Dataset Information

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.

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.

SUBMITTER: Jung M

PROVIDER: S-EPMC8987228 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

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.

Jung Minsun M Lee Cheol C Han Dohyun D Kim Kwangsoo K Yang Sunah S Nikas Ilias P IP Moon Kyung Chul KC Kim Hyeyoon H Song Min Ji MJ Kim Bohyun B Lee Hyebin H Ryu Han Suk HS

Frontiers in oncology 20220324

<h4>Background</h4>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.<h4>Methods</h4>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, a ...[more]

PMID: 35402263

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Project description:There have been a few case reports and one small series of low grade papillary sinonasal (Schneiderian) carcinomas (LGPSC) which mimic papillomas but have overtly invasive growth and which occasionally metastasize. We describe the morphologic, clinical, immunohistochemical, and molecular features of five patients with LGPSC compared with eight cases each of inverted papilloma (IP) and conventional nonkeratinizing squamous cell carcinoma (SCC) with papillary growth. All LGPSC were nested with predominantly pushing invasion, no stromal reaction, and frequent surface papillary growth. All consisted of one cell type only, with polygonal cells with round nuclei, no (or limited) cytologic atypia, low mitotic activity, and prominent neutrophilic infiltrate. One patient had slightly more infiltrative bone invasion, another lymphovascular, perineural, and skeletal muscle invasion, and a third nodal metastasis after 17 years. By comparison, IPs had bland cytology, neutrophilic microabscesses, mixed immature squamous, goblet cell, and respiratory epithelium, and extremely low mitotic activity. Nonkeratinizing SCCs had basaloid-appearing cells with nuclear pleomorphism, brisk mitotic activity, and apoptosis. All LGPSC were p63 positive. Mitotic activity and Ki67 indices were significantly higher for LGPSCs than IPs and significantly lower than NKSCCs, while p53 immunohistochemistry in LGPSC was identical to nonkeratinizing SCC and higher than for IP. Sequencing showed all five tumors to harbor a MUC6 mutation, one tumor to harbor CDKN2A and PIK3R1 mutations, and one tumor to harbor a NOTCH1 mutation. All LGPSC lacked EGFR and KRAS mutations and lacked copy number variations of any main cancer genes. At a median follow up of 12 months, two LGPSC recurred locally, and one patient died after massive local recurrences and nodal metastases. LGPSC is a distinct, de novo sinonasal carcinoma that can be differentiated from papillomas by morphology and selected immunohistochemistry.

Dataset Information

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.

Background

Methods

Results

Conclusion

Publications

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.

Similar Datasets

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