Identification of an immune-related risk signature and nomogram predicting the overall survival in patients with endometrial cancer

OBJECTIVE Aimed to construct an immune-related risk signature and nomogram predicting endometrial cancer (EC) prognosis. METHODS An immune-related risk signature in EC was constructed using the least absolute shrinkage and selection operator regression analysis based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A nomogram integrating the immune-related genes and the clinicopathological characteristics was established and validated using the Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve to predict the overall survival (OS) of EC patients. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) R tool was used to explore the immune and stromal scores. RESULTS CCL17, CTLA4, GPI, HDGF, HFE2, ICOS, IFNG, IL21R, KAL1, NR3C1, S100A2, and S100A9 were used in developing an immune-related risk signature evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had better OS (p<0.001). The area under the ROC curve (AUC) values of this model were 0.737, 0.764, and 0.782 for the 3-, 5-, and 7-year OS, respectively. A nomogram integrating the immune-related risk model and clinical features could accurately predict the OS (AUC=0.772, 0.786, and 0.817 at 3-, 5-, and 7-year OS, respectively). The 4 immune cell scores were lower in the high-risk group. Forkhead box P3 (FOXP3) and basic leucine zipper ATF-like transcription factor (BATF) showed a potential significant role in the immune-related risk signature. CONCLUSION Twelve immune-related genes signature and nomogram for assessing the OS of patients with EC had a good practical value.