Identification of prognostic and immune-related gene signatures in the tumor microenvironment of endometrial cancer

Abstract

Uterine corpus endometrial cancer (UCEC) is one of the most prevalent female malignancies in clinical practice. Due to the lack of effective biomarkers and personalized treatments, the prognosis of advanced-stage EC remains unfavorable. Modulation of the immune microenvironment is closely related to the onset and development of endometrial cancer. In the present study, we attempt to systematically analyze the characteristics of the immune microenvironment of endometrial cancer and investigate its association with clinical features by applying bioinformatics. RNA-Seq in TCGA (The Cancer Genome Atlas) and clinical follow-up information of patents were used for analysis. The Tumor Microenvironment (TME) score infiltration patterns of 523 endometrial cancer patients were evaluated using CIBERSORT. Random forest, multivariable cox analysis were used to build the TME score. Fisher’s exact test was used to compare the genes that show significant differences in the frequency of mutations between groups. Two TME phenotypes were defined. There is a significant relationship between the TME score and grade. High TME score samples are highly expressed in immune activation, TGF pathway activation and immune checkpoint genes, and low TME score samples have high frequency mutations of PTEN, CSE1L and ITGB3. Therefore, describing the comprehensive landscape of UCEC's TME characteristics may help explain patients' response to immunotherapy and provide new strategies for cancer treatment.