The goals of the Genetic Epidemiology and Risk Assessment (GERA) Program are to: 1) Utilize the tremendous advances in genetics and molecular biology in order to understand genetic, environmental, and gene-environment interactions in the etiology of cancer in human populations;2) Utilize these same advances in order to understand the molecular epidemiology of cancer prognosis and survivorship;and 3) Develop and apply novel statistical and informatics methods for the design and analysis of genetic and molecular epidemiology studies. Our cancer etiology studies use family-based, case-control and cohort study designs and focus on the genetic epidemiology of cancer, premalignant conditions, and intermediate phenotypes, as well as non-genetic risk factors and descriptive epidemiology. We are also addressing etiologic heterogeneity based on tumor phenotype. Our cancer prognosis research focuses on host factors, including genetic and serum biomarkers as well as lifestyle factors that influence prognosis;tumor biomarkers;and survivorship. Novel methods for the design and analysis of genetic and molecular epidemiologic studies are being developed, building on our expertise in biostatistics, medical informatics and bioinformatics. To achieve these goals we have assembled a team of 32 multidisciplinary investigators from over 10 divisions or departments. Total peer-reviewed funding is $8.81 M from 32.6 assigned grants, with 71% coming from the National Cancer Institute. Since 2008, the program has generated 622 publications, 43% reflecting intra-programmatic collaborations and 61% reflecting inter-programmatic collaborations. Notable contributions have been made in the epidemiology of pancreatic, lung, ovarian, breast, colon, lymphoma, and mammographic breast density, as well as to the statistical genetics and medical and bioinformatics literature. Leadership of the program is provided by Drs. Cerhan and Parker. The program makes extensive use of shared facilities. In the next 5 years, we will continue our innovative research in cancer etiology and prognosis with a focus on genomics, development and application of novel technologies and methods, and translation to the clinic and population as well as back to the lab to inform biology.
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