Cargando…
Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis
OBJECTIVE: This study aimed to identify key genes associated with the pathogenesis of nasopharyngeal carcinoma (NPC) by bioinformatics analysis. METHODS: Datasets (GSE13597 and GSE34573) were screened and downloaded from the comprehensive gene expression database (GEO). GEO2R online tool was adopted...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197650/ https://www.ncbi.nlm.nih.gov/pubmed/35712071 http://dx.doi.org/10.1155/2022/9022700 |
_version_ | 1784727465587900416 |
---|---|
author | Song, Yujie Feng, Tao Cao, Wenping Yu, Haiyang Zhang, Zeng |
author_facet | Song, Yujie Feng, Tao Cao, Wenping Yu, Haiyang Zhang, Zeng |
author_sort | Song, Yujie |
collection | PubMed |
description | OBJECTIVE: This study aimed to identify key genes associated with the pathogenesis of nasopharyngeal carcinoma (NPC) by bioinformatics analysis. METHODS: Datasets (GSE13597 and GSE34573) were screened and downloaded from the comprehensive gene expression database (GEO). GEO2R online tool was adopted to analyze microarray data GSE13597 and GSE34573 related to NPC. Volcano plot was generated using Bioconductor in R software. “Pheatmap” was used to draw heatmaps based on the top 10 regulated genes of GSE13597 and GSE34573. GO and KEGG analyses were conducted via online tool DAVID. We uploaded the DEGs of NPC to STRING software and then used Cytoscape software to draw PPI network of DEGs. RESULTS: 216 DEGs were obtained in GSE13597 between patient and control group (111 up-regulated DEGs and 105 down-regulated DEGs). 1101 DEGs were obtained in GSE34573 (470 up-regulated DEGs and 641 down-regulated DEGs). 63 common differential genes were screened named co-DEGs in the two datasets. These DEGs were mainly associated with defense response to bacterium, cell-matrix adhesion, chemokine-mediated signaling pathway, tissue homeostasis, humoral immune response, cilium movement, cilium organization, cilium assembly, and epithelial cilium movement. KEGG pathway enrichment analysis showed that DEGs were mainly involved in viral protein interaction with cytokine and cytokine receptor, salivary secretion, p53 signaling pathway, IL-17 signaling pathway, cell cycle, PI3K-Akt signaling pathway, and ECM-receptor interaction. We identified seven hub genes, including FN1, MMP-10, MUC1, KIF23, CDK1, MUC5B, and MUC5AC. CONCLUSIONS: Seven hub genes, including FN1, MMP-10, MUC1, KIF23, CDK1, MUC5B, and MUC5AC, might be therapeutic potential biomarkers of NPC. |
format | Online Article Text |
id | pubmed-9197650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-91976502022-06-15 Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis Song, Yujie Feng, Tao Cao, Wenping Yu, Haiyang Zhang, Zeng Comput Intell Neurosci Research Article OBJECTIVE: This study aimed to identify key genes associated with the pathogenesis of nasopharyngeal carcinoma (NPC) by bioinformatics analysis. METHODS: Datasets (GSE13597 and GSE34573) were screened and downloaded from the comprehensive gene expression database (GEO). GEO2R online tool was adopted to analyze microarray data GSE13597 and GSE34573 related to NPC. Volcano plot was generated using Bioconductor in R software. “Pheatmap” was used to draw heatmaps based on the top 10 regulated genes of GSE13597 and GSE34573. GO and KEGG analyses were conducted via online tool DAVID. We uploaded the DEGs of NPC to STRING software and then used Cytoscape software to draw PPI network of DEGs. RESULTS: 216 DEGs were obtained in GSE13597 between patient and control group (111 up-regulated DEGs and 105 down-regulated DEGs). 1101 DEGs were obtained in GSE34573 (470 up-regulated DEGs and 641 down-regulated DEGs). 63 common differential genes were screened named co-DEGs in the two datasets. These DEGs were mainly associated with defense response to bacterium, cell-matrix adhesion, chemokine-mediated signaling pathway, tissue homeostasis, humoral immune response, cilium movement, cilium organization, cilium assembly, and epithelial cilium movement. KEGG pathway enrichment analysis showed that DEGs were mainly involved in viral protein interaction with cytokine and cytokine receptor, salivary secretion, p53 signaling pathway, IL-17 signaling pathway, cell cycle, PI3K-Akt signaling pathway, and ECM-receptor interaction. We identified seven hub genes, including FN1, MMP-10, MUC1, KIF23, CDK1, MUC5B, and MUC5AC. CONCLUSIONS: Seven hub genes, including FN1, MMP-10, MUC1, KIF23, CDK1, MUC5B, and MUC5AC, might be therapeutic potential biomarkers of NPC. Hindawi 2022-06-07 /pmc/articles/PMC9197650/ /pubmed/35712071 http://dx.doi.org/10.1155/2022/9022700 Text en Copyright © 2022 Yujie Song 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 Song, Yujie Feng, Tao Cao, Wenping Yu, Haiyang Zhang, Zeng Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title | Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title_full | Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title_fullStr | Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title_full_unstemmed | Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title_short | Identification of Key Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis |
title_sort | identification of key genes in nasopharyngeal carcinoma based on bioinformatics analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197650/ https://www.ncbi.nlm.nih.gov/pubmed/35712071 http://dx.doi.org/10.1155/2022/9022700 |
work_keys_str_mv | AT songyujie identificationofkeygenesinnasopharyngealcarcinomabasedonbioinformaticsanalysis AT fengtao identificationofkeygenesinnasopharyngealcarcinomabasedonbioinformaticsanalysis AT caowenping identificationofkeygenesinnasopharyngealcarcinomabasedonbioinformaticsanalysis AT yuhaiyang identificationofkeygenesinnasopharyngealcarcinomabasedonbioinformaticsanalysis AT zhangzeng identificationofkeygenesinnasopharyngealcarcinomabasedonbioinformaticsanalysis |