Dr. Parekh started by presenting a case of a 67-year-old male with a PSA of 5.7 ng/mL, past medical history of hypertension and diabetes, with a SHIM of 25 and a desire to preserve sexual function. He subsequently underwent a prostate biopsy that showed two cores of Gleason Grade Group 1 and two cores of Gleason Grade Group 2 (one core 10% pattern 4, one core 5% pattern 4). Thus, based on his favorable intermediate risk disease, based on the NCCN guidelines he would be a candidate for active surveillance.
Dr. Parekh notes that there are three biomarkers typically used in active surveillance: Oncotype DX (GPS score), Myriad (Polaris), and Decipher Biosciences (Decipher). Recent work from Leapman et al.1 found that among 92,418 men with prostate cancer, the proportion of patients who received genomic testing increased from 0.8% in July 2012 to June 2013 to 11.3% in July 2017 to June 2018. Additionally, trajectory modeling identified 5 distinct regional trajectories of genomic testing adoption:
Although less than 1% of patients in each group were tested at baseline, group 1 (lowest adoption) increased to 4.0%. Groups 2 (7.8%), 3 (14.6%), and 4 (17.3%) experienced more modest growth, while in group 5 (highest adoption), use increased to 33.8% of patients tested from June 2017 to July 2018.
Based on work from Cooperberg et al. 2 assessing the diverse genomic landscape of 408 men with clinically low-risk prostate cancer, unsupervised clustering analysis of the hallmark gene set scores revealed three clusters, which were enriched for PAM50 luminal A, luminal B, and basal subtypes. Average genomic risk (based on 18 published prognostic signatures), but not the clusters, was associated with both pathological (OR 1.34, 95% CI 1.14-1.58) and biochemical outcomes (HR 1.53, 95% CI 1.19-1.93).
According to Dr. Parekh, there are several important questions with regards to biomarkers in prostate cancer:
- Should we be using tissue based genomic tests? What is the evidence?
- What are the limitations? Tumor heterogeneity
- Which test should I get?
With regards to whether we should be using tissue based markers, Dr. Parekh highlights that there is evidence from the breast cancer literature with six specific assays. Impressively, “Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer” was published in the New England Journal of Medicine in 2018. As such, the breast cancer landscape is significantly further ahead than for prostate cancer which is essentially based on retrospective analyses. Lin et al.3 evaluated the 17-gene Oncotype DX GPS as a predictor of outcomes in 432 patients on active surveillance. There were 101 men that underwent radical prostatectomy after a median 2.1 years of surveillance, with 52 having adverse pathology. A total of 167 men (39%) upgraded at a subsequent biopsy. GPS was significantly associated with adverse pathology when adjusted for diagnostic Gleason Grade (HR/5 GPS units, 1.18; 95% CI 1.04-1.44, p = 0.030), but not when also adjusted for PSA density (HR, 1.85; 95% CI, 0.99 to 4.19; p = 0.066). Dr. Parekh notes that the Genomics in Michigan to Adjust Outcomes of Prostate Cancer (G-MAJOR) for men with newly diagnosed favorable risk prostate cancer trial is currently accruing patients and will hopefully have a readout of results in the next 5 years.
Without question, there is tumor heterogeneity among patients with low risk prostate cancer. Wei and colleagues previously assessed the impact of genomic and transcriptomic diversity within and among intraprostatic prostate cancer foci on prostate cancer molecular taxonomy, predictors of progression, and actionable therapeutic targets. They found that there was considerable variability in genomic alterations among prostate cancer cores, and between RNA- and DNA-based platforms. Furthermore, heterogeneity was found in a molecular grouping of individual prostate cancer foci and the activity of gene sets underlying the assays for risk stratification and androgen receptor activity. 4
Dr. Parekh then discussed a recent publication from his group evaluating the variability in genomic risk assessment from different biopsy cores within the prostate using 3 prognostic signatures (Decipher, CCP, GPS).5 These patients were accrued from two prospective prostate cancer trials (including the Miami MAST active surveillance trial) of patients undergoing mpMRI targeted biopsy with genomic profiling of positive biopsy cores. Punnen et al. assessed the relationship among tumor grade, magnetic resonance imaging risk and genomic risk for each signature. Overall, there were 224 positive biopsy cores from 78 men with prostate cancer were profiled. For each genomic signature, higher biopsy grade (p <0.001) and MRI risk level (p <0.001) were associated with higher genomic scores. Genomic scores from different biopsy cores varied with risk categories changing by 21% to 62% depending on which core or signature was used. MRI targeted biopsy and profiling the core with the highest grade resulted in the highest genomic risk level in 72% to 84% and 75% to 87% of cases, respectively, depending on the signature used. As follows is (A) how often genomic risk level assignment for each signature was consistent among biopsy cores and how often they differed by 1 or 2 risk levels; (B) how often core with largest volume of highest grade cancer found highest genomic risk level among biopsy cores and how often 1 or 2 risk levels higher are found in different core for each signature; (C) how often MRI guided and template biopsy identified highest genomic risk level among biopsy cores for each signature:
Dr. Parekh concluded by noting that currently when we need to get a genomic test, it still remains unclear which test we should get.
Presented by: Dipen J. Parekh, Professor, Chairman for the Department of Urology/ Director of Robotic Surgery, University of Miami, Miami, FL
Written by: Zachary Klaassen, MD, MSc – Urologic Oncologist, Assistant Professor of Urology, Georgia Cancer Center, Augusta University/Medical College of Georgia Twitter: @zklaassen_md during the 85th Annual Southeastern Section of the American Urological Association, April 23-24, 2021
References:
- Leapman MS, Wang R, Ma S, et al. Regional adoption of commercial gene expression testing for prostate cancer. JAMA Oncol. 2021 Jan 1;7(1):52-58.
- Cooperberg MR, Erho N, Chan JM, et al. The diverse genomic landscape of clinically low-risk prostate cancer. Eur Urol. 2018 Oct;74(4):444-452.
- Lin DW, Zheng Y, McKenny JK, et al. 17-Gene Genomic Prostate Score Test Results in the Canary Prostate Active Surveillance Study (PASS) Cohort. J Clin Oncol. 2020 May 10;38(14):1549-1557.
- Wei L, Wang J, Lampert E, et al. Intratumoral and Intertumoral Genomic Heterogeneity of Multifocal Localized Prostate Cancer Impacts Molecular Classifications and Genomic Prognosticators. Eur Urol. 2017 Feb;71(2):183-192.
- Punnen S, Stoyanova R, Kwon D, et al. Heterogeneity in Genomic Risk Assessment from Tissue Based Prognostic Signatures Used in the Biopsy Setting and the Impact of Magnetic Resonance Imaging Targeted Biopsy. J Urol. 2021 May;205(5):1344-1351.