Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.

<h4>Background</h4>Papillary renal cell carcinoma (PRCC) is the most common type of renal cell carcinoma after clear cell renal cell carcinoma (ccRCC). Its pathological classification is controversial, and its molecular mechanism is poorly understood. Therefore, the identification of key...

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Autores principales:	Yingying Xu, Deyang Kong, Zhongtang Li, Lingling Qian, Junchao Li, Chunbo Zou
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6899ed3102614105ba22795c4ed190f1
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spelling	oai:doaj.org-article:6899ed3102614105ba22795c4ed190f12021-12-02T20:18:34ZScreening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.1932-620310.1371/journal.pone.0254868https://doaj.org/article/6899ed3102614105ba22795c4ed190f12021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254868https://doaj.org/toc/1932-6203<h4>Background</h4>Papillary renal cell carcinoma (PRCC) is the most common type of renal cell carcinoma after clear cell renal cell carcinoma (ccRCC). Its pathological classification is controversial, and its molecular mechanism is poorly understood. Therefore, the identification of key genes and their biological pathways is of great significance to elucidate the molecular mechanisms of PRCC occurrence and progression.<h4>Methods</h4>The PRCC-related datasets GSE7023, GSE48352 and GSE15641 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and gene ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Cytoscape and STRING were used to construct the protein-protein interaction network (PPI) and perform module analysis to identify hub genes and key pathways. A heatmap of hub genes was constructed using the UCSC cancer genomics browser. Overall survival and recurrence-free survival of patients stratified by the expression levels of hub genes were analysed using Kaplan-Meier Plotter. The online database UALCAN was applied to analyse gene expression based on tissue type, stage, subtype and race.<h4>Results</h4>A total of 214 DEGs, specifically, 205 downregulated genes and 9 upregulated genes, were identified. The DEGs were mainly enriched in angiogenesis, kidney development, oxidation-reduction process, metabolic pathways, etc. The 17 hub genes identified were mainly enriched in the biological processes of angiogenesis, cell adhesion, platelet degranulation, and leukocyte transendothelial migration. Survival analysis showed that EGF, KDR, CXCL12, REN, PECAM1, CDH5, THY1, WT1, PLAU and DCN might be related to the carcinogenesis, metastasis or recurrence of PRCC. UALCAN analysis showed that low expression of PECAM1 and PLAU in PRCC tissues was related to stage, subtype and race.<h4>Conclusions</h4>The DEGs and hub genes identified in the present study provide insight into the specific molecular mechanisms of PRCC occurrence and development and may be potential molecular markers and therapeutic targets for the accurate classification and efficient diagnosis and treatment of PRCC.Yingying XuDeyang KongZhongtang LiLingling QianJunchao LiChunbo ZouPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0254868 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yingying Xu Deyang Kong Zhongtang Li Lingling Qian Junchao Li Chunbo Zou Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
description	<h4>Background</h4>Papillary renal cell carcinoma (PRCC) is the most common type of renal cell carcinoma after clear cell renal cell carcinoma (ccRCC). Its pathological classification is controversial, and its molecular mechanism is poorly understood. Therefore, the identification of key genes and their biological pathways is of great significance to elucidate the molecular mechanisms of PRCC occurrence and progression.<h4>Methods</h4>The PRCC-related datasets GSE7023, GSE48352 and GSE15641 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and gene ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Cytoscape and STRING were used to construct the protein-protein interaction network (PPI) and perform module analysis to identify hub genes and key pathways. A heatmap of hub genes was constructed using the UCSC cancer genomics browser. Overall survival and recurrence-free survival of patients stratified by the expression levels of hub genes were analysed using Kaplan-Meier Plotter. The online database UALCAN was applied to analyse gene expression based on tissue type, stage, subtype and race.<h4>Results</h4>A total of 214 DEGs, specifically, 205 downregulated genes and 9 upregulated genes, were identified. The DEGs were mainly enriched in angiogenesis, kidney development, oxidation-reduction process, metabolic pathways, etc. The 17 hub genes identified were mainly enriched in the biological processes of angiogenesis, cell adhesion, platelet degranulation, and leukocyte transendothelial migration. Survival analysis showed that EGF, KDR, CXCL12, REN, PECAM1, CDH5, THY1, WT1, PLAU and DCN might be related to the carcinogenesis, metastasis or recurrence of PRCC. UALCAN analysis showed that low expression of PECAM1 and PLAU in PRCC tissues was related to stage, subtype and race.<h4>Conclusions</h4>The DEGs and hub genes identified in the present study provide insight into the specific molecular mechanisms of PRCC occurrence and development and may be potential molecular markers and therapeutic targets for the accurate classification and efficient diagnosis and treatment of PRCC.
format	article
author	Yingying Xu Deyang Kong Zhongtang Li Lingling Qian Junchao Li Chunbo Zou
author_facet	Yingying Xu Deyang Kong Zhongtang Li Lingling Qian Junchao Li Chunbo Zou
author_sort	Yingying Xu
title	Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
title_short	Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
title_full	Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
title_fullStr	Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
title_full_unstemmed	Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
title_sort	screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/6899ed3102614105ba22795c4ed190f1
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_version_	1718374288224944128

Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.

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