Abstract PL01-02: The heritable component of cancer: Insights from genome-wide association studies and beyond
For decades, the heritable contribution of cancer has been the subject of intense study, first pursued in families with multiple affected individuals and more recently investigated in unrelated population-based studies. For example, family studies have yielded important genes for breast cancer (BRCA1 and BRCA2), colon cancer (MSH2 and MLH1), and families with a spectrum of less common cancers (TP53). The pursuit of candidate genes yielded only a handful of conclusive associations, such as NAT2 and GSTM1 in bladder cancer or alcohol dehydrogenase genes (ADH1B and ADH7) in aerodigestive cancers. New genotyping technologies together with a comprehensive map of human haplotypes (International HapMap Project) have enabled investigators to scan across the genome in a sufficiently large set of cases and controls without a set of prior hypotheses in search of common susceptibility alleles with low effect sizes. Genome-wide association studies (GWAS) have emerged as an important tool for discovering regions of the genome using hundreds of thousands of common single nucleotide polymorphism (SNP) markers. This ‘agnostic’ approach has conclusively discovered more than 125 regions for nearly two dozen types of cancer. At least eight regions have been associated with more than one distinct cancer type. For instance, the region flanking the MYC oncogene on 8q24 harbors at least five independent loci associated with prostate cancer as well as loci associated with cancers of the breast, colon, bladder, ovaries, and chronic lymphocytic leukemia. On 5p15.33, there are at least seven cancers, namely, basal cell carcinoma, bladder, brain, lung (adenocarcinoma), melanoma, pancreas, and testicular that map to the TERT-CLPTM1L locus. This locus is notable for the telomerase gene (TERT) in which rare mutations have been associated with dyskeratosis congenital (an inherited bone marrow failure syndrome), idiopathic pulmonary fibrosis, acute myelogenous leukemia, and chronic lymphocytic leukemia. The number of variants identified by GWAS per cancer varies greatly, suggesting different underlying genetic architectures, namely genetic contributions to common and uncommon cancers. Of the 125 regions associated with cancer risk, none of the regions have been conclusively associated with prognosis. In prostate cancer, there are at least 35 distinct loci harboring common susceptibility alleles identified by GWAS yet not a single one clearly distinguishes between aggressive and nonaggressive disease. This observation suggests that there could be regions that distinctly contribute to cancer risk and cancer outcomes (e.g., aggressive or metastatic disease). For lung cancer, a disease strongly driven by exposure to tobacco products, so far, only three or four regions have been conclusively established. Of these regions, the signal on chromosome 15 could be related to smoking. For nearly all common SNP markers (namely those with a minor allele frequency of greater than 5%), the estimated effect sizes are below 1.5. A notable exception is for testicular cancer in which variants on chromosome 12 near the KITLG gene have estimated effect sizes of greater than 2.5 for heterozygotes; this is not surprising since the hereditary component of testicular cancer is very strong. Overall, each region confers a small contribution to the risk for cancer, which suggests that it is daunting to consider any single SNP as a clinical test. GWAS regions are undergoing fine mapping to nominate the optimal candidates for functional studies designed to explain the direct association. Nearly all GWAS signals have mapped to noncoding regions, underscoring the contribution of regulatory mechanisms in neighboring genes (e.g., FGFR2 and breast cancer, MSMB/NCOA4 and prostate cancer). The plausibility of the underlying association can form the foundation for developing new strategies to intervene or diagnose cancer at an earlier stage by providing new insights into biological mechanisms that become targets. The application of GWAS to therapeutic outcomes and toxicities is beginning to discover new regions worthy of follow-up studies. However, for pharmacogenomics to eventually have an impact in the clinic, there will have to be a transition from discovery to characterization of the regions that ultimately yields targets for therapy and chemoprevention. Since we are still early in the discovery of common genetic variants associated with risk for specific cancers, it is not surprising that the utility of applying common SNPs to disease prediction is premature. Common genetic variants represent only a proportion of genetic variants that contribute to disease risk; uncommon, rare and copy number variants will undoubtedly contribute to risk in both familial and unrelated settings, and their relative contributions are expected to vary by cancer site. The addition of common SNP markers to classical epidemiological risk factors for breast cancer has minimally shifted the receiver operator curve (ROC) from 50% to approximately 60%. For prostate cancer, a disease in which epidemiological studies have identified age, ethnic background, and family history as the only conclusive risk factors, it is not surprising that more than 30 common SNPs shift the ROC curve to roughly 65%. Discovery of additional genetic variants should improve the risk prediction but each will be limited by the overall heredity of the cancer. New approaches towards applying common genetic variants could be beneficial in the reclassification of individuals based on genetic risk profiles or alternatively, the identification of subsets of individuals at high risk who might undergo a diagnostic or therapeutic intervention. In conclusion, the fruits of GWAS have important implications for investigating the etiology of different cancers, particularly as it relates to gene-environment and gene-gene interactions. The complex genomic architecture of disease susceptibility will require further discovery of uncommon and rare variants using next-generation sequence technologies. It will be critical to assess the applicability of genetic tests in specific clinical settings, such as when to perform screening tests with calculable risks (e.g., biopsies or chemoprevention) before incorporating SNPs into clinical practice. To incorporate the fruits of current genomic observations, new studies will need to be designed to validate the utility of known genetic variants in assessing risk for cancer as well as its outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr PL01-02. doi:10.1158/1538-7445.AM2011-PL01-02
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