山东大学学报 (医学版) ›› 2020, Vol. 58 ›› Issue (7): 47-52.doi: 10.6040/j.issn.1671-7554.0.2020.0663
• • 上一篇
史爽1,2,李娟1,2,米琦1,2,王允山1,2,杜鲁涛1,2,王传新1,2
SHI Shuang1,2, LI Juan1,2, MI Qi1,2, WANG Yunshan1,2, DU Lutao1,2, WANG Chuanxin1,2
摘要: 目的 筛选与胃癌预后存在关联性的微小RNAs(miRNAs)生物标志物,构建风险评分模型用于患者预后评估。 方法 基于人类癌症和肿瘤基因图谱(TCGA)数据库下载胃癌miRNAs表达谱数据及样本相关临床信息,通过“DESeq2”软件包对miRNAs表达谱进行差异分析。采用单因素Cox回归分析和Kaplan-Meier生存分析筛选与预后存在关联性的miRNAs,并将预后miRNAs纳入多因素Cox回归分析用于预后风险评分模型的构建。通过“timeROC”软件包绘制受试者工作特征曲线(ROC),对模型效能进行评价。最后通过在线数据库对miRNAs可能结合的信使RNAs(mRNAs)进行预测,并通过基因本体(GO)、京都基因与基因组百科全书(KEGG)预测其功能。 结果 以log2 | Fold Change |>1,P<0.05为标准,筛选得到248个胃癌组织中差异表达的miRNAs。通过单因素Cox回归分析及Kaplan-Meier生存分析筛选到6个与患者总体生存率有关联性的差异表达的miRNAs,随后使用多因素Cox回归分析成功构建胃癌miRNAs预后风险评分模型,风险评分=0.048 35×miR-181b-1 +0.112 06×miR-548d-1+0.068 00×miR-675+0.075 87×miR-708+1.175 21×miR-4640+0.089 89×miR-4709。Kaplan-Meier生存曲线结果显示,风险评分高的患者预后较差(P<0.001);模型5年总体生存率ROC曲线下面积(AUC)为0.776,证明该模型能够有效预测胃癌患者预后风险。GO和KEGG功能分析结果显示,模型miRNAs分子参与多个肿瘤相关代谢通路。 结论 成功构建了miRNAs预后风险评分模型,且该模型对胃癌患者生存状态具有良好的预测效能。
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