The diverse genomic landscape of low−risk prostate cancer.

Abstract

74 Background: Among men with clinically low-risk prostate cancer, we have previously documented heterogeneity in terms of clinical characteristics and genomic risk scores. In this study, we aimed to study the underlying tumor biology of this patient population, by interrogating patterns of gene expression among men with clinically low-risk tumors. Methods: Prostate biopsies from 427 patients considered potentially suitable for active surveillance underwent central pathology review and genome-wide expression profiling. These cases were compared to 1290 higher-risk biopsy cases with diverse clinical features from a prospective genomic registry. Average genomic risk (AGR) was determined from 18 published prognostic signatures, and MSigDB Hallmark gene sets were analyzed using bootstrapped clustering methods. These sets were examined in relation to clinical variables and pathologic and biochemical outcomes using multivariable regression analysis. Results: 408 (96%) of biopsies passed RNA quality control. Based on average genomic risk quartiles defined by the high-risk multicenter cases, the UCSF low-risk patients were distributed across the quartiles as 219 (54%), 107 (26%), 61 (15%), and 21 (5%). Unsupervised clustering analysis of the Hallmark gene set scores revealed 3 clusters, which were enriched for the previously described PAM50 luminal A, luminal B and basal subtypes. These three clusters did not associate with existing clinical or known genomic risk characteristics, suggesting a novel and independent classification for low-risk prostate cancer. AGR was associated with both pathological (OR: 1.3, p < 0.001) and biochemical outcomes (OR: 1.5, p = 0.001 ) but the clusters were not. Conclusions: Prostate cancers that are largely homogeneously low-risk by traditional characteristics demonstrate substantial diversity at the level of genomic expression. Molecular sub-stratification of low-risk prostate cancer may facilitate better decision-making with respect to both timing and intensity of cancer surveillance and treatment.