Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer

Abstract

Localized prostate tumors show remarkably diverse clinical courses, with some being cured by local therapy alone, while others rapidly relapse and have a lethal course despite precision surgery or radiotherapy. Many genomic biomarkers have been developed to predict this clinical behavior, but these are confounded by the extreme spatial heterogeneity of prostate tumors: most are multifocal and harbor multiple subclonal populations. To quantify the influence of spatial heterogeneity on genomic prognostic biomarkers, we developed a case-control high-risk cohort (n = 42) using a prospective registry, risk matched by clinicopathologic prognostic indices. Half of the cohort had early biochemical recurrence (BCR; ie, ≤18 mo), while half remained without evidence of disease for at least 48 mo after radical prostatectomy. We then genomically profiled multiple tumor foci per patient, analyzing 119 total specimens. These data allowed us to validate three published genomic prognostic biomarkers and quantify their sensitivity to tumor spatial heterogeneity. Remarkably, all three biomarkers robustly predicted early BCR, and all three were robust to spatiogenomic variability. These data suggest that DNA-based genomic biomarkers can overcome intratumoral heterogeneity: single biopsies may be sufficient to estimate the risk of early BCR after radical treatment in patients with high-risk disease. PATIENT SUMMARY: We investigated whether heterogeneity between tumor regions within the prostate affects the accuracy of DNA-based biomarkers predicting early relapse after prostatectomy. We observed persistent accuracy in predicting disease relapse, suggesting that spatial heterogeneity may not hinder biomarker performance.

Keywords: Biomarkers; Genomics; Heterogeneity; Prognostication; Prostate cancer.