ArticleMolecular medicine (Cambridge, Mass.)2024
Assessing personalized molecular portraits underlying endothelial-to-mesenchymal transition within pulmonary arterial hypertension.
Article in Molecular medicine (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- SIRT6 alleviates ischemic injury via orchestrating the RREB1/Snail and STC1/Smad7 signaling pathways to regulate endothelial-mesenchymal transition.Science China. Life sciences · 2026Article
- Beyond the Vasculature: The Emerging Role of Systemic Metabolism and Immunometabolism in Pulmonary Arterial Hypertension.International journal of molecular sciences · 2026Review
- From Disease-Specific Models to Broad Clinical Utility: A Perspective on AI Hybrid Ensemble Frameworks.Advanced genetics (Hoboken, N.J.) · 2026Article
- Multi-omics integration study of vascular smooth muscle cell phenotypic conversion identified novel biomarkers in idiopathic pulmonary arterial hypertension.Respiratory research · 2026Article
- Development of a machine learning-based depression risk identification tool for older adults with asthma.BMC psychiatry · 2025Article
- Deciphering the Proteomic Landscape of Circulating Extracellular Vesicles in Human Abdominal Aortic Aneurysm.Journal of cellular and molecular medicine · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Pulmonary arterial hypertension (PAH) is a progressive and rapidly fatal disease with an intricate etiology. Identifying biomarkers for early PAH lesions based on the exploration of subtle biological processes is significant for timely diagnosis and treatment. In the present study, nine distinct cell populations identified based on gene expression profiles revealed high heterogeneity in cell composition ratio, biological function, distribution preference, and communication patterns in PAH. Notably, compared to other cells, endothelial cells (ECs) showed prominent variation in multiple perspectives. Further analysis demonstrated the endothelial-to-mesenchymal transition (EndMT) in ECs and identified a subgroup exhibiting a contrasting phenotype. Based on these findings, a machine-learning integrated program consisting of nine learners was developed to create a PAH Endothelial-to-mesenchymal transition Signature (PETS). This study identified cell populations underlying EndMT and furnished a potential tool that might be valuable for PAH diagnosis and new precise therapies.
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Registered trials
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