ArticleBMC cardiovascular disorders2025
Uncovering endothelial to mesenchymal transition drivers in atherosclerosis via multi-omics analysis.
Article in BMC cardiovascular disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Endothelial cells modulate immune cell responses during atherosclerosis.Trends in immunology · 2026Review
- Poly-Pharmacologic Disruption of the Proliferative-to-Mesenchymal Fate Branch Point Reverses EndMT and Pulmonary Hypertension.Research square · 2026Article
- Endothelial to mesenchymal transition in cardiovascular diseases: molecular insights and clinical perspectives.European heart journal · 2026Review
- Systematic Identification and Functional Validation of CASP10 as a DNA-Damage-Responsive Driver of Endothelial Pyroptosis in Atherosclerosis.Journal of cellular and molecular medicine · 2026Article
- Diabetes and its complications: molecular mechanisms, prevention and treatment.Signal transduction and targeted therapy · 2026Review
- LncRNA MAGI2-AS3 promotes the progression of atherosclerosis by sponging miR-525-5p.Journal of cardiothoracic surgery · 2025Article
- Integrated transcriptomic and proteomic analyses identify the TLR2-CXCR4 axis as a regulator of endothelial cell migration under simulated microgravity.Frontiers in physiology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to identify novel candidates that regulate Endothelial to mesenchymal transition(EndMT) in atherosclerosis by integrating multi-omics data.
methodsThe single-cell RNA sequencing (scRNA-seq) dataset GSE159677, bulk RNA-seq dataset GSE118446 and microarray dataset GSE56309 were obtained from the Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) were used for downscaling and cluster identification. Differentially expressed genes (DEGs) from GSE118446 and GSE56309 were analyzed using limma package. Functional enrichment analysis was applied by DAVID functional annotation tool. Quantitative real-time polymerase chain reaction (qPCR) and western blotting were used for further validation.
resultsNine endothelial cell (EC) clusters were identified in human plaques, with EC cluster 5 exhibiting an EndMT phenotype. The intersection of genes from EC cluster 5 and common DEGs in vitro EndMT models revealed seven mesenchymal candidates: PTGS2, TPM1, SERPINE1, FN1, RASD1, SEMA3C, and ESM1. Validation of these findings was carried out through qPCR analysis.
conclusionThrough the integration of multi-omics data using bioinformatics methods, our study identified seven novel EndMT candidates: PTGS2, TPM1, SERPINE1, FN1, RASD1, SEMA3C, and ESM1.
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