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南京医科大学学报(自然科学版) 第42卷第10期
·1376 · Journal of Nanjing Medical University(Natural Sciences) 2022年10月
·基础医学·
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
马牧溪 ,张发财 ,王明生 ,马洪贵 ,钟渠梁 ,胡 欢 ,吴志平 1,3*
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贵州医科大学临床医学院,贵州 贵阳 550000;贵州医科大学附属医院泌尿外科,贵州 贵阳 550000;黔南州人民医院
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泌尿外科,贵州 都匀 558000
[摘 要] 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3 613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。
[关键词] miRNA;肾透明细胞癌预后;生物标志物;蛋白互作网络
[中图分类号] R737.11 [文献标志码] A [文章编号] 1007⁃4368(2022)10⁃1376⁃11
doi:10.7655/NYDXBNS20221005
Construction of a prognostic model of miRNA in renal clear cell carcinoma based on TCGA
database and analysis of protein interaction network
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MA Muxi ,ZHANG Facai ,WANG Mingsheng ,MA Honggui ,ZHONG Quliang ,HU Huan ,WU Zhiping 1,3*
School of Clinical Medicine,Guizhou Medical University,Guiyang 550000;Department of Urology,Affiliated
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Hospital of Guizhou Medical University,Guiyang 550000;Department of Urology,Qiannan People’s Hospital,Duyun
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558000,China
[Abstract] 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:① Preliminary
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.
[基金项目] 贵州省科技计划项目(黔科合支撑[2021]一般060)
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通信作者(Corresponding author),E⁃mail:gzwzp@foxmail.com