Ahn Jae-Hak, Kang Chan-Koo, Kim Eun-Mee, Kim Ah-Ram, Kim Aram
Department of Urology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul 05030, Korea.
Department of Advanced Convergence, Handong Global University, Pohang 37554, Gyeongbuk, Korea.
Life (Basel). 2022 Mar 9;12(3):395. doi: 10.3390/life12030395.
Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.
膀胱癌是男性中第四大常见癌症,且大多数病例为非肌层浸润性。高复发率是非肌层浸润性膀胱癌的一个关键问题。可用的尿液检测方法较少,这阻碍了对浅表性和小膀胱肿瘤的有效检测。膀胱镜检查是诊断的金标准;然而,它与尿路感染、血尿和疼痛有关。由于干预会影响复发,早期检测至关重要。因此,需要开发尿液生物标志物来检测这些膀胱癌。最近,尿液中的几种蛋白质候选物已被鉴定为生物标志物。在本叙述性综述中,总结了尿液蛋白质生物标志物(包括美国食品药品监督管理局批准的生物标志物)的开发现状。此外,还报道了当代蛋白质组学技术,如基于抗体的方法、基于质谱的方法和基于机器学习的诊断。此外,还介绍了尿液中膀胱癌潜在生物标志物快速、准确分析的新策略及其局限性。本综述强调了尿液蛋白质生物标志物的优势以及几种相关技术的发展。此外,还提供了对非肌层膀胱癌监测的研究和临床应用中的科学背景和可用方案的深入理解。