Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression

Abstract

Several blood biomarkers are now considered increasingly important for stratifying risk, monitoring disease progression, and evaluating the response to therapy in ischemic stroke. The purpose of the present study was to identify the key genes associated with ischemic stroke progression and elucidate the potential therapeutic small molecules. Microarray datasets related to stroke for GSE58294, GSE22255, and GSE16561 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were filtered using the Limma package. DAVID was then searched to perform gene ontology (GO) and pathway enrichment analyses. Based on the DEGs, a protein-protein interaction (PPI) network was developed using Cytoscape, and MCODE was applied to conduct module analysis. Finally, to identify the potential drugs for ischemic stroke, the connectivity map (CMap) database was used. Sixty DEGs were identified after analyzing the three datasets. The GO data analysis revealed that the DEGs were significantly associated with biological processes, including positive regulation of programmed cell death, protein localization in organelles, and positive regulation of apoptosis. KEGG analysis showed that the DEGs were particularly enriched in the Fc epsilon RI signaling pathway, MAPK signaling pathway, and Huntington’s disease. We selected five DEGs with high connectivity (CYBB, SYK, DUSP1, TNF, and SP1) that significantly predicted stroke progression. In addition, CMap prediction showed ten small molecules that could be used as adjuvants when treating ischemic stroke. The outcomes of the present study indicated that the five genes mentioned above can be considered potential targets for developing new medications that can modify the ischemic stroke process, and mycophenolic acid was the most promising small molecule to treat ischemic stroke.