Abstract
Cellular senescence may contribute to lung ischemia-reperfusion injury (LIRI) through mechanisms such as oxidative stress, inflammatory responses, and epigenetic modifications while forming an intricate interaction network with the immune system. Consequently, therapeutic strategies targeting cellular senescence and immune responses hold promise for developing novel avenues in the prevention and treatment of LIRI. This study systematically integrated differential analysis, functional enrichment analyses (GO, KEGG, GSEA, and GSVA), and consensus clustering analysis to investigate the association between cellular senescence and LIRI. Immune infiltration analysis was employed to dissect the interplay between cellular senescence and immune dysregulation in LIRI. Finally, weighted gene co-expression network analysis (WGCNA) combined with multiple machine learning algorithms (LASSO, RF, and SVM-RFE) was utilized to identify senescence-associated biomarkers and elucidate their potential mechanisms. First, LIRI was found to be associated with multiple senescence- and immune-related pathways. A total of 370 pro-senescence genes were screened for GSVA scoring revealing a significant elevation in senescence scores during LIRI. Differential analysis demonstrated upregulated expression of most pro-senescence genes, particularly CDKN1A in injured tissues. Consensus clustering based on pro-senescence genes stratified LIRI into two distinct senescence subtypes; the high-senescence subtype (C1) exhibited closer resemblance to the disease phenotype. These findings underscore the critical involvement of cellular senescence in the pathogenesis of LIRI. Subsequent WGCNA and machine learning approaches identified four signature genes (ABL2, CSF3, GCH1, NFKB2), which were consistently upregulated in both LIRI and C1 subtypes. ROC curve analysis confirmed their robust diagnostic efficacy further validated in independent cohorts. Notably, these genes exhibited significant positive correlations with senescence scores and CDKN1A expression. Immune infiltration analysis revealed altered immune cell profiles in LIRI with neutrophils showing marked infiltration in both injury and C1 groups. Neutrophil abundance positively correlated with senescence scores as well as the expression of the four signature genes. This study elucidates cellular senescence as a pivotal mechanism in LIRI, with neutrophils potentially playing a central role. The identified signature genes (ABL2、CSF3、GCH1NFKB2) may serve as potential biomarkers and therapeutic targets for LIRI.