摘要
Abstract
Objective The aim of this study was to explore the key genes associated with skin burn through bioinformatics.Methods The burn gene microarray was obtained from GSE8056 database,the differential genes were obtained by R language analysis,Venn diagram was used to obtain the intersection of differential genes and glycolysis related genes,GO and KEGG enrichment analysis were then performed.LASSO regression and random forest algorithm were used to identify key genes,GSE77791 was used as an external validation set.CIBERSORT algorithm was used for immune infiltration analysis,and drugs targeting differential genes were predicted by Connectivity Map database.Results 1 355 differential genes were obtained from GSE8056,and 100 differential genes were obtained by intersection analysis.GO analysis mainly involved positive regulation of angiogenesis,vascular development,epithelial cell proliferation and so on.KEGG analysis showed that HIF-1 signaling pathway,IL-17 signaling pathway and cell cycle signaling pathway were closely related to burn process.Four key genes,PNP,DENND4C,FBXW7 and THBS1,were screened by machine learning method.Immune infiltration results showed that resting NK cells,M0 macrophages,activated mast cells and neutrophils in burn tissues were significantly higher than those in normal tissues,and correlation analysis showed that key genes were significantly correlated with immune processes.Lestaurtinib,PI-828,PIK-90 and Selumetinib were potential drugs for the treatment of burns.Conclusion PNP,DENND4C,FBXW7 and THBS1 are the key genes in the development of skin burn and significantly related to immune infiltration,the result provides the foundation for our future study on burn injury and drug research.关键词
烧伤/生物信息学/关键基因/免疫浸润/机器学习/糖酵解Key words
burns/bioinformatics/key gene/immune infiltration/machine learning/glycolysis分类
医药卫生
