Predictive Genomic Biomarkers of Hormonal Therapy Versus Chemotherapy Benefit in Metastatic Castration-resistant Prostate Cancer

• Published in: European urology Vol. 81; no. 1; pp. 37 - 47
• Main Authors: Graf, Ryon P., Fisher, Virginia, Mateo, Joaquin, Gjoerup, Ole V., Madison, Russell W., Raskina, Kira, Tukachinsky, Hanna, Creeden, James, Cunningham, Rachel, Huang, Richard S.P., Mata, Douglas A., Ross, Jeffrey S., Oxnard, Geoffrey R., Venstrom, Jeffrey M., Zurita, Amado J.
• Format: Journal Article
• Language: English
• Published: Switzerland Elsevier B.V 01.01.2022
• Subjects: Biomarkers, Tumor - genetics; Drug development; Humans; Male; Predictive biomarkers; Propensity; Prostate cancer; Prostate-Specific Antigen; Prostatic Neoplasms, Castration-Resistant - drug therapy; Prostatic Neoplasms, Castration-Resistant - genetics; Prostatic Neoplasms, Castration-Resistant - pathology; Real world; Retrospective Studies; Taxoids - therapeutic use; Treatment Outcome; Propensity; Drug development; Real world; Prostate cancer; Predictive biomarkers
• ISSN: 0302-2838; 1873-7560
• DOI: 10.1016/j.eururo.2021.09.030

Biomarkers available through routine comprehensive genomic profiling, especially AR amplification, can provide value for clinical decision-making by anticipating the relative efficacy and durability of standard of care treatment options. Biomarkers predicting second-generation novel hormonal therapy (NHT) benefit relative to taxanes are critical for optimized treatment decisions for metastatic castration-resistant prostate cancer (mCRPC) patients. These associations have not been reported simultaneously for common mCRPC genomic biomarkers. To evaluate predictive associations of common genomic aberrations in mCRPC using an established comprehensive genomic profiling (CGP) system. A retrospective cohort study used data from a deidentified US-based clinicogenomic database comprising patients treated in routine clinical practice between 2011 and 2020, evaluated with Foundation Medicine CGP in tissue biopsies obtained around the time of treatment decision. The main cohort included 180 NHT and 179 taxane lines of therapy (LOTs) from 308 unique patients. The sequential cohort comprised a subset of the main cohort NHT LOTs immediately followed by taxane from 55 unique patients. Prostate-specific antigen (PSA) response, time to next treatment (TTNT), and overall survival (OS) were assessed. Main cohort analyses were adjusted for known treatment assignment biases via inverse probability of treatment weighting (IPTW) in treatment interaction models. In the main cohort, patients with AR amplification (ARamp) or PTEN aberrations (PTENalt) had worse relative PSA response on NHT versus taxanes compared with patients without. Patients with ARamp, PTENalt, or RB1 aberrations (RB1alt) also had worse relative TTNT and OS on NHT but not on taxanes. In multivariable models for TTNT and OS adjusted via IPTW, ARamp, PTENalt, and RB1alt were shown as poor prognostic factors overall and demonstrated significant treatment interactions, indicating reduced hazards of therapy switch and death on taxanes versus NHT. Consistent associations favoring increased benefit from subsequent taxane despite prior NHT treatment line were observed only for ARamp in the sequential cohort, in which very few patients had RB1alt for assessment. ARamp status is a candidate biomarker to predict poor effectiveness of NHT relative to taxanes in mCRPC in scenarios where both options are considered. Specific alterations in the DNA of tumors may assist in choosing between novel oral hormonal therapies and standard chemotherapy in advanced prostate cancer patients.