Urine‐based liquid biopsy in bladder cancer: Opportunities and challenges

Abstract

Bladder cancer (BLCA) is a most common urological tumours with high rate of recurrence, which needs long‐term of follow‐up. To date, diagnosis and surveillance of BLCA still rely on cystoscopy, an invasive and expensive method that increases the difficulty for routine follow‐up. Therefore, exploring new biomarkers or tests is an effective way to improve the current clinical management of BLCA. Recent years, liquid biopsy has received increasing attention, especially for its great potential for clinical application in the non‐invasive detection of tumours. In addition, liquid biopsy involves a wide range of biomarkers, including DNA, RNA, proteins, extracellular vesicles and metabolites in blood, urine or other body fluids. For BLCA, urine is a most ideal body fluid to achieve non‐invasive diagnosis and surveillance. Here, we address recent developments of urine‐based biomarkers or tests for clinical diagnostic challenges in BLCA, such as early detection, minimal residual, recurrence monitoring and therapeutic response. Meanwhile, the many challenges of urine biomarkers that need to be overcome are also discussed.

Examining Longitudinal Markers of Bladder Cancer Recurrence Through a Semi-Autonomous Machine Learning System for Quantifying Specimen Atypia from Urine Cytology

“…The results of this study highlight the need for further research comparing the performance of the AutoParis-X system with other non-invasive methods for assessing the potential for bladder cancer recurrence. Many promising approaches make use of various molecular assays developed for liquid biopsies, and several screening programs have also been developed that use a combination of different assays to assess the potential for recurrence [107][108][109][110][111][112][113][114] . These should be considered for comparison when attempting to roll out potential screening systems/guidelines.…”

Examining longitudinal markers of bladder cancer recurrence through a semiautonomous machine learning system for quantifying specimen atypia from urine cytology

“…The results of this study highlight the need for further research comparing the performance of the AutoParis‐X system with other noninvasive methods for assessing the potential for bladder cancer recurrence. Many promising approaches make use of various molecular assays developed for liquid biopsies, and several screening programs have also been developed that use a combination of different assays to assess the potential for recurrence 108–115 . For instance, the UroVysion assay has been previously compared with traditional and quantitative cytology for the surveillance of nonmuscle‐invasive bladder cancer and recurrence risk.…”