Tumor-infiltrating immune cell score as an independent prognostic predictor for endometrial carcinoma: Insights from a comprehensive analysis of the immune landscape.

Abstract

Immune cells are crucial components in the tumor microenvironment and have a significant impact on the outcomes of patients. Here, we aimed to establish a prognostic score based on different types of tumor-infiltrating immune cells for Endometrial Carcinoma (EC). We enrolled and analyzed 516 EC patients from The Cancer Genome Atlas. The relative abundance of 22 immune cells were estimated by using the CIBERSORTx algorithm. Cox regression was performed to identify potential prognostic immune cells, which were used to develop a Tumor-infiltrating Immune Cell Score (TICS). The prognostic and incremental value of TICS for overall survival were compared with traditional prognostic factors using the C-index and decision curves. Clustering analysis using all immune cells identified three immune landscape subtypes, which had weak correlation with survival. A TICS was constructed using CD8T cells, resting memory CD4 T cells, activated NK and activated DCs, and classified patients as low-, moderate- and high-risk subgroups. The low-risk subgroup had higher tumor mutation burden and activation of IL2/STAT5, IL2/STAT3 and IFN-gamma response pathways. Conversely, the high-risk subgroup was associated with DNA copy number variation, hypoxia and EMT process. The TICS subgroups significantly predicted overall survival, which was independent of patient age, tumor stage, grade and molecular classification. Moreover, we developed a nomogram incorporating TICS and clinicopathologic factors, which significantly improved the predictive accuracy compared to the clinicopathologic model alone. The TICS is an effective and independent prognostic predictor for EC patients and may serve as a useful supplement to clinicopathological factors and molecular subtyping.