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Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis

BACKGROUND: Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database. METHODS: Differentially expressed genes (DEGs) were obtained using GEO2R. DAVID database was used to a...

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Autores principales: Li, Ting, Gao, Xujie, Han, Lei, Yu, Jinpu, Li, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6009060/
https://www.ncbi.nlm.nih.gov/pubmed/29921304
http://dx.doi.org/10.1186/s12957-018-1409-3
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author Li, Ting
Gao, Xujie
Han, Lei
Yu, Jinpu
Li, Hui
author_facet Li, Ting
Gao, Xujie
Han, Lei
Yu, Jinpu
Li, Hui
author_sort Li, Ting
collection PubMed
description BACKGROUND: Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database. METHODS: Differentially expressed genes (DEGs) were obtained using GEO2R. DAVID database was used to analyze function and pathways enrichment of DEGs. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape software. Then, the influence of hub genes on overall survival (OS) was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Additionally, potential stem loop miRNAs of hub genes were predicted by miRecords and screened by TCGA dataset. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst. RESULTS: In total, 67 DEGs were identified; upregulated DEGs were mainly enriched in biological process (BP) related to angiogenesis and extracellular matrix organization and the downregulated DEGs were mainly enriched in BP related to ion transport and response to bacterium. KEGG pathways analysis showed that the upregulated DEGs were enriched in ECM-receptor interaction and the downregulated DEGs were enriched in gastric acid secretion. A PPI network of DEGs was constructed, consisting of 43 nodes and 87 edges. Twelve genes were considered as hub genes owing to high degrees in the network. Hsa-miR-29c, hsa-miR-30c, hsa-miR-335, hsa-miR-33b, and hsa-miR-101 might play a crucial role in hub genes regulation. In addition, the transcription factors-hub genes pairs were displayed with 182 edges and 102 nodes. The high expression of 7 out of 12 hub genes was associated with worse OS, including COL4A1, VCAN, THBS2, TIMP1, COL1A2, SERPINH1, and COL6A3. CONCLUSIONS: The miRNA and TFs regulation network of hub genes in GC may promote understanding of the molecular mechanisms underlying the development of gastric cancer and provide potential targets for GC diagnosis and treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12957-018-1409-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-60090602018-06-27 Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis Li, Ting Gao, Xujie Han, Lei Yu, Jinpu Li, Hui World J Surg Oncol Research BACKGROUND: Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database. METHODS: Differentially expressed genes (DEGs) were obtained using GEO2R. DAVID database was used to analyze function and pathways enrichment of DEGs. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape software. Then, the influence of hub genes on overall survival (OS) was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Additionally, potential stem loop miRNAs of hub genes were predicted by miRecords and screened by TCGA dataset. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst. RESULTS: In total, 67 DEGs were identified; upregulated DEGs were mainly enriched in biological process (BP) related to angiogenesis and extracellular matrix organization and the downregulated DEGs were mainly enriched in BP related to ion transport and response to bacterium. KEGG pathways analysis showed that the upregulated DEGs were enriched in ECM-receptor interaction and the downregulated DEGs were enriched in gastric acid secretion. A PPI network of DEGs was constructed, consisting of 43 nodes and 87 edges. Twelve genes were considered as hub genes owing to high degrees in the network. Hsa-miR-29c, hsa-miR-30c, hsa-miR-335, hsa-miR-33b, and hsa-miR-101 might play a crucial role in hub genes regulation. In addition, the transcription factors-hub genes pairs were displayed with 182 edges and 102 nodes. The high expression of 7 out of 12 hub genes was associated with worse OS, including COL4A1, VCAN, THBS2, TIMP1, COL1A2, SERPINH1, and COL6A3. CONCLUSIONS: The miRNA and TFs regulation network of hub genes in GC may promote understanding of the molecular mechanisms underlying the development of gastric cancer and provide potential targets for GC diagnosis and treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12957-018-1409-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-19 /pmc/articles/PMC6009060/ /pubmed/29921304 http://dx.doi.org/10.1186/s12957-018-1409-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Li, Ting
Gao, Xujie
Han, Lei
Yu, Jinpu
Li, Hui
Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title_full Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title_fullStr Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title_full_unstemmed Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title_short Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
title_sort identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6009060/
https://www.ncbi.nlm.nih.gov/pubmed/29921304
http://dx.doi.org/10.1186/s12957-018-1409-3
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