基于癌症基因组图谱数据库的胶质瘤中协同调控免疫和线粒体能量代谢关键基因筛选及其免疫浸润分析  

Screening of key genes co-regulating immune and mitochondrial energy metabolism and analysis of immune infiltration in glioma based on the Cancer Genome Atlas database

作　　者：华丹 葛强[2] 常留栓[2] 贺一凡 史永恒[3] Hua Dan;Ge Qiang;Chang Liushuan;He Yifan;Shi Yongheng(Department of Neuropathology,Tianjin Neurological Institute,Tianjin Medical University General Hospital,Tianjin 300052,China;Department of Military Preventive Medicine,Faculty of Health Services,Logistic University of People's Armed Police Force,Tianjin 300309,China;School of Pharmacy,Shaanxi University of Chinese Medicine,Xianyang 712046,China)

机构地区：[1]天津医科大学总医院、天津市神经病学研究所神经病理学研究室,天津300052 [2]武警后勤学院卫生勤务系军事预防医学教研室,天津300309 [3]陕西中医药大学药学院,咸阳712046

出　　处：《肿瘤研究与临床》2024年第7期496-502,共7页Cancer Research and Clinic

基　　金：国家自然科学基金(82302908);天津市自然科学基金(16JCQNJC13400);中国留学基金委项目(201606945004);中央高校基本科研业务费专项资金资助项目(3332021084);天津医科大学总医院“卓越新星”培育项目(2020年)。

摘　　要：目的基于生物信息学方法筛选胶质瘤中协同调控免疫和线粒体能量代谢的关键基因,探讨这些基因与免疫浸润的关系。方法从癌症基因组图谱(TCGA)数据库中收集671例胶质瘤样本(肿瘤组)和5例非肿瘤脑组织样本(对照组),数据下载时间为2023年11月13日。检索GeneCards数据库和已发表文献中免疫相关基因(IRG)和线粒体能量代谢相关基因(MEMRG),经合并去重复后,对IRG和MEMRG取交集共得到76个免疫和线粒体能量代谢共相关基因(IR&MEMRG)。使用R软件limma包,筛选肿瘤组和对照组中的差异表达基因(DEG),与IR&MEMRG取交集得到胶质瘤中免疫和线粒体能量代谢共相关差异表达基因(IR&MEMRDEG)。采用R软件中clusterProfiler包对IR&MEMRDEG进行基因本体(GO)及京都基因和基因组百科全书(KEGG)富集分析。使用STRINGv12.0在线数据库(https://cn.string-db.org/),利用获得的IR&MEMRDEG构建蛋白质互作网络,获得排名前5位的关键核心基因。采用单样本基因集富集分析(ssGSEA)分析所有样本中各免疫细胞浸润的相对丰度,得出样本中免疫细胞浸润矩阵。利用R软件中ggplot2包分析免疫细胞浸润丰度在肿瘤组和对照组间的差异;R软件pheatmap包绘制相关性热图展示免疫细胞自身的相关性,基于Spearman算法并利用R软件ggplot2包计算蛋白质互作网络内排名前5位的关键核心基因与免疫细胞的相关性。结果TCGA数据库中,肿瘤组和对照组有3623个DEG;其中上调表达基因1711个,下调表达基因1912个。对DEG与获得的IR&MEMRG取交集,得到11个IR&MEMRDEG,分别为EIF4EBP1、TP53、IDH1、PRCKZ、CD200、GPI、PGM2、PKLR、AK2、ATP4A和ALDH3B1。GO富集分析结果显示,11个IR&MEMRDEG在生物过程层面主要富集在ATP代谢和ADP代谢、嘌呤核苷二磷酸代谢、嘌呤核糖核苷二磷酸代谢和核糖核苷二磷酸代谢;细胞成分层面主要富集在纤维胶凝蛋白-1富集颗粒、分泌颗粒腔、细胞质囊泡�Objective To screen key genes that co-regulate immune and mitochondrial energy metabolism through bioinformatics methods and to investigate the relationship between the key genes and immune infiltration.Methods A total of 671 glioma samples(the tumor group)and 5 non-tumor brain tissue samples(the control group)were collected from the Cancer Genome Atlas(TCGA)database on November 13,2023.Through a comprehensive search of the GeneCards database and immune-related genes(IRG)and mitochondrial energy metabolism-related genes(MEMRG)in previous published literatures,76 IRG and MEMRG(IR&MEMRG)were obtained by taking the intersection of IRG and MEMRG after merging and deduplicating.The limma package in R software was used to screen the differentially expressed genes(DEG)between the tumor group and the control group.Then,immune-related&mitochondrial energy metabolism-related differentially expressed genes(IR&MEMRDEG)were obtained by intersecting with IR&MEMRG.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted on the IR&MEMRDEG through the clusterProfiler package in R software.The STRINGv12.0 online database(https://cn.string-db.org/)was employed to construct a protein interaction network based on IR&MEMRDEG and to identify the top 5 key core genes.Single-sample gene-set enrichment analysis(ssGSEA)was used to determine the relative abundance of immune cell infiltration in all samples,and the immune cell infiltration matrices for both the tumor and the control groups were acquired.The expression differences in infiltration abundance of the immune cells in the tumor group and the control group were analyzing by using the ggplot2 package in R software.The heat map was drawn by utilizing the R software pheatmap package to show self-correlation of immune cells.The correlation between the top 5 key genes in the protein interaction network and immune cells was calculated by using the Spearman algorithm and the R software ggplot2 package.Results A total of 3623 DEGs were identified

关 键 词：胶质瘤 免疫浸润 线粒体 能量代谢 

分 类 号：R739.4[医药卫生—肿瘤]