||5R03CA123587-02 Interpret this number
||University Of Southern California
||A Comprehensive Analysis of Genetic Variation in DNA Repair Genes in Relation to
DESCRIPTION (provided by applicant): Excess exposure to endogenous and exogenous sources of estrogen heightens cell division in the endometrium which is thought to increase the rate at which somatic mutations occur and become fixed in subsequent mitoses, and serve as initiating events in the development of cancer. Multiple highly conserved mechanisms have evolved to identify and cope with constant insults on DNA from endogenous and exogenous sources and to maintain genomic integrity. Many human cancer syndromes are caused by rare germline mutations in DNA repair genes that result in deficiencies in normal DNA repair capacity. One such syndrome, caused by mutations in mismatch repair genes, is hereditary nonpolyposis colorectal cancer. Endometrial cancer is a common phenotype of this familial syndrome, directly implicating DNA repair capacity in the pathogenesis of this disease. To date, the role of low-penetrant alleles in genes involved in mismatch repair or other DNA damage repair or response pathways has not been thoroughly studied in relation to endometrial cancer risk. This current project builds on existing resources to study efficiently and comprehensively, the importance of common genetic variation in 61 candidate genes in DNA repair-related pathways on endometrial cancer risk. Over the past year we have constructed an optimal array of "tagging" SNPs designed using Illumina genotyping technology that provide high predictability of common genetic variation in these candidate genes across multiple racial-ethnic populations. In this application, we will utilize prospectively collected biospecimens, risk factor and outcome data from two established endometrial cancer case-control studies nested within the Multiethnic Cohort study (cases, n = 542; controls, n = 1,234) and the California Teachers Study (cases, n = 580; controls, n = 1,160) to assess associations between these selected tagging SNPs (approximately 1,200) and all known missense variants (approximately 300) in these genes in relation to endometrial cancer risk. This study will use novel high-throughput genotyping technology as well as rigorous statistical analytic methods to account for multiple hypothesis testing, and allows for replication and cross- validation of findings across these cohorts. The ability to accurately identify high-risk sub-groups may have profound implications on endometrial cancer prevention as well as advance research aimed at targeted drug development.