Myocardial ischemia-reperfusion injury (MIRI) limits the success of reperfusion therapies. Identifying potential biomarkers within the nuclear factor kappa-B (NF-κB) pathway is critical for developing new treatments. Transcriptomic data from mouse MIRI models were combined with NF-κB pathway-related genes. Candidate genes were identified from the overlapping differentially expressed genes. Potential biomarkers were selected via protein-protein interaction network analysis and validated with independent datasets. We performed functional analysis, built transcription factor and competing endogenous RNA (ceRNA) networks, and conducted drug prediction and molecular docking. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation was performed in a MIRI mouse model. Nine candidate genes were identified, with Nfkbia and Icam1 emerging as potential biomarkers. Functional analysis connected Nfkbia to mitochondrial metabolism and Icam1 to extracellular matrix processes/nuclear processes. A regulatory network involving mmu-miR-706 and seven lncRNAs was constructed. Drug prediction identified Tosyllysyl Chloromethyl Ketone (TLCK) as exhibiting favourable binding affinity for both targets. Experimental validation confirmed significant upregulation of Nfkbia and Icam1 in MIRI. This study established Nfkbia and Icam1 as key NF-κB-associated genes in MIRI and constructed a ceRNA network. These findings advance our understanding of MIRI mechanisms and support future therapy development. However, these findings were based on bioinformatics analysis and preliminary experimental validation, and required further functional experiments for confirmation.
Ting et al. (Mon,) studied this question.
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