基于GEO数据库筛选胶质母细胞瘤相关差异基因及信号通路  

Key genes and signaling pathways of glioblastoma based on GEO database

作　　者：韩阳[1] HAN Yang(Department of Clinical Laboratory,Beijing Friendship Hospital,Capital Medical University,Beijing 100050,China)

机构地区：[1]首都医科大学附属北京友谊医院检验科,北京100050

出　　处：《国际检验医学杂志》2023年第20期2473-2478,共6页International Journal of Laboratory Medicine

基　　金：首都医科大学附属北京友谊医院种子计划人才项目(YYZZ202249)。

摘　　要：目的使用基因表达谱数据库(GEO)快速筛选出与胶质母细胞瘤的发生、发展过程密切相关的差异基因及信号通路。方法利用生物信息学分析方法在GEO数据库中选择GSE31262数据集作为主要分析对象,包括5个成人神经干细胞个体样本和9个胶质母细胞瘤干细胞个体样本。从这些样本中筛选潜在的差异基因,使用京都基因和基因组百科全书(KEGG)通路分析与基因本体论(GO)富集分析对筛选到的差异基因进行对比。在STRING在线数据库(https://string-db.org/)中,对筛选出来的差异表达基因所编码的蛋白,构建蛋白质-蛋白质相互作用(PPI)分析网络,从而进一步筛选确定评分水平最高的前10位基因。通过癌症基因图谱(TCGA)、免疫细胞浸润分析及受试者工作特征(ROC)曲线分析等方法,分析差异基因与胶质母细胞瘤预后情况的相关性及其诊断价值。结果通过筛选GSE31262数据集得到差异基因共2692个(上调基因1182个,下调基因1510个)。KEGG通路分析和GO富集分析的结果发现,上述差异基因主要涉及细胞器裂变、核分裂、胚胎器官发育、染色体分离、轴突生成、胶质细胞再生,主要参与细胞内吞作用、溶酶体、MAPK信号通路、细胞周期、人乳头瘤病毒感染、人类免疫缺陷病毒感染等过程。在PPI网络中筛选出的评分居前10位的关键差异基因分别为CDK1、CCNB1、CCNA2、BUB1、KIF11、TOP2A、CCNB2、CHEK1、RRM2和ASPM,均与胶质母细胞瘤预后有关(P<0.0001)。免疫细胞浸润分析表明,Th2细胞的浸润水平与10个基因的表达呈正相关,巨噬细胞与RRM2的表达呈负相关,与其他9个基因的表达呈正相关。ROC曲线分析显示,10个基因在胶质母细胞瘤中均有较高的诊断价值。结论筛选得到的10个差异基因为CDK1、CCNB1、CCNA2、BUB1、KIF11、TOP2A、CCNB2、CHEK1、RRM2和ASPM,上述基因有望成为胶质母细胞瘤诊断及治疗的潜在分子靶点。Objective To screen the genes and signaling pathways closely related to the occurrence and development of glioblastoma in Gene Expression Omnibus(GEO)database by bioinformatics analysis,and to provide new ideas for further diagnosis and treatment.Methods GSE31262 gene expression profile data set was selected as analysis objects in GEO database,including 5 adult neural stem cell samples and 9 glioblastoma stem cell samples.The differentially expressed genes were screened out,and gene ontology(GO)enrichment analysis and genome database(KEGG)pathway analysis were performed for the differentially expressed genes.In the STRING online database,protein-protein interaction(PPI)network was constructed for the encoding proteins of the above screened differentially expressed genes,and the top 10 differentially expressed genes were screened.The relationship between key genes and prognosis of glioblastoma patients was analyzed from the Cancer Genome Atlas(TCGA)database.Immune infiltration analysis and receiver operating characteristic(ROC)curve analysis were also performed.Results Totally 2692 samples were selected from GSE31262 dataset,among which 1182 were up-regulated and 1510 down-regulated.GO enrichment analysis and KEGG pathway analysis showed that it was mainly involved in organelle fission,nuclear division,embryonic organ development,chromosome separation,axon generation,glial cell regeneration,protein localization in the cell periphery,etc.It is also mainly involved in cell endocytosis,lysosome,MAPK signaling pathway,cell cycle,human papillomavirus infection,human immunodeficiency virus infection,etc.In the PPI network,the top 10 key genes were CDK1,CCNB1,CCNA2,BUB1,KIF11,TOP2A,CCNB2,CHEK1,RRM2 and ASPM.The 10 differentially expressed genes were associated with patient prognosis(P<0.0001).Immune infiltration analysis showed that the infiltration level of Th2 cells was positively correlated with the expression of 10 genes,while macrophages were negatively correlated with the expression of RRM2,and significantly positi

关 键 词：胶质母细胞瘤 生物信息学 差异基因 信号通路 

分 类 号：R739.4[医药卫生—肿瘤]