Shi Sunyena, Feng Xu, Cao Zhan, Wang Lin, Sun Mingjian, Zhao Ziyi, Sun Wei
Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Cell Mol Neurobiol. 2025 May 25;45(1):51. doi: 10.1007/s10571-025-01567-9.
To investigate the relationship between Endoplasmic Reticulum Stress (ERS) and epilepsy, as well as their biological functions. We downloaded the GSE143272 dataset from the GEO database, identified differentially expressed genes (DEGs), and cross-analyzed them with ERS-related genes from GeneCards and the Molecular Signatures Database (MSigDB). Protein-protein interaction (PPI) networks were constructed, and Hub genes were screened. ROC curve analysis was conducted to assess the diagnostic utility of these genes, followed by qRT-PCR validation. This study identified a total of 83 ERS-related DEGs in epilepsy. PPI network analysis revealed eight feature genes: C-X-C motif chemokine ligand 8 (CXCL8), Toll-like receptor 4 (TLR4), Matrix metalloproteinase 9 (MMP9), Tumor necrosis factor receptor superfamily member 1A (TNFRSF1A), Prostaglandin-endoperoxide synthase 2 (PTGS2), Signal transducer and activator of transcription 1 (STAT1), B-cell lymphoma 2 (BCL2), and RELA proto-oncogene, NF-κB subunit (RELA). ROC curve analysis demonstrated that the combination of these eight feature genes exhibited the highest diagnostic potential. Among them, CXCL8 was the most valuable gene. qRT-PCR analysis showed that CXCL8 mRNA expression was significantly lower in the case group compared to the control group (P < 0.01). The results suggest that ERS is involved in physiological processes such as inflammation and neuronal apoptosis in epilepsy. This provides a bioinformatics evidence for exploring the biological functions and pathology of ERS in epilepsy, as well as serving as a reference for clinical diagnosis and potential therapeutic targets.
为了研究内质网应激(ERS)与癫痫之间的关系及其生物学功能。我们从基因表达综合数据库(GEO数据库)下载了GSE143272数据集,鉴定了差异表达基因(DEGs),并将其与来自基因卡片数据库(GeneCards)和分子特征数据库(MSigDB)的ERS相关基因进行交叉分析。构建了蛋白质-蛋白质相互作用(PPI)网络,并筛选了枢纽基因。进行受试者工作特征(ROC)曲线分析以评估这些基因的诊断效用,随后进行实时荧光定量聚合酶链反应(qRT-PCR)验证。本研究共鉴定出83个与癫痫相关的ERS差异表达基因。PPI网络分析揭示了八个特征基因:C-X-C基序趋化因子配体8(CXCL8)、Toll样受体4(TLR4)、基质金属蛋白酶9(MMP9)、肿瘤坏死因子受体超家族成员1A(TNFRSF1A)、前列腺素内过氧化物合酶2(PTGS2)、信号转导和转录激活因子1(STAT1)、B细胞淋巴瘤2(BCL2)和原癌基因RELA、核因子κB亚基(RELA)。ROC曲线分析表明,这八个特征基因的组合具有最高的诊断潜力。其中,CXCL8是最有价值的基因。qRT-PCR分析显示,与对照组相比,病例组CXCL8 mRNA表达显著降低(P < 0.01)。结果表明,ERS参与了癫痫中的炎症和神经元凋亡等生理过程。这为探索ERS在癫痫中的生物学功能和病理学提供了生物信息学证据,并为临床诊断和潜在治疗靶点提供了参考。