Integrative bioinformatics and machine learning approaches identify inflammation-related genes and drug candidates for future preclinical validation in ischemic stroke.

ABSTRACT:

Background

Inflammation 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.

Methods

Transcriptome 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.

Results

Four 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 interaction

SUBMITTER: Yuan J 

PROVIDER: S-EPMC12648819 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature