ArticleBMC neurology2025
Integrative bioinformatics and machine learning approaches identify inflammation-related genes and drug candidates for future preclinical validation in ischemic stroke.
Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundInflammation plays a critical role in ischemic stroke (IS). This study aimed to identify inflammation-related genes and explore potential pharmacological agents for future preclinical validation in IS.
methodsTranscriptome data were integrated to identify inflammation-related genes, which were functionally characterized and evaluated for diagnostic potential, with single-cell analysis and computational drug prediction.
resultsFour inflammation-related genes, C-C chemokine receptor type 7 (CCR7), CD7, CD96, and interleukin-7 receptor (IL-7R), were identified from integrated transcriptome analyses. These genes showed promising diagnostic potential (area under the curve (AUC) > 0.8) and were functionally associated with cytokine signaling, immune interactions, and calcium homeostasis. Drug-gene interaction and molecular docking analyses indicated that capecitabine and ruxolitinib are potential candidates for modulating CD96 and IL-7R.
conclusionThis study reveals four inflammation-related genes with preliminary diagnostic value and proposes capecitabine and ruxolitinib as candidate drugs for future preclinical research on IS.
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