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Abstract Uromonitor and urinary telomerase reverse transcriptase promoter mutation droplet digital PCR (uTERTpm ddPCR) are non-invasive tests designed to detect bladder cancer in urine. We aimed to compare the diagnostic performance of uTERTpm ddPCR, Uromonitor and urine cytology in detecting bladder cancer. Urine samples were collected prospectively from patients diagnosed with primary (n = 74) and recurrent bladder cancer (n = 20) or benign urological conditions (n = 48) prior to surgical resection. The samples were tested for bladder cancer via uTERTpm ddPCR, Uromonitor and urine cytology. The sensitivity, specificity, and predictive values were calculated for each test, including confidence intervals. The results were stratified by low-grade non-muscle-invasive bladder cancer, high-grade non-muscle-invasive bladder cancer and muscle-invasive bladder cancer. Compared with urine cytology (59.5%, p = 0.005) and Uromonitor (56.8%, p = 0.001), the uTERTpm ddPCR test had the highest sensitivity (79.7%) for the detection of primary bladder cancer. Specificity did not significantly differ. The uTERTpm ddPCR test exhibited superior diagnostic performance over urine cytology and Uromonitor, highlighting its potential for non-invasive primary bladder cancer diagnosis.

Abstract Objective There is a shortage of established prognostic biomarkers in bladder cancer. One candidate is tumour protein 63 (p63), a transcription factor of the p53 gene family that is expressed in the normal urothelium. Recently proposed RNA expression‐based molecular classifiers of bladder cancer identified high p63 expression as a component of a basal/squamous subtype linked to poor patient prognosis. Methods In this study, p63 protein expression was analysed by immunohistochemistry on more than 2500 urothelial bladder carcinomas in a tissue microarray format to determine its relationship with clinicopathological parameters of disease progression and patient outcome. Results Nuclear p63 staining was seen in all cells of normal urothelium and at elevated levels in pTaG2 tumours. The rate of p63 positive cases and the staining intensity was lower in pTaG3 tumours (93.2%, p

Abstract Background A high level of PD-L1 expression is the most relevant predictive parameter for response to immune checkpoint inhibitor (CPI) therapy in urinary bladder cancer. Existing data on the relationship between PD-L1 expression and the natural course of disease are controversial and sparse. Methods To expand our understanding of the relationship between PD-L1 expression and parameters of cancer aggressiveness, PD-L1 was analyzed on tissue microarrays containing 2710 urothelial bladder carcinomas including 512 patients with follow-up data who underwent radical cystectomy and follow-up therapies in the pre-immune checkpoint inhibitor therapy era. Results Tumor cell positivity in ≥10% of cells were seen in 513 (20%) and an immune cell positivity occurred in 872 (34%) of 2566 interpretable cancers. PD-L1 positivity in tumor cells increased from pTaG2 low grade (0.9% positive) to pTaG3 high grade (4.1%; p = 0.0255) and was even higher in muscle-invasive (pT2–4) carcinomas (29.3%; p

IntroductionTrophoblast cell surface antigen 2 (TROP2; EpCAM2) is a transmembrane glycoprotein which is closely related to EpCAM (EpCAM; EpCAM1). Both proteins share partial overlapping functions in epithelial development and EpCAM expression but have not been comparatively analyzed together in bladder carcinomas. TROP2 constitutes the target for the antibody-drug conjugate Sacituzumab govitecan (SG; TrodelvyTM) which has been approved for treatment of metastatic urothelial carcinoma by the United States Food and Drug administration (FDA) irrespective of its TROP2 expression status. MethodsTo evaluate the potential clinical significance of subtle differences in TROP2 and EpCAM expression in urothelial bladder cancer, both proteins were analyzed by multiplex fluorescence immunohistochemistry in combination with a deep-learning based algorithm for automated cell detection on more than 2,700 urothelial bladder carcinomas in a tissue microarray (TMA) format. ResultsThe staining pattern of TROP2 and EpCAM were highly similar. For both proteins, the staining intensity gradually decreased from pTa G2 low grade (TROP2: 68.8±36.1; EpCAM: 21.5±11.7) to pTa G2 high grade (64.6±38.0; 19.3±12.2) and pTa G3 (52.1±38.7; 16.0±13.0, p

ObjectiveMicro-ultrasound is an imaging modality used to visualize and target prostate cancer during transrectal or transperineal biopsy. We evaluated the effectiveness of a micro-ultrasound training program and estimated the learning curve for prostate biopsy. MethodsA training program registry was assessed for the rate of clinically significant prostate cancer (csPCa, grade group ≥ 2), negative predictive value, and specificity at each stage of the program. Nine metrics of biopsy quality were evaluated in 4 stages for each practitioner. Non-linear fitting and logistic regression models were used to evaluate the time-course of these metrics over training. ResultsThirteen practitioners from 8 institutions completed stages 1 to 3 of the program, and 9 completed all 4 stages. Over 1190 micro-ultrasound biopsy procedures were performed. Detection of csPCa increased from 40% to 57% from stage 1 to stage 4 (P < 0.01). Stage 4 “expert” level was independently associated with higher detection of csPCa when correcting for overall risk factors (OR 1.95; P = 0.03). Limitations include the retrospective analysis and variation in biopsy protocols. ConclusionThe micro-ultrasound training program was effective in improving biopsy quality and rate of csPCa detection. The presented learning curve provides an initial guide for acquiring expertise with real-time micro-ultrasound image-guided biopsy.