Multiple Tissue Biomarkers Independently and Additively Predict Prostate Cancer Pathology Outcomes

Abstract

Background: Distinguishing indolent from aggressive prostate cancer remains a key challenge for decision making regarding prostate cancer management. A growing number of biomarkers are now available to help address this need, but these have rarely been examined together in the same patients to determine their potentially additive value.

Objective: To determine whether two previously validated plasma markers (transforming growth factor β1 [TGFβ1] and interleukin-6 soluble receptor [IL6-SR]) and two validated tissue scores (the Genomic Evaluators of Metastatic Prostate Cancer [GEMCaP] and cell cycle progression [CCP] scores) can improve on clinical parameters in predicting adverse pathology after prostatectomy, and how much they vary within tumors with heterogeneous Gleason grade.

Design, setting, and participants: A case-control study was conducted among men with low-risk cancers defined by biopsy grade group (GG) 1, prostate-specific antigen (PSA) ≤10 ng/mL, and clinical stage ≤ T2 who underwent immediate prostatectomy. We collected paraffin-fixed prostatectomy tissue and presurgical plasma samples from 381 cases from the University of California, San Francisco, and 260 cases from the University of Washington.

Outcome measurements and statistical analysis: Pathologic outcomes were minor upgrading/upstaging (GG 2 or pT3a) or major upgrading/upstaging (GG ≥ 3 or ≥ pT3b), and multinomial regression was performed to determine putative markers' ability to predict these outcomes, controlling for PSA, percent of positive biopsy cores, age, and clinical site. For upgraded tumors, a secondary analysis of the GEMCaP and CCP scores from the higher-grade tumor was also performed to evaluate for heterogeneity.

Results and limitations: Overall, 357 men had no upgrading/upstaging event at prostatectomy, 236 had a minor event, and 67 had a major event. Neither TGFβ1 nor IL6-SR was statistically significantly associated with any upgrading/upstaging. On the contrary, both the CCP and the GEMCaP score obtained from Gleason pattern 3 tissue were directly associated with minor and major upgrading/upstaging on univariate analysis. The two scores correlated with each other, but weakly. On multinomial analysis including both scores in the model, the CCP score predicted minor upgrading/upstaging (odds ratio [OR] 1.62, 95% confidence interval [CI] 1.05-2.49) and major upgrading/upstaging (OR 2.26, 95% CI 1.05-4.90), p = 0.04), and the GEMCaP score also predicted minor upgrading/upstaging (OR 1.05, 95% CI 1.03-1.08) and major upgrading/upstaging (OR 1.07, 95% CI 1.04-1.11), p < 0.01). The other clinical parameters were not significant in this model. Among upgraded tumors including both Gleason patterns 3 and 4, both the GEMCaP and the CCP score tended to be higher from the higher-grade tumor. The main limitation was the use of virtual biopsies from prostatectomy tissue as surrogates for prostate biopsies.

Conclusions: Biomarker signatures based on analyses of both DNA and RNA significantly and independently predict adverse pathology among men with clinically low-risk prostate cancer undergoing prostatectomy.

Patient summary: Validated biomarker scores derived from both prostate cancer DNA and prostate cancer RNA can add independent information to help predict outcomes after prostatectomy.

Keywords: Adverse pathology; Biomarkers; Cell cycle progression; Genomic Evaluators of Metastatic Prostate Cancer; Prostate cancer; Prostatectomy.