ArticleBioMed research international2021
Bioinformatic Analysis of Key Genes and Pathways Related to Keloids.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Identification of potential therapeutic targetiScience · 2026Article
- Study on the Potential Molecular Mechanism of Keloid Disease Associated With Single Cell Combined Mendelian Randomization.Journal of cosmetic dermatology · 2026Article
- Identification of potential therapeutic target SPP1 and related RNA regulatory pathway in keloid based on bioinformatics analysis.Annals of medicine · 2024Article
- [Keloid nomogram prediction model based on weighted gene co-expression network analysis and machine learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Bioinformatics analysis and identification of dysregulated POSTN in the pathogenesis of keloid.International wound journal · 2023Article
- Identification and characterization of bone/cartilage-associated signatures in common fibrotic skin diseases.Frontiers in genetics · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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
methodsWe 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.
results117 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.
conclusionThis 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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