Within the last forty years, seminal contributions have been made in the areas of bladder cancer (BC) biology, driver genes, molecular profiling, biomarkers, and therapeutic targets for improving personalized patient care. This overview includes seminal discoveries and advances in the molecular oncology of BC. Starting with the concept of divergent molecular pathways for the development of low- and high-grade bladder tumors, field cancerization versus clonality of bladder tumors, cancer driver genes/mutations, genetic polymorphisms, and bacillus Calmette-Guérin (BCG) as an early form of immunotherapy are some of the conceptual contributions towards improving patient care. Although beginning with a promise of predicting prognosis and individualizing treatments, “-omic” approaches and molecular subtypes have revealed the importance of BC stem cells, lineage plasticity, and intra-tumor heterogeneity as the next frontiers for realizing individualized patient care. Along with urine as the optimal non-invasive liquid biopsy, BC is at the forefront of the biomarker field. If the goal is to reduce the number of cystoscopies but not to replace them for monitoring recurrence and asymptomatic microscopic hematuria, a BC marker may reach clinical acceptance. As advances in the molecular oncology of BC continue, the next twenty-five years should significantly advance personalized care for BC patients.

Purpose: Poor prognosis of patients with muscle-invasive bladder cancer that often metastasizes drives the need for discovery of molecular determinants of bladder cancer progression. Chondroitin sulfate proteoglycans, including CD44, regulate cancer progression; however, the identity of a chondroitinase (Chase) that cleaves chondroitin sulfate from proteoglycans is unknown. HYAL-4 is an understudied gene suspected to encode a Chase, with no known biological function. We evaluated HYAL-4 expression and its role in bladder cancer. Experimental Design: In clinical specimens, HYAL-4 wild-type (Wt) and V1 expression was evaluated by RT-qPCR, IHC, and/or immunoblotting; a novel assay measured Chase activity. Wt and V1 were stably expressed or silenced in normal urothelial and three bladder cancer cell lines. Transfectants were analyzed for stem cell phenotype, invasive signature and tumorigenesis, and metastasis in four xenograft models, including orthotopic bladder. Results: HYAL-4 expression, specifically a novel splice variant (V1), was elevated in bladder tumors; Wt expression was barely detectable. V1 encoded a truncated 349 amino acid protein that was secreted. In bladder cancer tissues, V1 levels associated with metastasis and cancer-specific survival with high efficacy and encoded Chase activity. V1 cleaved chondroitin-6-sulfate from CD44, increasing CD44 secretion. V1 induced stem cell phenotype, motility/invasion, and an invasive signature. CD44 knockdown abrogated these phenotypes. V1-expressing urothelial cells developed angiogenic, muscle-invasive tumors. V1-expressing bladder cancer cells formed tumors at low density and formed metastatic bladder tumors when implanted orthotopically. Conclusions: Our study discovered the first naturally-occurring eukaryotic/human Chase and connected it to disease pathology, specifically cancer. V1-Chase is a driver of malignant bladder cancer and potential predictor of outcome in patients with bladder cancer.

Background/Objectives: Multiparametric MRI (mpMRI) is widely established as the standard imaging modality for detecting clinically significant prostate cancer (csPCa), yet it can be limited by cost, accessibility, and the need for specialized radiologist interpretation. Micro-ultrasound (micro-US) has recently emerged as a more accessible alternative imaging modality. This review evaluates whether the evidence base for micro-US meets thresholds comparable to those that led to MRI’s guideline adoption, synthesizes diagnostic performance data compared to mpMRI, and outlines future research priorities to define its clinical role. Methods: A targeted literature review of PubMed, Embase, and the Cochrane Library was conducted for studies published between 2014 and May 2025 evaluating micro-US in csPCa detection. Search terms included “micro-ultrasound,” “ExactVu,” “PRI-MUS,” and related terminology. Study relevance was assessed independently by the authors. Extracted data included csPCa detection rates, modality concordance, and diagnostic accuracy, and were synthesized and, rarely, restructured to facilitate study comparisons. Results: Micro-US consistently demonstrated non-inferiority to mpMRI for csPCa detection across retrospective studies, prospective cohorts, and meta-analyses. Several studies reported discordant csPCa lesions detected by only one modality, highlighting potential complementarity. The recently published OPTIMUM randomized controlled trial offers the strongest individual-trial evidence to date in support of micro-US non-inferiority. Conclusions: Micro-US shows potential as an alternative or adjunct to mpMRI for csPCa detection. However, additional robust multicenter studies are needed to achieve the evidentiary strength that led mpMRI to distinguish itself in clinical guidelines.

Context (Background): Analysis of embryos for in vitro fertilization (IVF) involves manual grading of human embryos through light microscopy. Recent research shows that artificial intelligence techniques applied to time lapse embryo images can successfully ascertain embryo quality. However, laboratories often capture static images and cannot apply this research in a real-world setting. Further, current models do not predict the outcome of pregnancy. Aims: To create and assess a convolutional neural network to predict embryo quality using static images from a limited dataset. We considered two classification problems: predicting whether an embryo will lead to a pregnancy or not and predicting the outcome of that pregnancy. Settings and Design: We utilized transfer learning techniques using a pretrained Inception V1 network. All models were built using the Tensorflow software package. Methods: We utilized a total of 361 randomly sampled static images collected from four South Florida IVF clinics. Data were collected between 2016 and 2019. Statistical Analysis Used: We utilized deep-learning techniques, including data augmentation to reduce model variance and transfer learning to bolster our limited dataset. We used a standard train/validation/ test dataset split to avoid model overfitting. Results: Our algorithm achieved 0.657 area under the curve for predicting pregnancy versus nonpregnancy. However, our model was unable to meaningfully predict whether a pregnancy led a to live birth. Conclusions: Despite the limited dataset that achieved somewhat of a lower accuracy than conventional embryo selection, this is the first study that has successfully made IVF predictions from static images alone. Future availability of more data may allow for prospective validation and further generalisability of results.

BACKGROUND: Female authorship opportunities have lagged behind those of their male counterparts, with gender disparities most prominent in surgical specialties. Our objective was to determine trends of female first, last, and first or last authorships across time and surgical specialties and whether female first or last authorship was associated with journal impact factor. STUDY DESIGN: A systematic review of EMBASE (OvidSP), MEDLINE (OvidSP), and Cochrane (Wiley) databases from inception to December 22, 2017 was performed to identify all randomized controlled trials evaluating minimally invasive surgery vs classical surgical techniques. The primary end point was female first, last, and first or last authorship, with gender determined via an online search strategy and verified via Genderize.io. Secondary end point was journal impact factor, recorded from Clarivate Analytics InCites. RESULTS: There were 9,321 articles identified and 489 met our inclusion/exclusion criteria. Sixty-eight (13.9%) first and 60 (12.3%) last female authors were identified. A positive linear trend for female first (R ² = 0.35, Cochran-Armitage test for trend, p < 0.001), last (R ² = 0.30, p < 0.001), and first or last authorships (R ² = 0.40, p < 0.001) over time was identified. This trend was observed across surgical specialties except for orthopaedics. The highest calculated percentages of female first, last, and first or last authorships by the year 2017 were seen in obstetrics and gynecology (33.8%, 32.0%, and 43.8%, respectively), all significantly lower than the corresponding percentage of the female obstetrics and gynecology workforce in 2017 (57.0%). Neither female first nor last authorship positions were associated with journal impact factor. CONCLUSIONS: A significant increase in female first and last authorship in randomized controlled trials of minimally invasive surgical techniques in the last 3 decades has been observed, but continued efforts to bridge this gender gap are sorely needed.