Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.     

Transforming science: cancer gene identification

Methods for cancer gene discovery include identification of viral oncogenes, identification of genes associated with recurrent chromosomal aberrations, and screens for genes capable of the transformation of cells in culture. In recent years, the completed genome sequence of human and model organisms has markedly enhanced cancer gene identification. Whole genome, high-throughput screens have been facilitated by the advent of new technologies such as murine leukemia virus-based mutagenesis, Sleeping Beauty-based mutagenesis, RNA interference, exon re-sequencing, and high-resolution methods for detecting chromosomal amplifications and deletions; these, in turn, have led to the identification of novel tumor suppressors and oncogenes. The identification of genes that are altered by mutation or expression and which are directly involved in tumor initiation and maintenance will be instrumental for understanding cancer phenotypic variation and for identifying crucial therapeutic targets.     

Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer

Gene coexpression network analysis is a powerful “data-driven” approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few attempts to normalize and integrate co-expression data from scattered sources in a concise “meta-analysis” framework. We generated such a resource by exploring gene coexpression networks in 82 microarray datasets from 9 major human cancer types. The analysis was conducted using an elaborate weighted gene coexpression network (WGCNA) methodology and identified over 3,000 robust gene coexpression modules. The modules covered a range of known tumor features, such as proliferation, extracellular matrix remodeling, hypoxia, inflammation, angiogenesis, tumor differentiation programs, specific signaling pathways, genomic alterations, and biomarkers of individual tumor subtypes. To prioritize genes with respect to those tumor features, we ranked genes within each module by connectivity, leading to identification of module-specific functionally prominent hub genes. To showcase the utility of this network information, we positioned known cancer drug targets within the coexpression networks and predicted that Anakinra, an anti-rheumatoid therapeutic agent, may be promising for development in colorectal cancer. We offer a comprehensive, normalized and well documented collection of >3000 gene coexpression modules in a variety of cancers as a rich data resource to facilitate further progress in cancer research.     

Reviewing once more the c-myc and Ras collaboration: Converging at the cyclin D1-CDK4 complex and challenging basic concepts of cancer biology

The c-myc is a proto-oncogene that manifests aberrant expression at high frequencies in most types of human cancer. C-myc gene amplifications are often observed in various cancers as well. Ample studies have also proved that c-myc has a potent oncogenicity, which can be further enhanced by collaborations with other oncogenes such as Bcl-2 and activated Ras. Studies on the collaborations of c-myc with Ras or other genes in oncogenicity have established several basic concepts and have disclosed their underlying mechanisms of tumor biology, including “immortalization” and “transformation”. In many cases, these collaborations may converge at the cyclin D1-CDK4 complex. In the meantime, however, many results from studies on the c-myc, Ras and cyclin D1-CDK4 also challenge these basic concepts of tumor biology and suggest to us that the immortalized status of cells should be emphasized. Stricter criteria and definitions for a malignantly transformed status and a benign status of cells in culture also need to be established to facilitate our study of the mechanisms for tumor formation and to better link up in vitro data with animal results and eventually with human cancer pathology.Key words: c-Myc, Cyclin D1, transformation, immortalization, oncogeneC-myc is the first proto-oncogene discovered and is known to participate in many cellular functions,¹ including maintenance of stem cell properties.² Most types of human cancer manifest aberrant expression of c-myc at high frequencies, and gene amplification occurs in many cases of various cancers as well. Ample studies have demonstrated that c-myc has a potent oncogenicity, which can be further enhanced by collaborations with other oncogenes such as a Ras mutant or with many extracellular growth stimuli that activate Ras, such as epidermal growth factor (EGF) or transforming growth factor α (TGFα). Studies on the collaborations of c-myc with Ras and other genes have provided us with mechanistic details behind several basic concepts of cancer biology, including the “two-hit principle”,³ “immortalization” and “transformation”. In the meantime, however, many results from these studies also challenge these basic concepts and thus confuse us. We now discuss the data on the collaborations of c-myc with Ras and other genes and present a perspective that these collaborations may converge at the cyclin D1-CDK4 complex. We also appeal to emphasize the importance of an immortalized status of cells and to establish stricter criteria to better define a transformed and benign statuses, so as to better connect in vitro results with animal data and with human cancer pathology.     

HIF1-alpha functions as a tumor promoter in cancer associated fibroblasts,and as a tumor suppressor in breast cancer cells: Autophagy drives compartment-specific oncogenesis

Our recent studies have mechanistically implicated a loss of stromal Cav-1 expression and HIF1α-activation in driving the cancer-associated fibroblast phenotype, through the paracrine production of nutrients via autophagy and aerobic glycolysis. However, it remains unknown if HIF1α-activation is sufficient to confer the cancer-associated fibroblast phenotype. To test this hypothesis directly, we stably-expressed activated HIF1α in fibroblasts and then examined their ability to promote tumor growth using a xenograft model employing human breast cancer cells (MDA-MB-231). Fibroblasts harboring activated HIF1α showed a dramatic reduction in Cav-1 levels and a shift towards aerobic glycolysis, as evidenced by a loss of mitochondrial activity, and an increase in lactate production. Activated HIF1α also induced BNIP3 and BNIP3L expression, markers for the autophagic destruction of mitochondria. Most importantly, fibroblasts expressing activated HIF1α increased tumor mass by ∼2-fold and tumor volume by ∼3-fold, without a significant increase in tumor angiogenesis. In this context, HIF1α also induced an increase in the lymph node metastasis of cancer cells. Similar results were obtained by driving NFκB activation in fibroblasts, another inducer of autophagy. Thus, activated HIF1α is sufficient to functionally confer the cancer-associated fibroblast phenotype. It is also known that HIF1α expression is required for the induction of autophagy in cancer cells. As such, we next directly expressed activated HIF1α in MDA-MB-231 cells and assessed its effect on tumor growth via xenograft analysis. Surprisingly, activated HIF1α in cancer cells dramatically suppressed tumor growth, resulting in a 2-fold reduction in tumor mass and a three-fold reduction in tumor volume. We conclude that HIF1α activation in different cell types can either promote or repress tumorigenesis. Based on these studies, we suggest that autophagy in cancer-associated fibroblasts promotes tumor growth via the paracrine production of recycled nutrients, which can directly “feed” cancer cells. Conversely, autophagy in cancer cells represses tumor growth via their “self-digestion.” Thus, we should consider that the activities of various known oncogenes and tumor-suppressors may be compartment and cell-type specific, and are not necessarily an intrinsic property of the molecule itself. As such, other “classic” oncogenes and tumor suppressors will have to be re-evaluated to determine their compartment specific effects on tumor growth and metastasis. Lastly, our results provide direct experimental support for the recently proposed “autophagic tumor stroma model of cancer.”Key words: caveolin-1, autophagy, mitophagy, the Warburg effect, tumor stroma, hypoxia, HIF1A, NFκB, compartment-specific oncogenesis, cancer-associated fibroblasts     

Why cancer and inflammation?

Central to the development of cancer are genetic changes that endow these “cancer cells” with many of the hallmarks of cancer, such as self-sufficient growth and resistance to anti-growth and pro-death signals. However, while the genetic changes that occur within cancer cells themselves, such as activated oncogenes or dysfunctional tumor suppressors, are responsible for many aspects of cancer development, they are not sufficient. Tumor promotion and progression are dependent on ancillary processes provided by cells of the tumor environment but that are not necessarily cancerous themselves. Inflammation has long been associated with the development of cancer. This review will discuss the reflexive relationship between cancer and inflammation with particular focus on how considering the role of inflammation in physiologic processes such as the maintenance of tissue homeostasis and repair may provide a logical framework for understanding the connection between the inflammatory response and cancer.     

Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

Background

Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting.

Methodology

We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact.

Conclusions

Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.     

Large-scale mutagenesis in p19(ARF)- and p53-deficient mice identifies cancer genes and their collaborative networks

p53 and p19(ARF) are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19(ARF) deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19(ARF)-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.     

De novo DNA methyltransferases: oncogenes, tumor suppressors, or both?

Aberrant promoter DNA hypermethylation of tumor suppressor genes is a hallmark of cancer. This alteration is largely dependent on the action of de novo DNA methyltransferases (DNMTs) early during tumor progression, which supports the oncogenic role for these enzymes. However, recent research has identified several inactivating mutations of de novo DNMTs in various types of tumor. In addition, it has been shown that loss of de novo DNA methylation activity at advanced tumor stages leads to the promoter DNA demethylation-dependent expression of specific oncogenes. These new data support the notion that de novo DNMTs also have an important role in the maintenance of DNA methylation and suggest that, in addition to acting as oncogenes, they also behave as tumor suppressors. This potential dual role might have clinical implications, as DNMTs are currently considered bona fide targets in cancer therapy.     

Oncomine数据库在肿瘤研究中的应用

Oncomine 是目前世界上最大的癌基因芯片数据库和综合数据挖掘平台之一,该数据库整合了GEO、TCGA和已发表文献来源的RNA和DNA-seq数据。数据库目前含有715个基因表达数据集（datasheet）、86 733个人体肿瘤组织和正常组织样本的信息,且有新的数据不断更新。Oncomine 数据库囊括的肿瘤类型有19种,包括：膀胱癌、脑/中枢神经系统肿瘤、乳腺癌、宫颈癌、结直肠癌、食管癌、胃癌、头/颈肿瘤、肾癌、白血病、肝癌、肺癌、淋巴瘤、黑色素瘤、骨髓瘤、卵巢癌、胰腺癌、前列腺癌、肉瘤。本文就如何利用Oncomine数据库,进行肿瘤组织中癌基因表达差异性分析以及基因共表达分析、癌基因在肿瘤组织中的表达及拷贝数分析、多组研究数据集的荟萃分析（meta analysis）、以及癌基因表达与患者生存率关系等进行分析。通过该数据库可以对肿瘤癌基因进行研究前的筛查,有利于发现新的肿瘤生物标记物或治疗靶点,为临床科学研究奠定一定的理论基础。     

The Role of the Apoptotic Machinery in Tumor Suppression

Multicellular organisms have evolved processes to prevent abnormal proliferation or inappropriate tissue infiltration of cells, and these tumor suppressive mechanisms serve to prevent tissue hyperplasia, tumor development, and metastatic spread of tumors. These include potentially reversible processes such as cell cycle arrest and cellular senescence, as well as apoptotic cell death, which in contrast eliminates dangerous cells that may initiate tumor development. Tumor suppressive processes are organized as complex, extensive signaling networks, controlled by central “nodes.” These “nodes” are prominent tumor suppressors, such as P53 or PTEN, whose loss is responsible for the development of the majority of human cancers. In this review we discuss the processes by which some of these prominent tumor suppressors trigger apoptotic cell death and how this process protects us from cancer development.A malignant tumor is characterized by the ability to expand in an uncontrolled manner, destroy normal tissue architecture, and ultimately undergo metastatic spread (Hanahan and Weinberg 2000). Although the number of mutations required for neoplastic transformation may vary, all tumors are reliant on two critical mechanisms for their development; the activation of oncogenes that promote proliferation and survival of cancer cells, as well as the inactivation of tumor suppressor genes that normally repress development and growth of tumors (Hanahan and Weinberg 2000).Oncogenes can be activated via multiple mechanisms, including chromosomal translocations, deletions or insertions, as well as point mutations. One such example is the translocation between chromosomes 9 and 22 that is present in most cases of chronic myeloid leukemia. The juxtaposition of the BCR and c-ABL genes results in the production of an abnormal BCR-ABL fusion protein with constitutive kinase activity (Deininger et al. 2005). However, in other cancer-causing chromosomal translocations, such as the t[8;14] translocation in Burkitt’s lymphoma, the coding sequence of the oncogene, c-MYC, is unchanged; rather its activation results from deregulated expression in B lymphoid cells as a consequence of its proximity to the IGH gene enhancer (Cory et al. 1987). Tumorigenesis promoted by deregulated kinase activity frequently results from the acquisition of point mutations. In this context, a single amino acid substitution can dramatically enhance kinase activity by preventing binding of negative regulators or “locking” the catalytic domain in the active conformation. This is exemplified by the BRAF(V600E) mutation frequently observed in melanoma or colon carcinoma (Poulikakos and Rosen 2011) and the activating mutations in EGF-R observed in lung adenocarcinoma (Sharma et al. 2007).Analogous to the activation of oncogenes, tumor suppressor genes can be inactivated through multiple mechanisms, including large-scale chromosomal alterations or point mutations. However, in most cases both alleles of the gene must be compromised to abolish gene function, unless the mutated protein can act in a dominant-negative fashion to block the activity of its wild-type counterpart.Multicellular organisms have evolved a plethora of mechanisms to restrain the growth or even eliminate aberrant cells—these processes can all function as tumor suppressors. Notably, of the attributes that cells must acquire to become cancerous (“hallmarks of cancer”) discussed by Hanahan and Weinberg (2000), several relate to escape from regulatory processes that would normally suppress tumor growth. They include cell cycle arrest, cellular senescence, and cell death; of these only cell death is irreversible, all others can (at least potentially) be reversed. In this review, we describe the mechanisms by which tumor suppressors that are disabled in a broad range and large fraction of cancers trigger cell death, and how components of the apoptotic machinery can themselves act as tumor suppressors.     

microRNAs as oncogenes and tumor suppressors

microRNAs (miRNAs) are a new class of non-protein-coding, endogenous, small RNAs. They are important regulatory molecules in animals and plants. miRNA regulates gene expression by translational repression, mRNA cleavage, and mRNA decay initiated by miRNA-guided rapid deadenylation. Recent studies show that some miRNAs regulate cell proliferation and apoptosis processes that are important in cancer formation. By using multiple molecular techniques, which include Northern blot analysis, real-time PCR, miRNA microarray, up- or down-expression of specific miRNAs, it was found that several miRNAs were directly involved in human cancers, including lung, breast, brain, liver, colon cancer, and leukemia. In addition, some miRNAs may function as oncogenes or tumor suppressors. More than 50% of miRNA genes are located in cancer-associated genomic regions or in fragile sites, suggesting that miRNAs may play a more important role in the pathogenesis of a limited range of human cancers than previously thought. Overexpressed miRNAs in cancers, such as mir-17-92, may function as oncogenes and promote cancer development by negatively regulating tumor suppressor genes and/or genes that control cell differentiation or apoptosis. Underexpressed miRNAs in cancers, such as let-7, function as tumor suppressor genes and may inhibit cancers by regulating oncogenes and/or genes that control cell differentiation or apoptosis. miRNA expression profiles may become useful biomarkers for cancer diagnostics. In addition, miRNA therapy could be a powerful tool for cancer prevention and therapeutics.     

Genome-Wide Analysis of Small RNA and Novel MicroRNA Discovery in Human Acute Lymphoblastic Leukemia Based on Extensive Sequencing Approach

Background

MicroRNAs (miRNAs) have been proved to play an important role in various cellular processes and function as tumor suppressors or oncogenes in cancers including leukemia. The identification of a large number of novel miRNAs and other small regulatory RNAs will provide valuable insights into the roles they play in tumorgenesis.

Methodology/Principal Findings

To gain further understanding of the role of miRNAs relevant to acute lymphoblastic leukemia (ALL), we employed the sequencing-by-synthesis (SBS) strategy to sequence small RNA libraries prepared from ALL patients and normal donors. In total we identified 159 novel miRNAs and 116 novel miRNA*s from both libraries. Among the 159 novel miRNAs, 42 were identified with high stringency in our data set. Furthermore, we demonstrated the different expression patterns of 20 newly identified and several known miRNAs between ALL patients and normal donors, suggesting these miRNAs may be associated with ALL and could constitute an ALL-specific miRNA signature. Interestingly, GO “biological process” classifications revealed that a set of significantly abnormally expressed miRNAs are associated with disease relapse, which implies that these dysregulated miRNAs might promote the progression of ALL by regulating genes involved in the pathway of the disease development.

Conclusion/Significance

The study presents a comprehensive picture of the expression of small RNAs in human acute lymphoblastic leukemia and highlights novel and known miRNAs differentially expressed between ALL patients and normal donors. To our knowledge, this is the first study to look at genome-wide known and novel miRNA expression patterns in in human acute lymphoblastic leukemia. Our data revealed that these deregulated miRNAs may be associated with ALL or the onset of relapse.     

Selective gene expression profiling of mTOR-associated tumor suppressor and oncogenes in ovarian cancer

The aim of this study was to selectively profile the activation status of mammalian target of rapamycin (mTOR)-associated oncogenes and tumor suppressor genes (TSGs) in ovarian cancer specimens, healthy ovaries and benign ovarian tumors, including endometrial cysts. We used a novel type of microfluidic gene array to examine the expression of 15 human tumor suppressors and oncogenes in ovarian cancer specimens of 53 patients, benign ovarian cysts of 29 women (endometrial and simple) and 11 healthy ovaries of individuals in whom the material was obtained during total hysterectomies performed because of fibroid changes. The array was custom-designed to include the following genes: NF1, RHEB, mTOR1, AKT-1, PTEN, TSC1, TSC2, KRAS, RPS6KB1, 4EBP1, TP53, EIF4E, STK11, PIK3CA and BECN1. Confirmatory immunohistochemical detection was performed for a group of selected proteins. Particularly significant differences were observed as to the expression of PTEN (p < 0.0001), TP53 (p = 0.0003), PIK3CA (p = 0.0003) and BECN1 (p = 0.0014) which were shown to be downregulated in cancer patients when compared to healthy ovaries and benign ovarian cysts (endometrial and simple). These markers did not show association with grade or stage of the tumor. Immunohistochemistry showed that PTEN, TP53, PIK3CA and BECN1 proteins are expressed in ovarian cancer. Our results indicate that there are significant differences in the expression of some of the mTOR-related tumor suppressors and oncogenes which could be associated with the pathogenesis of ovarian cancer.     

Cancer microRNAs: from subtype profiling to predictors of response to therapy

MicroRNAs (miRNAs) are key regulators of gene expression that regulate important oncogenes and tumor suppressors. Many miRNAs can also act as oncogenes or tumor suppressors, and thus the altered expression of miRNAs is a hallmark of many cancer types. Dysregulated miRNAs provide a potentially powerful new tool that could be used to enable the characterization of tumor environments and identify novel and important oncogenic pathways. More recently, there has been growing interest in the field of miRNAs as biomarkers of cancer risk, diagnosis and response to therapy. Understanding the associations between miRNA expression and cancer phenotypes, and the potential of miRNA profiling in clinical applications, promises to be highly rewarding in the field of cancer research.     

Mitochondrial biogenesis in epithelial cancer cells promotes breast cancer tumor growth and confers autophagy resistance

Here, we set out to test the novel hypothesis that increased mitochondrial biogenesis in epithelial cancer cells would “fuel” enhanced tumor growth. For this purpose, we generated MDA-MB-231 cells (a triple-negative human breast cancer cell line) overexpressing PGC-1α and MitoNEET, which are established molecules that drive mitochondrial biogenesis and increased mitochondrial oxidative phosphorylation (OXPHOS). Interestingly, both PGC-1α and MitoNEET increased the abundance of OXPHOS protein complexes, conferred autophagy resistance under conditions of starvation and increased tumor growth by up to ~3-fold. However, this increase in tumor growth was independent of neo-angiogenesis, as assessed by immunostaining and quantitation of vessel density using CD31 antibodies. Quantitatively similar increases in tumor growth were also observed by overexpression of PGC-1β and POLRMT in MDA-MB-231 cells, which are also responsible for mediating increased mitochondrial biogenesis. Thus, we propose that increased mitochondrial “power” in epithelial cancer cells oncogenically promotes tumor growth by conferring autophagy resistance. As such, PGC-1α, PGC-1β, mitoNEET and POLRMT should all be considered as tumor promoters or “metabolic oncogenes.” Our results are consistent with numerous previous clinical studies showing that metformin (a weak mitochondrial “poison”) prevents the onset of nearly all types of human cancers in diabetic patients. Therefore, metformin (a complex I inhibitor) and other mitochondrial inhibitors should be developed as novel anticancer therapies, targeting mitochondrial metabolism in cancer cells.     

Interactions of circadian clock genes with the hallmarks of cancer

The molecular machinery of the circadian clock regulates the expression of many genes and processes in the organism, allowing the adaptation of cellular activities to the daily light-dark cycles.Disruption of the circadian rhythm can lead to various pathologies, including cancer. Thus, disturbance of the normal circadian clock at both genetic and environmental levels has been described as an independent risk factor for cancer. In addition, researchers have proposed that circadian genes may have a tissue-dependent and/or context-dependent role in tumorigenesis and may function both as tumor suppressors and oncogenes.Finally, circadian clock core genes may trigger or at least be involved in different hallmarks of cancer. Hence, expanding the knowledge of the molecular basis of the circadian clock would be helpful to identify new prognostic markers of tumorigenesis and potential therapeutic targets.     

Amplified genes as therapeutic targets in cancer

The most effective targeted cancer therapies have arisen from research into genetically altered oncogenes, including BCR-ABL, HER2, RAS and EGFR. Recent advances in cancer genetics have identified many regions of the genome that undergo amplification (increase in copy number) but, in most cases, the key oncogenic targets driving the growth and survival of cancer cells remain unknown. In this review, we discuss high-throughput technologies for the discovery of putative oncogenes, and clinical and functional validation of these genes as targets for therapy. New technologies in translational genomics facilitate the identification, validation and prioritization of candidate molecular targets for anti-cancer therapy.