COMMD7在脑低级别胶质瘤发生发展中作用机制的生物信息学分析  

Bioinformatics analysis on mechanism of COMMD7 in occurrence and development of brain low-grade glioma

作　　者：王小燕 胡溢洪 韩语诚 邹先琼 WANG Xiaoyan;HU Yihong;HAN Yucheng;ZOU Xianqiong(Experimental Teaching Center,School of Intelligent Medicine and Biotechnology,Guilin Medical University,Guilin 541199,China;Key Laboratory of Biochemistry and Molecular Biology of Guangxi Institutions of Higher Learning,Guilin 541199,China;Department of Biomedical Engineering,School of Intelligent Medicine and Biotechnology,Guilin Medical University,Guilin 541199,China)

机构地区：[1]桂林医学院智能医学与生物技术学院实验教学中心,广西桂林541199 [2]广西高校生物化学与分子生物学重点实验室,广西桂林541199 [3]桂林医学院智能医学与生物技术学院生物医学工程教研室,广西桂林541199

出　　处：《吉林大学学报（医学版）》2023年第2期414-424,共11页Journal of Jilin University：Medicine Edition

基　　金：国家自然科学基金项目(82160185);广西壮族自治区教育厅高校中青年教师基础能力提升项目(2023KY0525)。

摘　　要：目的:通过生物信息学方法分析COMM域包含蛋白质7 (COMMD7)的表达水平与脑低级别胶质瘤(LGG)患者预后之间的关系,以期寻找脑LGG新的潜在生物标志物,并建立预后预测模型,为患者预后预测及个性化治疗提供依据。方法:从UCSC基因组数据库下载523个脑LGG样本和1 152正常样本的数据。采用Mann-Whitney U检验分析COMMD7在脑LGG样本和正常样本中的表达差异,并采用人类蛋白图谱(HPA)数据库进行验证。使用R语言的DESeq软件包对COMMD7低表达组和COMMD7高表达组脑LGG样本进行差异表达基因(DEGs)鉴定,采用R语言的pROC软件包进行受试者工作特征(ROC)曲线分析,采用单因素和多因素Cox回归分析COMMD7表达与脑LGG患者临床病理特征的关系及对脑LGG患者1、3和5年生存率的影响,采用R语言的ggplot2软件包构建森林图,采用R语言的RMS软件包和Survival软件包构建列线图和Calibration预测模型,采用比例风险回归模型分析COMMD7用于区分脑LGG样本和正常样本的诊断价值。采用GEPIA数据库及Oncolnc数据库进一步验证COMMD7与脑LGG患者预后的关系。使用基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)对DEGs进行功能和通路富集分析,使用基因集富集分析(GSEA)获得DEGs显著富集的基因集,采用TISIDB数据库分析COMMD7表达与脑LGG患者免疫细胞浸润之间的相关性。结果:COMMD7在脑LGG样本中表达明显上调,HPA检测结果显示COMMD7在脑LGG样本中高表达。分析得到了764个DEGs (|log_(2)FC|>1,P<0.05),包括654个上调和110个下调DEGs。基于多因素分析的预测模型显示COMMD7是一个独立的预后因素。ROC分析,COMMD7用于区分癌组织和癌旁组织具有较高的诊断价值[ROC曲线下面积(AUC)=0.835,95%CI:0.816~0.853]。Cox回归分析,COMMD7高表达组脑LGG患者生存率明显低于COMMD7低表达组,COMMD7高表达与LGG患者的预后不良呈明显正相关关系(P<0.001)。GEPIA数据库514个�Objective:To analyze the relationship between the expression level of COMM domaincontaining protein 7(COMMD7)and prognosis of the brain low-grade glioma(LGG)patients by bioinformatics method,and to find new potential biomarkers of brain LGG,and to establish the prognostic prediction model,and to provide the basis for the prognostic prediction and individualized treatment of the patients.Methods:A total of 523 brain LGG samples and 1152 normal samples were downloaded from the UCSC Genome Database.Mann-whitney U test was used to analyze the expression difference of COMMD7 between brain LGG samples and normal samples.The Human Protein Atlas(HPA)Database was used to verify the results.DESeq software package of R language was used to screen the differentially expressed genes(DEGs)in the brain LGG samples in low expression of COMMD7 group and high expression of COMMD7 group;pROC software package of R language was used to perform the receiver operating characteristic(ROC)curve,univariate and multivariate Cox regression analysis were used to analyze the relationship between the COMMD7 expression and clinicopathological features of the brain LGG patients and its effects on the 1,3,and 5-year survival rates of the brain LGG patients;ggplot2 software package of R language was used to construct the forestplot;RMS software package of R language and survival package were used to construct the Nomogram and Calibration prediction model;the proportional risk regression model was used to analyze the diagnostic value of COMMD7 in distinguishing the brain LGG samples from normal samples.GEPIA and Oncolnc Databases were used to further verify the relationship between COMMD7 and prognosis of the brain LGG patients.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to analyze the function and pathway enrichment of the DEGs;Gene Set Enrichment Analysis(GSEA)was used to obtain the significantly enriched gene sets of DEG;TISIDB Database was used to analyze the correlation between the COMMD7 exp

关 键 词：COMM域包含蛋白质7 脑低级别胶质瘤 生物信息学 预后 免疫浸润 

分 类 号：R739.41[医药卫生—肿瘤]