The germline and somatic origins of prostate cancer heterogeneity

Abstract

Newly diagnosed prostate cancers differ dramatically in mutational composition and lethality. The most accurate clinical predictor of lethality is tumor tissue architecture, quantified as tumor grade. To interrogate the evolutionary origins of prostate cancer heterogeneity, we analyzed 666 prostate tumor whole genomes. We identified a compendium of 223 recurrently mutated driver regions, most influencing downstream mutational processes and gene expression. We identified and validated individual germline variants that predispose tumors to acquire specific somatic driver mutations: these explain heterogeneity in disease presentation and ancestry differences. High-grade tumors have a superset of the drivers in lower-grade tumors, including increased frequency of BRCA2 and MYC mutations. Grade-associated driver mutations occur early in tumor evolution, and their earlier occurrence strongly predicts cancer relapse and metastasis. Our data suggest high- and low-grade prostate tumors both emerge from a common premalignant field, influenced by germline genomic context and stochastic mutation timing. SIGNIFICANCE : This study uncovered 223 recurrently mutated driver regions using the largest cohort of prostate tumors to date. It reveals associations between germline SNPs, somatic drivers, and tumor aggression, offering significant insights into how prostate tumor evolution is shaped by germline factors and the timing of somatic mutations.

Description

DATA AVAILABILITY : All Canadian raw sequence data and variant calls are available on the European Genome-Phenome Archive (EGA) under accession EGAS00001000900 (https://www.ebi.ac.uk/ega/studies/EGAS-00001000900). Australian raw sequence data and variant calls are available on the EGA under accession EGAS00001003088 (https://www.ebi.ac.uk/ega/studies/EGAS00001003088). Canadian mRNA data are available on Gene Expression Omnibus (GEO) under accession GSE84043 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84043). Baca WGS data are available on dbGaP under accession phs000447.v1.p1 (https://www.ncbi.nlm.nih.gov/gap/?term=phs000447.v1.p1). Berger WGS data are available on dbGaP under accession phs000330.v1.p1 (https://www.ncbi.nlm.nih.gov/gap/?term=phs000330.v1.p1). Weischenfeldt WGS data are available on the EGA under accession EGAS00001000400 (https://www.ebi.ac.uk/ega/studies/EGAS00001000400). TCGA WGS data are available at Genomic Data Commons Data Portal (https://portal.gdc.cancer.gov/projects/TCGA-PRAD). French ICGC WGS data are available on the EGA under accession EGAD00001003115 (https://www.ebi.ac.uk/ega/datasets/EGAD00001003115). UK ICGC WGS data are available on the EGA under accession (https://www.ebi.ac.uk/ega/datasets/EGAD00001001116). Processed germline variant calls are available through the ICGC Legacy SFTP server (Host: icgc-legacy-1417 sftp.platform.icgc-argo.org, Port: 2222) with approved DACO access (https://docs.icgc-1418argo.org/docs/data-access/icgc-25k-data). Detailed information on access to these data is available at: https://docs.icgc-argo.org/docs/data-access/icgc-25k-data. Methylation data are available in GEO under accession GSE84043. Primary samples’ ChIP-seq data were retrieved from GEO under accession GSE120738.

Keywords

Prostate cancer, Prostate tumor whole genomes, Prostate tumor evolution, Germline factors, Somatic mutation

Sustainable Development Goals

SDG-03: Good health and well-being

Citation

Yamaguchi, T.N., Houlahan, K.E., Zhu, H. et al. 2025, 'The germline and somatic origins of prostate cancer heterogeneity', Cancer Discovery, vol. 15, no. 5, pp. 988-1017, doi : 10.1158/2159-8290.CD-23-0882.