基于TCGA数据库的肾透明细胞癌miRNA预后模型的构建及蛋白互作网络分析

Construction of a prognostic model of miRNA in renal clear cell carcinoma based on TCGA database and analysis of protein interaction network

目的:通过微小RNA(microRNA,miRNA)预后模型筛选肾癌高危人群并进行早期干预治疗,以提高患者的生存率。方法:基于癌症基因图谱(The Cancer Genome Atlas,TCGA)数据库,通过风险生存曲线、受试者工作特征(receiver operating characteristic,ROC)曲线及生存状态图对模型进行评价并对风险评分进行独立预后分析,筛选肾透明细胞癌预后相关的miRNA,建立预后风险模型。结果:①从TCGA数据库初步筛选3613个差异性表达的mRNA和49个差异表达的miRNA。②通过单、多因素Cox回归分析筛选出3个与预后相关的miRNA构建风险预后模型,并且Train组、Test组和所有样品的高低风险组存在明显生存差异;3组样本1、3、5年生存分析的ROC曲线下面积均接近或大于0.70,风险评分可以作为独立预后因子。③在GO富集分析中,主要富集在肾单位的发育、突触后密度及离子跨膜转运蛋白活性等;而在KEGG富集分析中,主要参与其他类型的O-聚糖生物合成、N-聚糖生物合成等通路。结论:基于TCGA数据库构建的3个miRNA风险预后模型可作为肾透明细胞癌的预后生物学标志物。

Objective:Screening individuals at high risk of renal cancer by miRNA prognostic model and performing early intervention treatment to improve patient survival.Methods:The models were evaluated by risk survival curve,receiver operating characteristic(ROC)curve and survival status plots based on the Cancer Genome Atlas(TCGA)database,and an independent prognostic analysis was performed to screen prognosis related miRNAs in clear cell renal cell carcinoma.Results:①Preliminary screening of 3613 differentially expressed mRNAs and 49 differentially expressed miRNAs.②Three miRNAs related to prognosis were screened by univariate and multivariate Cox regression analysis to construct a risk prognostic model,and there were obvious survival differences in the high and low risk groups of the Train group,the Test group,and all samples.The areas under the ROC curve of the 1,3 and 5-year survival analysis of the 3 groups were all close to or greater than 0.70,and the risk score can be used as an independent prognostic factor.③In GO analysis,it is mainly concentrated in the development of nephron epithelium and nephron,postsynaptic density,metal ion transmembrane transporter activity,etc.In KEGG enrichment analysis,it is mainly involved in other types of O-glycan biosynthesis and N-glycan biosynthesis.Conclusion:Three miRNA risk prognostic models based on TCGA database can be used as prognostic biomarkers of renal clear cell carcinoma.