Targeted-sequence of normal urothelium and tumor of patients with non-muscle invasive bladder cancer

Next-generation sequencing has diagnostic utility in challenging small/flat urothelial lesions

Small/flat urothelial lesions are challenging and currently available ancillary immunohistochemistry testing often cannot reliably distinguish between reactive lesions and urothelial carcinoma (UCa). UCa has a characteristic molecular profile, but small/flat urothelial lesions are typically considered too small to perform next generation sequencing (NGS). Herein, we present our institution's experience with utilizing comprehensive DNA-based NGS to evaluate small/flat urothelial lesions (n = 13 cases). NGS was ordered on 7/13 small/flat urothelial lesions initially diagnosed as urothelial atypia, ordered by the pathologist to aid in further diagnosis; the remaining 6/13 cases were diagnosed as urothelial carcinoma in situ (uCIS), ordered by a treating oncologist. The test was considered as adding value if it yielded pathogenic or likely pathogenic alterations previously associated with urothelial carcinoma in the literature. Macroscopic dissection was determined necessary in all cases and obtained either by scraping (7), punch biopsy (5) or scooping (1) of paraffin tissue blocks. In 4/13 cases, tumor content was considered low (<25%); in 2/13 cases, DNA quantity yield was considered below optimal (<250 ng); all cases met required DNA quantity for testing (>50 ng). Mean target coverage ranged: 498 to 985 (optimal >500 reads). NGS testing identified mutations compatible with urothelial carcinoma in all 7 cases initially diagnosed as atypical; and in one case, the tumor recurred as a lung metastasis. All 6 uCIS had NGS testing results concordant with UCa. In conclusion, despite small sample quantity with low tumor content and DNA concentration yield, NGS testing with appropriate methodology can be considered in the setting of small/flat urothelial lesions to aid in diagnosis or per oncologist request and yield interpretable results.

From Detection to Cure - Emerging Roles for Urinary Tumor DNA (utDNA) in Bladder Cancer

PURPOSE OF REVIEW

This review sought to define the emerging roles of urinary tumor DNA (utDNA) for diagnosis, monitoring, and treatment of bladder cancer. Building from early landmark studies the focus is on recent studies, highlighting how utDNA could aid personalized care.

RECENT FINDINGS

Recent research underscores the potential for utDNA to be the premiere biomarker in bladder cancer due to the constant interface between urine and tumor. Many studies find utDNA to be more informative than other biomarkers in bladder cancer, especially in early stages of disease. Points of emphasis include superior sensitivity over traditional urine cytology, broad genomic and epigenetic insights, and the potential for non-invasive, real-time analysis of tumor biology. utDNA shows promise for improving all phases of bladder cancer care, paving the way for personalized treatment strategies. Building from current research, future comprehensive clinical trials will validate utDNA's clinical utility, potentially revolutionizing bladder cancer management.

Mutation Hotspots Found in Bladder Cancer Aid Prediction of Carcinogenic Risk in Normal Urothelium

More than 80,000 new cases of bladder cancer are estimated to be diagnosed in 2023. However, the 5-year survival rate for bladder cancer has not changed in decades, highlighting the need for prevention. Numerous cancer-causing mutations are present in the urothelium long before signs of cancer arise. Mutation hotspots in cancer-driving genes were identified in non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) tumor samples. Mutation burden within the hotspot regions was measured in normal urothelium with a low and high risk of cancer. A significant correlation was found between the mutation burden in normal urothelium and bladder cancer tissue within the hotspot regions. A combination of measured hotspot burden and personal risk factors was used to fit machine learning classification models. The efficacy of each model to differentiate between adjacent benign urothelium from bladder cancer patients and normal urothelium from healthy donors was measured. A random forest model using a combination of personal risk factors and mutations within MIBC hotspots yielded the highest AUC of 0.9286 for the prediction of high- vs. low-risk normal urothelium. Currently, there are no effective biomarkers to assess subclinical field disease and early carcinogenic progression in the bladder. Our findings demonstrate novel differences in mutation hotspots in NMIBC and MIBC and provide the first evidence for mutation hotspots to aid in the assessment of cancer risk in the normal urothelium. Early risk assessment and identification of patients at high risk of bladder cancer before the clinical presentation of the disease can pave the way for targeted personalized preventative therapy.