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 wholegenome sequencing, setting the stage for studies of prognostic impact in conservatively treated cohorts.genomics | prognosis | oncology P rostate cancer is the second leading cause of cancer death and the most common malignancy in men. Given the slow growth rate and low metastatic potential of many primary prostate cancers (1), it is critical to identify those men who can be managed conservatively through active surveillance versus those who need aggressive therapy at time of first diagnosis (2, 3). Today, these treatment decisions are primarily made on the basis of tumor stage, prostate-specific antigen (PSA) level, and the histopathological measure of tumor cell differentiation, the Gleason score. These three factors, together with additional pathological variables assessed in the prostatectomy sample, such as lymph node involvement, are often used to estimate risk of relapse with accuracies in the 70-80% range (3). Postoperative nomograms that incorporate these variables have been developed using large cohorts of typically >1,000 patients and consistently show greater accuracy than preoperative nomograms, where pathological variables are limited to those than can be gleaned from biopsies (4). With increasing interest in active surveillance, however, it is critical to improve risk prediction in the preoperative setting (5, 6).