A circulating tumor cell RNA assay for dynamic assessment of androgen receptor signaling inhibitors sensitivity in metastatic castration-resistant prostate cancer.

Abstract

157 Background: Tissue-based gene signatures can predict clinical behavior in prostate cancer (PC). Our objective was to extend their application to circulating tumor cells (CTCs) and to show that changes in the signature were associated with changes in clinical behavior. Methods: Our approach combined the Thermoresponsive(TR)-NanoVelcro CTC purification system with the Nanostring nCounter system for cellular purification and transcriptomic analysis. The Prostate Cancer Classification System (PCS) panel was modified for use in CTCs. We selected 31 blood samples from 23 PC patients receiving androgen receptor signaling inhibitors (ARSI) and measured the PCS1 Z score (probability). These findings were compared with clinical outcome data (responsiveness/resistance). Results: A modified, 16-gene PCS1 signature was established and validated through a rigorous bioinformatics process. We performed analytical validation of our combined CTC-RNA system to ensure reproducibility and specificity. In patient bloods, ARSI-resistant samples (ARSI-R, n = 14) had significantly higher PCS1 Z scores as compared with ARSI-sensitive samples (ARSI-S, n = 17) (Rank-sum test, P = 0.003). The analyzed bloods contained samples from 8 patients who developed resistance to an ARSI allowing for dynamic measurement of gene expression. Our analysis found that the PCS1 Z score increased at the time that ARSI-resistance emerged (Pairwise T-test, P = 0.016). Conclusions: Using this new methodology, contemporary, clinically-relevant gene signatures such as PCS could be measured non-invasively in CTCs. These findings can be used to relate gene expression to clinical drug response. This approach also allowed for measurement of dynamic variations of gene expression in individual patients over time that correlated to ARSI sensitivity.