Joseph C. Liao

Introduction: Lateral extension (LE) in urinary bladder papillary urothelial carcinoma (PUC) refers to the phenomenon where atypical urothelium is seen extending laterally in a flat configuration from the base of the papillary tumour. LE is recognized but poorly defined, resulting in inconsistent diagnoses and interpretations amongst pathologists, ranging from atypia to carcinoma in situ (CIS). Herein, we aim to better characterize LE in high‐grade PUC, utilizing en bloc transurethral resection specimens. Methods: We reviewed 37 en bloc specimens from 25 patients and performed comprehensive morphological, molecular and immunohistochemical characterization of PUC and LE components. Results: Three morphological patterns were seen: no LE ( n = 24), LE with lower‐grade cytomorphology compared to adjacent PUC (lower‐grade LE, n = 10), and LE with cytomorphology similar to adjacent PUC (higher‐grade LE, n = 3). Mean LE length was 4.7 mm (range 1.5–10.8 mm). LE extended to mucosal margins in 12/13 (92%). Differential next‐generation sequencing was performed on paired PUC and adjacent LE components in 11/13 tumours with LE. In 9/11 (82%), LE and PUC showed at least a subset of shared pathogenic/likely pathogenic alterations, supporting clonality between the two components; in five tumours, there were additional alterations specific to PUC, with and without LE‐specific alterations. Immunohistochemical staining for CK20 and p53 showed LE with abnormal CK20 in all 11/11 tumours and aberrant p53 in 3/11 (27%). PUC and LE showed concordant p53 staining patterns in 10/11 (91%) and CK20 in only 6/11 (55%) specimens. Conclusion: We find that LE can extend at least 1 cm from the base of PUC, suggesting consideration for wider resection margins if complete surgical resection is desired. Additionally, LE is clonally related to PUC in most cases, albeit with heterogeneous relationships, as evidenced by both molecular and immunohistochemical findings. Notably, LE can show immunohistochemical findings similar to those commonly reported for CIS. Recognition of LE may improve diagnostic consistency and reduce overdiagnosis of CIS in the setting of prior papillary tumours.

Sepsis, a common consequence of bloodstream infection (BSI), is a leading cause of global mortality and morbidity. Diagnosis is challenging and slow due to extremely low pathogen loads and reliance on time-consuming blood culture, necessitating empiric therapy that worsens outcomes and antimicrobial resistance. Here, we introduce sedimentation-assisted tandem rocking and enrichment for analysis and monitoring (STREAM), a platform that efficiently isolates and enriches pathogens near their natural doubling times directly from whole blood. By integrating STREAM with single-cell analysis, we achieved rapid and robust diagnosis of BSI from whole-blood samples. Using molecularly barcoded sequential fluorescence in situ hybridization, pathogen identification in 104 positive blood culture samples showed 96.15% concordance with clinical laboratory results. Gel-based single-cell antimicrobial susceptibility testing yields 97.96% essential agreement and 93.9% categorical agreement across 219 drug-dose combinations. The platform enabled comprehensive BSI diagnosis directly from whole blood, achieving a detection limit as low as 0.1 to 1 CFU/ml and delivering full diagnostic results within 6.75 to 17 hours.

BACKGROUND. Current diagnosis and surveillance of bladder cancer relies on cystoscopy which is invasive and user dependent. The urine mRNA panel, uRNAp, measures expression of 3 genes for identification of bladder cancer. Here we report validation of uRNAp for patients undergoing initial work-up for suspected bladder cancer and surveillance for bladder cancer. METHODS. Urine specimens were prospectively collected prior to cystoscopy at two health care systems from patients without (detection cohort) or with (surveillance cohort) a history of bladder cancer. RNA was isolated from urine sediment for RT-qPCR to determine ROBO1, CRH, and IGF2 expression and calculate the uRNAp bladder cancer probability score. RESULTS. In the detection cohort, 547 samples were collected from 529 patients. There were 123 new diagnoses of bladder cancer in the detection cohort and uRNAp demonstrated 98% sensitivity and 51% specificity for identification of bladder cancer. In the surveillance cohort, 1543 samples were collected from 447 patients with 286 recurrences. uRNAp demonstrated 94% overall sensitivity with 43% specificity and 99% sensitivity for high-grade recurrence. The receiver operating characteristic area under the curve was 0.92 in the detection and 0.81 in the surveillance cohort. uRNAp scores significantly increased with tumor size and grade. CONCLUSIONS. Prospective validation of uRNAp demonstrated a strong potential clinical utility as a non-invasive adjunct to cystoscopy for management of bladder cancer. uRNAp may be a useful triage tool to defer or expedite cystoscopy for patients undergoing detection or surveillance of bladder cancer. FUNDING. Department of Veterans Affairs BLR&D Merit Review I01 BX004962 to JCL.

Cystoscopy is a common endoscopic procedure used for the visual inspection of the lower urinary tract, particularly for the detection and surveillance of bladder cancer. Artificial intelligence (AI) strategies could help address the recognized shortcomings of cystoscopy by identifying malignant and non-malignant regions of interest (ROIs) and providing real-time clinical decision support for biopsy and surgical resection. However, curating a dataset for training AI models is challenging and time-time consuming. We present CystoDS, a high-quality bladder imaging dataset derived from standard white light cystoscopy that is ready for AI applications for detection of bladder cancer and cancer-mimicking benign lesions. This dataset includes 8,067 images from 160 patients labelled with five classes and 22 subclasses, along with segmentation data for 768 of the images. We detail the methods used for image acquisition, the structure of the dataset, and our technical validation process to demonstrate the AI-readiness of the data.

The human immune system has evolved to interact with various commensal and pathogenic bacteria in intricate and nuanced ways. While the diversity of bacteria presents fundamental challenges in understanding immune-microbe interactions, it also offers ample opportunities for developing effective immunomodulatory therapies. Here we show microbial product cocktails as an alternative class of immunotherapy for cancer. Using freshly resected tumors from bladder cancer patients, an immuno-comparative analysis of recruitment and enhancement assay, and an artificial intelligence-guided optimization workflow, we establish a personalized platform for identifying potent microbial product cocktails that promote recruitment, infiltration, and activation of immune cells for cancer treatment. In an orthotopic mouse bladder cancer model, microbial product cocktails demonstrate immunoenhancement and improve survival rates compared with standard bacillus Calmette-Guérin immunotherapy.