Various devices for isolating and detecting circulating tumor cells (CTCs) have been developed, whereas the CellSearch® system has been clinically used in numerous prostate CTC studies. CTCs might become more useful surrogate markers of prostate cancer, and they should be measured in all settings, but a smaller, low-cost CTC capture system is required. An inexpensive and highly sensitive microfluidic CTC-capture polymeric chip, developed by the Toyama Industrial Technology Center, as described in the following text, was used to assess the number of CTCs from patients with metastatic prostate cancer. After verifying that cultured human prostate cancer cells (PC3 and LNCaP) could be captured with the chip coated with anti-epithelial cell adhesion molecule (CD326) antibody, whole blood samples of 14 patients with prostate cancer were screened. The average capture efficacy of PC3 cells was 94.60% in phosphate-buffered saline (PBS) and 83.82% in whole blood. The average capture efficacy of LNCaP cells was 82.73% in PBS and 75.78% in whole blood. CTCs were detected by the chip device in all 14 patients with metastatic prostate cancer using 2-mL blood samples. Although fewer CTCs were detected in patients with oligometastases, all patients with multiple distant metastases had CTCs. The average CTC count was 48 cells/mL (range 1-81 cells/mL). This CTC-chip will be able to capture CTCs and be useful to check CTCs as a surrogate marker in prostate cancer with smaller samples and lower cost in any small institution.

Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low–intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accuracy of deep learning analysis using multimodal medical data focused on clinically significant PCa in patients with PSA ≤ 20 ng/mL. Our cohort study included 178 consecutive patients who underwent ultrasound-guided prostate biopsy. Deep learning analyses were applied to predict clinically significant PCa. We generated receiver operating characteristic curves and calculated the corresponding area under the curve (AUC) to assess the prediction. The AUC of the integrated medical data using our multimodal deep learning approach was 0.878 (95% confidence interval [CI]: 0.772–0.984) in all patients without PSA restriction. Despite the reduced predictive ability of PSA when restricted to PSA ≤ 20 ng/mL (n = 122), the AUC was 0.862 (95% CI: 0.723–1.000), complemented by imaging data. In addition, we assessed clinical presentations and images belonging to representative false-negative and false-positive cases. Our multimodal deep learning approach assists physicians in determining treatment strategies by predicting clinically significant PCa in patients with PSA ≤ 20 ng/mL before biopsy, contributing to personalized medical workflows for PCa management.

In patients with high-risk prostate cancer (HRPC) after radical prostatectomy (RP), biochemical recurrence (BCR) increases the risk of distant metastasis. Accordingly, additional prognostic biomarkers are required to identify the subpopulation of patients with HRPC who develop clinical recurrence (CR) after BCR. The objective of this study was to identify biomarkers in formalin-fixed paraffin-embedded (FFPE) RP samples that are prognostic for CR in patients with HRPC who experience BCR after RP (post-RP BCR). First, we performed a preliminary RNA sequencing analysis to comprehensively profile RNA expression in FFPE RP samples obtained from patients with HRPC who developed CR after post-RP BCR and found that many snRNAs were very abundant in preserved FFPE samples. Subsequently, we used quantitative polymerase chain reaction (qPCR) to compare the expression levels of highly abundant snRNAs in FFPE RP samples from patients with HRPC with and without CR after post-RP BCR (21 CR patients and 46 non-CR patients who had more than 5 years of follow-up after BCR). The qPCR analysis revealed that the expression levels of snRNA RNU1-1/1-2 and RNU4-1 were significantly higher in patients with CR than in patients without CR. These snRNAs were significantly correlated with clinical recurrence-free survival (RFS) in patients with HRPC who experienced post-RP BCR. Furthermore, snRNA RNU1-1/1-2 could serve as an independent prognostic factor for clinical RFS in post-RP BCR of HRPC cases where known prognostic factors (e.g., Gleason score) cannot distinguish between CR and non-CR patients. Our findings provide new insights into the involvement of snRNAs in prostate cancer progression.

We investigated the clinical significance of positive surgical margins (PSMs) in index tumors following radical prostatectomy (RP), with particular attention to the tumor’s zonal origin. Among 1148 patients with localized prostate cancer who underwent RPs, 973 were included after excluding those who received perioperative therapy or had incomplete data. Index tumors were categorized by zonal origin: transition zone, peripheral zone, or central zone (CZ). Overall, PSMs were observed in 26.4% of index tumors. Although CZ index tumors were relatively uncommon (6.5%), they exhibited the highest PSM rate (42.9%) and showed the most aggressive pathological features. The 5-year biochemical recurrence (BCR)-free survival rate was significantly lower in patients with PSMs in index tumors than in those with negative surgical margins (45.6% vs. 86.8%, p < 0.0001). Notably, patients with PSMs in CZ index tumors had the worst outcomes, with a 5-year BCR-free survival rate of 22.0%. Multivariate analysis identified PSMs in index tumors as an independent predictor of BCR (HR: 3.4; 95% CI: 2.5–4.5), with a similar trend observed in early recurrence. These findings highlight the prognostic significance of PSMs in index tumors during RP, especially in CZ tumors, and emphasize the importance of securing local control in these cases.

Purpose: Although the hinotori™ surgical robotic system is Japan's first domestically developed platform, evidence regarding its clinical feasibility remains limited. Because adrenalectomy is a standardized minimally invasive procedure with well-defined perioperative outcomes, it provides an appropriate model for evaluating newly introduced robotic platforms. We evaluated the clinical outcomes and medical costs of robot-assisted adrenalectomy (RAAD) using the hinotori™ system (H-RAAD) and compared them retrospectively with those of da Vinci Xi™-assisted RAAD (D-RAAD). Materials and methods: We retrospectively examined patients who underwent RAAD at Nippon Medical School Hospital between September 2023 and May 2025. Baseline demographic characteristics, perioperative variables, postoperative outcomes, pathological findings, and medical costs extracted from the Diagnosis Procedure Combination (DPC) database were evaluated. Results: We evaluated 12 patients (H-RAAD, n = 5; D-RAAD, n = 7). Baseline characteristics were comparable between the groups, although the median tumor diameter was numerically smaller in the H-RAAD group. The median anesthesia, operative, and console times in the H-RAAD group were 264 (253-307, U = 10.0, p = 0.22), 189 (156-264, U = 10.0, p = 0.29), and 108 (71-180, U = 14.0, p = 0.57) minutes, respectively, comparable with those in the D-RAAD group. Total medical costs per case were similar between the D‐RAAD ($6,333.1) and H‐RAAD ($6,398.4) groups (U = 23.0, p = 0.34). Conclusions: In this small cohort, H-RAAD was completed safely without conversion or major complications, demonstrating perioperative outcomes similar to those of D-RAAD. Although individual cost components varied, total reimbursed medical costs under the DPC system were comparable. Given the limited sample size and exclusion of robotic system capital and maintenance costs, these findings remain exploratory.