Objective:Diabetic foot ulcer is a serious complications of diabetes.Despite the growing understanding of its pathophysiology as well as cellular and molecular levels,there is still a lack of clinically effective treatments.This study aimed to screen differentially expressed genes of diabetic foot ulcer based on bioinformatics analysis methods,construct competitive endogenous RNA(ceRNA)regulatory network,explore the molecular mechanisms related to diabetic foot ulcer and screen potential therapeutic targets.Methods:RNA-seq sequencing data of diabetic foot ulcer were obtained from GEO database.Differential expression analysis of genes was performed using R language Limma package,and long non-coding RNA(lncRNA)and mRNA with differential expression were screened out.GO and KEGG enrichment analysis of mRNA with differential expression was performed using Metascape database.TRRUST transcription factor database was used to predict transcription factors that might regulate the differential lncRNAs.Multiple online databases were used to predict related miRNAs and construct lncRNA-miRNA-mRNA regulatory networks.Results:212 lncRNAs and 534 mRNAs with significant differencewere obtained by differential expression analysis.The results of enrichment analysis showed that the differential genes were mainly enriched in the biological processes such as receptor ligand binding,calcium-related protein binding and enzyme activation.Cis-regulated gene analysis showed 7 groups of lncRNAs co-expressed with mRNA on chromosomes.Trans analysis showed that a total of 15 transcription factors regulated the expression of lncRNA and mRNA through 1132 TF-lncRNA relationships.Nine ceRNA regulatory networks related to diabetic foot ulcer were successfully constructed,among which LINC00424 was involved in 6 as a core lncRNA.Conclusion:Through bioinformatics network analysis,this study constructed the lncRNA axis ceRNA regulatory network of diabetic foot ulcer,providing an important basis for further study on the pathogenesis of diabetic foot ulcer and screening of new diagnostic and therapeutic markers.These nodes may become new candidate diagnostic markers or potential therapeutic targets. |