Constructing and validating a risk prognosis model for endometrial cancer based on angiogenic factors
Objective To explore the relationship between angiogenic factors(AFs)and the prognostic risk of endometrial cancer(EC),and to construct and validate a prognostic model for EC patients based on AFs related genes.Methods Download gene expression profile data and clinical data of EC patients(552 cases)from the TCGA database,and further use limma package to screen for differentially expressed AFs genes.Single factor regression analysis was used to screen for AFs related to the prognosis of EC patients,and the TCGA population was further divided into a test set and a validation set in a 1∶1 ratio.Based on the training set population,Lasso regression analysis was conducted to construct a risk prognosis model.K-M survival analysis,ROC curve,and other methods were used to analyze the test set and validate the predictive accuracy of the centralized prognosis model.Finally,a Nomogram was established based on the AFs related gene prognosis model and clinical characteristic factors.Results We constructed and validated an EC prognostic model„ for 7 AFs related genes(NR3C1,TNFRSF18,MALs,CDKN2A,PROS1,ASB2,and GRB14).K-M curve analysis suggests that patients with higher risk scores have poorer prognosis compared to those with lower risk scores(P＜0.05).The ROC curve analysis results indicate that the 5-year survival prediction AUC values of the prognostic model in the test set,validation set,and the entire cohort population are 0.829,0.756,and 0.790,respectively.GESA enrichment analysis showed that compared with low-risk patients,high-risk patients showed significant enrichment in cell cycle,DNA replicatión,and ERBB signaling pathway(P＜0.05).A Nomogram was constructed based on AFs related genes and clinical feature factors,and the calibration curve was used to evaluate its predictive accuracy.Conclusions This study constructed and validated a prognostic model for EC patients based on AFs related genes.The model can be used to accurately predict the prognosis of EC patients,and a Nomogram diagram based on independent prognostic factors can be constructed to assist clinical doctors in accurately judging patient prognosis and making the best clinical decisions.
万方数据
维普
