Volume 36, Issue 3 (9-2025)
Studies in Medical Sciences 2025, 36(3): 219-230 |
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Moraveji F, Rezaeiani S, Mosafer Yadegari A S. Convergence of Signaling Pathways and Bioinformatics Analysis in Mesodermal Differentiation of iPSCs: Focus on KDR+/PDGFRα+ Populations for Cardiovascular Regeneration. Studies in Medical Sciences 2025; 36 (3) :219-230
URL: http://umj.umsu.ac.ir/article-1-6494-en.html
URL: http://umj.umsu.ac.ir/article-1-6494-en.html
Cellular and Molecular Research Center, Cellular and Molecular Medicine Research Institute, Urmia University of Medical Sciences, Urmia, Iran , siamak.cytology@gmail.com
Abstract: (58 Views)
Abstract:
Background and Objective:
Cardiovascular diseases continue to be the leading cause of death worldwide. The use of iPSCs holds great promise for repairing heart and blood vessel tissues. Generation of cardiovascular progenitors requires precise modulation of these cells through signaling pathways. This study highlights the KDR and PDGFRα markers in guiding iPSCs toward mesodermal progenitors, specifically the KDR+/PDGFRα+ populations, which have enormous clinical promise for cardiovascular applications.
Method: Gene transcript analysis involved obtaining data from the GEO database with accession number GSE90000. The GEO2R tool was used to identify genes with significant changes, defined as p-values < 0.05 and absolute log-fold changes > 2.
Functional classification of genes was performed to identify biological processes and signaling pathways using GO analysis with the DAVID tool.
Protein-protein networks were analyzed by simulating protein interactions using the STRING database, which helped identify key genes such as EOMES.
Signaling pathway analysis used tools including Cytoscape, Reactome, and X2K to analyze pathways involved in iPSC differentiation into cardiomyocytes.
Results: Our studies on KDR+/PDGFRα+ cells derived from iPSC differentiation revealed 1,635 genes that were significantly downregulated during cardiomyocyte formation, with p-values < 0.05 and |log-FC| ≥ 2. These genes include COCH, CYP26A1, and TUNAR. Using protein-protein interaction analysis, we identified EOMES (p-value 0.0026, |log-FC| -6.357) as a central transcription factor. Moreover, pathway enrichment analysis revealed a gradual downregulation of genes involved in cardiac disease, suggesting potential therapeutic applications.
Conclusion: Integrating bioinformatics tools (GEO2R, STRING, Reactome) with multi-marker strategies (CD13, ROR2, APLNR) enhances the purity of cardiovascular progenitors, ultimately improving therapeutic applications in the treatment of cardiovascular diseases.
Background and Objective:
Cardiovascular diseases continue to be the leading cause of death worldwide. The use of iPSCs holds great promise for repairing heart and blood vessel tissues. Generation of cardiovascular progenitors requires precise modulation of these cells through signaling pathways. This study highlights the KDR and PDGFRα markers in guiding iPSCs toward mesodermal progenitors, specifically the KDR+/PDGFRα+ populations, which have enormous clinical promise for cardiovascular applications.
Method: Gene transcript analysis involved obtaining data from the GEO database with accession number GSE90000. The GEO2R tool was used to identify genes with significant changes, defined as p-values < 0.05 and absolute log-fold changes > 2.
Functional classification of genes was performed to identify biological processes and signaling pathways using GO analysis with the DAVID tool.
Protein-protein networks were analyzed by simulating protein interactions using the STRING database, which helped identify key genes such as EOMES.
Signaling pathway analysis used tools including Cytoscape, Reactome, and X2K to analyze pathways involved in iPSC differentiation into cardiomyocytes.
Results: Our studies on KDR+/PDGFRα+ cells derived from iPSC differentiation revealed 1,635 genes that were significantly downregulated during cardiomyocyte formation, with p-values < 0.05 and |log-FC| ≥ 2. These genes include COCH, CYP26A1, and TUNAR. Using protein-protein interaction analysis, we identified EOMES (p-value 0.0026, |log-FC| -6.357) as a central transcription factor. Moreover, pathway enrichment analysis revealed a gradual downregulation of genes involved in cardiac disease, suggesting potential therapeutic applications.
Conclusion: Integrating bioinformatics tools (GEO2R, STRING, Reactome) with multi-marker strategies (CD13, ROR2, APLNR) enhances the purity of cardiovascular progenitors, ultimately improving therapeutic applications in the treatment of cardiovascular diseases.
Keywords: Bioinformatics, Cardiovascular diseases, Differentiation, Regenerative medicine, Signaling pathways
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