Project 2: Elucidating interactions between genetic and environmental drivers of prostate cancer patient outcomes

University Of California, San Francisco, San Francisco CA

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY/ABSTRACT This Project aims to explain the persistent differences in prostate cancer (PC) outcomes, particularly the disproportionate burden of aggressive and lethal disease, among Black men compared to White men. The overarching goal is to explore the complex interplay between biological (genomic) and environmental factors, that contribute to these differences in outcomes. By focusing on the interactions among stress, inflammation, and immune pathways within the tumor microenvironment, the research seeks to uncover mechanisms that drive the development of aggressive prostate cancer in at-risk populations. Aim 1 will focus on identifying how adverse external factors associate predict identification aggressive prostate cancer. Using tissue samples from a large cohort of prostatectomy patients, the Aim will also assess both genomic risk and immune activation patterns, comparing Black, Hispanic, and Asian men to understand differences in tumor biology. The goal is to determine how adverse external factors drive differences in immune activation and the development of unfavorable prostate cancer histology. Aim 2 will dig deeper into prostate cancer biology using advanced genomics and spatial multi-omics. The research will map out the local immune environment in both cancerous and benign prostate tissues across different populations, providing a high-resolution analysis of the immune cell populations and their spatial relationships within the tumor microenvironment. This Aim will yield a comprehensive molecular atlas, allowing the investigators to correlate specific immune and inflammatory profiles with external factors and aggressive disease biology. Aim 3 will leverage the molecular data generated in the first two aims to develop deep learning transformer models that integrate genomic, immune, and environmental factors. These models will be designed to predict which men are at the highest risk for aggressive prostate cancer, enabling more accurate screening and early intervention. By combining molecular insights with clinical and environmental data, the study aims to improve the precision of prostate cancer prognosis and guide more personalized treatment strategies for high-risk populations. This interdisciplinary project will address a critical public health issue. The findings are expected to transform understanding of prostate cancer biology and improve outcomes for men most vulnerable to aggressive disease.