Molecular Epidemiology of Prostate Cancer Outcomes: Genetics, Multilevel Environ

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PROJECT SUMMARY (See instructions): Prostate cancer (PCa) is the most common non-cutaneous malignancy in US men and the second cause of cancer death, with age-adjusted mortality of 62.3 per 100,000 in African American (AA) and 25.6 per 100,000 in European American (EA) men. Although the high mortality from PCa represents a critical public health problem, our understanding of PCa etiology and predictors of poor outcomes remains limited. Screening can detect PCa at an early stage, but generalized use of screening of men at both high and low risk of unfavorable outcomes may result in unnecessary treatment for some and insufficient treatment in others. Thus, a critical public health goal is to optimize risk assessment and target cancer screening and treatment to reduce PCa mortality while minimizing over treatment and its negative side effects in men who are unlikely to experience unfavorable PCa outcomes. It is likely that the causes of unfavorable PCa outcomes are multifactorial and complex. Tumor and patient characteristics have been used to identify some men with poor prognosis. However, the potential additional contribution of biological or environmental factors to these predictive models is not well understood. The goals of the research proposed here are 1) to identify factors that predict PCa outcomes, and 2) to use this information to identify men who may benefit from specific screening and or treatment options. We hypothesize that long-term exposure to unfavorable individual-level and macro-environmental exposures influence PCa severity and access to health care. These exposures include area-level or neighborhood factors such as neighborhood deprivation and residential segregation. We further hypothesize that the response to these exposures is mediated by biomarkers. We propose to use a large, prospective cohort currently including 1,900 PCa cases with a projected average of 72 months of prospective follow at the time of analysis, tissue samples, geospatial data, questionnaire information, and medical records data to evaluate (1) the effect of tumor biomarkers on PCa aggressiveness and outcomes, (2) the effect of macroenvironmental contextual factors on biomarkers of unfavorable long-term exposures or PCa outcomes, and (3) Develop improved nomograms that include biomarkers, individual risk factors and macro-environmental factors (including factors identified in Project 1) to identify a multilevel set of predictors of PCa outcomes.