Identification of potential hub genes associated with skin wound healing based on time course bioinformatic analyses

Abstract Background The skin is the largest organ of body and has multiple functions. Wounds remain a significant healthcare problem due to large number traumatic pathophysiological conditions patients suffer. Methods Gene expression profiles 37 biopsies collected from undergoing split-thickness grafts at five different time points were downloaded two datasets (GSE28914 GSE50425) in Expression Omnibus (GEO) database. Principal component analysis (PCA) was applied classify samples into phases. Subsequently, differentially expressed genes (DEGs) analysis, Ontology (GO) Kyoto Encyclopedia Genes Genomes (KEGG) pathway functional enrichment analyses performed, protein–protein interaction (PPI) networks created for each phase. Furthermore, based on results PPI, hub phase identified by molecular complex detection combined with ClueGO algorithm. Results Using principal divided four phases, namely intact phase, acute wound inflammatory proliferation remodeling Intact used as control group. In total 1 upregulated 100 downregulated DEGs identified. Tyrosinase (TYR), tyrosinase Related Protein (TYRP1) dopachrome tautomerase (DCT) considered enriched tyrosine metabolism which dominate process melanogenesis. 85 164 CHEK1, CCNB1 CDK1 cell cycle P53 signaling pathway. 121 49 COL4A1, COL4A2, COL6A1 protein digestion absorption, ECM-receptor interaction. Conclusion This comprehensive bioinformatic re-analysis GEO data provides new insights pathogenesis healing potential identification therapeutic targets treatment wounds.