Transcriptomics-based screening and experimental validation of essential mitotic catastrophe-related genes in ischemic stroke

Abstract Background This study investigated key mitotic catastrophe (MC)-related genes and explored their diagnostic and therapeutic potential in ischemic stroke (IS). Methods Transcriptomic data from public databases and MC-related gene sets were analyzed. Key genes were screened using differential expression analysis, protein–protein interaction networks, and machine learning algorithms. Validation was performed via expression verification and receiver operating characteristic analysis. Subsequent investigations included nomogram construction, immune infiltration analysis, functional enrichment, prediction of regulatory miRNAs and targeting compounds, molecular docking, and real time-quantitative polymerase chain reaction (RT-qPCR). Finally, single-cell RNA sequencing was conducted. Results ARG1 and PTEN were identified as key MC-related genes, and they were significantly upregulated in IS samples, as validated by RT-qPCR. A diagnostic nomogram incorporating these genes showed favorable discriminatory performance in an independent external validation dataset, supporting its potential diagnostic value; however, its real-world clinical utility requires further validation in larger, prospectively collected cohorts. Both genes were significantly correlated with immune cell infiltration, exhibiting negative associations with naïve B cells and positive correlations with activated mast cells. GSEA identified PPAR signaling and regulation of the actin cytoskeleton among the pathways enriched in association with both ARG1 and PTEN . Twelve miRNAs were predicted to jointly regulate ARG1 and PTEN . Additionally, bisphenol A was computationally predicted via molecular docking to exhibit structural binding affinity for both ARG1 and PTEN. Nevertheless, given its well-recognized endocrine-disrupting properties, bisphenol A cannot be considered a candidate therapeutic compound, and this finding only provides structural-level clues for investigating the druggability of the two target proteins. Notably, monocyte-derived cells (MdCs) were identified as a key cell type in IS, and pseudotemporal analysis revealed dynamic expression patterns of key genes during MdC differentiation. Conclusion ARG1 and PTEN are promising key genes and therapeutic targets for IS. These findings offer novel insights into the molecular mechanisms of IS and potential treatment strategies.