Identification and validation of TNFRSF4 as a high-profile biomarker for prognosis and immunomodulation in endometrial carcinoma

• Published in: BMC cancer 2022-05, Vol.22 (1), p.543-543, Article 543
• Main Authors: Ma, Heng, Feng, Peng-Hui, Yu, Shuang-Ni, Lu, Zhao-Hui, Yu, Qi, Chen, Jie
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Biological markers; biomarker2; Biomarkers; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cancer; Carcinoma; Care and treatment; CD4 antigen; CD8 antigen; CD8-Positive T-Lymphocytes - metabolism; Diagnosis; DNA microarrays; Endometrial cancer; Endometrial carcinoma5; Endometrial Neoplasms - pathology; Endometrium; Female; Forkhead Transcription Factors - metabolism; Foxp3 protein; Gene expression; Gene Expression Regulation, Neoplastic; Gene set enrichment analysis; Genomes; Humans; Immunohistochemistry; Immunomodulation; Immunomodulation - genetics; Immunotherapy; Lymphocytes T; Medical prognosis; Methods; Molecular modelling; Patient outcomes; Prognosis; prognosis3; Protein interaction; Protein-protein interactions; Receptors, OX40 - genetics; Receptors, OX40 - metabolism; Regression analysis; Risk factors; Software; Survival analysis; TNFRSF41; Tumor microenvironment; Tumor Microenvironment - genetics; Tumor microenvironment4; Tumor necrosis factor; Tumor-infiltrating lymphocytes; Uterine cancer; Values
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-022-09654-6

The interaction between tumor microenvironment (TME) and tumors offers various targets in mounting anti-tumor immunotherapies. However, the prognostic biomarkers in endometrial carcinoma (EC) are still limited. Here, we aimed to analyze the TME features and identify novel prognostic biomarkers for EC. ESTIMATE, CIBERSORT, protein-protein interaction (PPI) network, univariate and multivariate 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 deconvolution algorithm were adopted to estimate the abundance of tumor-infiltrating immune cells (TICs) and their relationship with the target gene. In the validation section, tissue microarrays (TMAs) of EC and multiplex immunohistochemistry (m-IHC) were evaluated to validate the expression of TNFRSF4, and its correlation with immune markers, including CD4, CD8, and FOXP3. Besides, the receiver operating characteristic (ROC) curve was plotted to determine the diagnostic performance of TNFRSF4, CD4, CD8, and FOXP3 in EC. Two genes, TNFRSF4 and S1PR4, were screened out from 386 intersection differential expression genes (DEGs) shared by ImmuneScore and StromalScore in EC. 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 the prognosis in patients of EC, both verified by data from The Cancer Genome Altas (TCGA)-EC database and clinical samples. At the same time, the expression trend of TNFRSF4 was further confirmed by an integrated meta-analysis based on six microarrays from the Gene Expression Omnibus database (GEO). Collectively, TNFRSF4, a previously unrecognized key player in EC, could serve as a potential biomarker for prognosis prediction and immunomodulation of EC.