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The aim of the present study was to select key genes that are associated with fibroblasts and keratinocytes during keloid scar progression and development. The gene expression profile of GSE44270, which includes 32 samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in case samples compared with control samples were screened using the Limma R package followed by hierarchical clustering analysis. Protein-protein interaction (PPI) networks of the total selected DEGs were constructed using Cytoscape. Moreover, the Gene Ontology biological processes and significant Kyoto Encyclopedia of Genes and Genomes pathways of the total selected DEGs were enriched using the Database for Annotation, Visualization and Integrated Discovery. Significant pathways that may be associated with keloid scar were analyzed using deviation analysis of dynamic capabilities. There were 658 DEGs in fibroblast keloid vs. normal, 112 DEGs in fibroblast non-lesion vs. normal, 439 DEGs in fibroblast keloid vs. non-lesion, 523 DEGs in keratocyte keloid vs. normal, 186 DEGs in keratocyte non-lesion vs. normal, and 963 DEGs in keratocyte keloid vs. non-lesion groups. HOXA9, BMP4, CDKN1A and SMAD2 in fibroblasts, and HOXA7, MCM8, PSMA4 and PSMB2 in keratinocytes were key genes in the PPI networks. Moreover, the amino sugar and nucleotide sugar metabolism pathway, cell cycle, and extracellular matrix (ECM)-receptor interaction pathway were significant pathways. This study suggests that several key genes (BMP4, HOXA9, SMAD2, CDKN1A, HOXA7, PSMA4 and PSMB2) that participate in some significant pathways (cell cycle and ECM-receptor interaction pathways) may be potential therapeutic targets for keloid scars.

Functional analysis of keratinocyte and fibroblast gene expression in skin and keloid scar tissue based on deviation analysis of dynamic capabilities