A prognostic model based on immune cells in tumor microenvironment to predict prognosis in endometrial cancer

The interaction between the tumor immune microenvironment (TIME) and malignant tumor cells plays a crucial role in tumor initiation and progression. This study aimed to establish and validate a prognostic model based on TIME characteristics to predict prognosis and guide personalized treatment in patients with endometrial cancer (EC).

A total of 67 EC patients who underwent surgery and TIME profiling at Peking University People's Hospital between January 2018 and December 2022 were included in this study. A prognostic model was developed based on the densities of stroma CD3⁺cell and stroma CD8⁺cells. To validate the model, an independent cohort of 200 EC patients was used, in which immunohistochemical (IHC) staining for CD3⁺ and CD8⁺ cells was performed to assess the model's predictive accuracy.

(1) Multiplex immunofluorescence (mIF) analysis of the 67 EC patients revealed significant differences between the Recurrence and Non-Recurrence groups in the densities of stroma PD-L1⁺ cell, CD8⁺ cell, CD68⁺CD163^- cell, CD3⁺ cell and CD56⁺ cell, with stroma CD3⁺ cell showing the most significant difference (P = 0.004); (2) In 514 EC patients from The Cancer Genome Atlas (TCGA) database, significant differences were observed between the Recurrence and Non-Recurrence groups in the abundance of CD8⁺ cell, regulatory T cells (Tregs), and activated dendritic cells (DCs), with CD8⁺ cell showing the strongest association (P < 0.001); (3) Stroma CD3⁺ and CD8⁺cells were selected as modeling variables to construct the prognostic model, which stratified patients into three clusters: Cluster 1 (n = 17), Cluster 2 (n = 39), and Cluster 3 (n = 11). Survival analysis demonstrated significant differences among the three clusters (P = 0.006); (4) The three clusters also exhibited distinct immune cell compositions, molecular subtypes, and clinicopathological characteristics; (5) In the validation cohort of 200 EC patients, clustering based on IHC-measured CD3⁺ and CD8⁺ cells densities produced three clusters (Cluster 1, Cluster 2, and Cluster 3) with significantly different survival outcomes (P < 0.001), confirming the predictive accuracy of the proposed model.

This study identified two immune cell types-Stroma CD3⁺ and CD8⁺cells-significantly associated with the prognosis of EC and established a TIME-based prognostic model with robust predictive performance and accuracy.