Blood-based gene expression signature associated with metastatic castrate-resistant prostate cancer patient response to abiraterone plus prednisone or enzalutamide

Background: Precision medicine approaches for managing patients with metastatic castrate-resistant prostate cancer (mCRPC) are lacking. Non-invasive approaches for molecular monitoring of disease are urgently needed, especially for patients suffering from bone metastases for whom tissue biopsy is challenging. Here we utilized baseline blood samples to identify mCRPC patients most likely to benefit from abiraterone plus prednisone (AAP) or enzalutamide. Methods: Baseline blood samples were collected for circulating tumor cell (CTC) enumeration and qPCR-based gene expression analysis from 51 men with mCRPC beginning treatment with abiraterone or enzalutamide. Results: Of 51 patients (median age 68 years [51–82]), 22 received AAP (abiraterone 1000 mg/day plus prednisone 10 mg/day) and 29 received enzalutamide (160 mg/day). The cohort was randomly divided into training (n = 37) and test (n = 14) sets. Baseline clinical variables (Gleason score, PSA, testosterone, and hemoglobin), CTC count, and qPCR-based gene expression data for 141 genes/isoforms in CTC-enriched blood were analyzed with respect to overall survival (OS). Genes with expression most associated with OS included MSLN, ARG2, FGF8, KLK3, ESRP2, NPR3, CCND1, and WNT5A. Using a Cox-elastic net model for our test set, the 8-gene expression signature had a c-index of 0.87 (95% CI [0.80, 0.94]) and was more strongly associated with OS than clinical variables or CTC count alone, or a combination of the three variables. For patients with a low-risk vs. high-risk gene expression signature, median OS was not reached vs. 18 months, respectively (HR 5.32 [1.91–14.80], p = 0.001). For the subset of 41 patients for whom progression-free survival (PFS) data was available, the median PFS for patients with a low-risk vs high-risk gene expression signature was 20 vs. 5 months, respectively (HR 2.95 [1.46–5.98], p = 0.003). Conclusions: If validated in a larger prospective study, this test may predict patients most likely to benefit from second-generation antiandrogen therapy.