The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer

Abstract

Background: Among men with clinically low-risk prostate cancer, we have previously documented heterogeneity in terms of clinical characteristics and genomic risk scores.

Objective: To further study the underlying tumor biology of this patient population, by interrogating broader patterns of gene expression among men with clinically low-risk tumors.

Design, setting, and participants: Prostate biopsies from 427 patients considered potentially suitable for active surveillance underwent central pathology review and genome-wide expression profiling. These cases were compared with 1290 higher-risk biopsy cases with diverse clinical features from a prospective genomic registry.

Outcome measurements and statistical analysis: 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 pathological and biochemical outcomes using multivariable regression analysis.

Results and limitations: A total of 408 (96%) biopsies passed RNA quality control. Based on AGR quartiles defined by the high-risk multicenter cases, the University of California, San Francisco (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 three clusters, which were enriched for the previously described PAM50 luminal A, luminal B, and basal subtypes. AGR, but not the clusters, was associated with both pathological (odds ratio 1.34, 95% confidence interval [CI] 1.14-1.58) and biochemical outcomes (hazard ratio 1.53, 95% CI 1.19-1.93). These results may underestimate within-prostate genomic heterogeneity.

Conclusions: Prostate cancers that are homogeneously low risk by traditional characteristics demonstrate substantial diversity at the level of genomic expression. Molecular substratification of low-risk prostate cancer will yield a better understanding of its divergent biology and, in the future may help personalize treatment recommendations.

Patient summary: We studied the genomic characteristics of tumors from men diagnosed with low-risk prostate cancer. We found three main subtypes of prostate cancer with divergent tumor biology, similar to what has previously been found in women with breast cancer. In addition, we found that genomic risk scores were associated with worse pathology findings and prostate-specific antigen recurrence after surgery. These results suggest even greater genomic diversity among low-risk patients than has previously been documented with more limited signatures.

Keywords: Active surveillance; Biomarkers; Genomics; Low-risk prostate cancer; Prognosis; Prostate cancer biopsy; Subtyping; Tumor biology.

Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Figures

Fig. 1

– Heatmap of UCSF and GRID patients (n = 1698) ordered by increasing AGR. The map indicates the following (from top to bottom): (1) the average genomic risk colored by the study the patient is part of, (2) Gleason score, (3) normalized scores for 18 prognostic signatures, and (4) hallmark gene set scores and their correlations to AGR indicated. The patients are broken up into quartiles based on the GRID reference set, and the number (%) of UCSF patients in each quartile is annotated. UCSF patients are associated with lower AGR; however, some UCSF patients are also found in the highest-risk quartile. AGR = average genomic risk; GRID = Decipher Genomic Resource Information Database; GS = Gleason score; UCSF = University of California, San Francisco. * p < 0.05. ** p < 0.01. *** p < 0.001.

Fig 2

– Heatmap of the UCSF patients (n = 408) consensus clustered based on the expression score of 37 hallmark gene sets. The patients tend to cluster into three distinct groups, which are loosely associated with PAM50’s basal, luminal A, and luminal B subtypes. CAPRA = Cancer of the Prostate Risk Assessment; PSA = prostate specific antigen; UCSF = University of Calfornia, San Francisco.

Fig. 3

– Boxplot showing the AGR for each of the clusters from Figure 2. Patients in cluster 3 are found to be at the lowest AGR, while patients in cluster 2 are at the highest AGR (p < 0.001). AGR = average genomic risk.