Selecting a well-suited method for isolating/characterizing circulating tumor cells (CTCs) is challenging. Evaluating sensitive and specific markers for prostate cancer (PCa)-specific CTC identification and analysis is crucial. We used the CellCollector EpCAM-functionalized system (CC-EpCAM) and evaluated and developed a PCa-functionalized version (CC-PCa); we then compared CTC isolation techniques that exploit the physical and biological properties of CTCs. We established two cohorts of metastatic PCa patients (mPCa; 15 in cohort 1 and 10 in cohort 2). CTC cultivation experiments were conducted with two capturing methods (Ficoll and ScreenCell). The most sensitive detection rates and highest CTC counts were reached with the CC-PCa and ScreenCell system. Patients with ≥5 CTCs isolated with CC-EpCAM had an overall survival (OS) of 0.93 years, and patients with ≥5 CTCs isolated with CC-PCa had an OS of 1.5 years in cohort 1. Nevertheless, we observed the highest sensitivity and specificity for 24-month survival by the Ficoll with CD45 depletion and ScreenCell system with May-Grunwald Giemsa (MGG) staining. The EpCAM molecule is an essential factor related to OS for CTC isolation based on biological properties in mPCa patients. The best-suited CTC capture system is not limited to one characteristic of cells but adapted to downstream analysis.

Prostate cancer and breast cancer are the most common cancers worldwide. Anti-tumor therapies are long and exhaustive for the patients. The real-time monitoring of the healing progression could be a useful tool to evaluate therapeutic response. Blood-based biosources like circulating tumor cells (CTCs) may offer this opportunity. Application of CTCs for the clinical diagnostics could improve the sequenced screening, provide additional valuable information of tumor dynamics, and help personalized management for the patients. In the past decade, CTCs as liquid biopsy (LB) has received tremendous attention. Many different isolation and characterization platforms are developed but the clinical validation is still missing. In this review, we focus on the clinical trials of circulating tumor cells that have the potential to monitor and stratify patients and lead to implementation into clinical practice.

Background: The role of the androgen receptor (AR) in renal cell carcinoma (RCC) is unclear. We aimed to analyze the expression of AR and its splice variants (SVs) and their correlation with relaxin 2 (RLN2) and cytokines in RCC. Methods: We investigated the expression of RLN2 and AR variants in 25 clear cell RCC (ccRCC) and 9 papillary (pRCC) tumor tissues and the corresponding controls using quantitative PCR and serum RLN2, testosterone and cytokine levels in matched samples using ELISA and chemiluminescent immunometric assay, respectively. Results: ccRCC tissues but not pRCC tissues more frequently expressed AR and the SVs than did normal tissues. All pRCC samples expressed more AR than did ccRCC samples. The highest expression of all AR variants except AR-V12 was found in low-stage tumors, with dominant expression of AR-V7. In males in the ccRCC cohort, the expression of AR-FL, AR-V1 and AR-V3 was significantly correlated with that of RLN2. The secretion pattern of proinflammatory IL-6 was higher in ccRCC than in pRCC. Conclusions: The results highlight additional molecular differences between ccRCC and pRCC, suggesting the influence of external factors on the whole kidney or genetic predispositions to developing certain types of renal cancer, and may support further pathological analysis and studies of targeted hormone therapy.

We demonstrated that the CellCollector is an appropriate tool for detecting CTCs in RCC patients. We examined EpCAM and MUC1 expression levels in RCC tissues and cell lines and analyzed the detection rate of CTCs in blood samples ex vivo using an anti-EpCAM antibody-covered straight or spiraled CellCollector. Eight matched samples were examined for affinity to the anti-EpCAM vs. anti-EpCAM/anti-MUC1 antibody-covered wire. The use of this combination of antibodies allowed us to classify patients with lung metastasis. Finally, four patients were analyzed in vivo. In conclusion, both straight (ex vivo, in vivo) and spiraled (ex vivo) wires detected CTCs.

The expression and cellular mechanisms of programmed cell death-1 protein (PD-1) and its ligands (PD-L1 and PD-L2) in renal cancer cells are not well known. Here, we aimed to investigate the response of renal carcinoma subtypes to the immune checkpoint inhibitor nivolumab and its impact on related signaling pathways. All cell lines analyzed (clear cell (cc)RCC (Caki-1, RCC31) and papillary (p)RCC (ACHN, RCC30)) expressed PD-1 and both ccRCC cell lines, and RCC30 expressed PD-L1. Nivolumab treatment at increasing doses led to increased PD-1 levels in analyzed cells and resulted in aggressive behavior of pRCC but diminished this behavior in ccRCC. The analysis of PD-1/PD-L1-associated signaling pathways demonstrated increased AKT activity in Caki-1 and RCC30 cells but decreased activity in ACHN and RCC31 cells, while ribosomal protein S6 remained largely unchanged. Androgen receptors are related to RCC and were predominantly increased in RCC30 cells, which were the only cells that formed nivolumab-dependent spheroids. Finally, all cell lines exhibited a complex response to nivolumab treatment. Since the pRCC cells responded with increased tumorigenicity and PD-1/PD-L1 levels while ccRCC tumorigenicity was diminished, further studies are needed to improve nivolumab-based therapy for renal carcinoma subtypes, especially the identification of response-involved molecular pathways.

The identification of specific biomarkers that recognize the functional drivers of heterogeneity in prostate cancer (PCa) and personalized treatment remain challenging in systemic medicine. Liquid biopsy allows for the detection and analysis of personalized predictive biomarkers in single blood samples and specifies the current stage of cancer. The aim of our preliminary study was to investigate the association between an elevated circulating tumor cell (CTC) count and the levels of inflammatory factors (IL-6 and IL-8) and biomarkers (DKK-1, PSA, sHER2, and CD44) in patients with metastasized castration-resistant PCa (mCPRC) under chemotherapy and those with localized PCa. Such an association could be used as a component of cancer progression monitoring. We compared the sensitivity and specificity of two CTC isolation platforms. Twenty-eight patients (12 mCRPC and 16 localized PCa patients) were enrolled. Over the study period, the CTC detection rates were 84% with CellCollector^® and 73.5% with CellSearch^® System in mCPRC patients. The CTC counts determined by the CellSearch^® System (CTC_CS) were correlated significantly with the DKK-1, sHER-2, and PSA concentrations in mCRPC patients. The CTC counts captured by CellCollector^® demonstrated no significant association with the concentrations of the tested blood-based biomarkers. The CTC_CS count (AUC = 0.9 (95% CI: 0.72–1.0)) and the PSA level (AUC = 0.95 (95% CI: 0.83–1.0)) presented approximately the same sensitivity and specificity for the overall survival of mCRPC patients. For better personalized characterization, further research on CTC phenotyping and their interactions with tumor-associated blood-released factors is needed.