Differential gene screening and bioinformatics analysis of epidermal stem cells and dermal fibroblasts during skin aging

To explore the differentially expressed genes (DEGs) and potential therapeutic targets of skin aging in GEO database by bioinformatics methods. Dermal fibroblasts and skin aging related data sets GSE110978 and GSE117763 were downloaded from GEO database, and epidermal stem cells and skin aging related data sets GSE137176 were downloaded. GEO2R was used to screen DEGs of candidate samples from the three microarrays, GO function analysis and KEGG pathway analysis were performed. Protein interaction network was constructed using String database, and hub gene was obtained by Cytoscape. NetworkAnalys was used to analyze the coregulatory network of DEGs and MicroRNA (miRNA), interaction with TF, and protein-chemical interactions of DEGs. Finally, DSigDB was used to determine candidate drugs for DEGs. Six DEGs were obtained. It mainly involves the cytological processes such as response to metal ion, and is enriched in mineral absorption and other signal pathways. Ten genes were screened by PPI analysis. Gene-miRNA coregulatory network found that Peg3 and mmu-miR-1931 in DEGs were related to each other, and Cybrd1 was related to mmu-miR-290a-5p and mmu-miR-3082-5p. TF-gene interactions found that the transcription factor UBTF co-regulated two genes, Arhgap24 and Mpzl1. Protein-chemical Interactions analysis and identification of candidate drugs show results for candidate drugs. Try to explore the mechanism of hub gene action in skin aging progression, and to discover the key signaling pathways leading to skin aging, which may be a high risk of skin aging.

Automated summary

By using bioinformatics methods, this study explored differentially expressed genes (DEGs) and potential therapeutic targets of skin aging in the GEO database. Six DEGs were identified, which are involved in cellular processes such as response to metal ion and enriched in mineral absorption and other signaling pathways. Through protein interaction network and gene-miRNA coregulatory network analysis, the relationships between key genes and miRNAs related to DEGs were discovered. In addition, TF-gene interaction analysis and protein-chemical interaction analysis identified potential candidate drugs.