目的 筛选肿瘤微环境(tumor microenvironment,TME)中预后相关免疫基因并解析其在乳腺癌中的预后价值.方法 获取癌症基因组图谱(the cancer genome atlas,TCGA)数据库1 086 例乳腺癌样本和145 例正常样本的转录组数据和临床信息,排除无随访资料或随访时间＜1d的137 例样本后采用ESTIMATE算法计算免疫评分和基质评分;根据免疫评分和基质评分(高分组 vs.低分组)筛选差异表达基因(differentially expressed genes,DEGs);通过DEGs构建蛋白质-蛋白质相互作用(protein-protein in-teraction,PPI)网络,探究乳腺癌DEGs中的核心基因;通过单基因批量生存分析,明确核心基因与乳腺癌患者总生存期的相关性;通过RT-qPCR实验对数据库分析结果进行mRNA水平验证.结果 与N0 期比较,N1 期的患者免疫评分降低;与Stage Ⅰ期比较,Stage Ⅱ期、Ⅲ期患者免疫评分降低.Kaplan-Meier结果显示,与免疫评分低分组比较,高分组患者总生存期延长.筛选出免疫评分(高分组 vs.低分组)相关的200 个DEGs.基因本体论(gene ontology,GO)分析和京都基因与基因组百科全书数据库(Kyoto en-cyclopedia of genes and genomes,KEGG)富集分析筛选出T细胞激活、激活免疫反应、MHC Ⅱ类蛋白复合物、T细胞受体信号通路等免疫相关通路.蛋白质互作(potein-protein interaction,PPI)分析找到Degree值排名前15 的核心(hub)基因,单基因批量生存分析从中筛选出 9 个与乳腺癌预后显著相关的基因.RT-qPCR实验结果显示,与恶性程度较低的乳腺癌细胞相比,上述9 个基因在恶性程度较高的三阴性乳腺癌细胞中表达水平下降.基因组富集分析(gene set enrichment analysis,GSEA)显示,免疫相关基因HLA-DRA的高表达水平与乳腺癌、雌激素信号通路显著相关.结论 乳腺癌肿瘤微环境中免疫评分高的患者总生存期显著延长.免疫相关基因HLA-DRA可能是预测乳腺癌患者预后的潜在生物标志物.
Mining breast cancer prognostic biomarkers based on transcriptomic data
Objective To screen prognostic-related immune genes from tumor microenvironmet(TME)and to analyze the prognostic value in breast cancer.Methods Transcriptomic data and clinical information of 1 086 breast cancer samples and 145 normal samples from the cancer genome atlas(TCGA)database were obtained,and the ESTIMATE algorithm was used to cal-culate the immune score and the stromal score after excluding 137 samples that had no follow-up information or had a follow-up time of＜1 day;Differentially expressed genes(DEGs)were screened according to immune score and stromal score(high group vs.low group);The protein-protein interaction(PPI)network was constructed by DEGs to explore the hub genes in breast cancer DEGs;the correlation between hub genes and overall survival of breast cancer pa-tients was determined by single gene batch survival analysis;the results of the database analysis were verified at the mRNA level by RT-qPCR.Results Compared with stage N0,the immune score of patients in stage N1 was lower;compared with StageⅠ,the immune scores of patients with Stage Ⅱ and Stage Ⅲ were lower.The results of the Kaplan-Meier method showed that compared with the low group of immune score the overall survival in the high group of patients were prolonged.The 200 DEGs associated with immune score(high group vs.low group)were screened.Gene ontology analysis(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses screened immune-related pathways such as T-cell activation,activation of immune response,MHC classⅡprotein complex,and T-cell receptor signaling pathway.Pro-tein-protein interaction(PPI)indentified the top fifteen hub genes based on Degree value,a-mong which genes significantly associated with breast cancer prognosis were selected through single-gene batch survival analysis.The results of RT-qPCR experiments showed that the ex-pression levels of the above nine genes were decreased in more malignant triple-negative breast cancer cells compared with less malignant breast cancer cells.Gene set enrichment analysis(GSEA)showed that high expression levels of the immune-related gene HLA-DRA were signif-icantly associated with breast cancer and oestrogen signaling pathways.Conclusion The over-all survival of patients with high immune score in breast cancer tumor microenvironment is sig-nificantly prolonged.The immune-related gene HLA-DRA may be a potential biomarker for predicting the prognosis of breast cancer patients.
breast cancerimmune scoredifferential expression analysisfunctional enrich-ment analysissurvival analysis
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NSTL
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