Epithelial-Mesenchymal Transition gene database (dbEMT) Home
dbEMT
dbEMT 2.0
General information | Literature | Expression | lncRNA |Regulation | Mutation | Homolog | Interaction

Basic Information

Gene ID

406886

Name

MIRLET7D

Sentence

From PubMed database
Let-7d miRNA prevents TGF-beta1-induced EMT and renal fibrogenesis through regulation of HMGA2 expression.

TGF-beta1-induced epithelial to mesenchymal transition (EMT) process of tubular epithelial cells plays a leading role in the occurrence and progression of renal fibrosis as seen in diabetic nephropathy (DN). High mobility group AT-hook 2 (HMGA2) is considered to be involved in TGF-beta1-mediated EMT via multifactorial mechanisms. Specific microRNAs (miRNAs) are closely associated with EMT, and here we focused on let-7d miRNA as a regulator of HMGA2. This study aims to investigate the effects of HMGA2 on EMT process induced by TGF-beta1 using small interfering RNA (siRNA) technique in vitro, and further explore the potential role of let-7d miRNA during renal fibrosis in DN. We demonstrated that siRNA targeting HMGA2 was sufficient to inhibit TGF-beta1-induced EMT and fibrogenesis in rat kidney tubular epithelial cells (NRK52E). Furthermore, let-7d expression was significantly reduced by TGF-beta1 stimulation, we focused on let-7d and found that overexpression of let-7d down-regulated the expression of HMGA2 and in turn suppressed TGF-beta1-induced EMT and renal fibrogenesis. Inhibition of let-7d increased HMGA2 expression and enhanced the profibrogenic effects of TGF-beta1 on NRK-52E cells. Consistent with the above observations in vitro, let-7d expression was also decreased in the kidneys of unilateral ureter obstruction model, accompanied by the correspondingly increased expression of HMGA2 and fibrotic genes in this model. Collectively, HMGA2 and let-7d miRNA significantly impact on the progression of TGF-beta1-induced EMT and fibrogenesis both in vitro and in vivo, and they may represent novel targets for the prevention strategies of renal fibrosis in the context of DN.CI - Copyright (c) 2016 Elsevier Inc. All rights reserved.

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