Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualiz...

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Autores principales:	Congcong Wang, Jianping Guo, Xiaoyang Zhao, Jia Jia, Wenting Xu, Peng Wan, Changgang Sun
Formato:	article
Lenguaje:	EN
Publicado:	Tehran University of Medical Sciences 2021
Materias:	Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade
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spelling	oai:doaj.org-article:0b9b46cdf264433ab07087a497e9eade2021-12-02T17:09:48ZIdentification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis2251-60852251-6093https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade2021-10-01T00:00:00Zhttps://ijph.tums.ac.ir/index.php/ijph/article/view/24144https://doaj.org/toc/2251-6085https://doaj.org/toc/2251-6093 Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by CytoHubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA. Results: Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1. Conclusion: we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection. Congcong WangJianping GuoXiaoyang ZhaoJia JiaWenting XuPeng WanChanggang SunTehran University of Medical SciencesarticleBioinformatics analysisDifferently expressed genesHub genesPancreatic ductal adenocarcinomaPublic aspects of medicineRA1-1270ENIranian Journal of Public Health, Vol 50, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine RA1-1270
spellingShingle	Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine RA1-1270 Congcong Wang Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
description	Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by CytoHubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA. Results: Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1. Conclusion: we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.
format	article
author	Congcong Wang Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun
author_facet	Congcong Wang Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun
author_sort	Congcong Wang
title	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
title_short	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
title_full	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
title_fullStr	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
title_full_unstemmed	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
title_sort	identification of hub genes in pancreatic ductal adenocarci-noma using bioinformatics analysis
publisher	Tehran University of Medical Sciences
publishDate	2021
url	https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade
work_keys_str_mv	AT congcongwang identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT jianpingguo identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT xiaoyangzhao identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT jiajia identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT wentingxu identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT pengwan identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis AT changgangsun identificationofhubgenesinpancreaticductaladenocarcinomausingbioinformaticsanalysis
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Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

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