Significance of Tumor Infiltrating Immune Cells (TIICs) in Endometrial carcinoma: A Bioinformatics Analysis

Abstract

Background: Increasing evidence has revealed that tumor-infiltrating immune cells (TIICs) are involved in the development of endometrial carcinoma (EC). In this study, we aimed to reveal the significance of 28 TIIC types in the classification and prognosis of EC. Methods: Single-sample gene set enrichment analysis (ssGSEA) was used to calculate the abundance of the 28 TIIC types in EC patients from TCGA database. A consensus clustering algorithm was used to group the EC patients. Principal component analysis (PCA) algorithms were performed to calculate an ICI score for each sample to predict the sensitivity to ICIs therapy based on the 28 TIIC types.Results: The EC patients from The Cancer Genome Atlas (TCGA) database were classified into two groups (cluster.A and cluster.B) based on the 28 types of TIIC using a consensus clustering algorithm. The patients in the cluster.B group had increased immune cell infiltration, and higher expression of human leucocyte antigen (HLA) genes, immune checkpoint molecules, and immune activation-related genes, suggesting that they may be more sensitive to immune checkpoint inhibitors (ICIs) therapy. Differential analysis between cluster.A and cluster.B identified 591 immune-related genes. We validated the immune regulation mechanism based on the 591 immune-related genes using another consensus clustering algorithm. The EC patients were divided into two groups (gene.cluster.A and gene.cluster.B) based on the 591 immune-related genes. The patients in the gene.cluster.B group had increased immune cell infiltration, and higher expression of HLA genes, immune checkpoint molecules, and immune activation-related genes. In addition, we also calculated an ICI score for each patient with EC to predict the sensitivity to ICIs therapy based on the 28 TIIC types using principal component analysis algorithms. Conclusions: In summary, the 28 types of TIIC play non-negligible roles in the development of EC. Our investigation of the 28 types of TIIC may help to guide ICIs treatment strategies for patients with EC.