ARTICLE ABSTRACT
Lethal prostate cancer has passed through at least two evolutionary bottlenecks: acquisition of metastatic potential and development of castration resistance. A better understanding of how this affects genetic heterogeneity across metastatic sites is needed to develop strategies to block metastatic spread and to overcome resistance. By leveraging deep whole-exome sequencing of 93 tumors from 26 patients, we examined patterns of metastatic dissemination and clonal evolution of prostate cancer. Phylogenetic reconstruction and mathematical modeling enabled quantification of the number of mutations and clones in the cancer ecosystem and characterization of each patient’s disease as an evolutionary process. Although mutations of the earliest pathogenic genetic drivers of prostate cancer were truncal, most other likely passenger mutations, copy-number alterations, and clones arose after the cancer had spread and were confined to individual metastatic sites because of polyclonal and polyphyletic seeding. Single-tissue sequencing tended to overestimate mutation clonality and, apart from truncal drivers, underestimate mutation rates for both individual patients and cohorts. This study highlights the independent evolution of metastatic lesions, which has implications for diagnostic and targeted therapy strategies.
Genomic analysis of a multisite metastatic prostate cancer cohort reveals patterns of clonal heterogeneity, dissemination, and evolution, highlighting the need to evaluate multiple samples to fully characterize the clonal architecture of tumors.This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.
