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Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke

GSE248760 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2024/04/08 Platform GPL16791
Summary
Ischemic Stroke (IS) is one of the most impairing complications of sickle cell anemia (SCA), responsible for 20% of mortality in patients. Rheological alterations, adhesive properties of sickle reticulocytes, leukocyte adhesion, inflammation and endothelial dysfunction are related to the vasculopathy observed prior to ischemic events. The role of the vascular endothelium in this complex cascade of mechanisms is emphasized, as well as in the process of ischemia-induced repair and neovascularization. The aim of the present study was to perform a comparative transcriptomic analysis of endothelial colony-forming cells (ECFCs) from SCA patients with and without IS. Next, to gain further insights of the biological relevance of differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction network (PPI) construction and in silico prediction of regulatory factors were performed. Among the 2,469 DEGs, genes related to cell proliferation (AKT1, E2F1, CDCA5, EGFL7), migration (AKT1, HRAS), angiogenesis (AKT1, EGFL7) and defense response pathways (HRAS, IRF3, TGFB1), important endothelial cell molecular mechanisms in post ischemia repair were identified. Despite the severity of IS in SCA, widely accepted molecular targets are still lacking, especially related to stroke outcome. Thus, these exploratory results may contribute to a better understanding of the role of endothelial cells in SCA ischemic stroke recovery, and promote new insights to further studies on therapeutic strategies for this severe complication.
Published in
Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke
de Castro JNP, da Silva Costa SM, Camargo ACL et al. · Annals of hematology 2024 · PMID 38386032 · doi:10.1007/s00277-024-05655-6
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Also filed as BioProject PRJNA1045717 and SRA study SRP474726. Searching any of these in the dataset finder brings you back here.

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