ArticleHeliyon2024
Comprehensive bioinformatic analysis reveals a fibroblast-related gene signature for the diagnosis of keloids.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
- METTL3-modified exosomes from adipose-derived stem cells enhance the proliferation and migration of dermal fibroblasts by mediating m6A modification of CCNB1 mRNA.Archives of dermatological research · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: A keloid is a fibroproliferative cutaneous disorder secondary to skin injury, caused by an imbalance in fibroblast proliferation and apoptosis. However, the pathogenesis is not fully understood. In this study, candidate genes for keloid were identified and used to construct a diagnostic model. Methods: Three datasets related to keloids were downloaded from NCBI Gene Expression Omnibus. Fibroblast-related genes were screened, and fibroblast scores for the samples were determined. Then, a weighted gene co-expression network analysis (WGCNA) was used to identify modules and genes associated with keloids and the fibroblast score. Differentially expressed genes (DEGs) between keloid and control samples were identified and compared with fibroblast-related genes and genes in the modules. Overlapping genes were evaluated using functional enrichment analyses. Signature genes were further screened, and a diagnostic model was constructed. Finally, correlations between immune cell frequences and signature genes were analyzed. Results: In total, 124 fibroblast-related genes were obtained, and the fibroblast score was an effective indicator of the sample type. WGCNA revealed five modules that were significantly correlated with both the disease state and fibroblast scores, including 1760 genes. Additionally, 589 DEGs were identified, including 16 that overlapped with fibroblast-related genes and genes identified in the WGCNA. These genes were related to cell proliferation and apoptosis and were involved in FoxO, Rap1, p53, Ras, MAPK, and PI3K-Akt pathways. Finally, a six fibroblast-related gene signature ( Conclusion: The established model based on
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