Identification of key genes related to skin burns based on bioinformatics analysis.

To further understand the regulatory network and molecular mechanisms of gene expression after skin burns, we performed bioinformatics analysis of gene expression profiles of skin burn samples and identified key genes associated with skin burns. The GSE8056 dataset and GSE139028 dataset was downloaded from the Gene Expression Omnibus (GEO) database for analysis and validation. The limma package was used to screen for differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses (KEGG) were then performed. Subsequently, LASSO regression analysis was performed on DEGs and a regulatory network map of skin burn-related genes was constructed. Finally, the infiltration of immune cells was calculated and co-expression network maps of immune-related key genes and skin regeneration genes were constructed. Analysis of the GSE8056 dataset showed that 432 genes were upregulated and 351 genes were downregulated. The DEGs were mainly focused on immune response and skin regeneration. Meanwhile, these two groups of pivotal genes were significantly associated with abnormal infiltration of 9 immune cells. GSE139028 validation revealed that 3 hub genes associated with skin burn immunity were differentially expressed, except for S100A8, while only the DPT gene was differentially expressed among the seven hub genes associated with skin regeneration. In short, the effect of skin burn on patients is to regulate the expression of immune-related genes UPP1, MMP1, MMP3 and skin regeneration-related gene DPT, which may be the key target for the treatment of skin burn. © The Author(s) 2022. Published by Oxford University Press on behalf of the American Burn Association.

Citation

Boheng Zhu, Gaofei Zhang, Wuquan Li, Wende Cao, Jinglin Zhang, Hong Wang. Identification of key genes related to skin burns based on bioinformatics analysis. Journal of burn care & research : official publication of the American Burn Association. 2022 Sep 14

PMID: 36103997

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