CircRNA-3302 promotes endothelial-to-mesenchymal transition via sponging miR-135b-5p to enhance KIT expression in Kawasaki disease.
Chao NiHuixian QiuShuchi ZhangQihao ZhangRuiyin ZhangJinhui ZhouJinshun ZhuChao NiuRongzhou WuChuxiao ShaoAbdullah Al MamunBo HanMao-Ping ChuChang JiaPublished in: Cell death discovery (2022)
Endothelial-to-mesenchymal transition (EndMT) is implicated in myofibroblast-like cell-mediated damage to coronary artery wall of Kawasaki disease (KD) patients, which subsequently increases the risk of coronary artery aneurysm. Many circular RNAs (circRNAs) have been reported to be associated with cardiovascular diseases. However, the roles and underlying molecular mechanism of circRNAs in KD-associated EndMT remains indefinite. In this research, we screened out circRNA-3302 from human umbilical vein endothelial cells (HUVECs) treated by sera from healthy controls (HCs) or KD patients via circRNA sequencing (circRNA-seq). In addition, circRNA-3302 upregulation was verified in endothelial cells stimulated by KD serum and pathological KD mice modeled with Candida albicans cell wall extracts (CAWS). Moreover, in vitro experiments demonstrated that overexpression of circRNA-3302 could markedly induce EndMT, and silencing of circRNA-3302 significantly alleviated KD serum-mediated EndMT. To further explore the molecular mechanisms of circRNA-3302 inducing EndMT, RNA sequencing (RNA-seq), a dual-luciferase reporter system, nuclear and extra-nuclear RNA isolation, RT-qPCR and Western blot analyses and so on, were utilized. Our data demonstrated that circRNA-3302 contributed to the KD-associated EndMT via sponging miR-135b-5p to enhance KIT expression. Collectively, our results imply that circRNA-3302 plays an important role in KD-associated EndMT, providing new insights into minimizing the risks of developing coronary artery aneurysms.
Keyphrases
- coronary artery
- single cell
- endothelial cells
- rna seq
- end stage renal disease
- poor prognosis
- candida albicans
- pulmonary artery
- newly diagnosed
- chronic kidney disease
- stem cells
- cardiovascular disease
- peritoneal dialysis
- cell proliferation
- prognostic factors
- cell wall
- oxidative stress
- machine learning
- high glucose
- genome wide
- binding protein
- dna methylation
- big data
- risk assessment
- skeletal muscle
- artificial intelligence
- vascular endothelial growth factor
- deep learning