Identifying miRNA modules associated with progression of keloids through weighted gene co-expression network analysis and experimental validation in vitro

Abstract

Keloid is a type of skin fibroproliferative disease, characterized by excessive deposition of collagen in the extracellular matrix, myofibroblast activation and invasive growth to the surrounding normal skin tissue. However, the specific pathogenesis of keloids is not yet fully understood and existing treatment strategies are unsatisfied. It is therefore urgent to explore new biomarkers associated with its progression for keloids. In this study, the microarray dataset GSE113620 was downloaded from the Gene Expression Omnibus (GEO) database to screen out the differential expression of miRNAs (DEMs). The DEMs with large variance were applied to construct a weighted gene co-expression network to identify miRNA modules that are closely relevant to keloid progression. It is worth noting that miR-424-3p in the blue module (r = 0.98, p = 1e-18) is considered to be the ultimate target most relevant to keloid progression through co-expressed network analysis. Subsequently, the results of molecular biology experiments determine that miR-424-3p targeting Smad7 significantly enhanced the ability of cell proliferation, migration and collagen secretion after transfection with miR-424-3p mimic, while the apoptosis rate was significantly reduced. On the contrary, the miR-424-3p inhibitor performs the exact opposite function.

Keywords: Bioinformatics; Keloids; Smad7; TGF-β1/Smad pathway; miR-424-3p.