基于ESTIMATE算法探究TCGA数据库免疫相关基因在乳腺癌中的预后价值

Based on ESTIMATE algorithm exploring the significance of immune-related genes in TCGA database in prognosis of breast cancer

目的根据ESTIMATE算法探究TCGA数据库中免疫相关基因在乳腺癌中的预后价值。方法从TCGA数据库获取606例乳腺癌患者的临床信息和肿瘤样本的转录组数据,采用edgeR方法对转录组数据进行差异表达分析,通过ESTIMATE算法筛选出基于免疫分数或间质分数高低分组的差异表达基因;使用R软件绘制差异表达基因的聚类分析热图;使用韦恩图对基于免疫分数和间质分数得到的差异表达基因进行交集分析;运用STRING数据库,搜索并预测表达显著差异基因编码蛋白质之间的相互作用;通过单因素Cox回归分析评估差异表达基因的预后作用;运用DAVID数据库对差异表达基因进行GO富集分析以及KEGG通路富集分析。结果生存分析结果显示,高免疫分数组患者的总生存期中位值943天,而低分组患者总生存期中位值860天,显著高分组患者总生存期显著高于低分组患者(P<0.05);而间质分数与乳腺癌患者总生存期之间无差异(P>0.05)。进一步对免疫分数高分组和低分组患者表达上调的951个差异表达基因进行生存分析,发现160个基因与乳腺癌患者的总生存期显著相关;对上述160个基因进行蛋白质互作分析,富集出与乳腺癌患者总生存率呈正相关的CTLA4、CD8A、CD19、CD27、CD2、IL2、GZMB、IL2RB、CD3E、CD40LG等基因。对上述160个基因进行GO富集和KEGG通路分析,结果显示免疫功能相关信号通路T细胞受体信号通路、造血细胞系、T细胞活化等通路显著富集。结论本研究发现160个具有预后价值的免疫分数相关基因,免疫分数与乳腺癌患者的总生存期、预后改善相关,将为乳腺癌预后判断和靶向治疗提供新的潜在靶点。

Objective The value of relative gene in the TCGA database in the prognosis of breast cancer were analyzed based on the ESTIMATE algorithm.Methods The general information of 606 patients suffered from breast cancer and transcriptome data of tumor samples were obtained from the TCGA database.The edgeR method was used to analyze the differential expression of transcriptome data,and the ESTIMATE algorithm was used to screen out the differentially expressed genes based on the immune scores or interstitial scores grouping.R software was used to make the heat map of cluster analysis of differentially expressed genes.The intersection analysis of differentially expressed genes based on immune scores and interstitial scores was performed by Venn diagram.The STRING database was used to search and predict the interactions between the proteins encoded by the significantly differentially expressed genes.The prognostic effect of differentially expressed genes was evaluated by univariate Cox regression analysis.GO enrichment analysis and KEGG pathway enrichment analysis of differentially expressed genes were performed by DAVID database.Results The results of survival analysis showed that the overall survival of patients in the high immune score group was significantly higher than that in the low immune score group(943 d vs.860 d,P<0.05).There was no significant difference between stromal scores and overall survival of patients with breast cancer(P>0.05).Further survival analysis of 951 differentially expressed genes with up-regulated expression was performed in patients with high and low immune scores,and 160 genes were found to be significantly correlated with overall survival of breast cancer patients.Through the protein interaction analysis of the above 160 genes,CTLA4,CD8A,CD19,CD27,CD2,IL2,GZMB,IL2RB,CD3E,CD40LG and other genes were positively correlated with the overall survival rate of breast cancer patients.GO enrichment and KEGG pathway analysis of the above 160 genes revealed immune function related signaling pathways such as T cell receptor signaling pathway,hematopoietic cell line,and T cell activation.Conclusions In this study,160 genes related to the immune score with prognostic value are found,and the immune score is associated with overall survival and improved prognosis of breast cancer patients,which will provide new potential targets for prognosis judgment and targeted therapy of breast cancer.