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Transcriptomic exploration combined with experimental validation: uncovering the potential value of biomarkers related to ammonia-induced cell death in hepatic ischemia–reperfusion injury

转录组 生物标志物 列线图 免疫系统 基因表达 基因表达谱 生物 肝损伤 基因 细胞损伤 发病机制 计算生物学 小桶 生物信息学 程序性细胞死亡 折叠变化 微阵列分析技术 细胞 微阵列 诊断生物标志物 免疫学 CD8型 医学 外周血单个核细胞 癌症研究 基因表达调控 表型 代谢组学 生物标志物发现 脂肪肝 下调和上调 生物途径
作者
Runyu Zhuang,Junhao Xiao,Benliang Mao,Yong Yan,Wei Yuan,Fan Wu,Bailin Wang,Runyu Zhuang,Junhao Xiao,Benliang Mao,Yong Yan,Wei Yuan,Fan Wu,Bailin Wang
出处
期刊:European Journal of Medical Research [BioMed Central]
卷期号:30 (1)
标识
DOI:10.1186/s40001-025-03450-1
摘要

Abstract Background Hepatic ischemia–reperfusion injury (HIRI) represents the leading cause of postoperative liver dysfunction and failure. Ammonia-induced cell death (ACD), defined by lysosomal and mitochondrial disruption due to intracellular ammonia accumulation, appears to contribute to the pathogenesis of HIRI. Methods Transcriptomic datasets GSE151648 and GSE12720 were retrieved from the Gene Expression Omnibus (GEO), and 467 ACD-related genes were compiled from published reports. Differential expression analysis combined with Weighted Gene Co-expression Network Analysis (WGCNA) was applied to identify candidate genes and assess their functional relevance. Biomarkers closely associated with HIRI were subsequently determined through protein–protein interaction (PPI) network construction, machine learning approaches, and expression validation. A nomogram was then established based on these biomarkers, followed by Gene Set Enrichment Analysis (GSEA), immune infiltration profiling, and network prediction. Furthermore, single-cell analysis was employed to investigate the expression of biomarkers across different cell types. Finally, liver tissues from HIRI mouse models were examined to confirm biomarker expression. Results A total of 586 differentially expressed genes intersected with 762 key module genes, yielding 39 candidates primarily enriched in inflammatory signaling pathways. Among these, LCP1, SLC16A3, and RGS2 emerged as biomarkers, each markedly upregulated in HIRI samples. The biomarker-based nomogram demonstrated robust diagnostic accuracy. Enrichment analyses indicated that the biomarkers were closely related to immune and metabolic pathways. Consistently, immune cell infiltration and immune functions were elevated in HIRI samples and correlated significantly with biomarker expression. Concurrently, single-cell analysis revealed that all three biomarkers were expressed within mononuclear phagocytes, with their expression levels exhibiting significant differences between the HIRI group and the control group. Moreover, multiple miRNAs and lncRNAs were predicted to interact with the identified biomarkers. Validation in HIRI mouse liver tissues confirmed consistency with transcriptomic findings. Conclusion LCP1, SLC16A3, and RGS2 have been identified as biomarkers of HIRI. The study advances understanding of ACD-related genes signatures in HIRI and provides a foundation for future mechanistic research and therapeutic development.
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