视网膜母细胞瘤免疫细胞特征及关键基因的识别

Identification of key genes and immune cell characteristics of retinoblastoma

目的使用生物信息学手段探究视网膜母细胞瘤(retinoblastoma,RB)潜在肿瘤标志物和免疫细胞特征。方法对GEO数据库的3个基因表达数据集(GSE24673,GSE97508和GSE1108113)进行差异分析,Gene Ontology(GO)功能注释和Kyoto Encyclopedia of Genes and Genomes(KEGG)通路注释。从STRING数据库构建的蛋白互作网络(protein-protein interaction,PPI)中提取出重要模块联合cytoHubba筛选出核心基因,Xena在线平台对核心基因进行生存分析,通过single sample Gene Set Enrichment Analysis(ssGSEA)进行免疫浸润分析。结果通过分析共获得173个共有差异基因,其中上调基因70个,下调基因103个。GO分析发现,差异基因主要富集于DNA复制和有丝分裂等功能通路。KEGG分析发现大量基因富集于p53信号通路和细胞周期等通路。10个核心基因中CDC6,CDC45和KIF20A基因与RB患者的总生存期相关。我们还发现在肿瘤中CD8+T和γδT细胞浸润程度增加。结论筛选出的RB核心基因和免疫浸润细胞有助于我们在分子水平上更好的理解RB的发生发展机制,为确定新的RB预后标志物和免疫治疗提供理论依据。

This study was performed to explore the potential biomarkers and immune cell characteristics of retinoblastoma(RB)through bioinformatics methods.We analyzed three gene expression profiles(GSE24673,GSE97508 and GSE1108113)to acquire differentially expressed genes(DEGs).GO and KEGG analysis were performed to find out DEGs.The important module was extracted from the protein-protein interaction(PPI)network constructed by STRING database,which was combined with cytoHubba to screen out the hub genes.Survival analysis of hub genes was performed on Xena online platform,and single sample Gene Set Enrichment Analysis(ssGSEA)was used for analysis of immune cell infiltration.Data showed that a total of 173 common DEGs were identified,including 70 up-regulated genes and 103 down-regulated genes;GO analysis showed that the differential genes were mainly enriched in DNA replication and mitosis,and KEGG analysis showed that the differential genes were mainly enriched in the p53 signaling pathway and cell cycle.Ten hub genes were screened,and 3 genes(CDC6,CDC45 and KIF20 A)were found to be associated with overall survival in RB patients.We also found there were increased infiltration of CD8+T andγδT cells in tumor patients.In conclusion,the hub genes and the infiltrating immune cells contribute to a better understanding of the occurrence and development of RB at the molecular level,and provide a theoretical basis for the identification of new prognostic biomarkers and immunotherapy for RB.