胶质母细胞瘤氧化应激相关基因的表达分析

Expression analysis of oxidative stress-related genes in glioblastoma based on bioinformatics analysis

目的探讨胶质母细胞瘤(GBM)氧化应激关键基因的表达变化。方法从UCSC Xena数据库下载167例GBM基因表达谱数据(TCGA-GBM),从GeneCards数据库下载氧化应激基因集(168个氧化应激相关基因);通过富集分析确定差异表达基因(DEGs),建立蛋白-蛋白相互作用(PPI)网络识别关键基因,利用Spearman相关系数对免疫因子和免疫检查点与关键基因进行相关性分析。结果鉴定出两种与氧化应激相关的GBM分子亚型(Cluster1和Cluster2),Cluster1型GBM生存期明显高于Cluster2型(P<0.05)。共筛选出54个DEGs,在细胞因子/趋化因子相关功能中显著富集。PPI网络鉴定出10个关键基因,即CSF2、CSF3、CCL7、LCN2、CXCL6、MMP8、CCR8、TNFSF11、IL22RA2和ORM1。大多数免疫因子和免疫检查点与关键基因呈正相关。结论本文基于氧化应激相关基因将GBM划分为两个亚型,并且筛选出10个氧化应激基因,可能在GBM的发生、发展过程中起重要作用,也可能对GBM预后评估具有一定的价值。

Objective To investigate the expression changes of key genes related to oxidative stress in glioblastomas(GBM).Methods The transcriptome data of GBM(167 GBM patients)were downloaded from Cancer Genome Atlas(TCGA)database,and the oxidative stress gene set(168 oxidative stress-related genes)was downloaded from GeneCards database.The function of differentially expressed genes(DEGs)was determined by GO and KEGG enrichment analyses,and the protein-protein interaction(PPI)network was established to identify key genes.Spearman correlation coefficient was used to analyze the correlation between immune factors and checkpoints and key genes.Results Two molecular subtypes related to oxidative stress of GBM were identified(Cluster1 and Cluster2),and the survival time of Cluster1 was significantly longer than Cluster2(P<0.05).Fifty-four DEGs related to oxidative stress were identified and they were significantly enriched in cytokine/chemokine related functions.Ten hub genes were identified by PPI network,namely CSF2,CSF3,CCL7,LCN2,CXCL6,MMP8,CCR8,TNFSF11,IL22RA2 and ORM1.Most immune factors and immune checkpoints were positively correlated with the 10 hub genes.Conclusions Our results suggest GBM could be divided into two subtypes based on oxidative stress-related genes.Ten oxidative stress genes were screened out,which may play an important role in the tumorigenesis and development of GBM,and may also have a certain value for the prognosis assessment of GBM patients.