The Feasibility and Diagnostic Adequacy of PD-L1 Expression Analysis Using the Cytoinclusion Technique in Bladder Cancer: A Prospective Single-Center Study

细胞包涵体技术在膀胱癌中应用PD-L1表达分析的可行性及诊断效能:一项前瞻性单中心研究

阅读:3

Abstract

Background: Programmed death-ligand 1 (PD-L1) expression has been recognized as a potential biomarker for various cancers, yet its diagnostic and prognostic significance in urothelial bladder cancer (BCa) requires further investigation. Methods: In this prospective single-center study, we aimed to assess the feasibility and diagnostic adequacy of PD-L1 expression analysis using cytoinclusion in BCa patients. We enrolled consecutive patients undergoing endoscopic transurethral resection of bladder tumor (TURBT), repeat TURBT, or robot-assisted radical cystectomy. Urinary and tissue specimens were collected from these patients for cytoinclusion and histopathological analysis to evaluate PD-L1 expression. Results: Out of 29 patients, PD-L1 expression was detected from cytoinclusion in 42.8% (3 out of 7), 10% (1 out of 10), and 66.8% (8 out of 12) of patients with negative/papilloma, low-grade, and high-grade tumors, respectively. Conversely, histopathological analysis identified PD-L1 expression in 57.2% (4 out of 7), 30% (3 out of 10), and 83.3% (10 out of 12) of patients with negative/papilloma, low-grade, and high-grade tumors, respectively. The diagnostic concordance between cytoinclusion and histopathology was 85.7%, 80%, and 83.3% in patients with negative/papilloma, low-grade, and high-grade tumors, respectively. Conclusions: Our study underscores the promise of cytoinclusion as a minimally invasive method for quantifying urinary PD-L1 percentages. This approach could serve as both a potential prognostic and diagnostic indicator, easily obtainable from urine samples. Standardizing this technique could facilitate its widespread use as a valuable tool.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。