Identification of PANoptosis-associated genes in hepatic ischemia-reperfusion injury by integrated bioinformatics analysis and machine learning

Abstract

Background In the context of liver resection and transplantation, hepatic ischemia-reperfusion injury (hepatic IRI) remains a significant clinical challenge, profoundly impacting both postoperative short- and long-term recovery. A novel cell death pathway, PANoptosis, is implicated in infections, malignancies and sterile inflammation. While the specific role of PANoptosis in the development of hepatic IRI remains unclear, this study aims to provide new insights and perspectives into the underlying mechanisms, thereby addressing this knowledge gap. Methods We constructed a panoptosis-related gene panel and analyzed seven gene expression datasets on hepatic IRI available in the GEO database. Differential expression analysis, enrichment analysis, and multi-omics consensus analysis were performed on panoptosis-hepatic IRI DEGs. Core genes associated with hepatic IRI were identified using ten machine learning algorithms. Single-cell analysis and two immune infiltration algorithms were employed to assess immune cell infiltration and their interplay with core genes. To validate our findings, core gene expression was validated via serum detection, H&E staining, and quantitative real-time PCR in a mouse hepatic IRI. Results We identified 52 DE-PANRGs from a constructed panoptosis-related gene set of 485 genes. Functional enrichment analysis indicated their participation in necroptosis, apoptosis, cytokine-cytokine receptor interaction, NOD-like receptor signaling, and other related processes. Three distinct molecular subtypes of hepatic IRI were identified, with subtype C2 showing high expression of DE-PANRGs. Machine learning identified eight feature genes (IER3, CDKN1A, EMP1, IL1B, BTG3, JUN, HSPB1, and IL1A) with diagnostic potential. The function and correlation of core genes were confirmed through single-cell and immune infiltration analyses, and validated in a mouse hepatic IRI model. Conclusion Utilizing a panoptosis gene set, this study identified eight core genes involved in hepatic IRI, providing novel insights into panoptosis’ role in hepatic IRI.