Identification of Key Biomarkers Associated with Immunogenic Cell Death and Their Regulatory Mechanisms in Severe Acute Pancreatitis Based on WGCNA and Machine Learning

基于WGCNA和机器学习识别重症急性胰腺炎免疫原性细胞死亡相关关键生物标志物及其调控机制

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作者:Zhengjian Wang, Jin Liu, Yuting Wang, Hui Guo, Fan Li, Yinan Cao, Liang Zhao, Hailong Chen

Abstract

Immunogenic cell death (ICD) is a form of programmed cell death with a strong sense of inflammatory detection, whose powerful situational awareness can cause the reactivation of aberrant immunity. However, the role of ICD in the pathogenesis of severe acute pancreatitis (SAP) has yet to be investigated. This study aims to explore the pivotal genes associated with ICD in SAP and how they relate to immune infiltration and short-chain fatty acids (SCFAs), in order to provide a theoretical foundation for further, in-depth mechanistic studies. We downloaded GSE194331 datasets from the Gene Expression Omnibus (GEO). The use of differentially expressed gene (DEG) analysis; weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression analysis allowed us to identify a total of three ICD-related hub genes (LY96, BCL2, IFNGR1) in SAP. Furthermore, single sample gene set enrichment analysis (ssGSEA) demonstrated that hub genes are closely associated with the infiltration of specific immune cells, the activation of immune pathways and the metabolism of SCFAs (especially butyrate). These findings were validated through the analysis of gene expression patterns in both clinical patients and rat animal models of SAP. In conclusion, the first concept of ICD in the pathogenesis of SAP was proposed in our study. This has important implications for future investigations into the pro-inflammatory immune mechanisms mediated by damage-associated molecular patterns (DAMPs) in the late stages of SAP.

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