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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....

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Autores principales: Bi, Siwei, Liu, Ruiqi, Wu, Beiyi, He, Linfeng, Gu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
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.
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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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