Prostate cancer is a common but complex disease with a number of unresolved issues surrounding its natural history. These include concerns with screening, detection, and treatment, and reflect the substantial heterogeneity in prostate tumors: some will remain latent and have little impact on morbidity, whereas others progress rapidly in a potentially lethal manner. Genetic factors likely underlie some of these differences, and we propose a comprehensive evaluation of the genetic basis of prostate cancer risk and progression in a large, well-characterized study population. In particular, we will investigate rar functional variants across the exome and common SNPs across the genome. Our sample encompasses 8,078 prostate cancer cases and 8,078 age and ethnicity matched controls nested within the Kaiser / USCF Research Program on Genes, Environment and Health cohort. This population has existing genome-wide SNP measures, and uniformly collected clinical information on prostate cancer screening, diagnoses, and progression. We plan to type the new exome array on the cases and controls to assess the functional variants in protein coding regions across the human genome. With these data we will address our hypothesis that these genetic factors can be used to predict-and underlie an increasing proportion of the variation in-prostate cancer risk and progression. This project provides an efficient and innovative opportunity to obtain a comprehensive understanding of how these factors impact the natural history of prostate cancer. Our findings should supply important insights into the underlying mechanism of disease, with the ultimate goal of helping to improve screening and treatment for prostate cancer.

Public Health Relevance

Prostate cancer is one of the most common and clearly genetic cancers, but finding the mechanisms underlying the natural history of this disease has proven difficult. Our efforts toward deciphering the genetic basis of prostate cancer will help improve screening, treatment, and our understanding of this disease, all important goals of the overall National Cancer Institute's Mission. These advances will improve the overall health of men, providing much needed information about individual and population-level risks of prostate cancer development and progression.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA088164-13
Application #
8700326
Study Section
Epidemiology of Cancer Study Section (EPIC)
Program Officer
Elena, Joanne W
Project Start
2000-09-01
Project End
2016-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
13
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Cario, Clinton L; Witte, John S (2018) Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations. Bioinformatics 34:936-942
Majumdar, Arunabha; Haldar, Tanushree; Bhattacharya, Sourabh et al. (2018) An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations. PLoS Genet 14:e1007139
Wu, Yi-Hsuan; Graff, Rebecca E; Passarelli, Michael N et al. (2018) Identification of Pleiotropic Cancer Susceptibility Variants from Genome-Wide Association Studies Reveals Functional Characteristics. Cancer Epidemiol Biomarkers Prev 27:75-85
Gauderman, W James; Mukherjee, Bhramar; Aschard, Hugues et al. (2017) Update on the State of the Science for Analytical Methods for Gene-Environment Interactions. Am J Epidemiol 186:762-770
Hoffmann, Thomas J; Passarelli, Michael N; Graff, Rebecca E et al. (2017) Genome-wide association study of prostate-specific antigen levels identifies novel loci independent of prostate cancer. Nat Commun 8:14248
Ng, Maggie C Y; Graff, Mariaelisa; Lu, Yingchang et al. (2017) Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet 13:e1006719
Hoffman, Joshua D; Graff, Rebecca E; Emami, Nima C et al. (2017) Cis-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk. PLoS Genet 13:e1006690
Emami, Nima C; Leong, Lancelote; Wan, Eunice et al. (2017) Tissue Sources for Accurate Measurement of Germline DNA Genotypes in Prostate Cancer Patients Treated With Radical Prostatectomy. Prostate 77:425-434
Graff, Rebecca E; Möller, Sören; Passarelli, Michael N et al. (2017) Familial Risk and Heritability of Colorectal Cancer in the Nordic Twin Study of Cancer. Clin Gastroenterol Hepatol 15:1256-1264
Conti, David V; Wang, Kan; Sheng, Xin et al. (2017) Two Novel Susceptibility Loci for Prostate Cancer in Men of African Ancestry. J Natl Cancer Inst 109:

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