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

通过加权基因共表达网络分析和体外实验验证识别与瘢痕疙瘩进展相关的 miRNA 模块

阅读:8
作者:Wenchang Lv, Yuping Ren, Min Wu, Xiao Luo, Jing Yu, Qi Zhang, Yiping Wu

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。