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Copy number alteration burden predicts prostate cancer relapse

Author:
Hieronymus, Haley, Schultz, Nikolaus, Gopalan, Anuradha, Carver, Brett S., Chang, Matthew T., Xiao, Yonghong, Heguy, Adriana, Huberman, Kety, Bernstein, Melanie, Assel, Melissa, Murali, Rajmohan, Vickers, Andrew, Scardino, Peter T., Sander, Chris, Reuter, Victor, Taylor, Barry S., Sawyers, Charles L.
Source:
Proceedings of the National Academy of Sciences of the United States of America 2014 v.111 no.30 pp. 11139-11144
ISSN:
0027-8424
Subject:
DNA, biomarkers, biopsy, genome, histopathology, men, metastasis, patients, prostate-specific antigen, prostatic neoplasms, relapse, sequence analysis
Abstract:
Primary prostate cancer is the most common malignancy in men but has highly variable outcomes, highlighting the need for biomarkers to determine which patients can be managed conservatively. Few large prostate oncogenome resources currently exist that combine the molecular and clinical outcome data necessary to discover prognostic biomarkers. Previously, we found an association between relapse and the pattern of DNA copy number alteration (CNA) in 168 primary tumors, raising the possibility of CNA as a prognostic biomarker. Here we examine this question by profiling an additional 104 primary prostate cancers and updating the initial 168 patient cohort with long-term clinical outcome. We find that CNA burden across the genome, defined as the percentage of the tumor genome affected by CNA, was associated with biochemical recurrence and metastasis after surgery in these two cohorts, independent of the prostate-specific antigen biomarker or Gleason grade, a major existing histopathological prognostic variable in prostate cancer. Moreover, CNA burden was associated with biochemical recurrence in intermediate-risk Gleason 7 prostate cancers, independent of prostate-specific antigen or nomogram score. We further demonstrate that CNA burden can be measured in diagnostic needle biopsies using low-input whole-genome sequencing, setting the stage for studies of prognostic impact in conservatively treated cohorts.
Agid:
1786767