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,Visualizat...
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Autor*in:	Congcong Wang [verfasserIn] Jianping Guo [verfasserIn] Xiaoyang Zhao [verfasserIn] Jia Jia [verfasserIn] Wenting Xu [verfasserIn] Peng Wan [verfasserIn] Changgang Sun [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma

Übergeordnetes Werk:	In: Iranian Journal of Public Health - Tehran University of Medical Sciences, 2020, 50(2021), 11
Übergeordnetes Werk:	volume:50 ; year:2021 ; number:11

Links:	Link aufrufen Link aufrufen Journal toc Journal toc

Katalog-ID:	DOAJ065357779

Internformat


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520			\|a 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.
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allfields	(DE-627)DOAJ065357779 (DE-599)DOAJ0b9b46cdf264433ab07087a497e9eade DE-627 ger DE-627 rakwb eng RA1-1270 Congcong Wang verfasserin aut Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine Jianping Guo verfasserin aut Xiaoyang Zhao verfasserin aut Jia Jia verfasserin aut Wenting Xu verfasserin aut Peng Wan verfasserin aut Changgang Sun verfasserin aut In Iranian Journal of Public Health Tehran University of Medical Sciences, 2020 50(2021), 11 (DE-627)514237600 (DE-600)2240935-X 22516093 nnns volume:50 year:2021 number:11 https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade kostenfrei https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 kostenfrei https://doaj.org/toc/2251-6085 Journal toc kostenfrei https://doaj.org/toc/2251-6093 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 50 2021 11
spelling	(DE-627)DOAJ065357779 (DE-599)DOAJ0b9b46cdf264433ab07087a497e9eade DE-627 ger DE-627 rakwb eng RA1-1270 Congcong Wang verfasserin aut Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine Jianping Guo verfasserin aut Xiaoyang Zhao verfasserin aut Jia Jia verfasserin aut Wenting Xu verfasserin aut Peng Wan verfasserin aut Changgang Sun verfasserin aut In Iranian Journal of Public Health Tehran University of Medical Sciences, 2020 50(2021), 11 (DE-627)514237600 (DE-600)2240935-X 22516093 nnns volume:50 year:2021 number:11 https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade kostenfrei https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 kostenfrei https://doaj.org/toc/2251-6085 Journal toc kostenfrei https://doaj.org/toc/2251-6093 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 50 2021 11
allfields_unstemmed	(DE-627)DOAJ065357779 (DE-599)DOAJ0b9b46cdf264433ab07087a497e9eade DE-627 ger DE-627 rakwb eng RA1-1270 Congcong Wang verfasserin aut Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine Jianping Guo verfasserin aut Xiaoyang Zhao verfasserin aut Jia Jia verfasserin aut Wenting Xu verfasserin aut Peng Wan verfasserin aut Changgang Sun verfasserin aut In Iranian Journal of Public Health Tehran University of Medical Sciences, 2020 50(2021), 11 (DE-627)514237600 (DE-600)2240935-X 22516093 nnns volume:50 year:2021 number:11 https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade kostenfrei https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 kostenfrei https://doaj.org/toc/2251-6085 Journal toc kostenfrei https://doaj.org/toc/2251-6093 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 50 2021 11
allfieldsGer	(DE-627)DOAJ065357779 (DE-599)DOAJ0b9b46cdf264433ab07087a497e9eade DE-627 ger DE-627 rakwb eng RA1-1270 Congcong Wang verfasserin aut Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine Jianping Guo verfasserin aut Xiaoyang Zhao verfasserin aut Jia Jia verfasserin aut Wenting Xu verfasserin aut Peng Wan verfasserin aut Changgang Sun verfasserin aut In Iranian Journal of Public Health Tehran University of Medical Sciences, 2020 50(2021), 11 (DE-627)514237600 (DE-600)2240935-X 22516093 nnns volume:50 year:2021 number:11 https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade kostenfrei https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 kostenfrei https://doaj.org/toc/2251-6085 Journal toc kostenfrei https://doaj.org/toc/2251-6093 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 50 2021 11
allfieldsSound	(DE-627)DOAJ065357779 (DE-599)DOAJ0b9b46cdf264433ab07087a497e9eade DE-627 ger DE-627 rakwb eng RA1-1270 Congcong Wang verfasserin aut Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine Jianping Guo verfasserin aut Xiaoyang Zhao verfasserin aut Jia Jia verfasserin aut Wenting Xu verfasserin aut Peng Wan verfasserin aut Changgang Sun verfasserin aut In Iranian Journal of Public Health Tehran University of Medical Sciences, 2020 50(2021), 11 (DE-627)514237600 (DE-600)2240935-X 22516093 nnns volume:50 year:2021 number:11 https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade kostenfrei https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 kostenfrei https://doaj.org/toc/2251-6085 Journal toc kostenfrei https://doaj.org/toc/2251-6093 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 50 2021 11
language	English
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topic_facet	Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma Public aspects of medicine
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container_title	Iranian Journal of Public Health
authorswithroles_txt_mv	Congcong Wang @@aut@@ Jianping Guo @@aut@@ Xiaoyang Zhao @@aut@@ Jia Jia @@aut@@ Wenting Xu @@aut@@ Peng Wan @@aut@@ Changgang Sun @@aut@@
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callnumber-first	R - Medicine
author	Congcong Wang
spellingShingle	Congcong Wang misc RA1-1270 misc Bioinformatics analysis misc Differently expressed genes misc Hub genes misc Pancreatic ductal adenocarcinoma misc Public aspects of medicine Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
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topic_title	RA1-1270 Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis Bioinformatics analysis Differently expressed genes Hub genes Pancreatic ductal adenocarcinoma
topic	misc RA1-1270 misc Bioinformatics analysis misc Differently expressed genes misc Hub genes misc Pancreatic ductal adenocarcinoma misc Public aspects of medicine
topic_unstemmed	misc RA1-1270 misc Bioinformatics analysis misc Differently expressed genes misc Hub genes misc Pancreatic ductal adenocarcinoma misc Public aspects of medicine
topic_browse	misc RA1-1270 misc Bioinformatics analysis misc Differently expressed genes misc Hub genes misc Pancreatic ductal adenocarcinoma misc Public aspects of medicine
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title	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
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title_full	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
author_sort	Congcong Wang
journal	Iranian Journal of Public Health
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author_browse	Congcong Wang Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun
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author-letter	Congcong Wang
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title_sort	identification of hub genes in pancreatic ductal adenocarci-noma using bioinformatics analysis
callnumber	RA1-1270
title_auth	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis
url	https://doaj.org/article/0b9b46cdf264433ab07087a497e9eade https://ijph.tums.ac.ir/index.php/ijph/article/view/24144 https://doaj.org/toc/2251-6085 https://doaj.org/toc/2251-6093
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author2	Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun
author2Str	Jianping Guo Xiaoyang Zhao Jia Jia Wenting Xu Peng Wan Changgang Sun
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up_date	2024-07-03T14:20:11.002Z
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Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

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