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Background The transition of prostate adenocarcinoma to a predominantly androgen receptor (AR) signaling independent phenotype can occur in the later stages of the disease and is associated with low AR expression and/or the development of small cell or neuroendocrine tumor characteristics. As metastatic tumor biopsies are not always feasible and are difficult to repeat, we sought to evaluate noninvasive methods to identify patients transitioning towards a neuroendocrine phenotype (NEPC). Experimental Design We prospectively studied a metastatic tumor biopsy, serum biomarkers and circulating tumor cells (CTC, Epic Sciences) from patients with castration resistant prostate cancer (CRPC) including those with pure or mixed NEPC histology present on biopsy. CTCs labeled with the patient’s clinical status were used to learn features that discriminate NEPC patients, which was then applied to an independent cohort. Results Twenty-seven patients with CRPC including 12 NEPC and 5 with atypical clinical features suggestive of NEPC transition were studied. CTCs from NEPC patients demonstrated frequent clusters, low or absent AR expression, lower cytokeratin expression, and smaller morphology relative to typical CRPC. A multivariate analysis of protein and morphologic variables enabled distinguishing CTCs of NEPC from CRPC. This CTC classifier was applied to an independent prospective cohort of 159 metastatic CRPC patients and identified in 17/159 (10.7%) of cases, enriched in patients with high CTC burden (p<0.01) and visceral metastases (p=0.04). Conclusions CTCs from patients with NEPC have unique morphologic characteristics, which were also identified in a subset of CRPC patients with aggressive clinical features potentially undergoing NEPC transition.

The Epic Platform was developed for the unbiased detection and molecular characterization of circulating tumour cells (CTCs). Here, we report assay performance data, including accuracy, linearity, specificity and intra/inter-assay precision of CTC enumeration in healthy donor (HD) blood samples spiked with varying concentrations of cancer cell line controls (CLCs). Additionally, we demonstrate clinical feasibility for CTC detection in a small cohort of metastatic castrate-resistant prostate cancer (mCRPC) patients. The Epic Platform demonstrated accuracy, linearity and sensitivity for the enumeration of all CLC concentrations tested. Furthermore, we established the precision between multiple operators and slide staining batches and assay specificity showing zero CTCs detected in 18 healthy donor samples. In a clinical feasibility study, at least one traditional CTC/mL (CK+, CD45-, and intact nuclei) was detected in 89 % of 44 mCRPC samples, whereas 100 % of samples had CTCs enumerated if additional CTC subpopulations (CK-/CD45- and CK+ apoptotic CTCs) were included in the analysis. In addition to presenting Epic Platform's performance with respect to CTC enumeration, we provide examples of its integrated downstream capabilities, including protein biomarker expression and downstream genomic analyses at single cell resolution.

The heterogeneity of an individual patient’s tumor has been linked to treatment resistance, but quantitative biomarkers to rapidly and reproducibly evaluate heterogeneity in a clinical setting are currently lacking. Using established tools available in a CAP-accredited and CLIA-certified clinical laboratory, we quantified digital pathology features on 9,225 individual circulating tumor cells (CTCs) from 179 unique metastatic castration-resistant prostate cancer (mCRPC) patients to define phenotypically distinct cell types. Heterogeneity was quantified based on the diversity of cell types in individual patient samples using the Shannon index and associated with overall survival (OS) in the 145 specimens collected prior to initiation of second or later lines of therapy. Low CTC phenotypic heterogeneity was associated with better OS in patients treated with androgen receptor signaling inhibitors (ARSI), whereas high heterogeneity was associated with better OS in patients treated with taxane chemotherapy. Overall, the results show that quantifying CTC phenotypic heterogeneity can help inform the choice between ARSI and taxanes in mCRPC patients.