Plasma cell-free DNA-based predictors of response to abiraterone acetate/prednisone and prognostic factors in metastatic castration-resistant prostate cancer

Background The combination of abiraterone acetate and prednisone (AA/P) is used to treat metastatic prostate cancer, but molecular predictors of treatment response are not well elucidated. We evaluated plasma circulating tumor DNA- (ctDNA-) based copy number alterations (CNAs) to determine treatment-related predictive and prognostic biomarkers for metastatic castration-resistant prostate cancer (mCRPC). Methods Serial plasma specimens were prospectively collected from 88 chemotherapy-naive mCRPC patients before and after 12 weeks of AA/P treatment. Sequencing-based CNA analyses were performed on 174 specimens. We evaluated CNA-associated 12-week responses for primary resistance, time to treatment change (TTTC) for secondary resistance, and overall survival for prognosis (P < 0.05). Associations with primary resistance were analyzed using the Fisher exact test. Kaplan-Meier survival curves and Cox regression analyses were used to determine the associations of CNAs with acquired resistance and overall survival. Results ctDNA reduced by 3.89% in responders and increased by 0.94% in nonresponders (P = 0.0043). Thirty-one prostate cancer-related genes from whole genome CNAs were tested. AR and AR enhancer amplification were associated with primary resistance (P = 0.0039) and shorter TTTC (P = 0.0003). ZFHX3 deletion and PIK3CA amplification were associated with primary resistance (P = 0.026 and P = 0.017, respectively), shorter TTTC (P = 0.0008 and P = 0.0016, respectively), and poor survival (P = 0.0025 and P = 0.0022, respectively). CNA-based risk scores combining selected significant associations (AR, NKX3.1, and PIK3CA) at the univariate level with TTTC were predictive of secondary resistance (P = 0.0002). and established prognoses for survival based on CNAs in ZFHX3, RB1, PIK3CA, and OPHN1 (P = 0.002). Multigene risk scores were more predictive than individual genes or clinical risk factors (P < 0.05). Conclusion Plasma ctDNA CNAs and risk scores can predict mCRPC-state treatment and survival outcomes.