Endometrial cancer is a heterogeneous disease with distinct molecular characteristics, however, the current clinical trials in immunotherapies have reported only a 13% response rate in endometrial cancer. In this study, we aim to estimate the relative abundance of immune cells infiltrating into the tumor tissues. The samples were clustered based on the immune cell abundance. Most of cluster-specifically mutated genes were detected in clusters I and II, while the copy number alterations were specifically detected in cluster III. Overrepresentation enrichment analysis (ORA) of the genes specifically upregulated in a specific cluster revealed that the immune-related pathways were enriched by the genes in cluster I. Moreover, immune checkpoint proteins and immune co-stimulators were also observed to be highly expressed in cluster I. In addition, we also built a multivariable Cox regression model based on the immune checkpoint genes and co-stimulators. The high-risk and low-risk groups stratified by the risk scores of the Cox model exhibited significant prognostic difference in both training and validation datasets. In summary, the systematic analysis greatly improves our understanding of the immunophenotype of endometrial cancer and its association with biomarkers and prognosis.