At least 20%, perhaps as much as one-third of colon cancer is attributable to inherited factors. Identifying genetic variants is important to elucidate underlying mechanisms of colon cancer, the second leading cause of cancer death in the US. In the first 10 years of this grant, we have investigated several candidate-gene pathways. Our findings have contributed to the current understanding that numerous common genetic variants, with moderate associations, add substantially to the overall risk. To accelerate the discovery of colon cancer-related variants, we propose a genome-wide association study for all common amino-acid- altering (nonsynonymous) genetic variants in the human genome. Given recent advancements in genotyping technology, a genome-wide study has become feasible and presents the logical and critical next step to further explore the impact of genetic variants in this cancer. To address this research question, we have assembled an interdisciplinary team and established a new collaboration with the Women's Health Initiative (WHI) to ensure an appropriately powered study and the capacity to replicate study findings. We will focus on nonsynonymous single nucleotide polymorphisms (nsSNPs), which alter the amino-acid sequence of the protein and are more likely to be functionally relevant. We will conduct a genome-wide association study of all common nonsynonymous SNPs in the human genome (about 20,000). To balance sample size and cost efficiency, we propose a two-stage design. Stage I will be conducted within our existing multi-center, population-based colon cancer case-control study (530 cases, 530 matched controls). Stage II, an independent replication of findings from stage I, will be conducted in two study populations: (a) a different set of participants from our case-control study (800 cases and 800 matched controls) and (b) a nested case-control study within the WHI Observational Study cohort (930 cases, 930 matched controls). We will use appropriate high-throughput genotype technologies in both stages (stage I: MegaAllele(tm) System from Affymetrix and stage II: GoldenGate assay from Illumina). The study is powered to establish moderate gene-cancer associations (odds ratio of 1.4 for SNPs with minor allele frequency of 20%) while eliminating false-positive findings. We will further explore interactions between genes and environmental risk factors. The large number of well-characterized cases with DNA samples and detailed outcome and exposure assessment in both study populations provide an excellent resource. We expect that results will identify new candidate pathways and will improve our understanding of the molecular mechanisms of colon carcinogenesis;ultimately, the findings should provide directions for screening and prevention strategies.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Epidemiology of Cancer Study Section (EPIC)
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Seminara, Daniela
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Fred Hutchinson Cancer Research Center
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Zhao, Wei; Chen, Ying Qing; Hsu, Li (2017) On estimation of time-dependent attributable fraction from population-based case-control studies. Biometrics 73:866-875
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