Circulating Tumor Cells as a Predictor of Treatment Response in Clinically Localized Prostate Cancer.

ABSTRACT

PURPOSE: Using nonenrichment-based, potentially more sensitive Epic Sciences circulating tumor cell (CTC) platform, we sought to detect and characterize CTCs in untreated, high-risk localized prostate cancer and to evaluate their clinical implication. METHODS: Between 2012 and 2015, blood samples were prospectively collected from patients with National Comprehensive Cancer Network high-risk localized prostate cancer undergoing either radiotherapy (XRT) plus androgen deprivation therapy or radical prostatectomy (RP) with curative intent. Samples were analyzed with the Epic Sciences platform with 4J,6-diamidino-2-phenylindole, CD45, cytokeratin (CK), and androgen receptor (AR) N-terminal staining. CTC counts were correlated with biochemical recurrence (BCR). RESULTS: A diversity of CTC subtypes, including CK-positive, CK-negative, AR-positive, and CTC clusters, were observed in 73.3% (33 of 45) of patients with evaluable data. The median follow-up was 14.2 months (range, 0.5 to 43.7 months). BCR occurred more frequently in the RP group than XRT (15 of 26 v one of 19), with most patients in the XRT group continuing to receive androgen deprivation therapy. A higher proportion of metastatic events were observed in the RP group (five of 26 v one of 19). In the RP group, BCR and development of metastases were associated with a higher total number of CTCs, AR-positive CTCs, and CTC phenotypic heterogeneity. One patient who developed BCR and metastases quickly after RP had diverse phenotypical CTC subtypes, and single-cell genomic analyses of all detectable CTCs confirmed common prostate cancer copy number alterations and PTEN loss. CONCLUSION: CTCs can be identified in most patients with high-risk localized prostate cancer before definitive therapy using the Epic Sciences platform. If confirmed in a larger cohort with longer follow-up, phenotypic and genomic characterization of CTCs pretherapy may provide an additional means of risk stratifying patients with newly diagnosed high-risk disease and potentially help identify patients who could require multimodal therapy.