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Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis

Gastric cancer (GC) is one of the most common malignancies of the digestive system with few genetic markers for its early detection and prevention. In this study, differentially expressed genes (DEGs) were analyzed using GEO2R from GSE54129 and GSE13911 of the Gene Expression Omnibus (GEO). Then, ge...

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Autores principales: Chong, Xinyu, Peng, Rui, Sun, Yan, Zhang, Luyu, Zhang, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525308/
https://www.ncbi.nlm.nih.gov/pubmed/33015179
http://dx.doi.org/10.1155/2020/7658230
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author Chong, Xinyu
Peng, Rui
Sun, Yan
Zhang, Luyu
Zhang, Zheng
author_facet Chong, Xinyu
Peng, Rui
Sun, Yan
Zhang, Luyu
Zhang, Zheng
author_sort Chong, Xinyu
collection PubMed
description Gastric cancer (GC) is one of the most common malignancies of the digestive system with few genetic markers for its early detection and prevention. In this study, differentially expressed genes (DEGs) were analyzed using GEO2R from GSE54129 and GSE13911 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, STRING, and Cytoscape. Finally, we performed survival analysis of key genes through the Kaplan-Meier plotter. A total of 1034 DEGs were identified in GC. GO and KEGG results showed that DEGs mainly enriched in plasma membrane, cell adhesion, and PI3K-Akt signaling pathway. Subsequently, the PPI network with 44 nodes and 333 edges was constructed, and 18 candidate genes in the network were focused on by centrality analysis and module analysis. Furthermore, data showed that high expressions of fibronectin 1(FN1), the tissue inhibitor of metalloproteinases 1 (TIMP1), secreted phosphoprotein 1 (SPP1), apolipoprotein E (APOE), and versican (VCAN) were related to poor overall survivals in GC patients. In summary, this study suggests that FN1, TIMP1, SPP1, APOE, and VCAN may act as the key genes in GC.
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spelling pubmed-75253082020-10-02 Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis Chong, Xinyu Peng, Rui Sun, Yan Zhang, Luyu Zhang, Zheng Biomed Res Int Research Article Gastric cancer (GC) is one of the most common malignancies of the digestive system with few genetic markers for its early detection and prevention. In this study, differentially expressed genes (DEGs) were analyzed using GEO2R from GSE54129 and GSE13911 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, STRING, and Cytoscape. Finally, we performed survival analysis of key genes through the Kaplan-Meier plotter. A total of 1034 DEGs were identified in GC. GO and KEGG results showed that DEGs mainly enriched in plasma membrane, cell adhesion, and PI3K-Akt signaling pathway. Subsequently, the PPI network with 44 nodes and 333 edges was constructed, and 18 candidate genes in the network were focused on by centrality analysis and module analysis. Furthermore, data showed that high expressions of fibronectin 1(FN1), the tissue inhibitor of metalloproteinases 1 (TIMP1), secreted phosphoprotein 1 (SPP1), apolipoprotein E (APOE), and versican (VCAN) were related to poor overall survivals in GC patients. In summary, this study suggests that FN1, TIMP1, SPP1, APOE, and VCAN may act as the key genes in GC. Hindawi 2020-09-21 /pmc/articles/PMC7525308/ /pubmed/33015179 http://dx.doi.org/10.1155/2020/7658230 Text en Copyright © 2020 Xinyu Chong et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chong, Xinyu
Peng, Rui
Sun, Yan
Zhang, Luyu
Zhang, Zheng
Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title_full Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title_fullStr Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title_full_unstemmed Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title_short Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis
title_sort identification of key genes in gastric cancer by bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525308/
https://www.ncbi.nlm.nih.gov/pubmed/33015179
http://dx.doi.org/10.1155/2020/7658230
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