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Microarray Data Analysis of Molecular Mechanism Associated with Stroke Progression

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This study aimed to explore the molecular mechanism of stroke and provide a new target in the clinical management. The miRNA dataset GSE97532 (3 blood samples from middle cerebral artery… Click to show full abstract

This study aimed to explore the molecular mechanism of stroke and provide a new target in the clinical management. The miRNA dataset GSE97532 (3 blood samples from middle cerebral artery occlusion (MCAO) and 3 from sham operation) and mRNA dataset GSE97533 (3 blood samples from MCAO and 3 from sham operation) were obtained from GEO database. Differentially expressed mRNA (DEGs) and miRNAs (DEMIRs) were screened out between MCAO and sham operation groups. Then, DEMIR–DEG interactions were explored and visualized using Cytoscape software. Moreover, the enrichment analysis was performed on these DEMIRs and DEGs. Furthermore, protein–protein interaction (PPI) network was constructed. Finally, the DEG-target transcription factors (TFs) were investigated using the WebGestal software. The current bioinformatics analysis revealed 38 DEMIRs and 546 DEGs between MCAO and sham operation groups. The DEMIR–DEG analysis revealed 370 relations, such as miR-107-5p-Furin. The top 10 up- and downregulated DEMIRs were mainly enriched in pathways like cAMP signaling pathway. The PPI network analysis revealed 2 modules. The target DEGs of the 10 up- and downregulated DEMIRs in 2 modules were mainly assembled in functions like ATP binding and pathway including ABC transporters. Furthermore, the DEG–TF network analysis identified 5 outstanding TFs including androgen receptor (AR). miR107-5p might take part in the progression of stroke via inhibiting the expression of Furin. TFs like AR might be used as a novel gene therapy target for stroke. Furthermore, cAMP signaling pathway and ATP binding function might be a novel breakthrough for stroke treatment.

Keywords: analysis; sham operation; mcao sham; molecular mechanism

Journal Title: Journal of Molecular Neuroscience
Year Published: 2018

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