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Prostate cancer is characterized by profound heterogeneity in its clinical trajectory. While genomic heterogeneity has been well-characterized, epigenomic heterogeneity remains less understood. To fill this gap, we compiled 2,149 multi-ancestric prostate methylomes spanning normal tissue through localized disease of varying grades to poly-metastatic disease, most with multi-omic DNA and/or RNA characterization. We identify four subtypes that varied by stage, grade and mutational subtype. We identify extensive interplay between DNA ploidy and DNA methylation, with transcriptional consequences that vary across driver-genes. Each major prostate cancer driver gene mutation triggers a specific epigenetic dysregulation, and we define a set of 14 reusable models that accurately predict clinico-molecular features of a prostate cancer from DNA methylation data. Specific epigenetic features predict disease aggression, including metastasis, with epigenomic and genomic features synergizing to optimize predictions. These results define a complex interplay between tumour genetics and epigenetics that converges to modify gene-expression programs, and subsequent clinical presentation.
Competing Interest Statement
MLKC declared the following potential conflict of interest unrelated to the submitted work: personal fees from Astellas, Axiom, Bicara Therapeutics, IQVIA, Janssen, MSD, Seagen, Varian; non-financial support from Veracyte Inc; personal fees and grants from Bayer; personal fees and grants from BeiGene; consults for Bicara Therapeutics; consults for ImmunoScape; consults for PVMed; consults for Varian Thought Leadership Council; and is a co-inventor of the patent of a High Sensitivity Lateral Flow Immunoassay For Detection of Analyte in Sample (10202107837T), Singapore, and serves on the Board of Directors of Digital Life Line Pte Ltd that owns the licensing agreement of the patent. PCB sits on the Scientific Advisory Boards of BioSymetrics Inc. and of Intersect Diagnostics Inc., and formerly sat on that of Sage Bionetworks.
Footnotes
* A new section was added "Inverse associations between DNA methylation age and driver mutations" and Figure 5.