Abstract
The accurate diagnosis of papillary urothelial carcinoma (PUC) is frequently challenging due to benign mimickers. Other than morphology-based diagnostic criteria, reliable biomarkers for differentiating benign and malignant papillary urothelial neoplasms remain elusive, so we sought to discover new markers to address this challenge. We first performed tandem mass spectrometry-based quantitative proteomics using diverse papillary urothelial lesions, including PUC, urothelial papilloma (UP), inverted urothelial papilloma, and cystitis cystica. We prioritized potential diagnostic biomarkers using machine learning, and subsequently validated through immunohistochemistry (IHC) in two independent cohorts. Metabolism, transport, cell cycle, development, and immune response functions were differentially enriched between malignant and benign papillary neoplasms. RhoB and NT5DC2 were shortlisted as optimal candidate markers for PUC diagnosis. In our pilot study using IHC, NT5DC2 was subsequently selected as its expression consistently differed in PUC (p = 0.007). Further validation of NT5DC2 using 49 low-grade (LG) urothelial lesions, including 15 LG-PUCs and 17 UPs, which are the most common mimickers, concordantly revealed lower IHC expression levels in LG-PUC (p = 0.0298). Independent external validation with eight LG-PUCs and eight UPs confirmed the significant downregulation of NT5DC2 in LG-PUC (p = 0.0104). We suggest that NT5DC2 is a potential IHC biomarker for differentiating LG-PUC from its benign mimickers, especially UP.
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