cyclinE/negative Ki67 had poor prognosis in regards to disease free status. This might highlight the individual influence of cyclin E on survival. However, the lower rate of cells with characteristic E-/K+ expression seems to be associated with longer overall survival. Almost identical results on the possible interaction of CDC25A on overall or disease free survivals were found. However, to date, no available evidence supports a possible impact of these co-expressions on survival. Moreover, there was cooperation between the protein expression of Ki67 with either cyclin E or CDC25A. Our finding could highlight the “prognostic impact of cyclin E, or CDC25A expression individually or in combination of either Ki67, cyclin E or CDC25A. CDC25A was associated with poor overall survival.� However, such a combination of cell cycle regulator expressions could be clinically valuable for prognosis of potentially unfavorable outcomes of breast cancer [31]. A previous investigation had revealed that the overexpression of the G1phase regulatory proteins c-Myc and cyclin D1 could affect estrogen action through G1 phase of the cell cycle in the derived clonal MCF-7 breast cancer


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cell lines [42]. Inducible expression of either c-Myc or cyclin D1 was sufficient for S-phase entry and to activate cyclin E-Cdk2. They have stated the following facts regarding such interaction: 1. 2. 3. 4.

Increased expression of c-Myc failed to induce cyclin D1, and vice versa. Cyclin E-Cdk2 is activated following c-Myc or cyclin D1 expression. Cdk4 is activated by induction of cyclin D1, but not c-Myc. Induction of c-Myc or cyclin D1 led to activation of cyclin E-Cdk2 and hyperphosphorylation of pocket proteins. 5. c-Myc- and cyclin D1-induced activation of cyclin E-Cdk2 is associated with loss of other genes including p21 and association with p130. However, to highlight the importance of c-Myc, Cdc25 phosphatase and up-regulated cyclin E, they are capable of renovating cyclin E-Cdk2 complexes to induce the activated form [43-45].

The cell cycle at a glance There are four distinct phases in the mammalian cell cycle: S phase, in which DNA is replicated; M phase, in which the chromosomes are separated under two nuclei during the process of mitosis, “Gap” phases, which include G1 and G2, through which the cell organizes itself to enter to the S- and/or M- phases, respectively. Interestingly, the vast majority of human cells would not pass these phases and remain in G0. Meanwhile, there is a decisive checkpoint in the mammalian cell cycle called the Restriction point (R). This point is framed by the following routes: • •

The pre- restriction point, in which external factors, such as growth factors could influence the cell by leading it to progress through G1. The post- restriction point, in which an autonomous cell division cycle could be completed [46].

Regulation of cell cycle and cancer at a glance Cancer is due to multiprocessing genetic alterations in genes and their products leading to uncontrolled cell machinery including cell proliferation, differentiation or programmed cell death (apoptosis). Amongst the mutated genes in human cancer, the majority are directly related to the cell cycle. •

Oncogenes are mutated genes leading to stimulate cell proliferation.


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Tumour suppressor genes are capable to block abnormal growth and lose this normal characteristic by inactivation during tumourigenesis. The products of oncogenes and tumour suppressor genes eventually control transcription. Alterations in gene expression profile could lead to defective cellular behavior and diversity in genotype-phenotype correlation at cellular level.

Cyclins and cell cycle regulation at a glance A regulated process of cell cycle is programmed to control cell proliferation during normal growth and development. This machinery includes tumour suppressor genes, the cyclin-dependent kinases (cdks), their regulatory partners the cyclins (cyc), and the family of the cdk inhibitors. The cyclins are named “cyclins” according to their emergence during the cell cycle. The cyclical characteristic of the cyclins is partly due to a cell cycle regulated transcription of the responsible genes, and proteolysis is responsible for their disappearance (Fig.2).

• • • • •

In early G1, cyclin D is present and could be activated by CDK4 and -6 to form cyclin D/CDK4 (or -6) complexes. Such a complex is responsible for the initial phosphorylation of retinoblastoma in G1. In mid G1, cyclin E is generated and by binding to CDK2, create a complex which phosphorylates pRb in late G1. In S phase, cyclin A in complex with CDK2 leads to further phosphorylation of pRb. At the G1- to S phase transition, cyclin A is made. In G2 and M phases Cyclin B is made.

The mitogenic stimulation of resting cells could lead to expression of cyclin D1 through the activation of Ras. There are also other attractive insights in cancer cell biology. Previous investigators have reviewed the cell cycle regulatory system and presented a cascade of events involving the retinoblastoma tumour suppressor family (pRB, p107, p130), the cyclin-dependent kinases, the cyclins, and the cdk inhibitors [47]. They have highlighted the E2F activity as a required factor for transactivation of genes including c-Myc and cyclin E, DNA replication and mitosis to regulate the promotion of S phase. They have also discussed the importance of p53 involved in the control of cell cycle and apoptosis, as well as the control of glycolytic and oxidative metabolism, pten related to cancer development, and also metabolism homeostasis; and pRB which,


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besides regulating transitions between cell proliferation and terminal differentiation through cell cycle, is also the facilitator of cancer-type metabolism.

Role of ataxia telangiectasia-mutated gene It was stated that the molecular profiling of the transcripts or proteins within an individual tumour could be used as important prognostic and therapeutic clinical information either for the cancer patients or their relatives [48]. In this regard, the critical role of ATM is considered as a remarkable molecular target in this chapter and is discussed in section 2 as well. The ataxia telangiectasia-mutated (ATM), is involved in cell-cycle checkpoints and numerous damage repair signalling pathways. The ATM is a member of the phosphatidylinositol 3-kinase-like family, and its role in the repair of DNA double-strand breaks is due to a range of DNA-damaging agents including ionizing radiation [49]. This gene is located on chromosome 11q22-23, consisting of 66 exons, and it is involved in numerous damage repair signalling pathways and cell-cycle checkpoints [49-50]. The Loss of heterozygosity in the ATM gene has been reported in approximately 40% of human sporadic breast cancers, and the available results suggests that the heterozygous carriers of ATM-mutations provide an increased risk for the development of breast cancer [51-54]. A high percentage of ATM germline mutations were demonstrated among patients with sporadic breast cancer [7]. They have reported that “ATM heterozygotes have an approximately ninefold-increased risk of developing a type of breast cancer. This group of patients are characterized by frequent bilateral occurrence, early age at onset, and long-term survival. The specific characteristics of their population of patients may explain why such a high frequency was not found in other series”. The ATM D1853N polymorphism in this gene was previously reported by us and showed a significant difference between patients affected with primary breast cancer and controls as well [55]. This molecular alteration of ATM gene could be also confirmed by immunofluorescence with a low expression at cellular level (Fig.3/ c-2). In a recent publication, the association between ATM gene polymorphisms and breast cancer risk was evaluated [56]. They has performed a meta-analysis based on currently limited available evidence. They have stated that “the ATM 5557G>A (D1853N) polymorphism was significantly correlated with breast cancer risk when all studies were pooled into the meta-analysis (recessive model: odds ratio, OR = 0.67; 95% confidence interval (CI) 0.51–0.89).”


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A group of investigator has also evaluated the association between ATM exon 39, 5557G > A polymorphism and breast cancer susceptibility by metaanalysis [57]. They have considered subgroup analyses according to ethnicity and found that the ATM D1853N polymorphism was significantly associated with increased risk of breast cancer in the South American population but not in European and mixed populations. However, it was not clear how they finally concluded that “the ATM D1853N polymorphism is not associated with breast cancer risk”. They have stated that “this polymorphism is not an independent risk factor for the development of breast cancer”.

Figure 3. Expression profiling of the selected cell cycle proteins in breast tumour cells P.B.C.: Primary breast cancer / IDC, grade II. a)

b)

c)

Expression of cyclin D1, and cyclin E in a P. B.C. patient a-1: dapi filter, a-2: Cyclin D1, IG2a, conjugated with FITC, a-3: Cyclin E, IgG2b, conjugated with R-Pe, a-4: Co-expression of cyclin D1 and cyclin E. Items 2, and 3, show the high expression of Cyclin D1 and cyclin E respectively; item d, indicates the harmonic expression of both Cyclin D1and cyclin E. Expression of ki67 index in the same P.B.C. patient b-1: dapi filter, b-2: ki67, IgG2b, conjugated with FITC reflecting different degree of expression. Expression of ATM-gene in the same P.B.C. patient c-1: dapi filter, c-2:ATM, IgG1, conjugated with Cy5, reflecting a low expression of ATM- protein.


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However, our data in the Iranian breast cancer population [55] does not support the outcome of the above mentioned meta analysis published by Gao, et al., [57]. The main reason is due to the distribution of specific polymorphism in certain population, and screening of this polymorphism in different populations could define whether the ATM 5557G>A polymorphism plays a critical role in the target patients or not. This aim seems to be important and the Meta analysis alone may not clarify this question. In addition, a common ATM variant, IVS38-8T>C in cis with the 5557G>A (D1853N) ATM polymorphism, has been suggested to be associated with bilateral breast cancer as well [58]. However, it is very important to consider the ethnicity, to define the exact origin of population, and not rely solely on heterogeneous populations. Screening of D1853N- ATM polymorphism may provide a powerful tool for clinical management of breast cancer patients and their relatives.

Conclusion It was aimed to bridge cell biology and genetics to the cancer clinic. In this regard a pedigree- based research was designed. Protein expression of the key targets in cell cycle i.e., cyclin D1, cyclin E, CDC25A, ATM; and the proliferating Ki67 index were included. The prognostic impact of cyclin E, CDC25A expression individually or either combination of Ki67 with cyclin E or CDC25A could be highlighted. The significant association of CDC25A with poor overall survival could be considered as a matter for bridging strategy. In addition, the results of alterations at molecular- and protein expression- level in ATM gene were also discussed. In this regard, the ATM D1853N polymorphism revealed a significant difference between patients affected with primary breast cancer and controls.

Acknowledgements An unlimited and prompt cooperation of patients and their relatives is sincerely appreciated.

References 1.

2.

Mehdipour, P., M. Atri, E. Jafarimojarrad, S.S. Hosseini-asl, M.Javidroozi, Laddering Through Pedigrees: Family History of Malignancies In Primary Breast Cancer Patients. Asian Pacific J Cancer Prev, 2003. 4(3): p.185-192. Atri, M., E. Jafarimojarrad, M. Javidroozi, and P. Mehdipour, Lack of association between early onset of breast affected relatives in an Iranian population. Familial Cancer, 2003. 2(2): p. 117–118.


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Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 21-35 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

1.2. Three-hit hypothesis in astrocytoma Parvin Mehdipour Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran 1417613151, Iran

Abstract. Astrocytoma as a primary tumour is the core item in this section in which, by considering a pedigree-based research approach, the involvement of Ataxia-Telangiectasia (AT) gene is investigated. The two-hit -hypothesis of Knudson’s model is given to clarify the process of tumourigenesis in retinoblastoma. Lack of any available data for any hit hypothesis in brain tumours was the reason why the three-hit hypothesis in astrocytoma was formulated and included in this section. ATM alterations were reported in medulloblastomas, gliomas, but not in astrocytoma. The polymorphism D1853N was only reported in healthy individuals and medulloblastomas. This polymorphism was detected in a 28 year-old female- proband affected with astrocytoma. As the triangle initiator of the three-hit hypothesis, D1853N is the first germ line hit, IVS 38- 63T→A is the second hit, and IVS38- 30 A→G is the third hit. In addition, the D1853N polymorphism was on a different allele than from IVS 3863T→A and IVS 38- 30 A→G. However, these three triggers could be considered as triangle initiators for the course of evolution in astrocytoma. However, the present data could highlight the crucial role of specific intronic region of the ATM gene involved in cancer and also the importance of pedigree analysis. This polymorphism might be useful as a marker in astrocytoma. Correspondence/Reprint request: Professor Dr. Parvin Mehdipour, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O.Box 14155-6447, Zip code 14176-13151, Tehran Iran. E-mail: mehdipor@tums.ac.ir


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Introduction The brain, as a remarkable organ, governs the whole human body, world, edits the faith of the globe, and can coordinate harmony. Brain tumour is characterized by abnormal and uncontrolled growth of cells within the brain or located outside the brain within the skull classified as cancerous or noncancerous. But, still there are pitfalls in resolving the real picture of its nature. Different aspects in tumours of the central nervous system (CNS) were previously published [1]. They have stated that the general classification of astrocytic tumours relied on tumour location within the CNS system, age, gender, growth potential, spectrum of invasiveness, morphological features, progression and clinical outcome. In addition, genetic events play a critical role in tumour development. Primary tumours originating from glial cells, are called gliomas, and include astrocytoma, glioblastoma, and ligodendroglioma. Approximately three quarters of all gliomas are astrocytomas which are classified into four grades, including Grade 1 ( Pilocytic Astrocytoma), Grade 2 ( Low-grade) Astrocytoma, Grade 3 (Anaplastic Astrocytoma), and Grade 4 (Glioblastoma). In spite of its lengthy medical history and unlimited scientific documentation, still, its entire biology is not totally understood and is not well defined. Cancer, basically, reflects the regulation of cell growth and differentiation. Oncogenes with their novel properties are inappropriately expressed, and the nature of tumour suppressor genes (TSGs) was reported as recessive trait, containing loss-of-functional mutations [2]. It might follow the 'two-hit hypothesis', in which both alleles of a particular gene must be altered before the specific phenotype is manifested. This is due to the fact that when only one allele of a gene is damaged, the second is capable of producing the normal protein. However, mutant TSG usually acts as a recessive trait whereas mutant oncogene alleles are dominant and characterized by gain-of-functional mutations. The germline mutations of TSGs are passed on to the offspring of affected probands which increase the likelihood of cancer diagnosis in subsequent generations. This might increase the incidence of cancer for the family members. However, the tumour types depend on the nature of TSG mutation as well [3]. There are pitfalls in diagnosis and treatment of brain complications regarding the medical management of patients affected with brain tumours. Considering a significant estimation of new cases and deaths per year as a result of brain tumours, cooperation of medical and basic Sciences is essential for appropriate planning. This important process could try to


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provide the diagnostic tests, prognostic and predictive factors within a frame of biomarkers, towards screening of populations, genetic counselling, and early detection. All these steps could facilitate selection of appropriate protocol(s) for effective treatment and planning for pre-malignant lesions by considering the patients' benefit. There are many peculiarities in the central nervous system including the following questions in brain tumours (B.T.): 1. 2.

Do the brain tumour cells really have the same genomic origin? What is the spectrum of complexicity of organization and functions in B.T.? 3. How could we define the cellular diversity and cellular signaling in B.T.? 4. Is there any cooperation between exonic and intronic domains of specific genes in B.T. which possibly could lead to a successful outcome through the medical follow-up period of the patients’ life affected with B.T.?

Ataxia-Telangiectasia (AT) AT is reported by different investigators as a multisystem, autosomal recessive disorder with progressive neuronal degeneration. AT is caused by mutations in the ATM gene which encodes the nuclear protein kinase ATM. The reported mutations were correlated with variant phenotypes in ATpatients. AT and related AT-diseases are among the best studied and defined of the human neurological syndromes due to DNA damage response defects [4]. The typical AT phenotype could be due to homozygosity or composite heterozygosity for null ATM alleles. These situations would lead to truncation of ATM or inactivation of gene by missense mutations. Truncated ATM and other inactive forms of ATM could be unstable, therefore as it was also stated elsewhere, detection of protein expression in the cells of classical AT is not successful and they are mostly lacking [ 5,6]. It is also important to consider the pattern of accumulation on cell cycle, proliferation, differentiation and maturation resulting in diversity of cell functions. There are many other factors playing an important role in the medical complications in which ATM gene is involved. The occurrence of events, including translocations and telomeric fusions, and an increased rate of telomeric shortening which could be found in AT-patients, were also reported [7]. Regarding ATM mutations, it could occur throughout the entire ATM gene, and according to the previous reports, there are no hotspots or high frequency of mutations [8].


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Cancer might develop in approximately one-third of AT patients. Children might be affected with Acute Lymphocytic Leukemia (ALL) or B cell lymphoma, or T cell lymphomas and T cell Prolymphocytic Leukemia (TPLL). Non-lymphoid malignancies are seen predominantly in older AT patients. Telomeric stability and instability in human tumours have not been understood well in vivo. However, a recent publication by us [9] on alterations of telomere length in human brain tumours showed highly significant difference in meningioma and astrocytoma. The higher grade meningioma and astrocytoma tumours showed more heterogeneity in telomere length, and it might be concluded that the shortening process of telomeres is an early event in brain tumours. ATM protein expression was variable in the tumour glioma cell lines and at low level in primary tumours [10, 11]. At the cell line level, tissue culture and several established GBM cell lines from glioma specimens were used and the expression levels of ATM, p53, and p21 proteins were determined by Western blot [11]. There was a relationship between ATM protein expression and radiosensitivity, but with variability in the primary gliomas. This data emphasizes that attenuating ATM gene expression may be a successful strategy in the treatment of GBM tumours. However, our recent publication focused on the comparison of the mRNA expression of cyclin D2, P53, Rb and ATM, between astrocytoma and meningioma of human tumours with consideration given to different grades [12]. It has been shown that higher grade (III and IV) of astrocytoma tumours had up-regulation for cyclin D2 and ATM genes, and downregulation of P53 and Rb genes. Considering different templates of up-and down-regulation for these gene interactions in different types of brain tumours, it seems that these genes do not have a unique model of interaction. Although the application of multiple techniques were previously not available, innovation in tumour development could be based on the discovery of Knudson [13,14] who proposed that cancer development depended on two molecular events in retinoblastoma, including an inherited germ-line mutation in a tumour suppressor gene followed by a complementary mutation within the organism's life by inactivating the other allele of that TSG. This valuable historical phenomenon was not detected in other tumours for thirty-seven years; however, an additional step of tumour development could be proposed by proof as “the three-hit hypothesis� by considering different paradigms including molecular genetics and cell biology [15].


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Hypothesis Knudson’s model (13) has revealed the role of germline mutation in inherited retinoblastoma in which the process of tumour development could be beautifully clarified by a complementary somatic mutation. The Knudson hypothesis is derived from observations of accumulating mutations at DNA level. The multi-mutation theory on cancer was initially proposed by Nordling ( 16) and later formulated by Knudson whose work led indirectly to the new insight in cancer- discovery of cancer-related genes. Knudson suggested the requirement of multiple "hits" to DNA for cancer formation. Development of malignancy depends on the activation of protooncogenes by stimulating cell proliferation and deactivation of tumour suppressor genes by keeping proliferation in check. In addition, the first "hit" in an oncogene, and a damaged Rb1 gene as a TSG in retinoblastoma would not, as a sole alteration, lead to cancer. The two-hit hypothesis was initially published by Knudson in patients affected with retinoblastoma. He emphasized the requirement of two independent genetic events. The Retinoblastoma protein (pRb) was the first tumour-suppressor protein discovered in human retinoblastoma which was also considered as a tumour-survival factor [13,3]. Knudson has beautifully clarified tumourigenesis by his two hit hypothesis which included the first hit being a point mutation inactivating one copy of Rb1 (asTSG), and the second hit being a large deletion leading to loss of functioning of the TSG allele. These events lead to a non-functioning copy of the TSG and finally the development of cancer. However, the developmental role of ATM gene in cancer was not previously proposed in tumours. To varnish and highlight our knowledge in cancer, the following paradigms could be considered: 1.

Cancer cell biology, in which the researchers would be able to define the wide spectrum characteristics of normal-and malignant-tissues. By considering the required timing from initial cancer development and progression, specific biological behavior of the pre- and post- malignant cells gradually alter the original nature of tissue from normal to cancerous. 2. Clonal evolution might occur in an unchecked population of cells which is also called somatic evolution. This process shows how cancer originated and becomes more malignant [17, 18]. This avenue could pave the way to direct cells to choose their response to drugs, i.e., to be resistant or sensitive, which is the matter of pharmacogenetics.


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3.

Natural selection which considers the alterations in the cellular metabolism priority of the few cells with new genetic makeup that enhance their survival or reproduction, continue to multiply, and act in a dominant manner through which tumours could rapidly grow [19]. This may lead to genetic heterogeneity in cancer as well. However, the system instability was considered as a major contributing factor for genetic heterogeneity. Genetic instability could facilitate the acquisition of other mutations which have occurred due to defects in DNA repair [20]. 4. Regarding stem cells, biological behaviors vary in different types of cancers and also depend on the cancer stem cells which have the capacity of replication and could generate differentiated cells.

Three- hit hypothesis Available papers within the avenue of the molecular-hit hypotheses seem to be very limited and, so far, only include two papers; one on colorectal cancer and another on neurofibromatosis. The first study was performed on colorectal cancer (CRC) cell lines and primary CRCs [21]. They have shown that the two-hit model requires modification of the APC– tumour suppressor gene, leading to an optimal level of Wnt activation. They stated that “some had acquired third hits at APC which mostly was copy number gains or deletions and could be protein-truncating mutations". They have also noticed that the “third hit was significantly less common when the second hit at APC had originated by copy-neutral loss of heterozygosity”. The second paper reported patients affected with Neurofibromatosis 2 (NF2) who developed bilateral tumours of Schwann cells [22]. They revealed the occurrence of two mutations in these patients and have suggested that “more than two mutations may be necessary for NF2 development”. However, no available publication could be found on astrocytomas. Many studies are available at cytogenetic and descriptive molecular level. However, the initial finding of the three-hit hypothesis in brain tumour was published on astrocytomas by us [15].

Three- hit hypothesis in astrocytoma The ataxia telangiectasia (AT) gene was cloned at chromosome band 11q22~q23. It is mutated in AT patients and plays an important role in the double-stranded break DNA repair pathway and cell-cycle checkpoints. The ATM gene gives rise to a ubiquitously expressed transcript of ~ 13 kb which


Three--hit hypothesis in astrocytoma

27

encodes a nuclear protein of 350 kDa with homology to PI3 kinases [23]. It was reported that patients with AT have a predisposition to cancer including lymphocytic, chronic and B-cell origin leukemias, mucinous adenocarcinoma of the stomach, medulloblastomas and gliomas [24-26 ]. In this regard, two polymorphisms including D1853N and F858L were reported in medulloblastoma tumours of 19 children not affected with AT [27]. The available reports reveal around 479 mutations in this gene but there was no available report on brain tumours [28]. The main aim of our investigation was to trace the molecular alteration in exon 39 of the ATM gene in an astrocytic tumour of a proband, and through her pedigree generate a patterned model in direction of tumour development which is summarized from our previous publication [15].

Materials and methods Genetic counselling was performed to draw the pedigree. All relatives in this study were informed, in detail, regarding the nature and purpose of the study, and they, voluntarily, decided to participate in this investigation. The pathologic diagnosis in a 28 year- old female- proband was found to be differentiated astrocytoma, cystic grade I (in four grade classification) and sized 2 x 3 x 4 cm. Sampling included peripheral blood (PB) and brain tissue of proband for detecting germline and somatic events respectively. The proband's relatives included parents, 1 sister, 3 brothers, 1 nephew, 4 first cousins and 2 second cousins (Figure 1). Fourteen PBs were also sampled from healthy family members, as the familial controls within the pedigree (group I), and fourteen age-matched controls were also sampled (group II) without any family history of cancer or other medical complications. The details of standard techniques for DNA extraction, PCR, sequencing cloning, and immunofluorescence are available in our publication [15].

Results and discussion Pedigree could be laddered to screen the classic D1853N polymorphism through different generations (Fig. 1). Two novel intronic alterations i.,e, IVS 35- 63 T→A and IVS35- 30 A→G within spilicing sites could be found in proband’s peripheral blood and tumour respectively (Fig. 2). This polymorphism together with IVS 35- 15 G→C could be detected in proband’s mother (IV/10 (Fig. 1 and 2).


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Parvin Mehdipour

Figure 1. Pedigree of proband affected with astrocytoma and her relatives. Arrow indicates the proband affected with astrocytoma. Left main box illustrates information on peripheral blood sample. Right main box illustrates information on tumour sample for proband. Column left/top of each main box presents alteraions of the 3' splicing site of intron 38. Column left/bottom of each main box presents alteraions of exon 39. Left –side numbers of each individual presents age of healthy relatives at the time of sampling and age of deceased for two affected persons in the pedigree. Right-side numbers of each individual presents systematic reference number of individuals through each generation modified (from: ref.15).


Three--hit hypothesis in astrocytoma

29

It was stated in our previous paper that “genes are efficient and characterized by the programmed commitments. Cancer genes are cooperative and contribute their efforts in a harmonic manner through the tumourigenic process”[15]. Some facts were also highlighted which included specific organic targeting for each cancer gene, sharing by different genes, i.e., oncogenes, tumour suppressor- and predisposing-genes. The core reason for malignant behavior is due to the manner and timing of initiation, promotion, and progression of tumours through which we could find the roots in the function of genes and proteins. Complementary information on tumour genesis in brain tumours is not fully known which could be due to heterogeneity and lack of data on the involved genes in brain tumours. Two novel heterozygously intronic changes including IVS 35- 63 T→A and IVS35-30 A→G, found in a proband within 3' regions of splicing site, highlights the importance of this alteration during tumour genesis of our proband (Fig. 2). As a matterof fact, the splicing needs some intronic DNA sequences in which the 5' and 3' regions of intron are involved and play an important role supporting our finding [28]. As a matter of fact there is interaction between gene mutation and protein expression. In this regard, there are limited reports, even at brain tumour cell line level, on the protein expression of ATM. It was reported that ATM participates in controlling the S-phase checkpoint through CDK2dependent phosphorylation leading to degredation of Cdc25A [11, 29]. In order to confirm the diversity of ATM-protein expression, we analyzed individual cells by immunofluorescence which revealed low levels of ATM protein (Fig.3). The hit model proposed by Knudson (13) for the development of Retinoblastoma was based on family history, bilateral/ multifocal cases and young age at onset. However, in our investigation the heterozygous alterations in ATM could be confirmed by cloning results revealing the involvement of two alleles. Three categorical events for creation of the three-hit could be summarized: 1.

The first hit (D1853N) is a germline inherited trait from proband’s mother. This was the required fundamental change for initiation of an evolutionary process in astrocytoma. 2. The second hit is IVS 35- 63T→A as a result of the 1st somatic evolution in the proband’s peripheral blood and tumour. This trigger has apparently occurred at a very early moment in the zygotic stage of the


30

3. 4. 5. 6. 7.

Parvin Mehdipour

proband before differentiation of peripheral blood and brain tissues (Fig. 1: generation V/14). The third hit (IVS35- 30 A→G) is a somatic alteration which might have occurred in an astrocyte or during the development of an astrocytoma. These intronic triggers were required for promoting tumour genesis. These facts explain the catalytic and complementary role of events considered as the key triggers at genomic and somatic levels, respectively. There is correlation between severity of cancer and the number of hits in a specific gene. The role of environmental factors. The specific pattern at molecular- and expression- level in different populations.

A sad scenario in nature is played. The initiation and termination of two evolutionary events in a proband affected with astrocytoma has occurred which could have been passed on to her offspring, but the proband was deceased, and there was no chance and sign of inheritance any more. This might be called “genetic block” or “natural prevention”.

a:

b:

Figure 2. Partial sequence results of proband affected with astrocytoma; illustrating three- hit hypothesis through an evolutionary process (15). a: Alterations of ATM gene in Blood tissue b: Alterations of ATM gene in brain- tumour tissue. Arrows at N-positions, show the molecular alterations, as heterozygosity.


Three--hit hypothesis in astrocytoma

a

31

b

Figure 3. Expression of ATM protein by immunofluorescence. a: illustrates the proband’s tumour cells with DAPI filter. b: illustrates the conjugated ATM protein antibody with FITC in the same tumour cells, showing a low expression of protein.

The present thee-hit hypothesis could now be considered as an effective event in the course of tumour genesis in astrocytoma. In addition, to highlight the importance of genetic counselling, the proband’s relatives were informed and warned regarding such data as partial risk factor to avoid consanguineous marriage.The suggestion and performance of further genetic test(s) for the relatives in this pedigree seemed to be helpful. In addition, four unreported polymorphisms including D1853N, IVS 38-8 T→C, F858L, and P872T were also found by us in brain tumours other than medulloblastoma [30]. This was not the end of the scenario of the ATM gene.Up to the this point the importance of ATM involvement and the three-hit hypothesis were discussed in the brain. Now it is aimed to unfold a continuing story of the ATM gene in breast cancer. Further findings by us involved D1853N which was also reported in breast cancer patients [31]. The case- control study revealed that the frequency of this polymorphism in cases, internal and external controls was 31.0%, 26.9%, and 12.5% respectively. Regarding the Odd Ratio, a significant difference was observed between the patient-carriers and external healthy controls (P=0.001), and the difference between the internal-carrier-control and external controls was statistically significant as well (p=0.004). This finding could be considered as a predisposing marker in our population and specifically in the cancer-prone pedigrees. Tumour suppressor genes (TSGs) influence the cancer cellular territory, properties and abilities. However, there are various fields including genomic, proteomic and metabolic alterations for generating cancer cells including


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Parvin Mehdipour

mutation, aneuploidy, and expression by the involvement of the promoter. Although the occurrence of mutations in ATM play a vital role in tumour evolution, but the spectrum of protein expression could be considered as an important function and governing ability of this gene in different tumours. This paradigm is included in our current project. This field also requires the evaluation and confirmation of ATM-protein expression according to our previous report [15]. The ATM and p53 genes have functional mechanisms in common, but it seems that in spite of the broad involvement of p53 in variety of tumours, the status of this gene in human tumours cannot predict patients’ outcome [32]. So far the molecular process in cancer development is known to be programmed by mutations through a cascade of events that mediate the following genes and actions respectively: 1. 2. 3. 4.

Inactivating tumour suppressor gene leading to cell proliferation. Inactivating DNA repair gene. Alterations in proto-oncogene leading to activation of oncogene. Inactivating several tumour suppressor genes.

As it is obvious, there are two major, a primer and a final, gates which initiate malignant behavior and end up producing the malignant feature of a specific tissue. Inactivation is the key event for these genes except for oncogenes. But, cancer development seems to be beyond such pattern and lists of alterations at biological level are also involved. Some Genetic testing for high-risk individuals for specific cancers are available, but not for brain tumours. Early detection of inherited predisposing genetic trait for cancer, or a de novo alteration could lead the clinician toward cancer-preventing interventions. This could directly improve quality of life in high-risk relatives of cancer probands within pedigrees. Through tracing genomicsomatic evolution, we would be able to achieve a more complementary definition of the genome and its alterations beyond the previous outcomes; and consider it as the organisms’ measurable genes. This together with cell biology could lead scientists to the right direction in combating cancer by targeted therapy. Considering the involvement of ATM in healthy individuals in whom the cycling machinery function seems to be apparently normal, and in the cancer population with an abnormal and continuously cycling cell cycle, it could be presumed that this powerful gene has its own regulatory mechanism which may govern cells.


Three--hit hypothesis in astrocytoma

33

The clinical management for brain tumours relies on imaging, biopsy, tumour grading, and optional treatments including surgery and radiation. There are peculiarities in the genetic - based pattern of cancer development in primary and secondary stages, and there are also problems in clinical outcome for low- and high-grade astrocytoma. However, the fundamental genetic mechanisms and their inflection by environmental factors are important mechanisms through which we might achieve the new avenues for understanding the unknown corners of cancer to prevent or ideally cure it. One possible way would be by re-establishment of tumour-suppressor function. However, to achieve this strategy, a more complementary knowledge of TSGs, including the ATM gene is required.

Conclusion The three- hit hypothesis includes an inherited D1853N as a first hit at germ line, IVS 38- 63T→A as a second hit, and IVS38- 30 A→G as a third hit. These triggers could be considered as triangle initiators for the course of evolution in astrocytoma. The present data could address the crucial role of the specific intronic region of the ATM gene, and also the importance of pedigree analysis. This polymorphism might be useful as a marker in astrocytoma as well.

Acknowledgment I would like to thank the patient’s relatives for their volunteer participation in this investigation and providing the complementary Information. In spite of the absence of their loved patient, they have fully cooperated. They apparently believed in Science which is sincerely appreciated.

References 1. 2. 3. 4.

Kleihues, P., and W.K. Cavence, Pathology and Genetics of tumours of th Nervous System. 1st Ed. International Agency for Reseach on Cancer, Lyon, 1997. Croce, C. M., Oncogenes and cancer. The New England journal of medicine, 2008. 358(5): p.502–11. Sherr, C. J., Principles of tumour suppression. Cell, 2004. 116(2): p.235–46. Shiloh, Y. The ATM-mediated DNA-damage response: Taking shape. Trends Biochem Sci., 2006.31(7): p.402–410.


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12. 13. 14. 15.

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Becker-Catania, S. G., G. Chen, M. J. Hwang, Z.Wang, X. Sun, O. Sanal, et al., Ataxia- telangiectasia: Phenotype/genotype studies of ATM protein expression, mutations, and radiosensitivity. Mol Genet Metab, 2000.70(2): p.122– 133. Gilad, S., A. Bar-Shira, R. Harnik, D. Shkedy, Y. Ziv, R. Khosravi, et al., Ataxia-telangiectasia: founder effect among north African Jews. Hum Mol Genet, 1996. 5(12): p.2033-7. Khanna, K. K., K.E. Keating,S. Kozlov, S.Scott, M.Gatei,K. Hobson,et al., ATM associates with and phosphorylates p53: Mapping the region of interaction.Nat.Genet., 1998. 20(4): p.398–400. Ko, L. J., and C. Prives, p53: Puzzle and paradigm. Genes Devel., 1996.10 (9): p.1054 – 1072. Kheirollahi, M., M. Mehrazin, N. Kamalian, P. Mehdipour, Alterations of telomere length in human brain tumours. Med Oncol, 2010. DOI 10.1007/s12032-010-9506-3. Chan, D. W., D.P.Gately, S. Urban, A.M.Galloway, S.P. Lees-Miller, T. Yen,et al., Lac y. Int J Radiat Biol, 1998.74(2): p.217– 224. Tribius, S., A.k of correlation between ATM protein expression and tumour cell radiosensitivitPidel, and D. Casper, ATM protein expression correlates with radioresistane in primary glioblastoma cells in culture. Int J Radiation Oncology Biol Phys, 2001. 50(2): p.511–523. Kheirollahi, M., M. Mehrazin, N. Kamalian, P.Mehdipour, Expression of cyclin D2, P53, Rband ATM cell cycle genes in brain tumours. Med Oncol, 2009. DOI 0.1007/s12032-009-9412-8. Knudson, A. Mutation and cancer: statistical study of retinoblastoma. Proc Natl Acad Sci, 1971.68 (4): p.820–3. Knudson, A. G., Two genetic hits (more or less) to cancer. Nature reviews. Cancer, 2001.1(2): p.157–62. Mehdipour P, L. Habibi J. Mohammadi-Asl, N.Kamalin, M. Mehrazin, Three-hit hypothesis in astrocytoma: tracing the polymorphism D1853N in ATM gene through a pedigree of the proband affected with primary brain tumour. J Cancer Res Clin Oncol, 2008.134(11): p.1173–1180. Nordling, C. A new theory on cancer-inducing mechanism. Br J Cancer, 1953.7(1): p. 68–72. Fodde, R., and R. Smits, Cancer biology: A matter of dosage., 2002. 298(5594): p.761-3. Nowell, P. C. The clonal evolution of tumour cell populations. Science, 1976. 194(4260): p. 23–8. Merlo, L. M., J.W. Pepper,B.J. Reid, and C. C. Maley, Cancer as an evolutionary and ecological process. Nature Reviews Cancer, 2006. 6(12): p.924–935. Ye, C. J., G. Liu, S.W. Bremer, H. H. Heng, The dynamics of cancer Chromosomes and genomes. Cytogenet Genome Res, 2007. 118: 237–246. 21. Segditsas, S., A.J. Rowan, K. Howarth, A. Jones, S. Leedham, N.A.Wright, et al., APC and the three-hit hypothesis. Oncogene, 2009. 8.28(1): p.146-55.


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22. Woods, R., J.M. Friedman, D.G. Evans, M. E. Baser, H. Joe, Exploring the twohit hypothesis in NF2:tests of two-hit and three-hit models of vestibular schwannoma development. Genet Epidemiol., 2003.24(4): p.265-72. 23. Savitsky, K., A. Bar-Shira, S. Gilad,S., Y.Ziv, L. Vanagaite,D.A. Tagle, et al., A single ataxia telangiectasia gene with a product similar to PI–3 kinase. Science, 1995. 268(5218): p.1749– 1753. 24. S axon, A., R.H. Stevens, D.W. Golde, Helper and suppressorTlymphocyte leukemia in ataxia-telangiectasia. New Eng J Med, 1979. 300(13): p.700–704. 25. Haerer, A. F., J. F. Jackson, C.G. Evers, Ataxia-telangiectasia with gastric adenocarcinoma. JAMA, 1969.210(10): p.1884–1887. 26. Gatti, R. A., E. Boder, H. V. Vinters, R.S.Sparkes,A. Norman, K. Lange, Ataxia- telangiectasia: an interdisciplinary approach to pathogenesis. Medicine, 1991. 70(2): p.99–117. 27. Liberzon, E., S.Avigada, I. J.Cohen, I.Yaniv, S.H. Michovitz, R. Zaizov, ATM gene mutations are not involved in medulloblastoma in children. Cancer Genet Cytogenet., 2003. 146(2): p.167–169. 28. HGMD, Human gene mutation dbase at the institute of medical genetics inCardiff. http://www.hgmd.cf.ac.uk/ ac/gene.php?gene=ATM . 2006. 29. Matsuoka, S., M.Huang, and S.J.Elledge, Linkage of ATM to cell cycle regulation by the ChK2 protein kinase. Science, 1989.282(5395): p.1893–1897. 30. Habibi, L., M. Ghoudsi, A.F. Sarraf Nejad, R. Sharifi, P. Mehdipour, Analysis of Exon 19 and 39 of ATM Gene in Brain Tumours; Considering the P53 accumulation in Patients with ATM Alteration. J Sciences, IRI, 2008. 19(3): p.211-216. 31. Mehdipour, P., M.Mahdavi, J. Mohammadi-Asl, M.Atri, Importance of ATM gene as a susceptible trait: Predisposition role of D1853N olymorphism in breast cance. Med Oncol., 2010. DOI 10.1007/s12032-010-9525-0. 32. Rasheed, B. K., R.E. McLendon, J.E. H.S. Friedman, A.H. Friedman, D.D. Bigner, et al., Alterations of the TP53 gene in human gliomas. Cancer Res., 1994.54(5): p.1324–330.


Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 37-58 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

2. Cell signaling in cancer treatment and prevention Mina Tabrizi and Leila Youssefian Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Abstract. Deciphering the critical cell signaling events in tissue homeostasis and generation of aberrant signaling on the road to cancer development is the focus of many making strides in cancer treatment and prevention. Initially, a historical link between cancer and cell signaling is provided, and the example of the EGFR aberrant signaling discovery is briefly recounted. Targeting signaling molecules for drug design and patient stratification is discussed with remarks on successes and challenges in this area. Subsequently, insights from human germ line mutations in three receptor tyrosine kinases elucidate how goals for cancer specific treatment and use of genotype-phenotype relationship for clinical management has materialized for GIST and MEN2 and has the great potential to dominate medical practice in the near future. Correspondence/Reprint request: M. Tabrizi, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O. Box 14155-6447, Zip Code 14176-13151, Tehran, Iran E-mail: tabrizi@tums.ac.ir


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Mina Tabrizi & Leila Youssefian

Introduction Robert A. Weinberg, in his book, describes cancer as a disease of aberrant signaling [1]. Signaling events are key controlling events that determine the fate of a cell and ultimately the tissue and the organism. Critical events in cancer like the cell cycle and apoptosis are controlled by signaling between and within cells. Tissue homeostasis, the precisely controlled steady state between the birth rate and the death rate of cells, is under constant dictation of messages or signals sent and received between cells and between cells and their environment. Temporary overshooting proliferation may be normal in wound repair or in hormone-regulated physiological cycles, but when the tissue permanently moves away from homeostasis, atrophy and hyperplasia are two possible outcomes. Tissue homeostasis is not automatic or a passive event. Tissue homeostasis is controlled by an intricate balance of positive and negative signals controlling apoptosis, the cell cycle, senescence, differentiation, repair, migration, and cell metabolism [2, 3].

First cellular oncoprotein-cellular transformation by tyrosine phosphorylation Transforming proteins like v-Src demonstrate the importance of tyrosine phosphorylation in growth control. History of cell signaling significance in cancer began in 1911 when Peyton Rous, a pathologist, isolated the etiological agent for sarcomas in chicken. The etiological agent was identified to be the Rous Sarcoma Virus (RSV). Much later, in the 1950's, phosphorylation was identified as a reversible modification that can alter the activity of an enzyme. In 1971, v-Src was identified as the only RSV gene required for cell transformation. In 1976, c-src, cellular homologue and progenitor of v-src, was discovered in normal cellular DNA. In 1977, v-src gene product was discovered to be a phosphoprotein. In 1978, v-Src protein was found to have intrinsic kinase activity [4]. In 1980, Hunter et al. provided proof that v-Src phosphorylated tyrosine residue (Table 1) [5]. One-third of all cellular proteins in eukaryotic cells are covalently modified by protein phosphorylation at any one time. Majority of phosphorylation reactions occur on serine and threonine residues. 0.01 to 0.05% of cellular phosphoamino acid content is phosphotyrosine. Signaling molecules compromise 20% of the ~19,000 human coding genes. Only 1.5% of genes present in the human genome have documented mutations in human


Cell signaling in cancer

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cancer cell genomes. This amounts to 291 distinct genes. There are ~100 dominant oncogenes. Thirty percent of 100 dominant oncogenes are receptor tyrosine kinases and 14% are non-receptor tyrosine kinases. Humans have 58 known RTKs, which fall into 20 subfamilies. All RTKs have a similar molecular architecture, with ligand-binding domains in the extracellular region, a single transmembrane helix, and a cytoplasmic region that contains the protein tyrosine kinase (TK) domain. RTK structure, mechanism of activation, and key components of the intracellular signaling pathways that they trigger are highly conserved in evolution from the nematode Caenorhabditis elegans to humans, which is consistent with the key regulatory roles that they play. Furthermore, numerous diseases result from genetic changes or abnormalities that alter the activity, abundance, cellular distribution, or regulation of RTKs. Numerous diseases result from genetic changes or abnormalities that alter the activity, abundance, cellular distribution, or regulation of RTKs. Mutations in RTKs and aberrant activation of their intracellular signaling pathways have been linked to cancer, diabetes, inflammation, bone disorder, arteriosclerosis and angiogenesis. These connections have driven the development of a new generation of drugs that block or attenuate RTK activity [6]. Table 1. History of link between cancer and cell signaling. History of important phenomena in cancer biology

Year

Discovery

1911

Peyton Rous - Pathologist- isolated the etiological agent for sarcomas in chicken- Rous Sarcoma Virus (RSV)

1950’s

Phosphorylation as a reversible modification that can alter the activity of an enzyme v-src was identified as the only RSV gene required for cell transformation

1971 1976

c-src- cellular homologue and progenitor of v-src was discovered in normal cellular DNA

1977

v-src gene product was discovered to be a phosphoprotein

1978

v-Src protein was found to have intrinsic kinase activity

1980

Hunter et al. v-Src phosphorylated tyrosine residues


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Mina Tabrizi & Leila Youssefian

Aberrant receptor tyrosine kinase (RTK) signaling-the EGFR example As mentioned previously, Src was the first transforming protein to be discovered. Later it was realized that the transforming power of Src depended on its tyrosine kinase activity. Upon sequence alignment of Src with other molecules, the cytoplasmic domain of the Epidermal Growth Factor Receptor (EGFR) demonstrated amino acid sequence similarity to Src and this indicated that EGFR like Src contained intrinsic tyrosine kinase activity. Thus it became clear how the EGFR emits signals inside a cell once its ectodomain engages the ligand Epidermal Growth Factor (EGF). The Src-like kinase in its cytoplasmic domain becomes activated, proceeds to phosphorylate tyrosines on certain cytoplasmic proteins, and thereby causes a cell to proliferate [7]. The hunt for other molecules with amino acid sequence similarity to Src was initiated and eventually based on this sequence similarity, two classes of molecules with tyrosine kinase activity were proposed; a class of receptors with intrinsic tyrosine kinase activity similar to EGFR which were later termed the Receptor Tyrosine Kinases (RTKs), and a class containing Src itself which now belongs to a class of molecules called non-receptor tyrosine kinases (NRTKs). In 1984 it was realized that the sequence of EGFR is closely similar to the sequence of the erbB oncogene. This oncogene had been discovered originally in the genome of avian erythroblastosis virus (AEV), a transforming retrovirus that rapidly induces an erythroleukemia. A protein normally used to sense the presence of a growth factor (EGF) had been seized and changed into a potent retrovirus-encoded oncoprotein. Examined further, it was realized that the erbB oncogene lacked sequences present in the Nterminal ectodomain of the EGFR. The erbB oncogene cannot recognize and bind EGF without the N-terminal ectodomain, but it functions as a potent stimulator of cell proliferation. Deletion of the ectodomain allows the resulting truncated EGFR to send growth stimulating signals into cells in a constitutive manner, independent of ligand. Generally, alterations (mutations or deletions) in the genes coding for growth factor receptors (the Receptor Tyrosine Kinases) can provoke ligand-independent firing. Incidentally, structurally altered receptors influence the responsiveness of human tumors to anti-cancer drugs. The mystery behind the reduced requirement of cancer cells for growth factors for their growth and survival was suddenly solved. Whereas, normal cells require growth factors in their culture to grow, cancer cells contain


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Cell signaling in cancer

continuous growth signaling without the need for the growth factor (ligand). The ErbB oncoprotein releases signals very similar to those emitted by a ligand-activated EGF receptor. However, unlike the EGFR, the ErbB oncoprotein can send a constant, non-stop, stream of growthstimulating signals into the cell, thereby fooling the cell into believing that substantial amounts of EGF are present in its surroundings when there may be none [8]. Currently, it is realized that truncated versions of the EGFR are found in a number of human tumor cell types. In many lung cancers the EGFR mRNA lacks the coding sequences carried by exons 2 through 7. This deletion, removing the ectodomain of the receptor, results from alternative splicing of the precursor of mRNA. A variety of Receptor Tyrosine Kinases (RTKs) are either overexpressed or synthesized in a structurally altered form in human tumors. The Platelet Derived Growth Factor Receptor (PDGFR), KIT, and the Fibroblast Growth Factor Receptor (FGFR) are just additional examples of RTKs altered in cancer (Table 2). Table 2. Receptor Tyrosine Kinases (RTKs) Altered in Human Tumours.

Receptor

Ligand

Alteration

Tumor Type

overexpression Non-small cell lung cancer; breast, head and neck, stomach, colorectal, esophageal, prostate, bladder, renal, pancreatic, and ovarian carcinomas; glioblastoma EGFR/ Truncation of Glioblastoma, lung and breast ErbB1 ectodomain carcinomas ErbB2/HER2/Neu NRG, EGF overexpression 30% of breast adenocarcinomas

EGFR /ErbB1

EGF, TGF-Îą

ErbB3, 4 Flt-3

various FL

Kit

SCF

Ret

FGFR3

FGF

overexpression Oral squamous cell carcinoma Tandem Acute myelogenous leukemia duplication Amino acid Gastrointestinal stromal tumors substitutions fusion with Papillary thyroid carcinomas, other proteins, multiple endocrine neoplasia 2A and point mutations 2B overexpression, Multiple myeloma, bladder, and amino acid cervical carcinoma substitutions


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There are four ErbB receptors (EGFR, ErbB2, ErbB3, and ErbB4) regulated by multiple ligands. ErbB2 does not have a ligand of its own due to its truncated ectodomain but does have strong tyrosine kinase activity. ErbB2 is also denoted as HER2 (similar in structure to human EGFR) or Neu (derived from rat neuro/glioblastoma). ErbB3 is devoid of kinase activity and is phosphorylated by ErbB2, which has strong kinase activity, when the two form heterodimers. ErbB3 and ErbB4 bind neuregulins, a family of more than 15 ligands that are generated by alternative splicing. Regulation of the ErbB receptors by multiple ligands yields a broad array of signaling inputs [9]. Overall, signaling inputs from RTKs converge on a relatively limited set of highly conserved core processes, identical to the initial impression that a surprisingly small group of downstream signaling intermediates propagate signals from all RTKs. The choke point widens again as the core processes are linked to the control of transcriptional, cytoskeletal, and other "output" events that define the cellular response. Some examples of core processes are small GTPase cycles, kinase cascades, phosphoinositide signaling, nonreceptor tyrosine kinase activities, and ubiquitylation/deubiquitylation cycles. There is significant redundancy and substantial crosstalk between the subnetworks or modules that constitute the conserved core processes and this has been noted as a characteristic feature of robust and evolvable systems [10]. Negative feedback in a system can define the steady-state level of a response, keeping it constant over a wide range of signaling inputs. Phosphorylation and dephosphorylation cycles are common in cell signaling. RTK phosphorylation is reversed by Protein Tyrosine Phosphatases (PTPs). The Src Homology 2 (SH2) domain-containing phosphatases Shp1 (PTPN6) and Shp2 (PTPN11) are recruited to activated EGFR and promote its dephosphorylation in a negative feedback loop. It is well known that inhibiting Protein Tyrosine Phosphatases (PTPs) with pharmacological agents promotes general activation of RTKs in cells [11].

Targeting signaling molecules for drug design and patient stratification Majority of anti-cancer treatments widely used today were developed before 1975. Prior to 1975, there were no insights into molecular alterations. This was a time when development of therapeutics was not revolutionized by the genetic and biochemical mechanisms of cancer pathogenesis.


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Small-molecule therapeutics and their intracellular targets have been identified through research on the signaling pathways within cancer cells. Protein targets should be chosen whose inactivation is predicted to lead to the cessation of proliferation of tumor cells or to their death by apoptosis. The most successful anti-cancer drugs developed to date have been those that interfere with the functioning of various growth- and survival-promoting kinases like the receptor tyrosine kinases (RTKs). The first and the greatest success story of targeted therapy is Gleevec and it is considered the prototype of targeted therapy. Gleevec is a major victory for anti-cancer drug development because it is vastly superior to all alternative treatments. The story of targeted therapy begins in the 1990's when low molecular weight antagonists of Bcr-Abl tyrosine kinase activity started to be developed. It was realized that the transforming power of Bcr-Abl is in the tyrosine kinase catalytic activity. Gleevec (Imatinib mesylate, STI-571, Glivec) binds the catalytic cleft of Bcr-Abl. Other kinase inhibitors block ATP binding in the catalytic cleft, while Gleevec binds and stabilizes a catalytically inactive conformation of this enzyme. Although Abl kinase domain shares ~42% amino acid identity with a large number of other tyrosine kinases, the inhibitory effects of Gleevec on Bcr-Abl were found to be relatively specific. Gleevec also inhibits PDGFR α and β, Kit, and Arg (Abelson-related gene) protein. Only four out of approximately 90 or so human tyrosine kinases are inhibited when Gleevec is used at therapeutic concentrations [12]. Proliferation of Bcr-Abl-dependent cells could be inhibited at drug concentrations as low as 40 nM, indicating a high affinity of Gleevec for the catalytic cleft of the tyrosine kinase domain. Cells that depend on Bcr-Abl for survival can be forced into apoptosis by Gleevec’s inhibition of Abl kinase function. Initial clinical trials began in 1998. Remission from disease was achieved in all of the 31 treated CML patients. By 2002, six thousand patients had entered clinical trials of Gleevec. Early-stage CML demonstrated 90% response. Microscopic analysis of blood smears demonstrated profound shift in the cellular composition of blood. PCR analysis demonstrated extraordinary decline in BCR-ABL mRNA in blood. In 50% of patients with translocated Philadelphia chromosome, the translocatin was no longer detectable by karyotype of WBCs. Sixty percent of patients who had previously progressed to blast crisis responded to Gleevec, but they generally relapse after a period of some months [13]. If a drug such as Gleevec succeeds in generating clinical remissions that are durable over many years’ time, its inability to kill the stem cells of a CML may represent an acceptable limitation. Gleevec is a major victory of


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anti-cancer drug development because it is by far the best we got in treating this otherwise progressive disease. However, candidate drugs that kill only the transit-amplifying cells create the illusion of victory. Though a tumor will shrink substantially in response to treatment, it will rebound quickly once treatment is halted. This is called the “dandelion effect,� referring to the rapid re-emergence of weeds in a lawn following mowing, which cuts off the dandelion leaves but the root is still intact. Elimination of CSCs leaves the bulk of the cancer cell population intact. Tumor mass appears to be unaffected at first, but it will begin to shrink slowly only when these transit-amplifying cells gradually senesce and die in the following months [14]. Rituximab, anti-CD20 monoclonal antibody, is used to treat B-cell tumors. It eliminates tumor stem cells of multiple myelomas. It has also demonstrated efficacy for treating a wide range of B-lymphocyte-lineage tumors [15, 16]. The above mentioned success stories hardly calm the widely felt frustration among molecular oncologists that the potential of their research for contributing to new anti-cancer therapeutics has not yet been realized. This frustration is fueled most strongly by the slow pace at which advances have been made in the treatment of common solid tumors. In the following section, we will talk about gastrointestinal stromal tumors (GIST) and how they have become the solid tumor model for cancer specific treatment. This is a breakthrough in how we approach solid tumors. The ultimate challenge of current drug development is long-term efficacy which translates into extending life expectancy and achieving durable cures. Currently, choices of patients recruited into clinical trials are arbitrary and sub-optimal. The aim of the future is personalized molecular medicine at affordable cost. Detailed characteristics of each patient’s tumor and genetic constitution help in design of a customized therapy. In 2004, two hundred and ninety-one distinct genes, 1.5% of genes present in the human genome, were reported to be mutated in cancer cell genomes. Protein targets should be chosen whose inactivation is predicted to lead to the cessation of proliferation of tumor cells or to their death by apoptosis. As we discussed above, the most successful anti-cancer drugs developed to date have been those that interfere with the functioning of various growth and survival promoting kinases such as the receptor tyrosine kinases. We will talk in more detail about germ line mutations in three receptor tyrosine kinases and the great lessons they have taught the scientific and the medical community in the next section. Currently, indications for the clinical use of certain drugs depend primarily on empirical tests of how various types of human tumors respond to treatment, whereas in the future, indications for clinical use of certain drugs may be based on the known behavior of the targeted proteins in cancer cells.


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Stratification of outwardly similar tumors into narrow subclasses will help researchers and clinicians to match drugs to the specific tumor cell types they can most effectively treat. Researchers now believe that cancer is a collection of more than one hundred diseases, each affecting a distinct cell or tissue type in the body. Though there are eight histopathological categories of breast cancer, certain molecular defects and pathological processes are shared by different human cancers. In a 2002 issue of the New England Journal of Medicine, van de Vijver et al. published, “Stratify breast cancer using functional genomics.� Gene expression arrays show great promise by allowing clinicians to stratify cancers and to classify them into subgroups having distinct biological properties and prognoses. Gene expression arrays, analytical tools of the science of functional genomics, allow a researcher to survey the expression levels of 10,000 or more distinct genes in a tissue preparation. Bioinformatics, computerized analyses of the expression arrays, allows identification of a small subset of these genes expressed either at higher or lower than normal levels. Subsequent correlations of abnormal gene expression can be made with a specific biological phenotype, drug responsiveness, or prognosis. For instance, a certain profile of several dozen genes expressed in a tumor, the tumor gene expression signature, may be enough to serve as a strong predictor of its degree of progression or its association with one or another subtype of cancer [17]. Breast cancer can serve as an example to illustrate situations in oncology where there is a desperate need to distinguish primary tumors that are likely to metastasize from those tumors that will remain indolent and are unlikely to spread. The main prognostic parameters used to predict the course of tumor development have been age, tumor size, lymph node involvement, histologic type of tumor, pathological grade, and hormone-receptor status. These factors, used singly or in combination are not highly accurate predictors of prognoses. Due to lack of accuracy, majority of patients diagnosed with primary breast cancer are treated aggressively. This includes the 15% that will never develop metastatic disease with or without aggressive treatment. Gene expression arrays and bioinformatics provide greater prediction power for clinical course of breast cancer progression approaching more than 90% accuracy. This saves many women from unnecessary chemotherapy, but it is our hope that an expression array analysis provides enough information to allow an oncologist to tailor a treatment protocol resulting in a lasting clinical response and eventually cure [18]. It is rather unlikely that monotherapies will give cures. Successful clinical outcomes will probably depend on combination drugs. Tumor cell


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genomes are genetically unstable. Great numbers of neoplastic cells in tumors continually produce variant subclones which acquire resistance to a drug being used by the patient. These resistant cells will proliferate as other cells in a tumor are eliminated. This is similar to the behavior of bacterial populations becoming resistant to antibiotics; therefore, treatment, at times, may involve simultaneous use of two or more agents having very different mechanisms of action. The probability of acquiring resistance to two agents is much smaller than the probability of acquiring resistance to one agent, but even in infectious diseases we witness multi-drug resistance. Belief in multi-step tumorigenesis, that certain cancer cell phenotypes are the result of combined actions of several genetic and/or epigenetic alterations, suggests targeting all altered gene products. For example, in a tumor Ras may be activated but p53 and PTEN are inactivated. In this case, targeting Ras, p53, and PTEN may improve treatment outcome. In addition, low molecular weight tyrosine kinase inhibitors could act synergistically with monoclonal antibodies on a common target, the EGFR for instance, indicating that therapeutic benefits may also often come from surprising combinations of agents. It is a real possibility that powers of candidate drugs can only be realized in combination with several other drugs. This possibility demands increasing understanding of the cellular signaling pathways [19].

Insights from human germ line mutations in receptor tyrosine kinases In the last section of this chapter, we will explore three different human germ line mutations in three different receptor tyrosine kinases. Gathered data has led researchers and physicians to new realizations and discoveries into their approach and view of cancer, cancer research, and cancer treatment. Thus, models have been generated to revolutionize research and treatment of cancer. As mentioned in the previous chapter, solid tumors remain a challenge in cancer therapy, but gastrointestinal stromal tumors (GIST) have become the solid tumor model for cancer specific treatment. Research of multiple endocrine neoplasia 2 (MEN2) has provided a model by which genotype-phenotype relationship has allowed physicians the ability to stratify patients and this has great implications for clinical management. Finally, hereditary renal papillary cancer research has provided further evidence of epithelial-mesenchymal interaction (EMI) in tissues and this finding in tumor biology will most certainly affect the population of cells we consider in targeting when designing therapeutics [20].


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The solid tumor model for cancer specific treatment Gastrointestinal stromal tumors (GIST) Mutant receptor genes can be passed on to the next generation in an autosomal dominant inheritance pattern because phenotypic expression is delayed until after childbearing years. Alterations in the KIT gene, product of which is a receptor with tyrosine kinase activity, can result in acute myelogenous leukemia (AML), gastrointestinal stromal tumors (GIST), mastocytosis, and seminomas. In 1998, it was clear that 65-80% of GISTs are due to mutations in the KIT gene. The hot spot of mutations was in exon 11 encoding the juxtamembrane domain of the receptor. Specifically, deletion of a single amino acid in the juxtamembrane domain of the KIT receptor was the most common mutation (Fig. 8) [21]. In 2003, mutations in the platelet derived growth factor receptor alpha (PDGFRa) accounted for another 10% of GISTs. This time, the hot spot was in exon 18 which encodes a region lying in the catalytic cleft. Critical mutations resulting in pathology perturb Kit receptor signaling via PLCg, Jak2, Ras/MAPK, PI3K, Src, and the negative regulatory phosphatases Shp1 and Shp2 [22,23]. IT exon 11 mutations are more common in larger tumors and result in adverse prognostic influence. Deletions in this region are more unfavorable compared with point mutations. Patients with exon 11 mutations demonstrate increased response to Gleevec. Gleevec extends the survival of patients with unresectable or metastatic GIST from 20 months to 42 months. Mutations in exon 9 predict increased relative risk for disease progression, but even in these patients, high dose Gleevec can result in progression free survival. Gleevec, as mentioned previously, is a competitive inhibitor of the ATP binding site in BCR-Abl, Kit, and PDGFR. Even in cases where there is no observed Kit or PDGFRa mutation, low doses of Gleevec can prolong progression free survival [24]. Unfortunately, the weakness of this seeming magic bullet lies in development of resistance to the drug. Resistance to Gleevec develops as a result of two to five secondary Kit mutations as observed in separate metastases. On January 2006, the FDA approved Sutent (Sunitinib Malate, SU11248) for renal cell carcinoma. Later, Sutent was used to treat Gleevecresistant GIST. Sutent stopped progression of disease and sometimes it resulted in reversion of disease. Sutent is a small molecule receptor tyrosine kinase inhibitor for Kit, PDGFR, VEGFR, RET, CSF-1R, and Flt3. Other available drugs targeting signaling molecules are Everolimus (Certican, Afinitor, RAD-001) and Avastin (Bevacizumab). Everolimus is a derivative of Rapamycin. Both inhibit the mammalian target of Rapamycin


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(mTOR). This drug received FDA approval in 2009 for advanced renal cancer. Accumulating evidence has also recently implicated mTOR in aging. Avastin is a monoclonal antibody against all vascular endothelial growth factor (VEGF) isoforms. It was the first commercially available angiogenesis inhibitor. It received FDA approval in 2004, in combination with chemo, for metastatic colon cancer and non-small cell lung cancer. It received FDA approval for metastatic breast cancer in 2008 [25].

Genotype-phenotype relationship-implications for clinical management Multiple endocrine neoplasia 2 (MEN2) The rearranged during transfection (RET) gene gain of function germ line mutation results in multiple endocrine neoplasia 2 (MEN2) or familial medullary thyroid cancer (FMTC). On the opposite side of the coin, loss of function in the RET gene product yields intestinal aganglionosis and Hirschsprung’s disease where normal enteric nerves are absent. FMTC is 20% of all medullary thyroid cancer, occurs at an older age than MEN2A or MEN2B, and has an indolent course. MEN2A, or the sipple syndrome, consists of aggressive medullary thyroid cancer in 100% of the cases, benign or malignant bilateral pheochromocytoma in 40-50% of cases, and parathyroid hyperplasia in 10-20% of cases. MEN2B consists of medullary thyroid carcinoma, pheochromocytoma, and neuromas or ganglioneuromas. RET mutation in the catalytic domain is usually involved in MEN2B. Routine genetic testing identifies RET mutation carriers earlier and more reliably. Prophylactic thyroidectomy is usually carried out in all individuals carrying germ line RET mutations. Different RET gene mutations can inform the physician and the patient about time of onset, aggressiveness of disease, and presence or absence of other tumors along with medullary thyroid cancer. Thirty-five to 40% of all cases of MEN2 develop medullary thyroid cancer (MTC). Family history is inadequate. Genetic and biochemical screen often reveal a family history of MTC in patients thought to have the sporadic form. Prognosis is usually good except for codon 804 mutation which results in aggressive disease and death. MEN2A syndrome is the most common presentation with MTC in more than 90% of cases first manifesting between 5-25 years of age. MEN2B syndrome is the least common but most aggressive. Onset is usually in the first year of life. Thus, MEN2 can be clinically classified as seen in (Table 3) [26].


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Table 3. Clinical Classification of MEN2 and Occurrence of Medullary Thyroid Carcinoma (MTC) Associated Tumors and other Diseases [26].

Table 4. Patient Risk Groups Based on Genotype-Phenotype Correlation [26].

Raue and Raue (Fig. 1) propose that by documenting the exact identity of the RET gene mutation and diagnosis of carriers by their exact mutation, affected individuals can be stratified into risk groups [26]. There are more than 50 different RET missense mutations (Fig. 2). RET mutations have been classified into three risk levels using genotype-phenotype correlations. Risk levels are sensitive to age at onset, aggressiveness, and nodal metastases. Placement of affected individuals into risk levels will allow recommendations on timing of prophylactic thyroidectomy and extent of surgery, as illustrated in (Table 4). Genotype can guide the physician to decide whether to intensify screening for pheochromocytoma or hyperparathyroidism in patients with mutations associated with a higher risk. Genotype-phenotype correlation in MEN2 not only predicts age at onset, aggressiveness of MTC, and presence


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Figure 1. Patient Risk Groups; Allelic frequencies of G691S and tumor stage at diagnosis in 56 patients with MEN2 [26].

Figure 2. Distribution of germ line RET mutations found in our series of MEN2 cases according to different RET gene domains, codons, and exons [27].


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or absence of pheochromocytoma and hyperparathyroidism, it can also give us more detailed information. Eighty-five percent of MEN2A involves mutations in codon 634 and only 10-15% of cases involve mutations in codons 609, 611, 618, or 620. MEN2A with Hirschsprung’s disease involves exon 10. MEN2A with cutaneous lichen amyloidosis involves exon 11. Thus, a clear flow chart can be proposed for patient management bases on specific RET mutations predicting prognosis (Table 5). It is our hope to tailor individualized therapies based on patient codon-specific inhibition of tumor growth as we have been able to generate patient codon-specific prognosis [26, 27]. Table 5. Patient Management- Codon Specific Prognosis [26].

Recent findings in tumor biology and therapeutic approachepithelial-mesenchymal interaction (EMI) If cells of a tissue changed their lineage and acquired an entirely new set of differentiated features, this would be called transdifferentiation. For example, epithelial cells around many carcinomas often alter shape and gene expression programs in such a way that they become similar to stromal cells of mesenchymal origin. This great change in cell phenotype, termed the epithelial mesenchymal transition (EMT), will contribute wide plasticity to cells normally committed to being epithelial cells. This transition may endow invasive properties to carcinoma cells into adjacent normal tissues [28]. Human carcinomas are classically compromised of neoplastic epithelial cells and recent evidence supports significance of the tumor stroma in the developing/evolving tumor mass. Several lines of evidence show the substantial role of tumor stromal cells in the growth, survival, invasiveness,


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and metastatic ability of the neoplastic epithelial cells within these tumors. Recently, several studies have been conducted on the significance of hostderived cancer stem窶田ell niche and its role in cancer initiation and progression [29, 30]. First evidence on the role of tumor stromal cells comes from tumor neovascularization studies. In the tumor neovasculature, tumor cells release proangiogenic signals which recruit endothelial cells to the tumor mass [31]. The desmoplastic stroma, as a histopathologic entity, is almost always observed in malignant human carcinomas and is used by pathologists as a diagnostic parameter because of its association with invasiveness and poor prognosis. In addition, the extracellular matrix formed by mesenchymal cells is thought to control carcinoma cell growth and motility. For example, in the mammary gland, the composition and density of the extracellular matrix is a determinant of breast cancer risk [32]. The origins of stromal cells in a tumor have been the subject of intensive investigation and are not well understood yet. To some extent this uncertainty comes from the fact that fibroblasts, both normal and cancer-associated fibroblasts, are heterogeneous, and markers that are shared in common by all fibroblasts have not been defined. Most of the studies focus on the inflammatory/immune cells as the origin of stromal cells which originate in the hematopoetic system, particularly bone marrow, and move to the tumor stroma through blood circulation. Indeed, inflammatory cells derived from bone marrow have been found at high levels in the blood of patients with malignancies. Example of stromal cells derived from bone marrow origin are the endothelial cells and pericytes; however, the extent to which tumor vasculatuer is derived from bone marrow precursors is highly variable and still is a subject to be elucidated [33]. EMT is a necessary step for the reconstruction of the epithelial cell layer after wounding. In addition, EMT is widely used in certain morphogenic steps occurring during embryogenesis. EMT can also be seen at the edge of carcinomas that are invading adjacent tissues. There is strong resemblance between the pathological process of tumor invasiveness and normal steps of embryogenesis and wound healing. Normal complex morphogenic programs such as wound healing and EMT are likely to explain how carcinoma cells are clever enough to acquire the complex cell phenotypes that they need in order to execute the later stages of malignant progression. Cancer cells are so opportunistic that they co-opt and exploit normal biological processes to reach their needs. The first step in metastasis involves major changes in the phenotype of cancer cells within the primary tumor. In order to acquire mobility and invasiveness, carcinoma cells must lose their epithelial phenotype, detach from epithelial sheets and undergo EMT. In EMT, epithelial cells lose their morphology and gene expression pattern and assume the shape and transcriptional program of mesenchymal cells [34].


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Invasive properties of tumor cells are due to some characteristics associated with EMT. In EMT, expression of epithelial cell proteins like Ecadherin and cytokeratins is repressed but expression of mesenchymal cell cytoskeletal filaments like vimentin is increased. Furthermore, epithelial cells in EMT begin to make fibronectin that is normally secreted only by mesemchymal cells. E-cadherin is replaced by N-cadherin during EMT which is also seen during gastrulation in embryogenesis. For example, melanomas are among the most malignant tumors because of their invasiveness. The replacement of E-cadherin by N-cadherin in melanocytes when transformed into melanoma cells may facilitate invasion of the stromal cells. EMT is often induced by stromal signals. Cellular changes that are associated with EMT are mentioned in table 6. There are reasons that during the development of many carcinomas, EMT phenotype is acquired reversibly and when carcinoma cells have completed the multisteps of invasion and metastasis they often revert back to epithelial phenotype by passing through mesenchymal-epithelial-transition (MET). Table 6. Cellular Changes Associated with the Epithelial-Mesenchymal Transition [1]. Loss of cytokeratin (intermediate filament) expression epithelial adherens junction protein (e-cadherin) epithelial cell polarity Acquisition of fibroblast-like shape motility invasiveness mesenchymal gene expression program protease secretion (MMP-2, MMP-9) vimentin (intermediate filament) expression fibronectin secretion PDGF receptor expression avb6 integrin expression

Similar to major steps of embryogenesis, EMT is programmed by transcription factors. The changes in gene expression pattern of transcription factors may facilitate EMT including the organization of a cell's intermediate filament cytoskeleton, its mobility, its association with adjacent cells, its release of proteases and even its display of cell surface integrins and growth factor receptors [table 6]. Several transcription factors are involved in inducing EMT especially when ectopically expressed in certain epithelial cells


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Table 7. Transcription factors orchestrating the Epithelial-Mesenchymal Transition [1]. Name

Initial Identification

Type of Transcription Cancer Association Factor

E47/E2A Associated with EbHLH cadherin promoter FOXC2 Mesenchyme formation Winged helix/forkhead Basal-like breast cancer Goosecoid Gastrulation in frog

Paired homeodomain

SIP1

neurogenesis

Slug

2-handed zinc Ovarian, breast, liver finger/homeodomain carcinomas C2H2-type zinc finger Breast cancer cell lines, melanoma

Delamination of the neural crest and early mesoderm in chicken Mesoderm induction in C2H2-type zinc finger Drosophila; neural crest migration in vertebrates Mesoderm induction in bHLH Drosophila; emigration from neural crest

Snail

Twist

Various carcinomas

Invasive ductal carcinoma Invasive lobular breast cancer, diffuse-type gastric carcinoma, highgrade melanoma and neuroblastoma

[Table 7]. Recent studies have shown the relationship of some of these transcription factors with various types of human carcinomas. For instance, in human mammary ductal carcinoma which lack E-cadherin expression, a transcription factor named Snail is expressed. Slug expression was also found in human breast cancers. Twist showed increased expression levels in invasive ductal carcinoma cells. Furthermore, it has been indicated that both Twist and Slug enable cells to resist apoptosis and anoikis and can protect metastasizing cells from some physiological stresses that would cause their death [35, 36]. Currently, many investigators have this view that cancer is a tissue/organ based-disease and they focus on the role of tissue architecture and epithelialstroma interaction on cancer progression. Most of the cells such as those in the mammary gland act on and reciprocate dynamically with extracellular matrix (ECM) in vivo. ECM provides both biochemical and structural cues for epithelial cells. In recent studies, use of three dimensional cell cultures on biosynthesized scaffolds is extensively increasing. There is evidence which supports the role of 3D cell culture as a reliable model for verifying the effect of developing anti-cancer drugs at preclinical trials. For example, it was


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shown that if malignant MCF-7 cell lines were cultured three dimensionally in the presence of inhibitory agents, they would form reverted acini morphologicaly comparable to nonmalignant MCF10A acini. It has been shown that cell shape has profound influence on cell fate and gene expression and in conclusion architecture by it self is fate determining [37].

Hereditary renal papillary cancer Human germ line mutations in the Met receptor, a receptor tyrosine kinase, are responsible for hereditary renal papillary cancer. Met is abbreviation for mesenchymal-epithelial transition (MET) and this will become clearer in the remainder of this text. Of note is the localization or distribution pattern of the receptor and its ligand. The Met receptor is predominantly expressed on epithelial cells, whereas its ligand, the hepatocyte growth factor (HGF) or scatter factor, resides in the mesenchymal layer of tissues. The mesenchymal layer consists of fibroblasts, vascular endothelial cells, vascular smooth muscle cells, neutrophils and macrophages. Upon HGF binding to the Met receptor, five known signaling pathways can be activated; Ras, PI3K, Jak, B-Catenin, and Notch. During embryogenesis, the Met receptor contributes to mitogenesis and also to morphogenesis. Downstream of the Met receptor; Ras signaling is responsible for scattering and proliferation leading to branching morphogenesis, PI3K signaling is responsible for motility and survival, and the Jak/Stat pathway also contributes to branching morphogenesis. Met inhibitors have been designed that may be categorized into different groups such as kinase inhibitors or antibodies and decoys. Nakamura et al. and others have proven in different systems that HGF induces scattering and cancer cell invasion. There is a crosstalk between tumor cells, which are mostly of epithelial origin with the Met receptor on their surface, and stromal cells with HGF, the Met receptor ligand. In addition, factors that induce HGF release from the stromal layer, such as IL-1, PGE2, FGF, TGF-a, and PDGF are released by cancer cells in the epithelial layer (Fig. 3). NK4 is a HGF inhibitor with anti-invasion/metastases, anti-angiogenesis, and anti-growth properties. Work by Nakamura et al. and others on the Met receptor and HGF beautifully illustrates the importance of being aware of the EMI in biology and tumor biology. Evidence is accumulating to emphasize the significance of the EMI [37, 38]. This leads to a broader topic of the tissue microenvironment. Significance of the tissue microenvironment has been promoted by Dr. Mina J. Bissell, a pioneer in this field, since the 1970’s. For years, Dr. Bissell has been lecturing and writing about how when we think about cancer and its cure, we must also consider the biochemical


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and biophysical cues cells receive from the extracellular matrix, neighboring cells, the immune system, and soluble factors such as growth factors, cytokines, and hormones [39].

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33. Gao, D., Mittal, V., The role of bone-marrow derived cells in tumor growth, metastasis initiation and progression. Trends Mol Med, 2009. 15: p. 333-343. 34. Thiery, J.P., Epithelial-mesenchymal transitions in development and pathologies. Curr Opin Cell Biol, 2003.15 (6): p. 740-6. 35. Kalluri, R., Weinberg, R.A., The basics of epithelial-mesenchymal transition. J Clin Invest, 2009.119 (6): p.1420-8. 36. McAllister, S., Weinberg, R.A., Tumor-Host Interactions: A Far-Reaching Relationship. J. Clini. Oncology, 2010. 28 (26): p.4022-4028. 37. Vahidnezhad, H., Youssefian, L., Jeddi-Tehrani, M., Akhondi, M.M., Rabbani, H., Shokri, F., et al., Modeling breast acini in tissue culture for detection of malignant phenotype reversion to non-malignant phenotype. Iran Biomed J., 2009.13 (4): p.191-8. 38. Matsumoto, K., Nakamura, T., Sakai, K., Nakamura, T., Hepatocyte growth factor and Met in tumor biology and therapeutic approach with NK4. Proteomics, 2008. 8 (16): p.3360-3370. 39. Xu, R., Bourdeau, A., Bissell, M.J., Tissue architecture and function: dynamic reciprocity via extra- and intra-cellular matrices. Cancer Metastasis Rev, 2009.28 (1-2): p.167-76.


Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 59-82 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

3. Nutritional facts about macronutrients in cancer 1

Saeed Pirouzpanah1 and Fariba Koohdani2

Department of Community Nutrition, School of Health and Nutrition Tabriz University of Medical Sciences, Tabriz, Iran; 2Department of Nutrition and Biochemistry, School of Public Health and Institute of Public Health Research, Tehran University of Medical sciences, Iran

Abstract. Cancer has received increased attention in different societies in recent years. The dietary components have been proved to have important modulator impact on different stages of tumourigenesis and even have remarkable role in improving the prognosis of cancer. Macronutrients (protein, fat and carbohydrates) are believed to represent calorie to the cells and additionally could promote some physiological pathways attributing to increase risk of cancer. Consumption of protein and calorie is of much debate that lower consumption of protein and calories is the common nutritional problem facing many cancer patients and higher magnitude could support the burden of tumourigenesis. Numerous studies have evaluated the role of glycemic index or glycemic load on cancer risk producing inconsistent results and also the association between dietary fat and cancer development still remains controversial. This chapter review several evidence on tumourogenic effect of macronutrients and their constituents in dealing with tumour development. Correspondence/Reprint request: Dr. Saeed Pirouzpanah, Department of Community Nutrition, School of Health and Nutrition, Tabriz University of Medical Sciences, 5166614711 Tabriz, Iran E-mail: pirouzpanah@gmail.com


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Introduction The development of cancer is a complex multistage phenomenon with intricate etiology. Neoplasm is associated with numerous anomalous, biological alterations and defects in fundamental cell regulatory mechanism. Cancer results from aberrant and multiple accumulative changes in DNA damages that cause the net impaired in regular cell functions, metabolism, proliferation, differentiation and survival and eventually attributed to loss of normal tissue organization, and tissue invasion, spreading throughout the body and interfering with the normal function of intact tissues. Indeed, many biomolecules involve critically in cell signaling, regulation of cell cycle, and programmed cell death, where abnormalities in their activities led to tumour development. Importantly, the original progenitor cell does not have initially the acquired abnormalities. Several stages have been developed along with a progressive series of molecular changes to bring about tumour clonality. Different sorts of impaired biological mechanism involved in the etiology. One of the fundamental causes of changes is the interplay between molecular factors and the life style-related factors (e.g., dietary factors). A great deal has been focused about the intervening effects of dietary factors on inducing molecular defects responsible for many human cancers. Translating the empirical understandings of this interplay into practical dimension in cancer prevention and treatment could possibly provide appropriate considerations to pave the way toward overcoming crucial prognostic factor of disease.

Diet and nutrients Series of data from numerous studies have shown that diet as a major compartment of lifestyle-related factor may play a crucial role in tumourigenesis. Interestingly, many researchers thrived to unravel an effective intervening approach on broader dimensions from initiation of tumourigenesis toward advance stages of tumourigenesis [1, 2]. In this regard, to our knowledge, dietary-related factors could have potent roles from commencing the neoplastic cells toward advance phases of cancer [1, 3]. Several increasing body of evidence corroborated that every factor could have relative protective or noxious impact on different cellular aggravating mechanism and consequently on extremely unharness proliferation attributed in cancer [4]. In fact, many attempts are focused to find out a dietary pattern in which could be protective against cancer with invasive nature come out from diverse multifactorial etiology [5, 6]. However, there are many


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promising roles attributed to numerous dietary factors such as total calorie, protein, carbohydrate intakes and fatty acid composition of diet with respect to prevention and treatment implications against cancer, which recently various studies intriguingly reassure a possible link between life-style related factors and tumourigenesis [1, 7, 8]. In the context of this chapter we uncovered and review the attributed role of some dietary factors on biological mechanism involved in cancer prevention and treatment. Calorie There are several epidemiological evidence supporting the theory that diet plays an important role in the initiation, promotion and progression of many common cancers [3, 4, 9]. It is frequently addressed that imbalance calorie intake and a sedentary lifestyle profoundly associate with acquisition of adiposity over time and so-called as obesity [10, 11]. This feature is considered as an active predisposing risk factor for developing some malignancies such as endometrium, breast (postmenopausal), colon, esophagus, renal cell, pancreas, gallbladder and liver cancers [10, 12]. Long term appropriate physical activity and controlled calorie intake may have effect on some metabolic and hormonal alterations, which might cause negative energy balance and influence the procedure of adiposity [13]. Thereafter, reduction in adipose tissue, mainly visceral fat, could influence adipose derived hormones, which in part identified as adipokines. Adipokine profile predominantly consist of cytokines, where secrete from macrophage entrapped within fatty tissue and some originated from adipocyte itself [14]. Results of various researches suggest that chronic existence of adipokines could potentially interfere with cell responses to insulin and may attenuate insulin sensitivity in which subsequent insulin resistance could be clinically manifested [15]. Furthermore, obese individuals are prone to insulin resistance. In other sense, reduced fat mass is also accompanied with a reduction in circulating estrogen levels as a result of a reduction in aromatase activity [12, 16]. Hence, high circulation insulin level have been linked to lower expression of sex hormone binding globulin (SHBG) and subsequently increased free estrogens and testosterone. Therefore, weight loss may associate with decreased insulin level and increased SHBG concentration which could protect proliferating cells in hormone-responsive tumours from exposing high free estradiol and testestrone in blood. Decreased visceral adiposity may also come along with increased insulin-like growth factor binding protein-1 (IGFBP-1) and reduced free insulin-like growth factor-1 (IGF-1) that might preclude the possibility of cell division and invasiveness [12]. Weight loss is also associated with a reduction in inflammatory


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cytokines and prostaglandins, and may have effect on several factors of oxidative stress and subsequent DNA damages [17]. O'Callaghan et al., have recently shown that a 13-month weight loss intervention is associated with increased telomere length in the rectal tissue biopsies [18]. Therefore calorie restriction (CR) might preclude telomere shortening, which might contribute in prevention of many age-related unhealthy processes. The provided result in our previous report on a group of patients with breast cancer (BC) led to a new idea about the possible association between calorie intake and the risk of hypermethylation of tumour suppressor genes. We found out that high energy consumption might associate with the hypermethylation status of RARbeta2 gene in breast tumours [19], suggesting that tumours with unmethylated gene and subsequent expression of RARbeta2 as tumour suppressor gene might be more pronounced in BC patients consuming lower calories. Waterland has proposed that the beneficial effect of CR on colorectal cancer (CRC) risk is mediated through decreasing IGF-1 [20]. During adolescent the blood level of IGF-1 is high and suggested that CR can modify and influence the methylation patterns later in life [20]. Indeed, exposure to energy restriction during childhood and adolescence could possibly have more effect on lower risk of developing CRC. Hughes et al. (2009), proposed that severe transient energy restriction during adolescence due to famine during World War II is inversely associated with the risk of having a CpG island methylator phenotype (CIMP) tumour later in life [21]. From their findings, it is revealed that adolescence may be a critical and effective period of life span for epigenetic changes owing to environments that influence the risk of developing malignancy [21, 22]. The CR has long been known to suppress tumour growth in laboratory rodents [3]. Some sorts of developing tumours show a greater response to CR, and small proportion of tumours are resistant to the effects of CR in human studies [23]. The role of high IGF-1 level is anticipated to counterpart in carcinogenesis through stimulated PI3K pathway and repression of phosphatase tension human homology (PTEN) as molecular biomarkers that might significantly predict the responsiveness of a tumour to CR [23, 24]. Physiological impaired regulation of growth hormone secretion and also elevated IGF-I levels is common in acromegalic patients, which might be associated with the elevated risk of tumourigenesis [12]. Nutrition is one of the major regulators of circulating IGF-1levels [3]. Fasting in humans is a kind of CR in physiologic condition could markedly reduces serum IGF-1concentration [3]. Kalaany and Sabatini suggested that genetic alterations in PIK3CA or PTEN can predict the response of tumours to CR [24]. Indeed, two sets of tumour could be classified as CR-sensitive and


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CR-resistant tumours based on the existent mutation on these genes [24]. Their provided clues suggest that variant levels of PI3K activation in tumours may take part in their differential. From their findings, it is postulated that signaling pathways other than PI3K may take part in mediating the effects of CR in more advanced tumour stages [24]. In a meta-analysis on experimental animal studies carrying out interventional energy restriction consistently show that CR in itself protects against the development of mammary tumour in mice, irrespective of the macronutrients combination or other relevant study condition [25]. The CR may have negative association with the frequency of some mutation and may cause interference with impaired mechanisms such as the increased activity of FOXO pathways, inflammation and proliferation in the pre-neoplastic lesions and normal neighbor cells [3]. Rapid recurring of surgical injuries needs adequate calorie and protein intakes, likewise the principles of diet therapy for wound healing [11]. However, it is suggested that during post-surgical healing and chemotherapy adequate amount of calorie is essential [26]. Even sufficient calorie and weight gain could support long lasting chemotherapy and subsequent well prognosis of the disease. However, it shouldn’t be forgotten that calories are important for healing, fighting infection, and providing energy for normal cells. Nevertheless, the optimal body weight is recommended for patients during the therapy, X adiposity and relevant obesity might be attributable to non-responsiveness of tumour cells during chemotherapy [11]. Even so, the role of CR and other related dietary manipulations in cancer might be potentially correlated with different range of tumour regression in animal model and human studies, identifying the metabolic and molecular mechanisms responsible for the CR-dependent cancer preventive effect is unclear and it has the potential to lead researches to focus on CR-based therapies [12]. Macronutrients Consumption of diets that are adequate for energy, but low in red meat and fat has been recommended as an important preventive approach to decrease the risk of cancer [27], and have remarkable benefits to reduce cancer incidence by as much as 30% to 40% by an appropriate dietary guidelines (Table 1) [27]. In contrast, ingestion of vegetables, fruit, plantderived oils such as olive and flaxseed oils, and marine fish and their oils was associated with reduction in cancer risk.


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Table 1. Cancer prevention recommendations (population goals; individual guidelines) from the 1997 World Cancer Research Fund/American Institute of Cancer Research expert report [6, 28].


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Table 1. Contined

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Protein Essential amino acids (lysine, threonine, methionine, phenylalanine, tryptophan, leucine, isoleucine and valine) could provide substrate for normal metabolic requirements from protein rich food sources in diet [26]. In intact cells, amino acid could be utilized as catabolic substrate to yield acetyl group in order to produce energy through Kreb’s cycle. Amino acids also participate in the composition of structural and functional proteins in cells that could support cells integrity to live [29, 30]. In moderate restricted protein diet (<0.75 g of protein/kg body weight/day), which is consumed as common in vegetarian dietary pattern, significant lower serum concentrations of total and free IGF-1 is reported [12]. Moreover, reducing protein intake in individuals who consume strict CR with high protein intake (>1.65 g of protein/kg body weight/day) might have a 25% reduction in serum IGF-1 (from 194 ng/mL to 152 ng/mL), suggesting that the proportion of protein to calorie intake could play major role on circulating IGF-1 levels in humans relative to CR alone [12]. Protein intake was associated with increase in serum IGF-1 level, whereas calorie intake was associated with an increase in serum IGF-I concentration only in lean men with a body mass index <25 kg/m2 [12], suggesting the increased incidence of two adiposity-independent common cancers, such as prostate and premenopausal BC and high protein consumption. It is important to note that the recommended daily allowance for protein intake in healthy adults is 0.83 g/kg of body weight/day [24]. It is presumed that some noxious substances exist in protein and may take part in genotoxicity and carcinogenicity [31, 32]. Thus, high meat and processed meat intakes were linked in part to developing the neoplasm and initiation of cancer in epidemiologic studies [29]. Even though, the presence of adequate level of amino acids is vital for normal cells, it is extremely essential for tumour cells to compensate their sever demands for uncontrolled proliferation. The main cancer type that has been linked with high meat intake is CRC, based on a considerable number of reports [29]. Sandhu et al. (2001), suggested that a daily increase of 100 g of all meat or red meat is associated with a 12–17% increased risk of CRC, and a daily increase of 25 g of processed meat is associated with 49% increased risk, suggesting greater undesirable impact of processed meat in tumourigenesis [33]. Consistent conclusion was also drawn by Norat et al. (2002), supposed that individuals in the highest quartile of red meat consumption correlated with a 1.35-fold increased risk of CRC, while those in the highest quartile of processed meat intake showed a 1.31-fold increased risk [34]. Larsson and Wolk (2006) bring out the similar result (1.28-fold increased CRC risk for the highest as


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compared with the lowest red meat intake, and 1.20-fold increased risk for processed meat) [35]. However, the reviews concluded that there was no significant association between total meat intake and CRC risk [30]. Whereas, there is consensus that cancer risk might associate with higher consumption of animal protein [22]. There is also possible explanation that the relationship between cancer risk and formation of neoplasm may be linked with dietary pattern, type of meat preparing and invisible fat exist in meat [30]. There are some possible mechanistic evidence about the correlation between meat consumption and cancer. These factors were possibly linked to high-fat content of meats, the production of mutagenic aldehydes, DNA alkylating agents such as heterocyclic amines (HCAs) and/or polycyclic aromatic hydrocarbons (PAHs) during overheated and direct flame-exposed cooking (barbeque, grilling, frying and so forth), the formation of carcinogenic N-nitroso compounds (NOCs) either within meat per se or as a preservative, and the promotion of lipoperoxidation and/or cytotoxicity by haem iron [30]. It is also suggested that the high fat content and also calorie density of protein in meat are in attribution with the increased likelihood of obesity, which is highlighted as a major risk factor for some cancer [30]. Results of a cohort study from Finland suggest that the risk of BC was increased (80%) in individuals consuming fried meat (highest versus lowest tertile RR, 1.80; 95% CI, 1.03-3.16), whereas other meat consumption was not correlated with BC [36, 37]. In a nested case-control study among the Iowa Women’s Health Study cohort [22], the risk of BC risk was high among regular consumers of well-done and fried meats (more than 4-fold) in compared with whom consuming medium or rare meat. Conjugated linoleic acids (CLAs) are a bundle of polyunsaturated fatty acids (PUFAs) with positional and geometric conjugated isomers of linoleic acid usually found in the cis-9, trans-11 isomers [30]. The CLAs are found predominantly in dairy products and tissues derived from ruminant animals. Rumen bacteria in part are responsible for producing CLAs due to partial hydrogenation of PUFAs [26]. There is emerging clues about possibly anticarcinogenic properties of CLAs, but their mode of action is poorly understood [26]. In animal studies, CLAs inhibit carcinogenesis, possibly through modulating immune function [38]. It is proposed that CLAs could be catalyzed by cyclooxygenase (COX) and may decrease the production of potent proinflammatory mediators and eventual cause to increase immune function [39]. It is underlined that t11-CLA inhibited the COX-2 pathway and t10, c12-CLA inhibited the lipooxygenase pathway [40]. Some evidence showed that CLAs are also capable to induce apoptosis but relevant molecular signaling which is not clarified thus far, based on human data [39].


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In addition, Ip et al. (2003) indicated that CLA might inhibit angiogenesis in vivo, in part, through mediating the CLA-induced decrease in serum vascular endothelial growth factor (VEGF) and mammary gland VEGF and flk-1[41]. The way of cooking and food preparation are important factors to keep essential ingredients intact to some extent and precluding from production of toxic compounds in protein rich foods such as meat [30, 32]. Fat content of animal sources is a causing factor of undesirable sources in the process of cooking and storing the food. Removal of visible fat and cooking method will also be important for reducing the possible sources of risky components [29]. Carcinogenic heterocyclic amines (HCAs) are DNA alkylating agents can induce mutations in DNA following activation by various hepatic xenobiotic metabolizing enzymes [31]. There are various enzymes involved in catalyzing HCAs, including cytochrome P450, glutathione S-transferase, UDP-glucuronosyltransferases, sulfortransferases and N-acetyltransferases. Various responses to the presence of HCAs and toxicity among individuals could be possibly explained by the existence of single nucleotide polymorphisms (SNPs) in these enzymes in which could intervene with the metabolism of HCAs [32]. Thus, in the condition of carrying SNPs variation, overcooked meats may bring about hazardous impact on developing cancer [32]. In this case, preparing meat in the presence of other mutation modulating agents such as fiber and phytochemicals may be a convenience way to reduce the possibility of DNA damages. There is evidence suggesting that a diet high in dietary fiber sources such as wheat bran may reduce the absorption of HCAs and therefore reduce possibly the carcinogenic effects of HCAs [30, 32]. Carter et al. (2007) suggested that epigallocatechin-3-gallate, and caffeine (tea) may suppress HCA-induced colonic lesions and cell proliferation in the colon [42]. Cruciferous vegetables and polyphenol rich fruits and vegetables contain vitamins and phytochemicals modulating the activity of certain xenobiotic metabolising enzymes. Hence, they can interfere with the methabolism of HCAs and reducing the induction of activated mediators of HCAs [30]. The ability of vitamins C and E are wellestablished to inhibit the formation of carcinogenic N-nitroso compounds (NOCs) in meat per se and in nitrite-preserved meat. Vitamin C also consider as antioxidant counterparts in reduction of nitrite transformation to NOCs. These nitric based compound significantly produced through microbial flora of gut and other tissues proning factors to produce the N-nitroso derivatives (such as mouth, esophagus, stomach, intestines, colorectal, uterus, bladder and so on) [43, 44]. In an animal study, Koohdani and Mehdipour suggest that the number of a chromosomal defects as micronuclei might be elevated by exposure to nitrite meanwhile the rats nourished with high level of sodium


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chloride, suggesting high nitrite content of processed meats often contain high salt in a meal and may increase the possibility of genotoxic effects [45]. Urethane is a potent carcinogenic by-product of fermentation and exist at considerable levels in fermentated dairy product such as cheese [44]. It is indicated that the expression of Ki-67 antigen might be increased by urethane in lung tissue and likely be more aggravating while nitrite ion coexist in food [44]. The major sources of nitrite provision is addressed markedly to foods and drinks which are polluted and cultivated utmost in the exposure of chemical fertilizers and natural sources of nitrite [26]. Some additives and spices may also provide the circumstantial amount of NOCs to access of living cells, if they are consumed regularly in common dietary pattern. Meat is also useful source of highly bioavailable zinc, as well as providing vitamin B6, B12, vitamin D, calcium, folate and selenium [28]. Each of these micronutrients may have beneficial effects in cancer protection, via different mechanistic pathway. Linos et al. (2008), have shown that the exogenous hormones content of meat, e.g., diethylstilbestrol, have been used worldwide for growth stimulation in cattle, and residual amounts of these components in beef may have implications in carcinogenesis [22]. They also explained a possible mechanism related to induction of oxidative stress by dietary iron consumption. In animal studies, it is shown that dietary iron may enhance estrogen carcinogenicity possibly by promoting free radical damage to DNA [22]. In some case-control studies, high rate of mutation in the HFE gene has been indicated among BC patients, which is a well-known genetic characteristic in the etiology of hereditary hemochromatosis [46]. This finding indirectly implicates iron overload in BC pathogenesis. Iron in meat exists in the form of heme and readily bioavailable form of iron and significantly contributes to stored body iron [22]. Hence, the link between dietary protein intake and premenopausal BC risk might be explained in part by contribution of iron-related genetic variation and dietary iron consumption during adolescence and the effect of red meat appears to be independent of animal fat intake. Eventually, several lines of evidence have support a conclusion that high meat intake, processed meat, and fried and flame direct-exposed cooking methods for red meats may increase the hazard of certain cancers development [30, 32]. Besides, it is important to reinforce the nutritional impact of amino acids and several micronutrients to meet normal metabolic demand of human body [37]. It is mostly achievable to provide some possible approaches to maintaining a moderate intake of meat, alongside selecting healthy dietary pattern to eat (e.g., low fat meat, plant-source protein, unprocessed food, modulating the cooking methods and so forth) to reduce


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cancer risk and also possibly pave the way in part to restrict the tumour growth during therapeutic intervention [30].

Dietary fat Dietary fat with high energy density could bear out about 9 kcal/gr of fat in common dietary pattern [26]. The average amount of dietary fat intake in normal dietary composition recommended around 15-30% of total energy intake[26]. However, some dietary pattern consists of more than suggested magnitude. Although genetic predisposing factors and different pattern of environmental features influences the risk of cancer development, several investigators have discussed the effect of different levels of total fat intake and different levels of total energy intake [12, 25]. However, no clear conclusion is available on whether the effect of fat intake on tumour incidence is adjusted by the level of calorie intake. However, there is consensus that CR retained by reducing the intake of fat which might be more effective in achieving the goals related to energy restriction compared to the effect of reducing carbohydrates [25]. Consistently, Freedman et al. (1990), find out that the effect of dietary fat was comparable to total calorie intake toward independently increased mammary tumour incidence (2/3 the magnitude of the calorie effect) in both Sprague-Dawley rats and mice [47]. However, World Cancer Research Fund/American Institute for Cancer Research [9], reported that limited data exist to suggest possible link between intake of foods containing animal fat and increased risk of CRC. Several studies have attempted to show that dietary fat may in part have role in increasing the risk of cancer development particularly in breast, ovary, esophagus, colorectal and prostate cancer, but it still remains to be elusive. Data from animal studies and some case–control studies propose that high intake of total fat elevate BC risk, but results from prospective cohort studies are inconsistent [1, 48].

Total fat Decreasing dietary total fat intake is a plausible target in most studies to meet the preventive approach in development of BC [49]. The epidemiological case-control studies (WCRF/AICR, 2007) showed a positive association between total fat intake and BC risk but no supportive association was reported in the Women Health Initiative’s (WHI) randomized controlled trial [49, 50]. In this regard, some biological plausibility was anticipated to reveal the related risk to lipids as follow: It has been known that the required bile acids to digest fat in humans may promote the development of some


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cancers [48]. Specifically, the metabolism of secondary bile acids (deoxycholic acids) from primary bile acids by anaerobic bacteria in the large bowel is known to be toxic and mutagenic to cellular systems and may cause damage to intercolonic membranes or intracellular mitochondrial function cancer cells. In addition, it has also been hypothesized that elevated concentrations of transforming growth factor-b1 (TGF-b1), a cytokine predominantly responsible for regulating the growth of epithelial cells, may aid in the progression of related cancer cells [48]. Inflammation and fat have been shown to increase TGF-b1in cancer risk. Another hypothetic implication is the participation of lipids in the excess of energy intake which could help to draw the conclusion about fundamental effect of energy intake [48]. If total fat intake has an impact on cancer risk (such as CRC), the contribution of caloric intake and/or dietary pattern with high content of energy by fat could explain this phenomenon in part. However, this issue was not consistently described by different studies [25, 48]. The acquisition of body fat in premenopause women and consecutive levels of adding estrogen in comparison to gonadal secretion of estradiol would be less important in attributing to risk for BC [51]. For postmenopausal women, it is believed that adiposity is a risk factor for hormone related cancers due to extragonadal estrogen synthesis mediated by adipose tissue. Thus, the role of nutrition-related factors on promoting the body fat accumulation and maintenance appears more preponderant in postmenopausal women, where the estrogenic agonist role of extragonadal hormone profile is important [51, 52]. Importantly, several studies showed increased survival in BC patients with low intake of total fat [7, 48]. Although there are still inconstant results brought about different epidemiological methods, total fat content of a regular diet has been suggested to be low as 15-30% to decrease possibly the chance of cancer development [6, 28]. In addition to total fat, various studies draw the conclusion that dietary fatty acid composition might have greater role in cancer risk.

Saturated FA Based on the existence of double bounds between two carbon in the chemical structure of fatty acid chain, fatty acids in regular diet consist saturated, monounsaturated and polyunsaturated total fat [26]. There are many kinds of naturally occurring saturated fatty acids, which differ by the number of carbon atoms, ranging from 3 carbons (propionic acid) to 36 (Hexatriacontanoic acid). Some foods consist of high proportion of saturated fatty acids include dairy products (particularly cream, cheese, butter and ghee);


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animal fats such as suet, tallow, lard and fatty meat; cottonseed oil, coconut oil, palm kernel oil, chocolate, and some prepared foods with high fat [26]. Serum saturated fatty acid is generally higher in smokers, alcohol drinkers and obese people [53]. Some studies show that high saturated fat intake might be associated with greater BC risk. This result was particularly addressed by Sieri et al. (2008) [53] that the highest quintile of saturated fat intake contribute in greater risk compared with the lowest quintile and showed that for a 20% increase in saturated fat consumption expected marginally to increase the risk magnitude at OR=1.02 (95%CI, 1.00-1.04). In menopausal women, the positive association with saturated fat was confined to nonusers of hormone therapy. In consistent, Bingham, et al (2003) showed a significant relationship between SFA and BC risk [54]. Thus, it was concluded that the effect of SFA was similar to that of total fat. The similar effects of these FA on CRC are also comparable to total fat.

n–6 polyunsaturated fatty acids PUFA that contain the latest double binds in n-6 position of the end of fatty acid chain categorized as n-6 PUFA. They are more often occurred in regular diet as linoleic and arachidonic acids development [26], and hypothesized that could likely increase the risk of neoplastic development [26]. Although there are series of data from recent case-control and cohort studies that they were not drawn any conclusion and explaining the link between n-6 FA consumption and risk status of cancer, the impact of long time n-6 FA intake on the risk remains to be elucidated [48]. It is hypothesized that n-6 PUFA could take part in promoting the production of proinflammatory mediators and oxidation due to presence of several double bounds in FA chain. Despite the non-conclusive results from several studies, these reasons could support hypothetically the probable tumourogenic effect of longitude consumption of n-6 PUFA on neoplastic changes in some tissues [26, 48].

n–3 polyunsaturated fatty acids Fish oil is the main animal sources of eicosapentaenoic acid (EPA; 20:5, n−3) and docosahexaenoic acid (DHA; 22:6, n−3). Seafood and especially fatty fish (trout, salmon, tuna, mackerel, sardine, herring, and so on) are major dietary sources in most populations [26]. Alpha-linolenic acid (ALA) is a n-3 PUFA and fundamentally provided by some plant sources, e.g., seeds and nuts. EPA and DHA can be synthesized by humans from dietary ALA,


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but with low efficiency [26]. Although there is sufficient evidence from in vitro and animal studies that these n-3 PUFA can reduce the progression of tumours in various tissues, hormone-related ones, the evidence from several epidemiologic studies is still in debate [55]. There is limited statistically significant data reported for ALA connecting with cancer risk [56]. In a cohort study based on serum FA evaluation proposed a marked decreased CRC risk in men and a non-significant increased risk in women [57]. Siere et al. (2008) found out that BC risk of development is in inverse association with PUFA [53]. Leitzmann et al. (2004) found out that EPA and DHA intakes could be related with lower risk of prostate cancer (PC) [58]. This result is consistent with that of a Japanese study, which showed a negative relation between PC mortality and serum n-3 PUFA (mainly EPA and DHA) [59]. Hence, a high intake of EPA and DHA was associated suggestively with a decreased risk of total and advanced PC [58]. In animal models, it has been reported that high n–3 PUFA containing diet precludes colon tumourigenesis compared with a Western diet with high fat content [60]. However, some studies were not capable to support this hypothesis [48, 61]. The heterogeneity of the findings cannot be explained. But, there are presumptions could support the biological plausibility related to n–3 PUFA on reducing the risk of cancer: (1) the anti-inflammatory effect via introducing pro-inflammatory mediators with relative neutral inflammatory function and suppression of COX 2 enzyme and cytokine production, (2) the anti-apoptotic effect and up-regulating effects on expression of proliferative, antioxidant contributing genes, 3) n-3 PUFA interfere in androgen receptormediated events (inhibit 5a-reductase, the expression of PSA protein and the androgen receptor-mediated transcription gene) and alteration of cell signaling, 4) inducing the expression of peroxisome proliferator-activated receptors gamma and modification of membrane phospholipids composition [56, 62, 63]. Although meat appears to be a risk factor in the case of CRC, replacing meat by fish meat might have reducing effect on the risk of cancer. In addition, the recent studies strengthen the probability of a causal relationship between fish intake and CRC [30]. Moreover, two recent cohort studies and experimental models draw a conclusion suggesting a favorable effect of n–3 PUFA on CRC risk and recommended that an intake of ≥500 mg combination of EPA and DHA daily is necessary for a significant risk reduction (20–25%) [48]. Consistently, it is relevant that Asian populations had high amount of n-3 PUFA intake and their average intakes ≥1.500 mg/day may help significant decrease on BC risk (50%) [48].


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Dietary n–6 to n–3 PUFA ratio Several researchers have come to a relative consensus that a high ratio of n–6: n–3 PUFA is associated with an increased risk of CRC, PC and BC [61, 63]. From a prospective study data (Shanghai Women's Health Study), Murff et al. (2010) showed that the ratio of n-6 to n-3 PUFA ratio may be positively associated with CRC and BC among Chinese women [61, 64]. If the intake of EPA and DHA is increased as recommended above, the ratio is likely to improve. In the Health Professionals Follow-Up Study, Leitzmann et al. (2004), proposed that linoleic acid (LA) to ALA is inversely correlated with the risk of advanced BC, whereas, LA to EPA plus DHA was positively associated with risk of advanced BC [58]. They concluded that our result suggest that a high ALA intake is associated with an increased risk of advanced BC. In contrast, high EPA and DHA intakes may be associated with a decreased risk of total and advanced PC [58]. Nevertheless no precise conclusion put forth by epidemiological studies, it is recommended that a diet with a ratio of n-6 to n-3 essential fatty acids (EFA) of approximately 1-3 could be acceptable to prevent some chronic disease.

Trans fatty acids In case-control and cohorts showed an increased risk of PC for the highest exposure to trans 16: 1, 18: 1 and 18: 2 [65], and 18: 1 11 trans and 18: 2 9 cis 12 trans [66] and trans 18: 1 and total trans FA [48, 67]. However, another cohort study failed to support any association [68]. Liu et al. (2007) suggest that, the polymorphic genotype of QQ/RQ at RNAsel (R462Q) may consider as predisposing factor to deficient proapoptotic activity. Interestingly, this genotype may consider as predisposing risk factor to PC in the case of exposure to total trans FA, trans 18: 1, trans 18: 2 intakes [65]. Indeed, Trans isoform of FAs are generated in ruminant meats and dairy products as a result of fermentation of FA via bacterial micro flora exist in ruminant gut.

Monounsaturated FA There are too limited data to support any conclusion about monounsatuared FA (MUFA). The desirable effect might be attributed to: 1) the presence of leuropein, a phenolic compound in olive oil capable of inducing of phase I and II enzymes, 2) the Mediterranean dietary pattern is rich source of MUFA and associated with lower risk of atherosclerosis and cancer risk. Double bond present in unsaturated FA (PUFA and MUFA) is


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vulnerable to oxidation and could potentially take part in oxidative stress. MUFA in comparison to PUFA had a double bond and have lower opportunity to oxidation [26]. Thus, consuming the MUFA rich diet (containing olive oil) underlines the beneficial importance in prevention of many chronic disease, e.g., some sorts of cancer [48].

Carbohydrate Carbohydrate is one of the major macronutrients in composition of food that yield considerable calorie through metabolic reactions [26]. They are categorized as: 1) monosaccharide-glucose, fructose (fruit sugar) and galactose which are rarely present in the nature as monosaccharide and combined with other one to build disaccharides and polysaccharides, 2) disaccharides such as sucrose (sugars), lactose (milk sugar) and maltose (malt sugar) widely consumed in the dietary pattern of Western countries. Polysaccharides such as starch consist of monosaccharide units joined by glycosidic links and are polymer of monosaccharides [26]. Starch is a polysaccharide stored by plant as granules in plant-derived food and build up a significant part of calorie from carbohydrate source in food [26]. Carbohydrate intake may influence BC risk by affecting insulin resistance and plasma levels of insulin and glucose [1]. Numerous studies have evaluated the role of glycemic index (GI) or glycemic load (GL) on BC risk producing inconsistent results. GL and GI are dietary characteristics that are useful for estimating the effect of dietary carbohydrates on the insulin response physiologically. The overall GI, a ranking system for carbohydrates according to their effect on blood glucose concentrations, reflects the average quality of carbohydrates consumed. The total dietary GL, the sum of the GLs for the total serving of all carbohydrate-containing foods consumed per day reflects both the average quantity and quality of carbohydrates [69]. Diets high in GI and GL have been associated with different range of chronic disorders such as obesity, diabetes mellitus, hyperlipidemia, heart disease, and stroke [70]. In cohort studies, an association between GI and overall cancer risk was seen among overweight individuals [70]. Increased risk of pancreatic cancer was proposed among cases with frequent consumption of foods high in sugar, hyperinsulinemia and the condition of insulin resistant [70]. Overweight and obesity are accompanied by higher fasting serum and free IGF-1. In particular, insulin promotes the production and activity of IGF-I that may increase cell proliferation and may inhibit cell apoptosis [71]. Hyperinsulinemia affects the production of sex hormones such as androgens and estrogens and decrease the production of SHBG that accompany with


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elevated level of free sex hormones in circulation, which may be associated with cancer growth. In the Syrian hamster model, estrogen treatment resulted in kidney tumour, whereas antiestrogens reduced tumour formation [15]. The epidemiologic evidence suggests that a possible link between insulin and growth factors is directly come along with some evidence in CRC. It has also been proposed that high-GI and high-GL diets may promote weight gain over time. Being overweight or obese has been associated with esophageal adenocarcinoma and CRC from several meta-analyses evidence [69]. Dietary fiber is the major ubiquitous polysaccharide found in fruits and vegetables and has been suggested to reduce BC risk through an effect on estrogen signaling or via the insulin growth factor system. Some case-control studies have shown negative association between dietary fiber intake and BC risk, whereas it was not conclusively support by prospective cohort studies [1, 8]. Some researchers tried to reveal the hypothetic link between consumption of total dietary fiber and BC risk through the expression status of estrogen and progesterone receptors (ER and PR), which could involve in tumourigenesis and progration of tumour. However, they did not reach to a significant result and suggest that different plant foods might be differentially associated with BC [1]. Some studies show that other nutrients in addition to fiber exist in plant derived food (i.e. folate) that their insufficient intake might contribute in carcinogenesis of BC via repressing some tumour. Suppressor genes [19, 72]. We found out that folate deficiency may be involved in hypermethylation status of RARbeta2 and ERalpha genes and suppressed ER expression analyzed by immunohistochemistry in BC tumours [72]. Thus, ER and PR downregulation histologically in BC tumours might be attributed to folate deficiency that it could be additionally implicated by dietary fiber derived from vegetables and fruits. Therefore, it could be noticed that carbohydrate particularly mono- and di-saccharides show high GI and GL and could be involved in hyperinsulinemia, increased IGF-1 and subsequent tumour growth. Digesting recommended amount of starchy carbohydrate in the form of breads and cereals with high fiber content would reverse these associations and have more beneficial effect on health besides providing other essential nutrients to human body.

Conclusion The promising role of dietary factors has been identified in the etiology of cancer. Several lines of evidence support the fact that dietary energy restriction could convey beneficial considerations for prevention by controlling the healthy pattern of genomic content during life-long and also inducing repression on tumour development. Therefore, it is hypothesized


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that manipulation of CR seems to be a new attitude focusing on prevention and also a new target for restraining tumour development. Although protein can provide the essential nutrient for normal metabolism, some components in dietary protein sources could have anticarcinogenic impacts. However, several epidemiological studies suggest that meat and processed meat could associate with tumourigenesis stages and contribute in elevating the risk of cancer development. It is increasingly evident that dietary fat might involve in carcinogensis not only due to providing condensed energy but its FA constituents may play considerable role in the process of tumour development. Carbohydrate as the source of cellular energy and possibly increase the insulin level in postprandial episode. Dietary pattern consisting of higher rate of simple carbohydrate and low fiber may potentiate hyperinsulinemia and consecutive insulin resistance that considered as risk factors for cancer development. Dietary factors have been interested evidently and their effects identified potently as modulators of almost every step of tumourogensis. However, there is so many unraveled dimensions of nutrition (nutriceutic) which could be considered along with cancer treatment in parallel to promote disease prognosis via synergistic effects of dietary factors.

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54. Bingham, S.A., R. Luben, A.Welch, N.Wareham, K.T. Khaw, N. Day, Are imprecise methods obscuring a relation between fat and breast cancer? Lancet, 2003. 362(9379): p. 212-4. 55. Terry, P.D., T.E. Rohan, A. Wolk, Intakes of fish and marine fatty acids and the risks of cancers of the breast and prostate and of other hormone-related cancers: a review of the epidemiologic evidence. Am J Clin Nutr, 2003. 77(3): p. 532-43. 56. Simon, J.A., Y.H. Chen, S. Bent, The relation of alpha-linolenic acid to the risk of prostate cancer. Am J Clin Nutr, 2009. 89(5): p. 1558S-64S. 57. Kojima, M., K. Wakai, S. Tokudome, K. Suzuki, K. Tamakoshi, Y. Watanabe, , et al., Serum levels of polyunsaturated fatty acids and risk of colorectal cancer: a prospective study. Am J Epidemiol, 2005. 161(5): p. 462-71. 58. Leitzmann, M.F., M.J. Stampfer, , D.S. Michaud, K. Augustsson, G.C. Colditz, , W.C. Willett, et al., Dietary intake of n-3 and n-6 fatty acids and the risk of prostate cancer. Am J Clin Nutr, 2004. 80(1): p. 204-16. 59. Kobayashi, M., S. Sasaki, G.S. Hamada, S. Tsugane, Serum n-3 fatty acids, fish consumption and cancer mortality in six Japanese populations in Japan and Brazil. Jpn J Cancer Res, 1999. 90(9): p. 914–21. 60. Rao, C.V., Y. Hirose, C. Indranie, B.S. Reddy, Modulation of experimental colon tumorigenesis by types and amounts of dietary fatty acids. Cancer Res, 2001. 61(5): p. 1927-33. 61. Murff, H.J., X.O. Shu, H. Li, Q. Dai, A. Kallianpur, G.Yang, et al., A prospective study of dietary polyunsaturated fatty acids and colorectal cancer risk in Chinese women. Cancer Epidemiol Biomarkers Prev, 2009. 18(8): p. 2283-91. 62. Astorg, P., Dietary N-6 and N-3 polyunsaturated fatty acids and prostate cancer risk: a review of epidemiological and experimental evidence. Cancer Causes Control, 2004. 15(4): p. 367-86. 63. Olivo-Marston, S.E., Y. Zhu, R.Y. Lee, A. Cabanes, G. Khan, A. Zwart, et al., Gene signaling pathways mediating the opposite effects of prepubertal low-fat and high-fat n-3 polyunsaturated fatty acid diets on mammary cancer risk. Cancer Prev Res (Phila), 2008. 1(7): p. 532-45. 64. Murff, H.J., X.O. Shu, H. Li, G.Yang, X. Wu, H. Cai, et al., Dietary polyunsaturated fatty acids and breast cancer risk in Chinese women: A prospective cohort study. Endocr Relat Cancer, 2010. 17(2): p. 373-82. 65. Liu, X., F.R. Schumacher, S.J. Plummer, E. Jorgenson, G. Casey, J.S. Witte, Trans fatty acid intake and increased risk of advanced prostate cancer modification by RNASEL R462Q variant. Carcinogenesis, 2007. 28(6): p. 1232-6. 66. King, I.B., A.R. Kristal, S. Schaffer, M. Thornquist,, G.E.Goodman, Serum trans -fatty acids are associated with risk of prostate cancer in beta-Carotene and Retinol Efficacy Trial. Cancer Epidemiol Biomarkers Prev, 2005. 14(4): p. 988-92. 67. Chavarro, J.E., M.J. Stampfer, H. Campos, T.Kurth, W.C. Willett, J. Ma, A prospective study of trans-fatty acid levels in blood and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev, 2008. 17(1): p. 95-101.


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68. Neuhouser, M.L., M.J. Barnett, A.R.Kristal, C.B.Ambrosone, I. King, M. Thornquist, et al., (n-6) PUFA increase and dairy foods decrease prostate cancer risk in heavy smokers. J Nutr, 2007. 137(p. 1821-7. 69. Mulholland, H.G., Murray, L.J., Cardwell, C.R., Cantwell, M.M., Glycemic index, glycemic load, and risk of digestive tract neoplasms: a systematic review and meta-analysis. Am J Clin Nutr, 2009. 89(2): p. 568-76. 70. Simon, M.S., J.M. Shikany, M.L.Neuhouser, T. Rohan, K. Nirmal Y. Cui, et al., Glycemic index, glycemic load, and the risk of pancreatic cancer among postmenopausal women in the women’s health initiative observational study and clinical trial. Cancer Causes Control, 2010. 71. Cheung, C.W., D.A.Vesey, D.L.Nicol, D.W.Johnson, The roles of IGF-I and IGFBP-3 in the regulation of proximal tubule, and renal cell carcinoma cell proliferation. Kidney Int, 2004. 65(4): p. 1272-9. 72. Pirouzpanah, S., F.A Taleban, M. Atri, A.R. Abadi, P. Mehdipour, The effect of modifiable potentials on hypermethylation status of retinoic acid receptor-beta2 and estrogen receptor-alpha genes in primary breast cancer. Cancer Causes Control, 2010 (accepted). 73. Mulholland, H.G., Murray, L.J., Cardwell, C.R., Cantwell, M.M., Dietary glycaemic index, glycaemic load and breast cancer risk: a systematic review and meta-analysis. Br J Cancer, 2008 99(7): p. 1170-5. 74. Pirouzpanah, S., Taleban, F.A., ATRI, M., Abadi, A.R., Mehdipour, P., Association of plasma folate, vitamin B12 and homocysteine levels with hypermethylation status of ERalpha gene in primary breast carcinoma. Iran J Nutr Sci, 2009. 4(11): p. 39-48.


Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 83-98 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

4. Potential of cancer-testis antigens as targets for cancer immunotherapy Mohammad Hossein Modarressi1,2, and Soudeh Ghafouri-Fard3 1

Department of Medical Genetics, Tehran University of Medical Sciences Tehran, Iran; 2Pasteur Institute of Iran, Tehran, Iran; 3Department of Medical Genetics, Shahid Beheshti University of Medical Sciences and Health Services, Tehran, Iran

Abstract. Cancer-testis antigens are tumour antigens with limited expression in male germ cells in the testis, ovary and trophoblasts. Recently, their expression has been seen in different types of tumours. Due to the existence of the blood-testis barrier, testis is considered an immune-privileged site; and testis-specific genes, if expressed in cancers, can be immunogenic. For this reason, cancertestis antigens are promising candidates for cancer immunotherapy and have become a major focus for the development of vaccinebased clinical trials in recent years. These antigens may be used as biomarkers for early detection of cancers. Expression of these genes in cancer reflects gene reprogramming and may have a role in neoplastic features such as metastasis and immune evasion.

Introduction Tumourigenesis and germ cell development have many common characteristics. There is a great variety of evidence for this theory. First of all, many kinds of epithelial tumours secrete Chorionic Gonadotropin and other Correspondence/Reprint request: Dr. Mohammad-Hossein Modarressi, Department of Medical Genetics School of Medicine, Tehran University of Medical Sciences, Tehran, IR Iran. E-mail: modaresi@tums.ac.ir


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trophoblastic hormones. In addition, a new category of tumour antigens called Cancer-Testis Antigens (CTAs) has been found with limited expression in normal tissues rather than germ cells and trophoblast [1]. Immature germ cells of fetal ovary (oogonia and primary oocytes) express CTAs but their expression has not been seen in oocytes in the resting primordial follicles. Cytotrophoblast and syncytiotrophoblast of the placenta express some CTAs. Expression of these antigens in the placenta has a special pattern; some of them are not expressed in the placenta but some are highly expressed, and their expression is not completely paralleled with their presence in the fetal germ cells. Some characteristics of malignant tissues, such as invasiveness, destructiveness, and metastatic features, are shared with trophoblastic cells, and thus gene expression profile in the placenta can be similar to cancer. Some CTAs are expressed in nongametogenic tissues such as the pancreas, liver, and spleen; but at levels much less than germ cells [2]. This expression in non-testicular tissues are usually at less than 1% of their expression levels in testis and has not been confirmed at protein level by immunohistochemical analysis. Another group of genes has been described with limited expression in testis and brain [3]. These two tissues share another feature of having blood barriers. It was recently reported that some CTAs such as N-RAGE, NY-ESO, MAGE, and SSX are expressed in both adult and fetal human mesenchymal stem cells of the bone marrow but after differentiation of osteocytes and adipocytes, their expression is down-regulated. It has been suggested that expression of CTA, in addition to being a special characteristic of gametogenesis, can be a stem cell marker. This restricted expression of these antigens in undifferentiated somatic and germ cells is suggestive of their essential role in embryonic development. In addition, expression of CTAs in cancer stem cells may provide special targets for treatment of cancer recurrences and metastasis. Maintenance of undifferentiated phenotype in cancer stem cells is needed for expression of CTAs; so cancer cells, in which CTAs are expressed, may have lost their differentiation ability. Supposing that cancer stem cells are sources of metastasis and recurrence, drugs targeting CTAs may be efficient in cancer treatment [4]. To prevent autoimmunity, a proper tumour antigen for immunotherapy must have no or highly restricted expression in normal tissues. Because of their highly tissue restricted expression, CTAs are considered as promising target molecules for cancer vaccines. Spontaneous humoral and cell-mediated immune responses have been found for at least some of them. Until now at least 70 families of cancer-testis genes with 140 members have been placed in this group and their expression has been studied in different types of tumours. Some of them have been originally identified


CTAs as potential targets for immunotherapy

Table 1. CTAs of X chromosomes expressed in less than 5 normal tissues [2].

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Table 1. Continued

because of their immunogenicity in cancer patients and their recognition by CD8+ T cells and antibodies [5]. Classifying genes in this gene group is based on some characteristics: 1) mRNA expression in normal tissues is almost limited to testis, fetal ovary, and placenta, and 2) mRNA expression has been seen in different cancers. In cancers immunohistochemical analysis also has shown their expression at protein level. Contrary to other differentiation antigens, CTAs expression in cancers is predominately heterogeneous and usually small subsets of cancer cells express CTAs. One reason for this heterogeneous expression could be the fact that CTA expression marks cancer stem cells, and this expression disappears after the differentiation of cancer cells [5]. It is possible to assess expression of CTAs in normal tissues by means of digital differential display to find those with more limited expression in normal tissues which are more appropriate for cancer immunotherapy (Tables 1 and 2). CTAs can be targets for siRNA and if expressed at cell surface, they can serve as targets for monoclonal antibodies. It is worthy to mention that for each type of cancer, CTA expression is usually related to worse outcome, higher grade and metastasis; hence it shows a relationship between their expression and the level of dedifferentiation.

Classification of CTAs CTAs are classified according to their gene locations on chromosomes to cancer-testis-X CT-X or non X-CT. About 50% of cancer-testis genes, including


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Table 2. CTAs of non-X chromosomes expressed in less than 5 normal tissues [2].

including those which have been used in cancer immunotherapy, are located on the X chromosome. These CT-X genes usually form gene families connected to inverted DNA repeats. Study of the sequence of the human X chromosome has shown that about 10% of all genes on the X chromosome belong to the cancer-testis gene family. In normal testis, the CT-X genes are generally expressed in the spermatogonia, which are proliferating germ cells. The biological function of some CT-X genes has been characterized. For instance, MAGE genes can have a role in signal transduction and transcription modulation and a member of GAGE family can repress apoptosis [6]. Most of CT-X genes are clustered in two regions: Xp11 and Xq26-q28. High level of multigenicity of many CTAs can be attributed to gene duplication and subsequent divergence [7]. Expression of CT-X antigens is different in different types of tumours. Their highest expression frequency has been seen in bladder cancer, lung


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cancer, ovarian cancer, hepatocellular carcinoma, and melanoma. CT-X genes are usually expressed in parallel, and tumours that express them tend to express several CT-X antigens. For example, in a study, it was revealed that 40% of breast tumours and 65% of melanomas expressed three or more CT-X [8]. CT-X genes have more restricted expression in normal tissues compared with non X-CTs and hence more likely to be used in immunotherapy approaches. In contrast to CT-X genes, the genes for non-X cancer testis genes are distributed throughout the genome and do not generally form gene families and are not located within genomic repeats. In the testis, they are expressed more predominantly in later stages of germ cell differentiation, such as in spermatocytes. It seems that many have a role in meiosis; so their aberrant expression in cancer may contribute to abnormal chromosome segregation and aneuploidy [1]. These two groups of CTAs seem to have different functions because of their expression in different stages of spermatogenesis. RT-PCR and digital differential display analysis show that CT-X genes are under more stringent transcriptional restriction in somatic tissues than non X-CT genes which have more expression in somatic tissues.

Identification of CTAs Several strategies have been used to identify CTAs. Many CTAs have been identified as a result of their recognition by CD8+ T cells and antibodies. Strategies such as T cell epitope cloning and SEREX rely on the ability of CTAs to elicit humoral or cellular immune response. So, gene products identified by such tools are true antigens, whereas genes identified by other strategies may not be immunogenic.

T cell epitope cloning Many antigens recognized by CD8+ T cells have been discovered by cDNA libraries constructed from tumour cells transduced into target cells, which express the suitable HLA molecule. Subsequently, antitumour T cells were isolated from tumour infiltrates to detect the antigen epitopes presented by HLA on the surface target cells. This approach was first used by Bruggen et al., and the first cloned antigen by this technique was the melanoma antigen MAGE-1. This antigen was shown to be a target antigen for one of the cytotoxic T cell clones and the first recognized immunogenic tumour antigen eliciting T cell responses in a cancer patient [9]. Other new tumour


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antigens including B melanoma antigen (BAGE) and G antigen (GAGE) gene family were identified by this strategy [10, 11].

Serological analysis of cDNA expression libraries (SEREX) This method was first developed by Sahin and his colleagues who used antibody repertoire of cancer patients to identify antigens. Using this method, antibody response can be detected. In this approach, a cDNA expression library is constructed from a fresh tumour specimen and cloned into phage expression vectors. Then, E.coli cells are transduced by these recombinant phages. Recombinant proteins expressed by bacteria are incubated with serum from the autologous patient. Clones reactive with high-titer antibodies are distinguished and nucleotide sequence of the cDNA insert will be identified. This technique was applied to identify CTAs NY-ESO-1, CT7/MAGE-C1, SCP-1, OY-TES1, HOM-TES-85, CAGE, cTAGE, and PASD1 [3]. But the clinical significance of these anti-tumour antibodies is unknown; so, the antigens recognized by these antibodies should be screened for T cell recognition by reverse T-cell immunology. To accomplish this, antigen presenting cells should be either loaded with selected major histocompatibility complex (MHC) class I binding peptides or transduced by cDNA of the antigen [2].

Differential gene expression analysis Differential display is a powerful tool for the comparison of gene expression between two or more mRNA populations. This technique consists of PCR and denaturing polyacrylamide gel electrophoresis steps to provide DNA fingerprints of tissues. RNAs extracted from the sources to be compared are reverse transcribed with one of a possible set of four degenerate oligonucleotide primers (dT)12VC, (dT)12VA, (dT)12VG, or (dT)12VT where V is C, A, or G. First-strand cDNA is used as a template in the PCR with oligo(dT) primer mixture and a decamer sequence that has been randomly generated. The complex mixtures of cDNAs are then separated by electrophoresis by a denaturing polyacrylamide gel. Cancer-testis genes can be efficiently identified through comparison of testis and cancer tissue libraries [2].

DNA and tissue microarrays Microarrays are miniature devices having thousands of DNA sequences as gene-specific probes, immobilized on solid support (nylon, glass, silicon).


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cDNA targets labeled with a radioactive, fluorescent, or chemiluminescent tag are hybridized with sequences on array, and the intensity of the signal generated by each bound probe indicates the relative abundance of that transcript in the sample. Using this technology, gene pool of tumour samples are compared with DNA sequences derived from testis-specific genes. This has been applied to identify a new CTA named STK31 in colorectal cancer. Tissue microarray technology is a powerful tool for simultaneous analysis of hundreds of tissue specimens in a single experiment. A tissue microarray is constructed by taking core biopsies of paraffin-embedded tissues and re-embedding them on a single arrayed ‘‘master block’’. Tissue microarrays are dependent on a variety of techniques such as immunohistochemistry for protein expression and fluorescence in situ hybridization (FISH) to detect DNA alterations. Tissue microarrays have the advantage of examining a single gene product per experiment in a large number of samples. So, it is possible to assess expression of a single testis gene in various tumour samples [2].

Massively parallel signature sequencing (MPSS) In this approach millions of short sequence tags associated to transcript from different RNA preparations are generated and MPSS data of normal testis and different cancer tissues are compared. Using this approach a new CT gene called CT45 was found which is frequently expressed in lung cancer.

Serial analysis of gene expression (SAGE) Serial analysis of gene expression (SAGE) is a method that has the ability to quantitate and compare large numbers of transcripts. Only a portion of the cDNA transcript, which is known as a SAGE tag, is needed to analyze the expression profile of each particular tissue. As the first concatemers (DNA segments composed of repeated sequences linked end to end) of SAGE tags are made; then, up to 30 tags will be sequenced at once. The frequency of each tag in the concatenated sequence shows the abundance of the corresponding transcripts in that cell. So, expression levels of a sequence can be compared between two populations. SAGE libraries can be used to analyze the differences in gene expression between cells or tissues [2]. A more comprehensive approach to identify CT genes is a combination of four platforms: MPSS, Expressed sequence tags (ESTs), Cap-analysis of Gene Expression (CAGE) and RT-PCR. This comprehensive approach


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resulted in categorization of 153 CT genes according to their expression in normal tissues rather than testis [12]. A CT database has been recently established by the Ludwig Institute for Cancer Research (http://www.cta.lncc.br/) which contains results of standardized RT-PCR analysis of each CTA in a panel of 22 normal tissues and 32 cancer cell lines.

Function of CTAs Biological functions of CTAs are not completely understood, but the function of non X-CTs is better clarified than CT-X antigens. The fact that expression of CTAs is much higher in high grade tumours and metastases provides clues that CTA expression has a role in tumourigenesis rather than being unrelated by-products of this process. It was found that cell lines expressing at least one of the three MAGE genes were more resistant to TNFmediated cytotoxicity. Transfection of cells with MAGEA2 or MAGEA6 genes also gives them a proliferative advantage [2]; and Mage-A2 protein strongly down-regulates p53 trans-activation [12]. MAGE-A11 has a role in the regulation of androgen receptor function and MAGE-A4 binds to oncoprotein gankirin [12]. Multiple MAGE proteins can form complexes with Kap-1, a co-receptor of p53; and suppression of these gene products by siRNA results in p53 expression and apoptosis. Similar anti-apoptotic activity was found for CAGE. A newly identified CT gene, Spermatogenesis Associated 19 (SPATA19) has been proposed to participate in cell differentiation, multicellular organismal development and spermatogenesis. It was shown that SPATA19 is expressed in basal cell carcinoma [13] and prostate adenocarcinoma [14]. SPATA19 contains a mitochondria-targeting signal and works as an adhesive molecule between the adjacent mitochondria of the sperm sheath, so it has a role in the maintenance of the normal mitochondrial sheath. Activation of the mitochondrial pathway can reverse cellular energy metabolism to nonmalignant phenotype and also promotes reactive oxygen species (ROS) production by mitochondria and increase the susceptibility of tumour cells to apoptosis. Consequently, targeting of the mitochondria is a promising strategy for induction of apoptosis in tumour cells. SPATA19 has the special characteristic of having a mitochondria-targeting signal, so it can be a potential target in this field [14]. TSGA10 is a new cancer-testis gene whose function is partly identified. Mouse homologue of TSGA10 mRNA has mitotic arrest deficient domain and was first detected in the postmeiotic phase of spermatogenesis. It is then


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processed to a major fibrous sheath protein of the sperm tail. Mitotic arrest deficient is a mitotic checkpoint protein. The mitotic spindle checkpoint monitors proper attachment of the bipolar spindle to the kinetochores of aligned sister chromatids. Recently, a protein–protein interaction between hypoxia inducible factor 1 (HIF-1), a transcriptional regulator of genes involved in oxygen homeostasis, and the TSGA10 was identified by yeast two- hybrid screening. Recent models suggest that TSGA10, after processing, can also serve as a scaffold for protein complexes involved in regulating signal transduction and cell division processes [15-17]. TSGA10 has been reported to be expressed in different types of tumours including 84.6% of acute lymphoblastic leukemia samples [18, 19]. The outer dense fiber (ODF) proteins have preferential expression during mammalian spermiogenesis. These proteins co-assemble along the axoneme during the development of the sperm tail and play a role in maintaining the passive elastic structures and elastic recoil of the sperm tail. It has been shown that ODF1 and ODF2 are expressed in basal cell carcinoma and prostate cancer [13, 14]. In another experiment, it was suggested that SSX has a functional role in cell migration and a potentially similar function in cancer cell metastasis. It has been revealed that when SSX is down-regulated in a melanoma cell line expressing SSX, the migration of cells will decrease [2]. As many of the important characteristics of cancer cells such as migration, invasion, immune subversion, apoptosis resistance, and induction of angiogenesis are also seen in gametogenesis or placentation processes, it is possible that CTA products controlling gametogenesis processes give similar characteristics to cancer cells. Briefly, CTA functions can be categorized as follows:

♣ Structural components of spermatozoa such as TSGA10. ♣ Possible role in transcription regulation such as MAGE-A, SSX, ♣ ♣ ♣ ♣ ♣ ♣

HOM-TES-85, E2Flike/ HCA661, TAF7L, BRDT, PLU-1, BORIS, NXF2. Possible role in signal transduction such as LIP1, SGY1, MAGE. Helicase-like features such as CAGE, HAGE. Cell to cell binding such as SPA17, TPX1, ADAM2. Enzymatic actions such as ADAM2, LIP1, TSP50, LDHC, TPTE. Probable role in inhibition of apoptosis such as CAGE. Components of synaptonemal complex such as SCP1, SPO11 [2].


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It has been suggested that expression of these antigens in tumour tissues is restricted to cells that maintain stem cell properties. CTAs may be true hallmarks of cancer stem cells and can be considered as targets for interference in recurrence and metastatic processes.

Regulation of CTA expression An important question regarding their expression is about the mechanism of their transcriptional silencing in normal tissues except testis and their derepression in malignancies. Activation of CTAs in cancer may be the result of induction of a gametogenic program in cancer and different CTA expression profile observed in cancer may be a reflection of CTA expression profile in different stages of gametogenesis or placentation [12]. Especially for CT-X genes, expression can be induced by DNA methyl-transferase 1 inhibitors, 5-aza-2’-deoxycytidine (5DC), and by histone deacetylase (HDAC) inhibitors. It has been proven that DNA methylation is the primary silencing mechanism for these genes and demethylation is necessary and sufficient to produce their expression. It was also shown that heavy methylation represses gene expression in cells despite the presence of transcription factors required for expression. In another study, it was shown that the site specific hypomethylation of MAGE-A1 in tumour cells depends on demethylation and then persistent local inhibition of remethylation [2]. Multiple sequence alignment results and comparison of the 5’ flanking regions of the mouse and human TSGA10 genes indicate that the homologue of the first exon of the mouse gene is located at 8.3 kb upstream of human exon 1. This result may indicate TSGA10 genes use different exon 1 sequences and different promoters; so, different mechanisms may act in different animals. The presence of an alternative promoter in human and pig TSGA10 genes compared with mouse and rat genes still needs to be investigated [16]. The mechanism of epigenetic regulation is somehow clear for some genes. For instance, recent data indicate that reciprocal binding of CCCTCbinding factor (zinc finger protein, CTCF) and CCCTC-binding factor like (BORIS) to the NY-ESO-1 promoter mediates epigenetic regulation of this CTA in lung cancer cells, and suggest that induction of BORIS may be a novel strategy to enhance immunogenicity of pulmonary carcinomas. It has also been shown that intratumoural heterogeneity of expression of CTAs in melanoma is regulated by methylation and using the demethylation agent 5-aza-2’- deoxycytidine they could induce expression of several CTAs [2].


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CTAs as targets for cancer immunotherapy Blood-testis barrier Pathophysiologic data suggest that a blood-testis barrier exists in testis. As spermatogenesis begins at puberty, new cell surface antigens are expressed when the immune system has refined the ability to distinguish self from nonself. So, sperms in the testis do not stimulate immune responses. In addition, although antigen-presenting cells are commonly seen in the interstitial spaces of the testis, these cells are scarcely seen within the seminiferous tubules. So, testis is considered as an immuneprivileged site. The mechanical barrier is made by tight junctions between Sertoli cells along the basolateral aspect and between capillary endothelial cells. The apparent lack of human leukocyte antigen (HLA) class I expression on the surface of germ cells is also important in making the testis an immune privileged site.

Figure 1. The Blood-Testis Barrier is a result of tight junctions between Sertoli. cells along the basolateral aspect and between capillary endothelial cells. 1: Basal lamina, 2: Sertoli cell, 3: Tight junction Modified from: http://en.wikipedia.org/wiki/Bloodtestis_barrier.


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Immunogenicity of CTAs The characteristics of CTAs (expression in different type of cancers but not in normal tissues rather than testis) make them promising candidates for immunotherapy. To use CTAs in immunotherapy approaches, the first step is to prove their immunogenicity. Ability of CTAs to elicit cellular and humoral responses has led directly to the development of antigen-specific cancer vaccines. Humoral responses to CTAs have been seen in several tumours usually by means of ELISA testing against recombinant CT protein. For instance, antibodies against SCP-1 in pancreatic cancer, antibodies against NY-ESO-1, SCP-1, and SSX-2 in breast cancer, antibodies against CTSP-1 in prostate, thyroid, and breast tumours, antibodies against TSGA10 in hepatocellular carcinoma and malignant melanoma, and antibodies against MAGEA3, SSX2, and NY-ESO-1 in multiple myeloma, have been detected. Among these CTAs, NY-ESO-1 is the most attractive for cancer immunotherapy. The prevalence of anti-NY-ESO-1 antibodies in patients with advanced NY-ESO-1 positive tumours is estimated at 25-50% and the antibody titer increases with progression of the cancer and decreases after removal of the tumour [12]. CTAs are also immunogenic to cytotoxic T lymphocytes. For instance, Sp17 specific HLA-A1 and B27 restricted cytotoxic T lymphocytes generated from peripheral blood of a healthy donor were able to kill HLA-matched myeloma cells [2]. HLA-restricted T-cell epitopes have been identified for several CTAs including MAGE-A, NY-ESO-1 and SSX. Concurrent humoral and cellular responses have been detected for NY-ESO-1, MAGE-A and SSX antigens [12]. Another important point is to investigate the composite expression of CTAs in tumours. This is crucial for developing polyvalent vaccines because it is necessary to know what proportion of patients with a certain type of cancer can benefit from a polyvalent vaccine and which antigens are more suitable to be used in a polyvalent cancer vaccine for a certain type of cancer.

Cancer vaccine trials using CTAs Vaccination with antigens specifically expressed by tumours can trigger the immune system and produce specific anti -umour response. There are a growing number of human tumour specific antigens and their encoded MHC epitopes; and among them many epitopes are encoded by CTAs. Multiple clinical trials have been conducted using MAGE-A3 or NYESO-1. Both have resulted in tumour regression in melanoma patients.


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Immunological responses were also detected in both but more frequently in NY-ESO-1 than MAGE-A3 vaccinated patients [20, 21]. Over 34 trials with different NY-ESO-1 vaccine formulations have been performed. NY-ESO-1 peptide, protein, and pox-NY-ESO-1 vaccines can all induce strong NY-ESO-1 humoral and cellular responses in patients with no pre-existing NYESO- 1 immunity. The NY-ESO-1 Protein/ISCOMATRIX速 trial conducted by Jonathan Cebon had some hopeful results and a Phase II randomized trial is now ongoing. The salmonella/NY-ESO-1 vaccine, which has had considerable therapeutic effects in mice, is now being prepared for the clinic and NY-ESO-1 adenovirus constructs for vaccination will be developed in the near future. Although the field of antigen-specific cancer vaccine is still in its early steps, it is anticipated that CTAs will be at the center of attention for immunotherapy in the future.

Future directions As mentioned above, expression of CTAs often shows marked specificity for tumour cells. These markers can be used for early detection of cancer cells and specific gene immunotherapy of cancer. Active immunotherapy is still in preclinical and clinical trial phases of development but it will become available in the clinics in the near future. The growing knowledge in CTAs and their ability to elicit cellular and humoral responses will provide new tools for active immunotherapy of patients. Recent studies have shown that CTAs can be useful in adaptive Tcell transfer approaches [12]. Recent experiments postulate a relation between germline stem cells and cancer stem cells (CSC) with some evidence for CTA expression in both stem cells. This hypothesis needs to be investigated in different tumours and tissues. The embryonic stem (ES) cell and germline stem cell genes are subverted in precancerous stem cells. For example, the germline stem cell protein piwil2 may play an important role during the development of CSC, and these kinds of proteins may be used as common biomarker for early detection, prevention, and treatment of cancers [22]. Finally, many changes in tumoural cells are caused by post-translational modifications which are not detected by DNA/RNA analyses; so proteomicsbased studies of different tumour types are now underway. As a result, modifications of CTAs at protein level in tumoural cells may be detected and compared with normal cells with the aim to find new biomarkers for cancers [2].


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Conclusion CTAs are tumour antigens with limited expression in male germ cells in the testis and different types of tumours. Due to the existence of the bloodtestis barrier, if testis specific proteins are expressed in other sites of body, they can elicit immune response. CTAs are promising candidates for cancer immunotherapy and have become a major focus for the development of vaccine-based clinical trials in recent years. In addition, these antigens may be used as biomarkers for early detection of cancers in the future.

References 1.

Simpson, A.J.G., O.L. Caballero, A. Jungbluth, Y. Chen, L.J. Old, Cancer/testis antigens, gametogenesis and cancer. Nat Rev Cancer, 2005. 5: p. 615-25. 2. S. And M.H. Modarressi, Cancer-testis antigens: potential targets for cancer immunotherapy. Arch Iranian Med, 2009. 12(4): p. 395-404. 3. Caballero, O.L. and Y.T. Chen, Cancer/testis (CT) antigens: Potential targets for immunotherapy. Cancer Sci, 2009. 100(11): p. 2014-21. 4. Costa, F.F., K.L. Blanc, B. Brodin, Concise review: cancer/testis antigens, stem cells, and cancer. Stem Cell, 2007. 25: p. 707-11. 5. Old, L.J. Cancer is a somatic cell pregnancy. Cancer Immunity, 2007. 7: p. 19. 6. Stevenson, B.J., C. Iseli, S. Panji, M. Zahn-Zabal, W. Hide, L.J. Old, et al., Rapid evolution of cancer/testis genes on the X chromosome. B M C Genomics, 2007. 8: p. 129-39. 7. Zendman, A.J.W., D.J. Ruiter, G.N.P. van Muijen, Cancer/testis assosiated genes: identification, expression profile, and putative function. J Cell Physiol, 2003. 194: p. 272-88. 8. Sahin, U., O. TĂźreci, Y.T. Chen, G. Seitz, C. Villena-Heinsen, L.J. Old, Expression of multiple cancer/testis (CT) antigens in breast cancer and melanoma: basis for polyvalent CT vaccine strategies. Int J Cancer, 1998. 78: p. 387-9. 9. van der Bruggen, P., C. Traversari, P. Chomez, C. Lurquin, E. De Plaen, B. van den Eynde, et al. A gene encoding an antigen recognized by cytolytic T lymphocytes on a human melanoma. Science, 1991. 254: p. 1643-7. 10. BoĂŤl, P., C. Wildmann, M.L. Sensi, R. Brasseur, J.C. Renauld, P. Coulie, et al. BAGE, a new gene encoding an antigen recognized on human melanomas by cytolytic T lymphocytes. Immunity, 1995. 2: p. 167-75. 11. van den Eynde, B., O. Peeters, O. De Backer, B. Gaugler, S. Lucas, T. Boon, A new family of genes coding for an antigen recognized by autologous cytolytic T lymphocytes on a human melanoma. J Exp Med, 1995. 182: p. 689-98. 12. Hofmann, O., O.L. Caballero, B.J. Stevenson, Y.T. Chen, T. Cohen, R. Chua, et al. Genome-wide analysis of cancer/testis gene expression. Proc Natl Acad Sci U S A, 2008. 105: p. 20422-7.


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13. Ghafouri-Fard, S., A. Abbasi, H. Moslehi, N. Faramarzi, S. Taba taba, S.Vakili, et al., Elevated expression levels of testis-specific genes TEX101 and SPATA19 in basal cell carcinoma and their correlation with clinical and pathological features. B J D, 2010. 162(4): p. 772-9. 14. Ghafouri-Fard, S., Z. Ousati Ashtiani, B. Sabah Golian, S.M. Hasheminasab, M.H. Modarressi, Expression of two testis-specific genes, SPATA19 and LEMD1, in prostate cancer. Arch Med Res, 2010. 41(3): p. 195-200. 15. Modarressi, M.H., J. Cameron, K.E. Taylor, J. Wolfe, Identification and characterisation of a novel gene, TSGA10, expressed in testis. Gene, 2001. 262: p. 249-55. 16. Modarressi, M.H., B. Behnam, M. Cheng, K.E. Taylor, J. Wolfe, F.A. van der Hoorn, Tsga10 encodes a 65-kilo-dalton protein that is processed to the 27-kilodalton fibrous sheath protein. Biol Reprod, 2004. 70: p. 608-15. 17. Behnam, B., M.H. Modarressi, V. Conti, K.E. Taylor, A. Puliti, J. Wolfe, Expression of of Tsga10 sperm tail protein in embryogenesis and neural development: from cilium to cell division. Biochem Biophys Res Commun, 2006. 344: p. 1102-10. 18. Mobasheri, M.B., I. Jahanzad, M.A. Mohagheghi, M. Aarabi, S. Farzan, M.H. Modarressi, Expression of two testis-specific genes, TSGA10 and SYCP3, in different cancers regarding to their pathological features. Cancer Detect Prev, 2007. 31: p. 296-302. 19. Mobasheri, M.B., M.H. Modarressi, M. Shabani, H. Asgarian, R.A. Sharifian, P. Vossough, et al., Expression of the testis-specific gene, TSGA10, in Iranian patients with acute lymphoblastic leukemia (ALL). Leuk Res, 2006. 30: p. 883-9. 20. Jager, E., J. Karbach, S. Gnjatic, A. Neumann, A. Bender, D. Valmori, et al., Recombinant vaccinia/fowlpox NY-ESO-1 vaccines induce both humoral and cellular NY-ESO-1-specific immune responses in cancer patients. Proc Natl Acad Sci U S A, 2006. 103: p. 14453-8. 21. Marchand, M., N. van Baren, P. Weynants, V. Brichard, B. DrĂŠno, M.H. Tessier, et al., Tumor regressions observed in patients with metastatic melanoma treated with an antigenic peptide encoded by gene MAGE-3 and presented by HLA-A1. Int J Cancer, 1999. 80: p. 219-30. 22. Gao, J.X., Piwil2 is expressed in various stages of breast cancers and has the potential to be used as a novel biomarker. J Cell Mol Med, 2008. 12: p. 67-96.


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Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 99-113 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

5. Ethics in the cancer clinic 1

Javad Tavakkoly Bazzaz1, Elahe Motevaseli1 Mahsa M. Amoli2 and Bagher Larijani2 Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; 2Endocrinology and Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran

Abstract. While acquired genetic alterations are the basis of most cancers, a small but noticeable portion of cancers results from germ line mutations. There are some commercially available tests for mutation detection in these cancers. Although the tests would be useful from many aspects, it should be noted that many ethical dilemmas will emerge from the knowledge of the genetic susceptibility of an individual to cancer. The purpose of this chapter is to explain some hereditary cancer predisposing syndromes and ethical considerations for genetic testing by practitioners to offer some proper and practical recommendations.

Introduction While acquired genetic alterations are the basis of most cancers, a small but noticeable portion of cancers result from germ line mutations. Several major types of these mutations have been characterized in the past few years by significant advances in molecular genetics. Nowadays, there are some Correspondence/Reprint request: Dr. Javad Tavakkoly Bazzaz, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O.Box 14155-6447, Tehran, Iran E-mail: tavakkolybazzazj@tums.ac.ir


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commercially available tests for mutation detection in cancer predisposing genes, which can be used to identify people at high risk for hereditary cancers and their referral for preventive options. These options include targeted surveillance, chemoprevention, and surgical procedures. Although genetic testing would be useful from many aspects, it should be noted that many ethical dilemmas will emerge from the knowledge of the genetic susceptibility of an individual to cancer. One of the major dilemmas arises when a person with positive test results does not want to inform his/her family members of their risks. Thus, the practitioner will be faced with a challenge between confidentiality of the patient and his/her duty to warn the index patient’s relatives. In the case of high penetrance cancers with effective preventive options, this issue would be more pronounced. Therefore, the need for outlining ethical principles and rules for clarifying such challenges and offering proper options would be more realized. There are more examples of such dilemmas, and because they are common in cancer genetics clinics, practitioners should be aware of these issues and relevant ethical rules and remedies. The purpose of this section is to explain some of these issues to offer some proper and practical recommendations. The 2003 statement of American Society of Clinical Oncology (ASCO) policy on genetic testing for cancer susceptibility, its update (Genetic and Genomic Testing for Cancer Susceptibility, 2010), and Ethical Guidelines for Genetic Research in Iran will be used as the basis for defining the ethical rules [1-3].

Hereditary cancer predisposition syndromes The hereditary component of many cancers was recognized many years ago. Epidemiologic studies showed that some cancers cluster in certain families, and they have hereditary basis. For example, in 1865, Broca described the incidence of hereditary breast cancer in four generations [4], and in 1913, Aldrin Warthin characterized a family with a cluster of gastrointestinal and gynecologic malignancies, which seemed to be hereditary nonpolyposis colorectal cancer (HNPCC) [5,6]. Nowadays, Genetic testing for predisposing cancer mutations has been widely implemented in the clinical setting. Recent studies indicate that 5–10% of the common cancers (i.e., colon, breast, and prostate) occur in individuals that have inherited predisposing cancer genes, which can be passed onto their offspring [7-9]. Most cancer syndromes are related to single-gene mutations not multipleloci gene mutations. The onset of some hereditary cancer syndromes are in the earlier stages of life. For example, retinoblastoma is generally diagnosed


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before the age of 4 years. However, most cancers have a late-onset and are commonly diagnosed during the middle period of life [9]. Different hereditary cancer syndromes have different penetrance (i.e., the lifetime risk of developing cancer) and expression risks among mutation carriers. However, the risk for a particular cancer can approach 85–100% over a lifetime. Hereditary cancers mainly develop at a younger age and often prior to the time when general screening is done. Nowadays, the risk assessment by genetic testing is mostly offered for well-defined hereditary cancers with high penetrance. Examples include mutations of the BRCA1 and BRCA2 genes, which predispose the carriers to breast and ovarian cancer, and the mismatchrepair genes that predispose one to Lynch syndrome (hereditary nonpolyposis colon cancer [HNPCC]) [10]. This section focuses primarily on the above mentioned cancers, including breast-, ovarian- cancers and Lynch syndrome (Table 1) because breast and ovarian cancers are the most common cancers in women and colorectal cancer is one of the most important causes of cancer related deaths in men. Table 1. Brief clinical descriptions of HNPCC and HBOCS [11]. Condition

Genes

Families are characterized by

HNPCC (hereditary nonpolyposis colorectal cancer.)

MLH1, MSH2, MSH6, PMS2ab PMS1ab

Colorectal and endometrial cancer, age of onset 50 yrs. May observe extracolonic cancers such as stomach, small bowel, ureter or renal-pelvis, ovary, brain, sebaceous skin tumors Autosomal dominant transmission: multiple cases of HNPCC-related tumors in paternal or maternal lineage, and in more than one generation

HBOCS (hereditary breast and ovarian cancer)

BRCA1, BRCA2

Breast cancer, age at onset 50 yrs. Nonmucinous epithelial ovarian cancer Autosomal dominant transmission: multiple cases of breast and/or ovarian cancer in paternal or maternal lineage, and in more than one generation


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Hereditary colorectal cancer There are two main types of hereditary colorectal cancer syndromes: Lynch syndrome or hereditary non-polyposis colorectal cancer (HNPCC), and the familial adenomatous polyposis (FAP) syndrome [6]. Most FAP syndromes are related to mutations in the adenomatous polyposis coli (APC) gene (5q21–q22), which encodes a protein that controls apoptosis, others may be caused by biallelic mutations in the MYH gene [12]. The penetrance of FAP is near 100% by age 35 and the risk of colon cancer is close to 100% with an average age of onset of 39 years [4]. FAP has an autosomal dominant inheritance pattern. Thus, the offspring of a carrier will have a 50% chance of predisposition to colorectal cancer or other cancers [9]. Lynch syndrome (hereditary nonpolyposis colon cancer [HNPCC]) is defined by microsatellite instability (MSI) in the tumor. MSI is characterized by appearance of multiple repeats of small snippet DNAs in the polymerase chain reaction as an indication of a DNA-mismatch- repair defect in cells. At present, MSI detection is mainly substituted with immunohisotchemical staining of the protein products of the DNA-repair genes [13-14]. About 45–70% of HNPCC families have germ line mutations in one of the hMSH2, hMLH1 and hMSH6 genes. In addition, mutations in hPMS1 and hPMS2 genes have also been defined as the cause of the HNPCC syndrome. All of the above mutations contribute to 3–5% of all colorectal cancers [4, 15]. Box 1. Revised Bethesda Guidelines (2004) for testing of the Lynch syndrome [16]. •

Colorectal cancer diagnosed in a patient less than 50 years of age

Presence of synchronous, metachronous colorectal, or other tumors associated with Lynch syndrome (HNPCC) regardless of age (Lynch syndrome–related tumors include cancers of the colon, rectum, endometrium, stomach, ovaries, pancreas, ureter, renal pelvis, biliary tract, small bowel, and brain, usually glioblastomas (Turcot syndrome), sebaceous gland adenomas, or keratoacanthomas (Muir–Torre syndrome).

Colorectal cancer with the MSI-high histology diagnosed in a patient less than 60 years of age [MSI-high refers to peaks in more than one of the recommended microsatellites (BAT25, BAT26, D2S123, D5S346, and D17S250)].

Colorectal cancer diagnosed in one or more first-degree relatives with an HNPCC-related tumor and with one of the cancers being diagnosed at less than 50 years of age.


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Table 2. Clinical management and genetic status [11]. Genetic testing status No testing information (family history alone) uninformativenegative test result Positive for mutation

Negative for familial mutation

Endometrial cancer Endometrial biopsies and transvaginal ultrasound every year

Colonoscopy Every 1–3 yrs.

Annually Endometrial biopsies and transvaginal ultrasound annually; consideration prophylactic hysterectomy, oophorectomy None Every 5 years starting at age 50 yrs.

HNPCC syndrome usually arises before 50 years of age, and its related tumors include colorectal, endometrial, stomach, ovarian, and pancreatic carcinoma, with the risk of colon and endometrial cancers ranging from 70- 90% and 30-60%, respectively [4, 16]. The burden for both FAP and HNPCC is devastating for the patients and their families. Furthermore, genetic testing (Box 1) can refer patients to surveillance or surgical intervention programs (Table 2) [9, 11, 17]. Because these programs can prevent or diagnose cancer at an early stage, genetic testing and disclosure of the information to the other family members is likely to have an important role in improvement of their heath and a reduction in morbidity and/or mortality.

Hereditary breast and ovarian cancer Hereditary breast and ovarian cancers are mainly associated with BRCA1 and BRCA2 mutations [18]. There are some blood tests available that can identify the germ line mutation carriers. One in 300-800 individuals in the population carry genetic susceptibility (usually BRCA1 and/or BRCA2 mutations) to breast or ovarian cancer, and this accounts for 3-10 percent of all cases of breast cancer. The penetrance of mutations has been estimated to be in the range of 50–80% for BRCA1 and 40–70% for BRCA2, with the range influenced by the studied population [4, 18]. The ovarian cancer risk among BRCA gene mutation carriers is about 40% over a lifetime.


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Children of a patient with BRCA1/ BRCA2 germline mutation have a 50% risk of inheriting that mutation. However, because of the incomplete penetrance and variable expression, the development and onset of cancer cannot be precisely predicted. Women of reproductive age with BRCA1/2 mutations often are faced with family-planning and reproductive issues that will raise important ethical dilemmas, especially in pre-implantation and prenatal diagnosis procedures [19].

Ethical considerations for genetic testing practitioners Ethical principles Every healthcare provider should initiate his/her activity in the medical clinic by adhering to the original ethical principles. The four original principles of biomedical ethics are: 1) respect for autonomy; 2) beneficence; 3) justice; and 4) nonmaleficence [20-24]. Autonomy The principle of autonomy defines the right of an individual to selfdetermination. It relies on having the ability to make informed decisions about one’s own personal matters. The respect for this principle requires that action of a medical professional never have harmful effects upon the patient’s autonomy, even if that professional disagrees with that individual’s decision. Benificence The principle of beneficence means doing well unto others. It emphasizes serving the best interest of the patients. Practitioners must regularly ask themselves who will benefit from their actions, and in what way. Justice The principle of justice means that the benefits and burdens should be shared equally among the population. In practice, practitioners should be certain of equitable treatment of patients, especially the more vulnerable groups (e.g. children and mentally retarded persons). Furthermore, the equity of access to genetic testing should be considered seriously.


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Non-maleficence The principle of non-maleficence means “above all [or first], to do no harm,” and states an obligation not to inflict harm intentionally. Practitioners should recognize those who may be harmed by a particular's action, and inform them in an open and truthful manner. Ethical rules Although ethical principles are important, the ethical rules, and the “informed consent and confidentiality,” derived from those principles are more efficient. These two rules underline the majority of the dilemmas practitioners encounter for either genetic testing recommendations, or passing on the results. Generally speaking, practitioners should be aware of both international and national laws regarding informed consent, confidentiality, and genetic counselling and discrimination [21].

Informed consent Informed consent is based on autonomy to protect patient’s autonomous decision. To make an informed and autonomous decision, a person should be aware of the available preventive options and their implications [25.] A patient’s decision must be free from coercive impacts, and it must be based on the patient’s own beliefs [25]. Informed consent is an important part of genetic testing for hereditary cancer syndromes, and it includes a careful discussion of the possible outcomes, benefits, risks, and limitations of the genetic testing, as well as a discussion of the alternatives [26]. Deciding to accept or decline the test should be made autonomously in line with the patient’s own desires and plans [1]. ASCO states (Table 3) that oncologists should consider offering genetic testing only if they are able to provide or make available adequate genetic education and counseling as well as access to preventive and surveillance options. Otherwise, they should consider referring the patient and his/her family to these services. Because of the medical, social, and legal ramifications associated with the results of genetic testing, ASCO strongly recommends that genetic testing should be done only when paired with preand post-test counseling [1,2]. Pre-test counseling ensures that patients are aware of the potential implications of their test results and post-test counseling will also ensures that patients make informed medical decisions after receiving their test results.


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Table 3. Basic Elements of Informed Consent for Cancer Susceptibility Testing (modified from American Society of Clinical Oncology 2003 statement) [2]. 1.

Information on the specific genetic mutation(s) or genomic variant(s) being tested, including whether the range of risk associated with the variant will impact medical care 2. Implications of a positive and negative result 3. Possibility that the test will not be informative 4. Options for risk estimation without genetic or genomic testing 5. Risk of passing a genetic variant to children 6. Technical accuracy of the test including, where required by law, licensure of the testing laboratory 7. Fees involved in testing and counseling and, for DTC testing, whether the counselor is employed by the testing company 8. Psychological implications of test results (benefits and risks) 9. Risks and protections against genetic discrimination by employers or insurers 10. Confidentiality issues, including, for DTC (direct to consumer) testing companies, policies related to privacy and data security 11. Possible use of DNA testing samples in future research 12. Options and limitations of medical surveillance and strategies for prevention after genetic or genomic testing 13. Importance of sharing genetic and genomic test results with at-risk relatives so that they may benefit from this information 14. Plans for follow-up after testing Table 4. Questions to Ask Patients With and Without Cancer [26]. Questions to ask all patients • Age • Personal history of benign malignant tumors • Major illnesses • Hospitalizations • Surgeries • Biopsy history • Reproductive history • Cancer surveillance • Environmental exposures

Questions to ask patients who have had cancer/or regarding relatives with cancer • Organ in which tumor developed • Age at time of diagnosis • Number of tumors • Pathology, stage, and grade malignant tumor • Pathology of benign tumors • Treatment regimen (surgery, chemotherapy, radiation)


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Pretest genetic counselling The first step of counselling is the collection of a patient’s personal and family medical history. The information to be obtained includes the frequency of cancer surveillance, the date and results of recent screening examinations and details about pertinent environmental exposures (Table 4,5) [26,27]. The information that a practitioner is required to be provided to a patient: 1. Why the test is recommended and who should be tested. 2. Reviewing the relevant information about cancer genes and their risks. 3. Defining the implications of all possible test results a. Positive result: The possibility of developing various cancers depends upon different genes, their penetrance, and expressivity. b. Negative result: In the absence of a known mutation in a family, genetic heterogeneity should be considered. c. Variants with unknown significance which would be alterations in sequences not known to be involved with mRNA processing. 4.

5. 6. 7. 8.

Possibility of a positive result using statistical models and pedigree assessment in order to provide qualitative and quantitative information for the patient. Explaining likelihood of a false-positive or a false-negative result for the patients. Informing the patient regarding the cost of genetic testing Informing the patient about potential risk for discrimination Explaining the possible psychosocial aspects. a. b. c. d.

Anticipated reaction to results. Timing and readiness for testing. Family issues. Preparing for results.

9. Discussion of confidentiality issues when the results would be disclosed to other family members. 10. Reviewing utilizations of the test including medical surveillance and preventative procedures. 11. Discussing the alternatives to genetic testing. 12. Informing the patient about storage and potential reuse of genetic material [26].


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Table 5. Components of a typical genetic counselling session [27].

¾ Collecting personal medical history ¾ Collecting family medical history ¾ Physical examination to evaluate features related to inherited syndromes Risk assessment ¾ Analyzing the information gathered to develop a list of differential diagnoses Education ¾ Communicate information to the patient and their family about the condition, inheritance, and medical management Psychosocial counseling ¾ Promoting conversation about the patient’s feeling regarding how a diagnosis of a hereditary condition may affect their health and impact their family members, their fears, and their anticipated responses to the outcome of genetic testing Information gathering

Confidentiality and disclosure Confidentiality is a central and essential part of a doctor–patient relationship. In general, no medical information can be disclosed to any other person without the consent of the tested individual. However, when family-specific mutations are identified, individuals should be encouraged to disclose the results to other at-risk relatives to facilitate predictive testing, especially when proven surveillance and prophylactic measures are available. Furthermore, sharing of this information could influence other family members’ reproductive decisions. In case this disclosure to other relatives can be a burden for the index patient, the practitioner should consult the situation with the ethics committees [28]. Possible reasons for patient’s non-disclosure include: absence of interest, denial, difficult relationships with the family members, reluctance to deliver bad news, and practical barriers to communication. Non-disclosure is most important for high-penetrant genes (as in familial adenomatous polyposis and hereditary breast and ovarian cancer), for which there are surveillance or surgical procedures available, and diagnosis at an early stage results in significant reduction of morbidity and mortality [9, 25].


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Post-test counseling This is a multi-step process, optimally done during a face-to-face meeting. 1. Disclosure of the results. After obtaining the client’s consent, inform him/her of the result. 2. Significance of the test results. Review the specificity and sensitivity of the test and discuss how the client’s result affects his/her cancer risk. 3. Impact of the results. Assess the emotional impact of the result on the client and his/her support person through verbal and nonverbal cues; provide support as needed. 4. Medical management. Review screening recommendations and options of cancer-risk reduction, such as chemoprevention or prophylactic surgery, if available, and also include the benefits, risks, and limitations of such options. Provide referrals to other medical professionals for additional discussions of these topics and strongly encourage compliance with screening recommendations. 5. Informing other relatives. Discuss cancer risks to other relatives and the importance of informing the family members about family history and the genetic test results. Written documentations that the client can share with relatives may be provided, safeguarding confidentiality as desired by the client. If a high-risk client refuses to contact the at-risk relatives, consulting with the ethics committee would be an option [26, 29]. 6. Future contact. In case the follow-up care will be managed elsewhere, encourage the client to maintain his/her contact with the cancer risk assessment center for updates about their family history, the genetics of familial cancer disorders, and the management of inherited predisposition to cancer. The same applies to high-risk families with negative test results who maybe candidates for future testing. When available, offer clients the option of participating in long-term follow-up studies. 7. Resources. Provide the client with resources for cancer genetics and possibility of contacts with other willing clients, if desired and available. This could serve as a psychosocial support resource for the client or refer to other qualified individuals if additional support is needed [26].

Different kinds of discrimination Discrimination based on genetic information may be in many forms including insurance and employment. Thus, practitioners should make their patients aware of potentials for discrimination during the pre-test counseling session. ASCO supports establishing a federal law to prohibit discrimination


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by health insurance providers and employers on the basis of an individual’s inherited susceptibility to cancer [14, 21].

Ethical dilemmas Prenatal diagnosis or pre-implantation genetic diagnosis for cancer-predisposition genes Prenatal diagnosis means identification of a family specific mutation in a cancer-predisposition gene and collection of a fetal sample by chorionicvillus sampling or amniocentesis to find out whether or not the fetus is affected. Such testing provides an option to terminate the pregnancy if the fetus is affected. Pre-implantation genetic diagnosis involves the use of invitro fertilization to create several embryos. By day 3, the embryo consist of six to ten cells, one or two of which could be removed for analysis. PCR is used to amplify the DNA to detect single gene diseases [30]. Then, only unaffected embryos are re-implanted. This technique has been used for a range of genetic disorders for which family-specific mutations have been identified, including Huntington’s disease, cystic fibrosis, and Duchenne muscular dystrophy [25, 30]. Although many cancer predisposing genes do not have full penetrance and they can be early detected, many believe that PGD is ethically acceptable because of the heavy burden imposed on the carrier patients and their quality of life by preventive measures in cancer predisposition syndromes [30].

Genetic testing of children Cancer genetic testing not only provides useful information regarding the susceptibility of at-risk individuals to cancer and early death, but also reveals genetic information about the health of their family members including the offspring. Identification of an individual’s susceptibility to a particular hereditary cancer syndrome may eventually allow their family members to benefit from preventive and therapeutic modalities based on their genotypes. Testing for cancer-predisposition genes in children is recommended if a malignant disease is likely to develop in childhood and if evidence-based-risk-reduction strategies exist that could be implemented in childhood. Examples include retinoblastoma-gene testing (to avoid eye examinations under anaesthesia every 3 months), RET gene testing for multiple endocrine neoplasia 2 (to guide the need for thyroidectomy), and APC-gene testing for familial adenomatous polyposis (to guide the need for sigmoidoscopy).


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ASCO advises that if there is no cancer risk in childhood, testing should be deferred until adulthood. The reasoning behind this advice is to protect the child’s future autonomy and right not to know, to ensure that the child is not treated differently by the parents and is not stigmatized with limited education, marriage, and reproduction opportunities [31]. However, some argue that the idea of the child’s best interests includes more than medical interests; predictive testing in children can have important psychosocial benefits including self knowledge and planning [31].

Conclusion Genetic testing in cancer genetic clinics predicts future health and tries to facilitate the practice of preventive oncology for the individual and for his/her family members. The task of regulating ethical rules for protection of genetic information is essential to ensure that the most good and the least harm come to patients and their family.

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American Society of Clinical Oncology, American Society of Clinical Oncology policy statement update: genetic testing for cancer susceptibility. J Clin Oncol, 2003. 21(12): p. 2397-2406. Robson, M.E., C.D. Storm, J.Weitzel, D.S. Wollins and K. Offit, American Society of Clinical Oncology policy statement update: genetic and genomic testing for cancer susceptibility. J Clin Oncol.2010. 28(5): p. 893-901. Motevasseli , E., M. Akrami, S. Zeinali, MH. Modaresi, A. Parsapoor and K. Aramesh, A Review of compiling of Ethical Guidelines for Genetic Research in Iran. . Journal of Babol University of Medical Sciences 2006. 8(3): p. 49-54. Garber, J.E. and K. Offit, Hereditary cancer predisposition syndromes. J Clin Oncol, 2005. 23(2): p. 276-292. Warthin, A.S, Classics in oncology. Heredity with reference to carcinoma as shown by the study of the cases examined in the pathological laboratory of the University of Michigan, 1895-1913. 1913. CA Cancer J Clin, 1985. 35(6): p. 348-359. Oseni, T. and I. Jatoi, An overview of the role of prophylactic surgery in the management of individuals with a hereditary cancer predisposition. Surg Clin North Am, 2008. 88(4): p. 739-758. Claus, E.B., N. Risch, and W.D. Thompson, Genetic analysis of breast cancer in the cancer and steroid hormone study. Am J Hum Genet, 1991. 48(2): p. 232-242. Newman, B. H. Mu, L. M. Butler, R. C. Millikan, P. G. Moorman and M. C. King, Frequency of breast cancer attributable to BRCA1 in a population-based series of American women. JAMA, 1998. 279(12): p. 915-921.


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24. Larijani, B., F. Zahedi, and F. Asghari Ethics in genetic research. IJDLD, 2005. Supplement of Ethics in Clinical Research (4): p. 71-82. 25. Harris, M., I. Winship, and M. Spriggs, Controversies and ethical issues in cancer-genetics clinics. Lancet Oncol, 2005. 6(5): p. 301-310. 26. Trepanier, A., M. Ahrens, W. McKinnon, J. Peters, J.Stopfer, S.C. Grumet, et al., Genetic cancer risk assessment and counseling: recommendations of the national society of genetic counselors. J Genet Couns, 2004. 13(2): p. 83-8114. 27. Raymond, V.M. and J.N. Everett, Genetic counselling and genetic testing in hereditary gastrointestinal cancer syndromes. Best Pract Res Clin Gastroenterol, 2009. 23(2): p. 275-283. 28. Julian-Reynier, C., F. Eisinger, P. Vennin, F. Chabal, Y. Aurran, C. Nogues, et al., Attitudes towards cancer predictive testing and transmission of information to the family. J Med Genet, 1996. 33(9): p. 731-736. 29. American Society of Human Genetics, ASHG statement. Professional disclosure of familial genetic information. The American Society of Human Genetics Social Issues Subcommittee on Familial Disclosure. Am J Hum Genet, 1998. 62(2): p. 474-483. 30. Sermon, K., A. Van Steirteghem, and I. Liebaers, Preimplantation genetic diagnosis. Lancet, 2004. 363(9421): p. 1633-1641. 31. Savulescu, J., Predictive genetic testing in children. Med J Aust, 2001. 175(7): p. 379-381.


Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

Bridging Cell Biology and Genetics to the Cancer Clinic, 2011: 115-124 ISBN: 978-81-7895-518-6 Editor: Parvin Mehdipour

6. The final words The cyclic bridging programme for the cancer clinic Parvin Mehdipour

Department of Medical Genetics, School of Medicine Tehran University of Medical Sciences Tehran, Iran

Abstract. A cyclic bridging model for the management of cancer patients in cancer clinic is provided in which different fields and principles have been considered. These paradigms included Cell Biology / Genetics, Surgery, Oncology/Radiotherapy, macro- and, micro- environments influences, and ethics. The importance of culture and psychology, for supporting the cancer patients is highlighted as well. A package of refreshing, reconstructing, revising, re-evaluating, and, re-establishing in the whole systems is also considered for a cancer clinic. Including the subdivisions of cell biology, and genetics as the important issues in patients together with in vitro and in vivo experiments are also considered as the key paradigms in cancer clinic. An optimal aim in cancer clinic is personalized cancer programme for the targeted diagnostic/preventive/ predictivepackage in which the translational paradigm is planned. The applicable examples in cancer clinic were translated from different chapters as well. Correspondence/Reprint request: Professor Dr. Parvin Mehdipour, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O.Box 14155-6447, Tehran, Iran E-mail: mehdipor@tums.ac.ir


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Introduction Programming for cancer clinic is representative of diverse models which may be established by considering the essential requirements of different population, but a key question is “what is the outcome of management for the non-native cancer patients who have been born and grown up in a different condition, including society, habits, and cultures?” First, there are major characteristics of individuals which may guarantee the manner of response to therapy; these include tolerance, sensitivity to different therapeutic protocols either as a sole or in combination, and dosage as well. In another word, what is the manner of pharmaco-genetics which is somehow naturally programmed in individual pedigree rather than in the target population and has its roots in inheritance? Second, the cancer patients expect a suitable communication, attention, and sympathy as well. In certain population, the tight linkage between members of a family or even between different relatives within a pedigree could guarantee the reliable support for cancer patients and would bring about a moral condition with a bulk of “HOPE”. Therefore, it is essential to establish a core national cancer clinic (CNCC), according to the global characteristics of the target population. But, an open access and the interaction, complementary collaboration, and cooperation between other cancer clinics in the world is required for exchanging the diverse experiences because cancer is a disease with full of diversity. It was reported that “Cancer is increasing, and we might face the population structural changes in future. If we miss the boat now, millions of people are going to die as a consequence.” [1]. They have also paid attention to the importance of local resource limitations and performing research that’s regionally appropriated, and believed in working a long term to achieve standardized, evidence-based approach to treatment. They highlighted the evidence-based medicine, and it was stated that “treatment protocols developed in the UK or USA are often modified in developing countries to cut costs, without follow-up to determine outcomes”. The requirements are simple interventions and include defining the healthy environment, improving the global system of healthcare structures, providing the prompt diagnosis, using appropriate protocols by considering the clinical package (surgery, effectiveness of radiation therapy and chemotherapy drugs). The outcome of a comparative study provided by the Veneto Cancer Registry was focused on stage distribution and biological features of interval cancers (I.C.), screen-detected cancers (S.D.C.) and "clinical" cancers (C.C.) occurring in the absence of screening [2]. They reported that I.C. were more aggressive than S.D.C., the difference being statistically for grading,


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estrogen-, and progesterone- receptors, but not for Ki67. Although the features of I.C. were not more aggressive than C.C., but it was only significant for Ki67. These outcomes are valuable and reflect the biological importance in cancer registry for the benefit of cancer patients.

Modeling in cancer management The clinical-biological-, genetic- based programming is required to initiate a systematic modeling for cancer management as a core reference centre by considering a real “bridging-system�. In addition, if the appropriate outcome is achieved and approved in this systematic model, then it could be used as a reliable reference core, could be translated and applied in general hospitals and clinical centres.

Cyclic bridging programme As the final words, I would like to propose a model which is based on belief in bridging between basic Science and medicine. Therefore, the following items could be considered for the cancer clinic: 1. 2. 3. 4. 5.

6.

7. 8. 9. 10. 11. 12.

A guideline for foundation or improving the cancer clinic. The approaches in cancer care. The appropriate programme for training the staff. A standard programme for initiating and improving the quality of research. Considering different paradigms, including, surgery, pathology, basic Science (cell biology and genetics), oncology, and the essential modern available approaches. Considering the supportive packages from the ministry of health, universities, hospitals, and clinics including governmental and nongovernmental. Looking at cancer as an educational package from past, to present, and future. Focusing on apparently healthy individuals who might have symptoms that could be caused by undetected malignancy. Considering the palliative care. Considering the strategy of prediction, prevention, and early detection. Believing in the pedigree analysis, documentation of available data to create a database, and a reasonable follow-up study. Including the healthy relatives of cancer patients in the screening programme, if they wish to do so.


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An ideal cancer clinic is required to be established according to the variety of disciplines and values including geographic distribution, type of cancers, culture, psychology, economy, nutritional habits, health-policy, healthcare systems, and environmental influences.

Important comments for the selected items “Cancer is not only a genetic disease, but belongs to the “PsychoBiologic-Somatic-combined classification”. Cancer type Although the priority is important to be considered, but the rare cancers also must be included within the list of bridging programme. Culture and psychology Cancer clinic is supposed to be founded according to the cultural backgrounds in the target-nation and cancer population which could provide a case-control study-package. Why is the nationality important? The cancer patients depend on the relatives and friends who had some role through their life. Therefore, psychological paradigm will be the next issue of attention. Cancer patients have inherited combination of traits from their ancestral line, but they could be affected by some environmental factor (s) through which the specific acquired phenotype or behavior might be developed. Cancer patients are very sensitive who demand and deserve a psychological supports. This could definitely improve their emotional status indirectly facilitate and provide a suitable condition leading to optimization and improvement of the immunological status and alternatively an effective therapy. The available remedies for these purposes are: 1. Support of physician and nurses who could communicate in their native language. 2. Support of family members and relatives within different generations of cancer patients’ pedigree. 3. Support of friends. 4. Support of society.


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Figure 1. A Model of the genetics and cell biology based for the cancer clinic.

Final words To provide a cyclic bridging model for the management of cancer patients in the cancer clinic, the following fields and principles could be considered: Genetics /cell biology, surgery, oncology/radiotherapy, macro- and, micro-environmental influences, and ethics (Fig.1). The subdivisions of genetic-paradigms include cancer genetic counselling, cytogenetics, molecular genetics, immunogenetics, genetic engineering, and pharmacogenetics. By considering biochemistry, immunology, mathematics, and statistics, a directed therapeutic modulation could be planned for the specific cancer patients. As a matter of fact, beside the investigation in human, in vitro and in vivo experiments are required for therapeutic modulation as well. By pedigree-based analysis, an early clinical management could be planned for the relatives of cancer patients who are carrier of predisposing trait (s).


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It could be concluded that the cell biology and genetics play a core role in cancer clinic; genetic counselling could be provided for different categories of cancer including familial and non-familial and/or inherited of colon, breast, ovarian, uterus, prostate, melanoma, thyroid, sarcoma, childhood cancers and also other rare cancers. Genetic counselling as a package could be provided pre- and post-diagnosis and also during the life of patients and their relatives. The achieved applicable outcome through the cyclic bridging programme might be translated to the patients by considering the national ethics’ rules and regulations. Cancer research for cancer clinic require the following facts, by considering the importance of reasonable, and reliable clinical follow-up of all events through this period: 1. 2. 3. 4. 5. 6. 7.

Refreshing the insights. Reconstructing the system. Revising the model. Refreshing and re-evaluating the database. Re-establishing the risks. Cancer relies on the individual data (patient-pedigree-based). Giving right to the cancer probands’relatives to be included in the early screening and predicting strategies. 8. Decision making in cancer must be according to an evolutionary avenues of research-plans which could be linked to cancer clinic. 9. Although in familial cancer there is an autosomal dominant genes, as a powerful trait, but in cancer management nothing work as a sole, and, still there are interaction of other gene (s) and cellular biology parameters. 10. To include the personalized cancer programme for the targeted diagnostic/preventive/ predictive- package. The final question is: where is the right location for establishing a cancer clinic? Within a general hospital or near a hospital, or far away from any clinical centre. Cancer clinic must be characterized with, a quiet atmosphere in nature, providing all classic and modern facilities and paradigms, together with other required elements, including morals for the benefit of cancer patients.

Applicable examples in cancer clinic The available examples based on our experiences could be listed according to the chapters of this book:


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By linking the first chapter to the final words, the translating paradigm between either the molecular- or cellular- behaviors could be given as an example of bridging between cell biology and genetics to the cancer clinic. In chapter 1/ section 1, the prognostic implication of CDC25A and cyclin E expression on primary breast cancer patients was discussed within territory of cell cycle. The prognostic impact of cyclin E, CDC25A expression individually or either combination of Ki67 with cyclin E or CDC25A was highlighted, and it is shown that the CDC25A was associated with poor overall survival. Another insight in cancer genetics and cell biology is found to be the role of ataxia telangiectasia-mutated gene (ATM) in the patients affected with primary breast cancer (P.B.C.). In this regard, the ATM D1853N polymorphism showed a significant difference between P.B.C. and controls. This paradigm could be used as a key marker in breast cancer patients. This is an example of bridging between cell biology and genetics to the cancer clinic in future. To highlight the importance of pedigree analysis, a pedigree sample of a proband affected with P.B.C. who carries a novel mutation in BRCA2-gene is illustrated (Fig. 2) [4]. As this pedigree shows the family history consisting of two breast- and two unknown- cancers. The family history of BC and an early age of onset in proband and her sister convinced us to perform the screening test for BRCA1 and BRCA2. However, by providing multi-genetic counselling to this family, the screening test of the targeted molecular alteration, i.e., 4643del4 of BRCA2 gene was suggested to the family members. This is also an applicable insight in cancer clinic by considering the predictive and preventive approaches.

unknown cancer79y d80y

2 unknown cancer

BC d50y

BC37y BRCA2 4643del4

BC39y

Figure 2. A pedigree with family history of cancers. Arrow refers to proband, age of onset: 37 years. BC: breast cancer d: deceased at age of 50 years.


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Upon the results achieved from our previous investigation [4], our next objective was planned to estimate the penetrance of two specific gene mutations of BRCA1 and BRCA2 in Iranian women affected with BC [5]. Our results indicated that the low value of the estimated penetrance in this study might be attributed to the rare mutation in our patients. However, the reliable information of penetrance may play a key role in genetic counselling. Establishment and use of a kin-cohort gene databank could be proposed for an appropriate management of the screening programme, and the estimation of the penetrance contributes to our knowledge base towards risk assessment of cancer. In chapter 1 / section 2, the three-hit hypothesis in astrocytoma was provided as an example. In this section a pedigree- based investigation and application of two essential tools including the molecular and expression analyses in a pedigree with a proband affected with astrocytoma are considered. The screening test could be offered to the relatives of the proband which is another example of bridging between cell biology and genetics to the cancer clinic in the future. According to our previous report, the specific molecular alteration of ATM gene in the proband affected with astrocytoma and in her 13 relatives including six 1st degrees, one 2nd degree, three 3rd degrees and two 4th degrees was initially traced [3]. The pedigree included six generations, representative of high consanguinity between different degrees of relatives of the proband (Chapter1/section 2, Fig.1). The details of our findings and the importance of screening in the healthy relatives of the proband affected with astrocytoma is discussed. The positivity of the molecular alteration in the healthy relatives could be used as a informative guide, at least to avoid the hazard factors in the whole environment, and plan for a more appropriate style of life against cancer. In chapter 2, insights from human germ line mutations in three receptor tyrosine kinases elucidate how goals for cancer specific treatment and use of genotype- phenotype correlation have materialized. This has the great potential to dominate medical practice in the near future. Two examples include Gastrointestinal Stromal Tumors (GIST) and Multiple Endocrine Neoplasia 2 (MEN2) illustrating the applicability the cancer clinic. By linking chapter 3 to the final words, the translating paradigm between nutrition and genetics could be given as an example of bridging between these fields to the cancer clinic. Diet and nutrients could be considered as a two edged sward with effects which depends on the amount, the manner and period of consumption.


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In addition, the paradigm of nutrigenomics is a familiar, supportive gate capable of balancing and unbalancing the life style by leading the cells to cancerous behavior or keeping them in non-cancerous condition.The macronutrients as reliable examples are associated with reduction in cancer risk. To highlight the importance of animal study in nutrigenomics, our data showed the anti-tumorigenic effect of vitamin D3 in lung tumors induced by urethane. However, Vitamin D may reduce the risk of a tumorigenic diet that includes high fermented foods and beverages that produce urethane in the processing. Our previous publication also revealed that the expression of Ki67 proliferation index could be increased by urethane. This emphasize the hazard of urethane which is used in the food processing and wine producing manufactures. Our recent publication is representative of interaction between ER and PR downregulation, folate deficiency, and hypermethylation status of RARβ2 and ERα genes in human breast tumours. This data showed that by involving the molecular aspects in nutrition, the bridging between nutrigenomic and cancer clinic could be facilitated. In chapter 4, cancer-testis antigens are highlighted as promising candidates for cancer immunotherapy. This target has become a major focus for the development of vaccine-based clinical trials in recent years as well. This also may be an example regarding the bridging system in cancer clinic in future. In chapter 5, the task of regulating ethical rules for protection of genetic information was highlighted as an essential paradigm. This may ensure that the most good and the least harm come to patients and their family members. Genetic testing could be included as a predicting tool in cancer clinic, and sharing the genomic test results could be considered as beneficial and preventive tools for the family members. This facilitates the manner of preventive oncology for the probands and their relatives. It seems that in our population, the close relationship between the family members and friends could support the application of ethical regulations in the cancer clinic as well.

Conclusion The presented “Cyclic Bridging programme for cancer clinic” is based on the belief that cancer could be defined as a “Psycho-Biologic-Somaticcombined classification”. Based on this fact, a pedigree-based design was considered. Cancer clinic is required to be founded according to the cultural backgrounds in the targeted nation and cancer population, providing a casecontrol study- package as well.


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In our experiences the applicable examples in cancer clinic are: 1. The prognostic impact of cyclin E, CDC25A expression, and the important role of ataxia telangiectasia-mutated (ATM) gene in breast cancer patients. 2. The significant role of ATM gene in astrocytoma through three-hit Hypothesis. 3. The importance of pedigree-based screening in the relatives of affected Probands. 4. The germ line mutations of the receptor tyrosine kinases in GIST and MEN2. 5. To include the in vitro, animal and human studies in the nutrigenomics paradigm, by considering diet and nutrients as an important frame in the tumorigenic research, and including these elements in our nutrition basket. 6. The cancer-testis antigens as promising candidates for cancer immunotherapy. 7. The close relationship between family members and friends, as complementary support regarding ethical issues in cancer clinic and style of life. Finally, an optimal aim in cancer clinic is a personalized cancer programme which could pave our way towards a targeted diagnostic/preventive/ predictive- package in which the translational paradigm is planned for individual cancer patient.

References 1. 2.

3.

4.

5.

Crompton, S., Yes we can treat cancer –even in the poorest countries. Cancer World, 2010.: p. 32-38. Caumo, F., Vecchiato, F., Strabbioli, M., M. Zorzi , S. Baracco, S. Ciatto, et al., Interval cancers in breast cancer screening: comparison of stage and biological characteristics with screen-detected cancers or incident cancers in the absence of screening. Tumori, 2010. 96(2): p.198-201. Mehdipour P, L. Habibi., Mohammadi-Asl, N.Kamalin, and M. Mehrazin, Three-hit hypothesis in astrocytoma: tracing the polymorphism D1853N in ATM gene through a pedigree of the proband affected with primary brain tumour. J Cancer Res Clin Oncol, 2008.134: p.1173–1180. Pitchmann, A., P. Mehdipour, M. Atri, W. Hofmann, S. S., Hosseini-Asl,S. Scherneck, S. Mundlos, et al., Mutation analysis of BRCA1and BRCA2genes in Iranian highrisk breast cancer families. J Cancer Res Clin Oncol, 2005. 131(8): p.552–558. Hashemian A.H., E.Hajizadeh, A. Kazemnejad, M.Atri, P. Mehdipour, Penetrance of BRCA1/BRCA2 specific gene mutations in Iranian women with breast cancer.Saudi Med J. 2009 Jan; 30(1): 41-4.



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