基于GEO数据库对多原发肺癌差异表达基因的生物信息学分析  

Bioinformatics analysis on differentially expressed genes in multiple primary lung cancers based on GEO database

作　　者：刘博 孙超[1] 王旭[1] 马克威[1] LIU Bo;SUN Chao;WANG Xu;MA Kewei(Tumor Center,First Hospital,Jilin University,Changchun 130021,China)

机构地区：[1]吉林大学第一医院肿瘤中心,吉林长春130021

出　　处：《吉林大学学报(医学版)》2025年第2期437-446,共10页Journal of Jilin University:Medicine Edition

基　　金：国家自然科学基金项目(81501962);吉林大学科研项目(Z61007523124090432);吉林大学横向科研项目(2018175)。

摘　　要：目的:采用生物信息学方法筛选多原发肺癌(MPLCs)的差异表达基因(DEGs),分析其生物学功能以及对肺腺癌预后的影响。方法:在高通量基因表达综合数据库(GEO)下载GSE200972单细胞转录组测序数据。采用R软件进行数据初步处理后,采用Seurat R包进行数据处理与细胞聚类及注释并得到DEGs。采用clusterProfiler R包进行基因集富集分析(GSEA),采用STRING数据库和Cytoscape软件建立蛋白-蛋白相互作用(PPI)网络并筛选关键基因(Hub基因),采用基因表达水平值的交互式分析(GEPIA)检测基因在肺腺癌数据库中的表达水平,采用实时荧光定量PCR (RT-qPCR)法检测基因在A549细胞原位移植瘤小鼠肿瘤与正常小鼠肺组织中的表达情况,采用Kaplan Meier-Plotter软件进行预后分析。结果:细胞聚类分析共识别出上皮细胞、内皮细胞、成纤维细胞、T细胞和自然杀伤(NK)细胞、B细胞、髓系细胞和肥大细胞共7种细胞类型,以及肿瘤上皮细胞与正常上皮细胞14 605个DEGs。GSEA分析,得到4个在肿瘤样本中发生激活的通路[原癌基因蛋白(MYC)通路、P53通路、氧化磷酸化通路和糖酵解通路]以及1个抑制通路[肿瘤坏死因子α/核因子κB (TNF-α/NF-κB)通路]。筛选PPI网络中的CXC趋化因子8 (CXCL8)、甘油醛-3-磷酸脱氢酶(GAPDH)、趋化因子受体4 (CXCR4)、鼠类肉瘤病毒癌基因(KRAS)、CXC趋化因子1 (CXCL1)、趋化因子配体2 (CCL2)、黏蛋白1 (MUC1)和分泌型磷蛋白1 (SPP1)为Hub基因。GEPIA数据库分析与动物实验,与肺正常组织比较,在非小细胞肺癌组织中SPP1 mRNA表达水平升高(P<0.01)。Kaplan-Meier生存曲线分析,SPP1高表达患者总生存期(OS)短于低表达患者(P<0.01)。结论:MPLCs中不仅有原癌基因相关通路的激活,也有抑癌通路起拮抗肿瘤进展作用,同时非小细胞肺癌中SPP1基因表达水平升高提示有相对较差的预后。Objective:To screen out the differentially expressed genes(DEGs)in multiple primary lung cancers(MPLCs)using bioinformatics methods,and to analyze their biological functions and their influence in the prognosis of lung adenocarcinoma.Methods:Single-cell transcriptome sequencing data(GSE200972)was downloaded from the Gene Expression Omnibus(GEO)database.After preliminary data processing with R software,the Seurat R package was used for data processing,cell clustering,and annotation.The clusterProfiler R package was used for Gene Set Enrichment Analysis(GSEA).The STRING database and Cytoscape software were employed to construct the protein-protein interaction(PPI)network and to screen out the key genes(Hub genes).The gene expression levels in the lung adenocarcinoma database were analyzed using Gene Expression Profiling Interactive Analysis(GEPIA)database.Real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the gene expression in tumor tissue of A549 xenograft mice and lung tissue of normal mice.Kaplan-Meier Plotter was used for prognosis analysis.Results:Seven cell types were identified from cell clustering analysis,which were epithelial cells,endothelial cells,fibroblasts,T cells and natural killer(NK)cells,B cells,myeloid cells,and mast cells.A total of 14605 DEGs were screened out between tumor epithelial cells and normal epithelial cells.The GSEA results revealed four activated pathways in tumor samples[myelocytomatosis oncogene(MYC)pathway,P53 pathway,oxidative phosphorylation pathway and glycolysis pathway]and one inhibited pathway[tumor necrosis factor-α(TNF-α)and nuclear factor kappa B(NF-κB)pathway].The Hub genes identified from PPI network included CXC motif chemokine ligand 8(CXCL8),glyceraldehyde-3-phosphate dehydrogenase(GAPDH),CXC motif chemokine receptor 4(CXCR4),kirsten rat sarcoma viral proto-oncogene(KRAS),CXC motif chemokine ligand 1(CXCL1),C-C motif chemokine ligand 2(CCL2),mucin 1(MUC1),and secreted phosphoprotein 1(SPP1).The GEPIA database analysis and animal experimen

关 键 词：多原发肺癌 单细胞转录组测序 生物信息学 基因集富集分析 生存分析 

分 类 号：R734.2[医药卫生—肿瘤]