Transcriptome-Based Prognostic and Predictive Biomarker Analysis of ENACT: A Randomized Controlled Trial of Enzalutamide in Men Undergoing Active Surveillance

Abstract

PURPOSE Few studies have explored the potential for pharmacological interventions to delay disease progression in patients undergoing active surveillance (AS). This preplanned transcriptomic analysis of patient samples from the ENACT trial aims to identify biomarkers in patients on AS who are at increased risk for disease progression or who may derive the greatest benefit from enzalutamide treatment. PATIENTS AND METHODS In the phase II ENACT (ClinicalTrials.gov identifier: NCT02799745 ) trial, patients on AS were randomly assigned 1:1 to 160 mg orally once daily enzalutamide monotherapy or continued AS for 1 year. Transcriptional analyses were conducted on biopsies collected at trial screening, year 1, and year 2. Three gene expression signatures were evaluated in samples collected at screening and in available samples from patients on AS at any time during surveillance (expanded cohort): Decipher genomic classifier, androgen receptor activity (AR-A) score, and Prediction Analysis of Microarray 50 (PAM50) cell subtype signature. RESULTS The Decipher genomic classifier score was prognostic; higher scores were associated with disease progression in the expanded cohort and AS arm of the expanded cohort. Patients with higher Decipher scores had greater positive treatment effect from enzalutamide as measured by time to secondary rise in prostate-specific antigen >25% above baseline. In patients treated with enzalutamide, higher AR-A scores and PAM50 luminal subtypes were associated with a greater likelihood of negative biopsy incidence at year 2. CONCLUSION This analysis suggests that the Decipher genomic classifier may be prognostic for disease progression in AS patients with low- to intermediate-risk prostate cancer. Higher Decipher and AR-A scores, as well as PAM50 luminal subtypes, may also serve as biomarkers for treatment response.