Journal
FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.841398
Keywords
inverted urothelial papilloma; papillary urothelial carcinoma; transitional cell carcinoma (TCC); tandem mass spectrometry (MS; MS); machine learning analysis; immunohistochemistry; biomarkers; differential diagnosis
Categories
Funding
- National Research Foundation of Korea (NRF) - Ministry of Science, ICT and Future Planning [NRF-2019R1C1C1006640, 2021R1F1A1063982, 2021R1A2C4086635, 2022R1A2C4001439]
- National Research Foundation of Korea [2022R1A2C4001439, 2021R1A2C4086635, 2021R1F1A1063982] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Proteomic analysis revealed distinct 'NU-like' and 'PUC-like' signatures in IUP, with SERPINH1, PKP2, and PYGB identified as potential diagnostic biomarkers. Immunohistochemical validation confirmed PYGB as a specific biomarker to distinguish between IUP and PUC with inverted growth, suggesting its promising role in routine practice for IUP diagnosis.
BackgroundThe molecular biology of inverted urothelial papilloma (IUP) as a precursor disease of urothelial carcinoma is poorly understood. Furthermore, the overlapping histology between IUP and papillary urothelial carcinoma (PUC) with inverted growth is a diagnostic pitfall leading to frequent misdiagnoses. MethodsTo identify the oncologic significance of IUP and discover a novel biomarker for its diagnosis, we employed mass spectrometry-based proteomic analysis of IUP, PUC, and normal urothelium (NU). Machine learning analysis shortlisted candidate proteins, while subsequent immunohistochemical validation was performed in an independent sample cohort. ResultsFrom the overall proteomic landscape, we found divergent 'NU-like' (low-risk) and 'PUC-like' (high-risk) signatures in IUP. The latter were characterized by altered metabolism, biosynthesis, and cell-cell interaction functions, indicating oncologic significance. Further machine learning-based analysis revealed SERPINH1, PKP2, and PYGB as potential diagnostic biomarkers discriminating IUP from PUC. The immunohistochemical validation confirmed PYGB as a specific biomarker to distinguish between IUP and PUC with inverted growth. ConclusionIn conclusion, we suggest PYGB as a promising immunohistochemical marker for IUP diagnosis in routine practice.
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