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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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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. |
format | Online Article Text |
id | pubmed-7525308 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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