Cited 5 times in
Proteomic-Based Machine Learning Analysis Reveals PYGB as a Novel Immunohistochemical Biomarker to Distinguish Inverted Urothelial Papilloma From Low-Grade Papillary Urothelial Carcinoma With Inverted Growth
DC Field | Value | Language |
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dc.contributor.author | 정민선 | - |
dc.date.accessioned | 2022-07-08T03:06:59Z | - |
dc.date.available | 2022-07-08T03:06:59Z | - |
dc.date.issued | 2022-03 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/188672 | - |
dc.description.abstract | Background: The 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. Methods: To 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. Results: From 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. Conclusion: In conclusion, we suggest PYGB as a promising immunohistochemical marker for IUP diagnosis in routine practice. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Frontiers Research Foundation | - |
dc.relation.isPartOf | FRONTIERS IN ONCOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Proteomic-Based Machine Learning Analysis Reveals PYGB as a Novel Immunohistochemical Biomarker to Distinguish Inverted Urothelial Papilloma From Low-Grade Papillary Urothelial Carcinoma With Inverted Growth | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Pathology (병리학교실) | - |
dc.contributor.googleauthor | Minsun Jung | - |
dc.contributor.googleauthor | Cheol Lee | - |
dc.contributor.googleauthor | Dohyun Han | - |
dc.contributor.googleauthor | Kwangsoo Kim | - |
dc.contributor.googleauthor | Sunah Yang | - |
dc.contributor.googleauthor | Ilias P Nikas | - |
dc.contributor.googleauthor | Kyung Chul Moon | - |
dc.contributor.googleauthor | Hyeyoon Kim | - |
dc.contributor.googleauthor | Min Ji Song | - |
dc.contributor.googleauthor | Bohyun Kim | - |
dc.contributor.googleauthor | Hyebin Lee | - |
dc.contributor.googleauthor | Han Suk Ryu | - |
dc.identifier.doi | 10.3389/fonc.2022.841398 | - |
dc.contributor.localId | A06280 | - |
dc.relation.journalcode | J03512 | - |
dc.identifier.eissn | 2234-943X | - |
dc.identifier.pmid | 35402263 | - |
dc.subject.keyword | biomarkers | - |
dc.subject.keyword | differential diagnosis | - |
dc.subject.keyword | immunohistochemistry | - |
dc.subject.keyword | inverted urothelial papilloma | - |
dc.subject.keyword | machine learning analysis | - |
dc.subject.keyword | papillary urothelial carcinoma | - |
dc.subject.keyword | tandem mass spectrometry (MS/MS) | - |
dc.subject.keyword | transitional cell carcinoma (TCC) | - |
dc.contributor.alternativeName | Jung, Minsun | - |
dc.contributor.affiliatedAuthor | 정민선 | - |
dc.citation.volume | 12 | - |
dc.citation.startPage | 841398 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN ONCOLOGY, Vol.12 : 841398, 2022-03 | - |
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