基于生物信息学筛选肝脏缺血-再灌注损伤泛凋亡关键基因

Screening key genes of PANoptosis in hepatic ischemia-reperfusion injury based on bioinformatics

    摘要
  • 摘要:
    目的 探讨泛凋亡与肝脏缺血-再灌注损伤（HIRI）之间的关系，筛选HIRI的泛凋亡关键基因。
    方法 通过基因表达综合数据库和GeneCards数据库获得泛凋亡相关差异表达基因（PDG）。通过基因本体（GO）、京都基因与基因组百科全书（KEGG）以及基因集富集分析（GSEA）探索PDG相关的生物学途径。构建蛋白质相互作用网络。筛选关键基因，评估关键基因的诊断价值，并在HIRI小鼠中进行验证。基于转录样本中不同细胞类型相对丰度算法进行免疫细胞浸润分析。
    结果 经筛选共获得16个PDG。GO结果显示，PDG与细胞代谢密切相关；KEGG结果显示，PDG主要富集在细胞凋亡等细胞死亡途径以及肿瘤坏死因子信号通路等免疫相关信号通路；GSEA结果显示，关键基因主要富集在丝裂原活化蛋白激酶（MAPK）信号通路等免疫相关信号通路。筛选出DFFB和TNFSF10 2个关键基因，其在诊断HIRI方面准确度高，曲线下面积分别为0.964、1.000。Cibersort分析结果显示，初始B细胞浸润丰度与DFFB表达呈正相关（r=0.7，P=0.035），M2型巨噬细胞浸润丰度与TNFSF10表达呈正相关（r=0.68，P=0.045）。
    结论 泛凋亡相关基因DFFB和TNFSF10可能是HIRI潜在的生物标志物和治疗靶点。

     

    Abstract:
    Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI.
    Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the liver tissues of HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts.
    Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism, KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor (TNF) signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.7, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045).
    Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

     

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