mRNAs列线图模型对宫颈腺癌患者生存状况的预测价值

The predictive value of mRNAs nomogram model of cervical adenocarcinoma to the survival status of patients

目的通过分析宫颈腺癌(CAC)的mRNAs差异表达谱及模型mRNAs的基因集富集分析(GSEA),寻找其稳定可靠的靶向治疗、预后评估的新型分子标志物。方法2019年8-10月在兰州大学第一医院实施研究。下载癌症基因组图谱数据库(TCGA)中CAC的mRNAs相关数据,使用R3.6.1软件进行差异分析、mRNAs筛选和预后模型构建。使用GSEA4.0.1软件进行模型mRNAs的癌症和效应特征基因集富集分析。结果经单因素Cox回归、Lasso回归分析、多因素Cox逐步回归分析获得CAC患者预后评估的列线图模型。该模型C-指数为0.95,3年生存率的AUC为0.9501,5年生存率的AUC为0.9497,风险评分为0.94474×CILP+3.86633×MYH13-3.7763×ANKRD53-1.91299×GLIPR2-0.64192×CPQ,生存分析提示低风险组患者生存预后显著优于高风险组(P<0.05)。经基因集富集分析显示,VEGFAUP.V1UP、MYC TARGETS V1和MTORC1 SIGNALING基因集分别与4个和3个模型mRNAs显著相关。结论列线图模型可有效预测CAC患者生存状况,模型mRNAs可能通过VEGFAUP.V1UP、MYC TARGETS V1和MTORC1 SIGNALING等途径影响患者预后,模型mRNAs及其核心基因集有望成为靶向治疗、预后评估的新靶标。

Objective Through the analysis of mRNA differential expression profile of cervical adenocarcinoma(CAC)and gene set enrichment analysis(GSEA)of model mRNAs,to find a stable and reliable new molecular marker for targeted treatment and prognosis evaluation.Methods From August to October 2019,the research was carried out in the First Hospital of Lanzhou University.Download the mRNAs related data of CAC in TCGA,and use r3.6.1 software to carry out differential analysis,mRNAs screening and prognosis model construction.GSEA 4.0.1 software was used to analyze the cancer and effect characteristic gene set enrichment of model mRNAs.Results By single factor Cox regression,Lasso regression analysis and multi factor Cox stepwise regression analysis,the nomogram model for prognosis evaluation of CAC patients was obtained.The C index of the model is 0.95,AUC of 3-year survival rate is 0.9501,AUC of 5-year survival rate is 0.9497,risk score is 0.94474×CLIP+3.86633×MYH13-3.7763×ANKRD53-1.91299×GLIPR2-0.64192×CPQ,survival analysis indicates that survival prognosis of low-risk group is significantly better than that of high-risk group(P<0.05).The analysis of gene set enrichment showed that VEGF_A_UP.V1_UP,MYC TARGETS V1 and MTORC1 signaling gene sets were significantly correlated with 4 and 3 model mRNAs respectively.Conclusion The model mRNAs may affect the prognosis of CAC patients through VEGF_A_UP.V1_UP,MYC TARGETS V1 and MTORC1 signaling.The model mRNAs and its core gene set are expected to be new targets for targeted therapy and prognosis evaluation.