Prostate cancer (PCa) is the most common solid tumor in men and is a major cause of cancer-related morbidity and mortality. Prostate-specific antigen (PSA) testing has increased the number of men diagnosed with PCa, but -30-42% of these patients have indolent tumors that carry a low probability for progression to clinically significant PCa. Clinicopathological criteria alone are not always adequate for predicting which tumors will remain indolent vs become aggressive, so many patients are over-treated and some are undertreated. Thus, biomarkers to distinguish men with less vs more aggressive disease are urgently needed. Both inherited genetic variation (e.g., SNPs) and tumor epigenomic aberrations (e.g., DNA hypermethylation) likely contribute to PCa aggressiveness. Preliminary evidence supports both mechanisms, which may alter host-tumor immunity, tumor growth rate, or metastatic propensity. The overall intent of this population sciences research is to validate genetic-epigenetic biomarkers for aggressive PCa that can be translated into clinical use. Toward this goal, the project has the following aims: 1) To complete validation of a panel of 30 PCSM-associated SNPs in two independent PCa patient cohorts;2) To characterize genome-wide DNA methylation (450K CpG sites) profiles in prostate tumor tissue in association with PCa-specific outcomes (e.g., recurrence, metastasis, PCSM);and, 3) To test validated PCSM-associated SNPs (Aim 1) and top-ranked differentially methylated genes (Aim 2) as an integrated panel of prognostic biomarkers for distinguishing clinically localized aggressive PCa. The proposed plan builds on our prior SPORE work, taking advantage of a population-based PCa cohort with germline DNA, tumor tissue, clinical and PCa-specific outcomes data, as well as other PCa cohorts with available DNA and outcomes data. Univariate, stratified, and multivariate analyses will be completed to evaluate PCSM-associated SNPs and top-ranked differentially methylated genes associated with aggressive PCa for potential clinical utility. The Cox proportional hazards model will be used to calculate hazard ratios, 95% CIs, and p-values to examine the association of individual and combinations of germline genetic and somatic (DNA methylation) biomarkers with PCa outcomes. The overall goal is to identify and validate prognostic genetic-epigenetic biomarkers that will translate into better patient management and outcomes as well as to identify new molecular targets that may lead to novel therapies or prevention approaches for PCa.

Public Health Relevance

Prostate cancer (PCa) is a major cause of mortality, but it is not currently possible to accurately predict which tumors will remain indolent vs become life-threatening. To identify prognostic biomarkers, the proposed study will utilize samples and data from a population-based cohort of 1,458 PCa patients to assess genome-wide DNA methylation in tumor tissue and germline single nucleotide variants in candidate genes in relation to recurrence and PCa-specific mortality. Our goal is to identify and validate prognostic genetic-epigenetic biomarkers that will translate into better patient management and outcomes.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center (P50)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-RPRB-M (M1))
Program Officer
Hruszkewycz, Andrew M
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Fred Hutchinson Cancer Research Center
United States
Zip Code
Zhang, Ailin; Zhang, Jiawei; Plymate, Stephen et al. (2016) Classical and Non-Classical Roles for Pre-Receptor Control of DHT Metabolism in Prostate Cancer Progression. Horm Cancer 7:104-13
Uo, T; Dvinge, H; Sprenger, C C et al. (2016) Systematic and functional characterization of novel androgen receptor variants arising from alternative splicing in the ligand-binding domain. Oncogene :
Faltermeier, Claire M; Drake, Justin M; Clark, Peter M et al. (2016) Functional screen identifies kinases driving prostate cancer visceral and bone metastasis. Proc Natl Acad Sci U S A 113:E172-81
Lam, Hung-Ming; McMullin, Ryan; Nguyen, Holly et al. (2016) Characterization of an abiraterone ultraresponsive phenotype in castration-resistant prostate cancer patient-derived xenografts. Clin Cancer Res :
Saranchova, Iryna; Han, Jeffrey; Huang, Hui et al. (2016) Discovery of a Metastatic Immune Escape Mechanism Initiated by the Loss of Expression of the Tumour Biomarker Interleukin-33. Sci Rep 6:30555
Qu, Xiaoyu; Jeldres, Claudio; Glaskova, Lena et al. (2016) Identification of Combinatorial Genomic Abnormalities Associated with Prostate Cancer Early Recurrence. J Mol Diagn 18:215-24
Gulati, Roman; Cheng, Heather H; Lange, Paul H et al. (2016) Screening men at increased risk for prostate cancer diagnosis: Model estimates of benefits and harms. Cancer Epidemiol Biomarkers Prev :
Shui, Irene M; Kolb, Suzanne; Hanson, Christi et al. (2016) Trichomonas vaginalis infection and risk of advanced prostate cancer. Prostate 76:620-3
Coleman, Daniel J; Van Hook, Kathryn; King, Carly J et al. (2016) Cellular androgen content influences enzalutamide agonism of F877L mutant androgen receptor. Oncotarget 7:40690-40703
Pritchard, Colin C; Mateo, Joaquin; Walsh, Michael F et al. (2016) Inherited DNA-Repair Gene Mutations in Men with Metastatic Prostate Cancer. N Engl J Med 375:443-53

Showing the most recent 10 out of 323 publications