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Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis
BACKGROUND: Hutchinson–Gilford Progeria syndrome (HGPS) is a rare lethal premature and accelerated aging disease caused by mutations in the lamin A/C gene. Nevertheless, the mechanisms of cellular damage, senescence, and accelerated aging in HGPS are not fully understood. Therefore, we aimed to scre...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035007/ https://www.ncbi.nlm.nih.gov/pubmed/32049798 http://dx.doi.org/10.1097/MD.0000000000019022 |
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author | Wang, Dengchuan Liu, Shengshuo Xu, Shi |
author_facet | Wang, Dengchuan Liu, Shengshuo Xu, Shi |
author_sort | Wang, Dengchuan |
collection | PubMed |
description | BACKGROUND: Hutchinson–Gilford Progeria syndrome (HGPS) is a rare lethal premature and accelerated aging disease caused by mutations in the lamin A/C gene. Nevertheless, the mechanisms of cellular damage, senescence, and accelerated aging in HGPS are not fully understood. Therefore, we aimed to screen potential key genes, pathways, and therapeutic agents of HGPS by using bioinformatics methods in this study. METHODS: The gene expression profile of GSE113648 and GSE41751 were retrieved from the gene expression omnibus database and analyzed to identify the differentially expressed genes (DEGs) between HGPS and normal controls. Then, gene ontology and the Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. To construct the protein-protein interaction (PPI) network, we used STRING and Cytoscape to make module analysis of these DEGs. Besides, the connectivity map (cMAP) tool was used as well to predict potential drugs. RESULTS: As a result, 180 upregulated DEGs and 345 downregulated DEGs were identified, which were significantly enriched in pathways in cancer and PI3K-Akt signaling pathway. The top centrality hub genes fibroblast growth factor 2, decorin, matrix metallopeptidase2, and Fos proto-oncogene, AP-1 transcription factor subunit were screened out as the critical genes among the DEGs from the PPI network. Dexibuprofen and parthenolide were predicted to be the possible agents for the treatment of HGPS by cMAP analysis. CONCLUSION: This study identified key genes, signal pathways and therapeutic agents, which might help us improve our understanding of the mechanisms of HGPS and identify some new therapeutic agents for HGPS. |
format | Online Article Text |
id | pubmed-7035007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-70350072020-03-10 Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis Wang, Dengchuan Liu, Shengshuo Xu, Shi Medicine (Baltimore) 3500 BACKGROUND: Hutchinson–Gilford Progeria syndrome (HGPS) is a rare lethal premature and accelerated aging disease caused by mutations in the lamin A/C gene. Nevertheless, the mechanisms of cellular damage, senescence, and accelerated aging in HGPS are not fully understood. Therefore, we aimed to screen potential key genes, pathways, and therapeutic agents of HGPS by using bioinformatics methods in this study. METHODS: The gene expression profile of GSE113648 and GSE41751 were retrieved from the gene expression omnibus database and analyzed to identify the differentially expressed genes (DEGs) between HGPS and normal controls. Then, gene ontology and the Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. To construct the protein-protein interaction (PPI) network, we used STRING and Cytoscape to make module analysis of these DEGs. Besides, the connectivity map (cMAP) tool was used as well to predict potential drugs. RESULTS: As a result, 180 upregulated DEGs and 345 downregulated DEGs were identified, which were significantly enriched in pathways in cancer and PI3K-Akt signaling pathway. The top centrality hub genes fibroblast growth factor 2, decorin, matrix metallopeptidase2, and Fos proto-oncogene, AP-1 transcription factor subunit were screened out as the critical genes among the DEGs from the PPI network. Dexibuprofen and parthenolide were predicted to be the possible agents for the treatment of HGPS by cMAP analysis. CONCLUSION: This study identified key genes, signal pathways and therapeutic agents, which might help us improve our understanding of the mechanisms of HGPS and identify some new therapeutic agents for HGPS. Wolters Kluwer Health 2020-02-14 /pmc/articles/PMC7035007/ /pubmed/32049798 http://dx.doi.org/10.1097/MD.0000000000019022 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 3500 Wang, Dengchuan Liu, Shengshuo Xu, Shi Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title | Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title_full | Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title_fullStr | Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title_full_unstemmed | Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title_short | Identification of hub genes, key pathways, and therapeutic agents in Hutchinson–Gilford Progeria syndrome using bioinformatics analysis |
title_sort | identification of hub genes, key pathways, and therapeutic agents in hutchinson–gilford progeria syndrome using bioinformatics analysis |
topic | 3500 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035007/ https://www.ncbi.nlm.nih.gov/pubmed/32049798 http://dx.doi.org/10.1097/MD.0000000000019022 |
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