缺血性脑卒中诊断性生物标志物解析及靶向铜死亡相关基因的实验验证  

Analysis of diagnostic biomarkers for ischemic stroke and experimental validation of targeted cuproptosis related genes

作　　者：陈莹[1,2] 郭晓婧 莫雪妮 马威[1] 武尚志 李相玲 谢婷婷 Chen Ying;Guo Xiaojing;Mo Xueni;Ma Wei;Wu Shangzhi;Li Xiangling;Xie Tingting(Zhuang Yao Institute of Traditional Chinese Medicine,Guangxi University of Chinese Medicine,Nanning 530222,Guangxi Zhuang Autonomous Region,China;Department of Rehabilitation,Guangxi International Zhuang Medical Hospital,Nanning 530022,Guangxi Zhuang Autonomous Region,China)

机构地区：[1]广西中医药大学中医药壮瑶医药研究院,广西壮族自治区南宁市530022 [2]广西国际壮医医院康复科,广西壮族自治区南宁市530022

出　　处：《中国组织工程研究》2025年第35期7562-7570,共9页Chinese Journal of Tissue Engineering Research

基　　金：广西自然科学基金资助项目(2023GXNSFAA026105),项目负责人:陈莹;广西中医药大学校级科研项目(2023QN006),项目负责人:马威。

摘　　要：背景:研究表明,缺血性脑卒中的各个过程都有免疫细胞参与,其中铜死亡也起着关键作用。目的:通过生物信息学筛选出与缺血性脑卒中进展有关的诊断性生物标记物,并对与其发生发展密切相关的铜死亡基因进行分析及验证。方法:从GEO数据库中获取GSE16561芯片,共包含39例缺血性脑卒中组与24例对照组数据,解析缺血性脑卒中芯片数据的差异表达基因,对差异基因进行GO与KEGG富集分析;通过LASSO和Random Forest法,筛选出影响缺血性脑卒中发生发展的关键基因,建立诊断模型并加以验证;通过免疫细胞浸润与加权基因共表达网络对差异基因进行分析,差异表达的免疫相关基因与铜死亡基因取交集,获得铜死亡免疫相关的Hub基因,并进行体外细胞实验,将大鼠海马神经元细胞分为正常组和缺血性脑卒中组,进行qPCR实验验证。结果与结论:①差异分析获得573个差异表达基因,主要富集于免疫反应的正向调节等生物学过程和脂质与动脉粥样硬化等信号通路;②机器学习方法筛选出MFN2、PKM2、CREG1、FOXO3A诊断性基因,对缺血性脑卒中可能具有一定的诊断价值;③免疫浸润分析发现浆细胞、NK细胞静息、巨噬细胞等,表明免疫细胞在缺血性脑卒中的发病中发挥着一定作用;④WGCNA结合免疫浸润分析获得118个关键模块基因,与铜死亡基因取交集获得2个铜死亡与免疫特征基因;4个诊断性基因与Hub基因的相关性分析结果显示FOXO3A与MFN2、PKM2与BCL2L1、MTF1与MFN2、ATP7B与BCL2L1的表达具有相关性;⑤qPCR结果显示,与空白组相比,缺血性脑卒中组基因MTF1、ATP7B存在显著差异,证实ATP7B、MTF1可作为缺血性脑卒中铜死亡的特征基因,可能通过干预ATP7B、MTF1调节铜死亡来改善缺血性脑卒中。BACKGROUND:Studies have shown that immune cells are involved in all processes of ischemic stroke,in which cuproptosis also plays a key role.OBJECTIVE:To screen diagnostic biomarkers related to the progression of ischemic stroke through bioinformatics,and analyze and validate cuproptosis-related genes closely related to the occurrence and development of ischemic stroke.METHODS:The GSE16561 microarray was obtained from the GEO database,containing data from 39 cases of ischemic stroke(ischemic stroke group)and 24 controls(control group).Differentially expressed genes from the ischemic stroke microarray data were analyzed.Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed.By using LASSO and Random Forest methods,key genes affecting the occurrence and development of ischemic stroke were screened,and a diagnostic model was established and validated.Differential gene analysis was performed through immune cell infiltration and weighted gene co expression network.The differentially expressed immune-related genes were intersected with cuproptosis genes to obtain the hub genes related to cuproptosis immunity.In vitro cell experiments were conducted to divide rat hippocampal neurons into a normal group and an ischemic stroke group,and qPCR experiments were performed to verify the results.RESULTS AND CONCLUSION:(1)573 differentially expressed genes were obtained by differential analysis.Differentially expressed genes were mainly enriched in biological processes,such as positive regulation of immune response,and signaling pathways such as lipid and atherosclerosis.(2)Machine learning methods were used to screen diagnostic genes such as MFN2,PKM2,CREG1,and FOXO3A,which may have some diagnostic value for ischemic stroke.(3)Immune infiltration analysis revealed resting plasma cells,NK cells,macrophages,etc.,indicating that immune cells play a certain role in the pathogenesis of ischemic stroke.(4)Weighted gene co-expression network analysis combined with immune infiltration analysis obtai

关 键 词：缺血性脑卒中 机器学习 生物信息学 免疫浸润 铜死亡 细胞实验 ATP7B MTF1 

分 类 号：R496[医药卫生—康复医学] R318[医药卫生—临床医学] R743.3