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Integrated proteogenomics uncovers ancestry-specific and shared molecular drivers in localized prostate cancer

Schafer, C. C.; Abulez, T. S.; Zhang, X.; Ho, K.-L.; Jiang, J.; Young, D.; Fox, J.; Conrads, K. A.; Hood, B. L.; Sukumar, G.; Nousome, D.; Raj-Kumar, P.-K.; Russo, M.; Shafi, A. A.; Su, X. A.; Dobi, A.; Ali, A.; Elsamanoudi, S.; Cullen, J.; Figg, W. D.; Petrovics, G.; Dalgard, C. L.; Wilkerson, M. D.; Bateman, N. W.; Conrads, T. P.; Sesterhenn, I. A.; APOLLO Research Network, ; Ellis, L.; Shriver, C. D.; Chesnut, G. T.; Tan, S.-H.

2025-11-29 cancer biology
10.1101/2025.11.28.691220 bioRxiv
Show abstract

Our integrative proteogenomics (genome, proteome and phosphoproteome) of localized prostate cancer (PCa) in an equal-access Military Health System patient cohort (57 Black and 55 White) revealed significant ancestry-associated differences. Somatic and germline regulatory differences converged on androgen, metabolic, PI3K/AKT/mTOR, and DNA damage response (DDR) pathways, with ancestry-specific immune- and stromal-associated signals. Black patients displayed greater genomic variability, enhanced androgen response, fatty-acid metabolism, and epithelial-mesenchymal transition, while White patients showed prevalent DDRG alterations, activated oncogenic signaling (MYC, E2F, mTORC1), and cell cycle regulation. Phosphoproteomics highlighted distinct kinase activities and candidate druggable dependencies. Multiomics integration revealed three exploratory tumor subtypes whose distinct biological programs were reproducibly validated. Ancestry-associated eQTLs supported inherited regulation of the proteome independent of CNAs. Ancestry-specific CNA and protein panels improved progression risk prediction beyond PSA and pathology models. These findings provide a framework for ancestry-informed prognostic models and generate testable hypotheses for precision therapies to reduce outcome disparities.

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