Circulating Tumor Cell–Based Molecular Classifier for Predicting Resistance to Abiraterone and Enzalutamide in Metastatic Castration-Resistant Prostate Cancer

• DOI: 10.1016/j.neo.2019.06.002
• Publication Date: 2019-07-02T19:31:58Z
• Authors: Jae-Seung Chung; Yugang Wang; James Henderson; Udit Singhal; Yuanyuan Qiao; Alexander B. Zasl...; Daniel H. Hovelson; Daniel E. Spratt; Zachery Reichert; Ganesh S. Palapattu; Russell S. Taichman; Scott A. Tomlins; Todd M. Morgan
• Keywords: Male; Original article; Kaplan-Meier Estimate; 03 medical and health sciences; 0302 clinical medicine; Antineoplastic Combined Chemotherapy Protocols; Nitriles; Phenylthiohydantoin; Biomarkers, Tumor; Humans; Neoplasm Metastasis; Aged; Neoplasm Staging; Aged, 80 and over; Gene Expression Profiling; Computational Biology; Middle Aged; Neoplastic Cells, Circulating; Prognosis; 3. Good health; Drug Resistance, Neoplasm; Benzamides; Androstenes; Neoplasm Grading

While circulating tumor cell (CTC)-based detection of AR-V7 has been demonstrated to predict patient response to second-generation androgen receptor therapies, the rarity of AR-V7 expression in metastatic castrate-resistant prostate cancer (mCRPC) suggests that other drivers of resistance exist. We sought to use a multiplex gene expression platform to interrogate CTCs and identify potential markers of resistance to abiraterone and enzalutamide. 37 patients with mCRPC initiating treatment with enzalutamide (n = 16) or abiraterone (n = 21) were prospectively enrolled for CTC collection and gene expression analysis using a panel of 89 prostate cancer-related genes. Gene expression from CTCs was correlated with PSA response and radioclinical progression-free survival (PFS) using Kaplan-Meier and Cox regression analyses. Twenty patients (54%) had detectable CTCs. At a median follow-up of 11.3 months, increased expression of the following genes was significantly associated with shorter PSA PFS and radioclinical PFS: AR, AR-V7, PSA, PSCA, TSPAN8, NKX3.1, and WNT5B. Additionally, high SPINK1 expression was associated with increased PFS. A predictive model including all eight genes gave an area under the curve (AUC) of 0.84 for PSA PFS and 0.86 for radioclinical PFS. In comparison, the AR-V7 only model resulted in AUC values of 0.65 and 0.64.These data demonstrate that clinically relevant information regarding gene expression can be obtained from whole blood using a CTC-based approach. Multigene classifiers in this setting may allow for the development of noninvasive predictive biomarkers to guide clinical management.