Longitudinal assessment of plasma androgen receptor copy number predicts overall survival in subsequent treatment lines in castration-resistant prostate cancer: analysis from a prospective trial.

Background: Baseline plasma androgen-receptor copy number (AR-CN) is a promising biomarker for metastatic castration-resistant prostate cancer (mCRPC) outcome and treatment response; however, the role of its longitudinal testing is unproven. We aimed to evaluate the prognostic role of AR-CN assessed before subsequent treatment lines in mCRPC patients.
Methods: A subgroup analysis of a prospective multicenter biomarker trial (IRSTB030) was carried out. Plasma AR-CN status (classified as normal or gain, cut-off value = 2) was assessed with digital PCR before each treatment line.
Results: Forty mCRPC patients receiving sequentially docetaxel, cabazitaxel and an AR signaling inhibitor (abiraterone or enzalutamide) were analyzed. At multivariate analysis, at each assessment overall survival (OS) was independently correlated with AR-CN status [first line: hazard ratio (HR) 4.1 [95% confidence interval (CI) 1.6-10.5]; second line: HR 2.4 (95% CI 1.1-5.3); third line: HR 2.1 (95% CI 1.0-4.3)] and median prostate-specific antigen [first line: HR 4.4 (95% CI 1.8-10.9); second line: HR 3.4 (95% CI 1.6-7.2); third line: HR 2.5 (95% CI 1.2-5.6)]. In the three subsequent assessments, AR-CN status changed from normal to gain in 15 (38%) patients. These patients had longer OS (47 months) compared with patients presenting AR-CN gain from first assessment (36 months), but shorter than those maintaining normal AR-CN (69 months) (P = 0.003).
Conclusions: Plasma AR-CN correlates with survival not only at baseline (before first treatment), but also in the assessments before the following lines. Interestingly, AR-CN status may change from normal to gain across subsequent treatments in a significant number of cases, identifying a group of patients with intermediate outcomes. Longitudinal assessment of AR-CN status could represent a promising method to capture mCRPC intrinsic heterogeneity and to improve clinical management.
Competing Interests: Disclosure NB has received travel support from Ipsen, Novartis and Pfizer and speaker honoraria from Bristol-Myers Squibb. VC has received speaker honoraria or travel support from Astellas, Janssen-Cilag and Sanofi-Aventis, and has received consulting fee from Bayer. CL received honoraria for consulting (advisory board) from Bristol-Myers Squibb and Janssen-Cilag. UDG received honoraria for advisory boards or invited speaker fees from Pfizer, Bristol-Myers Squibb, Merck Sharp & Dohme, PharmaMar, Astellas, Bayer, Ipsen, Novartis, Roche, Clovis, AstraZeneca, institutional research grants from AstraZeneca, Sanofi and Roche. All other authors have declared no conflicts of interest.
(Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)