Nature Communications (Aug 2023)

Copy number architectures define treatment-mediated selection of lethal prostate cancer clones

  • A. M. Mahedi Hasan,
  • Paolo Cremaschi,
  • Daniel Wetterskog,
  • Anuradha Jayaram,
  • Stephen Q. Wong,
  • Scott Williams,
  • Anupama Pasam,
  • Anna Trigos,
  • Blanca Trujillo,
  • Emily Grist,
  • Stefanie Friedrich,
  • Osvaldas Vainauskas,
  • Marina Parry,
  • Mazlina Ismail,
  • Wout Devlies,
  • Anna Wingate,
  • Mark Linch,
  • Cristina Naceur-Lombardelli,
  • PEACE consortium,
  • Charles Swanton,
  • Mariam Jamal-Hanjani,
  • Stefano Lise,
  • Shahneen Sandhu,
  • Gerhardt Attard

DOI
https://doi.org/10.1038/s41467-023-40315-9
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 16

Abstract

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Abstract Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient evolutionary relationships of metastases that evade treatment, we perform genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer. We identify diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number changes, we confirm a common clone of origin across metastases and diagnostic biopsies, and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. These autosome-defined clusters are characterized by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance (p-values 3.07 × 10−8 and 6.4 × 10−4). Integration with anatomical sites suggests patterns of spread and points of genomic divergence. Here, we show that copy number boundaries identify treatment-selected clones with putatively distinct lethal trajectories.