Identification of TNFRSF4 as a Diagnosis and Prognosis Biomarker Associated with Immune Microenvironment in Uterine Corpus Endometrial Carcinoma

Abstract BackgroundThe interaction between tumor microenvironment (TME) and tumors offers various targets in mounting anti-tumor immunotherapies. However, the diagnostic and prognostic biomarkers in uterine corpus endometrial carcinoma (UCEC) are still limited. Here, we aimed to analyze the TME features and identify novel prognostic biomarkers for UCEC. MethodsESTIMATE, CIBERSORT, protein-protein interaction (PPI) network, univariate Cox regression, and functional enrichment analysis were performed to identify immune- and survival-related hub genes as well as possible molecular mechanisms. The limma package and the deconvolution algorithm were adopted to estimate the tumor-infiltrating immune cells (TICs) abundance and their relationship with the target gene. Tissue microarrays (TMAs) of UCEC were evaluated to validate protein expression of the identified immune markers, including TNFRSF4, CD4, and CD8. The receiver operating characteristic (ROC) curve was used to determine the efficacy of TNFRSF4 in diagnosing UCEC. ResultsTwo genes, TNFRSF4 and S1PR4, were screened out from 386 intersection differential expression gene (DEGs) shared by ImmuneScore and StromalScore in UCEC. Highlighted by TNFRSF4, we found that it was not only positively correlated with the TICs (mainly CD4+ T cells, CD8+ T cells, and Tregs) but significantly related to diagnosis and prognosis in patients of UCEC, both verified by data from the TCGA database and clinical samples. ConclusionsCollectively, TNFRSF4 could serve as a high-profile biomarker to robustly predict immune microenvironment, clinical diagnosis and prognosis for UCEC.