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Bioinformatic Analysis of Key Genes and Pathways Related to Keloids
BACKGROUND: The pathophysiology of keloids is complex, and the treatment for keloids is still an unmet medical need. Our study is aimed at identifying the hub genes among the differentially expressed genes (DEGs) between normal skin tissue and keloids and key pathways in the development of keloids....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009712/ https://www.ncbi.nlm.nih.gov/pubmed/33860039 http://dx.doi.org/10.1155/2021/5897907 |
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author | Bi, Siwei Liu, Ruiqi Wu, Beiyi He, Linfeng Gu, Jun |
author_facet | Bi, Siwei Liu, Ruiqi Wu, Beiyi He, Linfeng Gu, Jun |
author_sort | Bi, Siwei |
collection | PubMed |
description | BACKGROUND: The pathophysiology of keloids is complex, and the treatment for keloids is still an unmet medical need. Our study is aimed at identifying the hub genes among the differentially expressed genes (DEGs) between normal skin tissue and keloids and key pathways in the development of keloids. MATERIALS AND METHODS: We downloaded the GSE92566 and GSE90051 microarray data, which contain normal skin tissue and keloid gene expression data. GSE92566 was treated as a discovery dataset for summarizing the significantly DEGs, and GSE90051 served as a validation dataset. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, Reactome enrichment analysis, gene set enrichment analysis, and gene set variation analysis were performed for the key functions and pathways enriched in DEGs. Moreover, we also validated the hub genes identified from the protein-protein interaction network and predicted miRNA-hub gene interactions. RESULTS: 117 downregulated DEGs and 204 upregulated DEGs in GSE92566 were identified. Extracellular and collagen-related pathways were prominent in upregulated DEGs, while the keratinization-related pathway was associated with downregulated DEGs. The hub genes included COL5A1, COL5A2, and SERPINH1, which were also validated in GSE90051. CONCLUSION: This study identified several hub genes and provided insights for the underlying pathways and miRNA-hub gene interactions for keloid development through bioinformatic analysis of two microarray datasets. Additionally, our results would support the development of future therapeutic strategies. |
format | Online Article Text |
id | pubmed-8009712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-80097122021-04-14 Bioinformatic Analysis of Key Genes and Pathways Related to Keloids Bi, Siwei Liu, Ruiqi Wu, Beiyi He, Linfeng Gu, Jun Biomed Res Int Research Article BACKGROUND: The pathophysiology of keloids is complex, and the treatment for keloids is still an unmet medical need. Our study is aimed at identifying the hub genes among the differentially expressed genes (DEGs) between normal skin tissue and keloids and key pathways in the development of keloids. MATERIALS AND METHODS: We downloaded the GSE92566 and GSE90051 microarray data, which contain normal skin tissue and keloid gene expression data. GSE92566 was treated as a discovery dataset for summarizing the significantly DEGs, and GSE90051 served as a validation dataset. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, Reactome enrichment analysis, gene set enrichment analysis, and gene set variation analysis were performed for the key functions and pathways enriched in DEGs. Moreover, we also validated the hub genes identified from the protein-protein interaction network and predicted miRNA-hub gene interactions. RESULTS: 117 downregulated DEGs and 204 upregulated DEGs in GSE92566 were identified. Extracellular and collagen-related pathways were prominent in upregulated DEGs, while the keratinization-related pathway was associated with downregulated DEGs. The hub genes included COL5A1, COL5A2, and SERPINH1, which were also validated in GSE90051. CONCLUSION: This study identified several hub genes and provided insights for the underlying pathways and miRNA-hub gene interactions for keloid development through bioinformatic analysis of two microarray datasets. Additionally, our results would support the development of future therapeutic strategies. Hindawi 2021-03-23 /pmc/articles/PMC8009712/ /pubmed/33860039 http://dx.doi.org/10.1155/2021/5897907 Text en Copyright © 2021 Siwei Bi 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 Bi, Siwei Liu, Ruiqi Wu, Beiyi He, Linfeng Gu, Jun Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title | Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title_full | Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title_fullStr | Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title_full_unstemmed | Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title_short | Bioinformatic Analysis of Key Genes and Pathways Related to Keloids |
title_sort | bioinformatic analysis of key genes and pathways related to keloids |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009712/ https://www.ncbi.nlm.nih.gov/pubmed/33860039 http://dx.doi.org/10.1155/2021/5897907 |
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