Three RNA-binding protein signature as a novel biomarker to predict endometrial cancer prognosis

The aim of this study was to build a prognostic model for endometrial cancer (EC) patients based on RNA-binding proteins (RBPs). RNA sequencing and clinical data for uterine corpus EC (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Univariate and multivariate Cox regression analysis were used to obtain the following risk formula: score = sum (corresponding coefficient × expression of each gene). A nomogram was developed to accurately predict patient survival based on risk score, age, stage, and grade. Immunohistochemistry (IHC) was used to verify the expression of RBPs in EC. The mRNA expression of RBPs was measured by qRT-PCR. The effects of RBPs on the malignant biologic behavior of EC were detected using CCK-8, colony formation, and transwell invasion assays. A novel prognostic signature was constructed, comprising three RBPs (CD3EAP, SBDS, and TDRKH). The risk score was: Risk score = (0.860 × CD3EAP expression) + (0.622 × 6SBDS expression) + (0.427 × 4TDRKH expression). The area under the receiver operating characteristic curves (AUCs) of risk score for 1-, 3-, and 5-year overall survival (OS) was 0.75, 0.68, and 0.65, respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.811, 0.793, and 0.814, respectively. In our independent cohort, the IHC results revealed that CD3EAP (P < 0.001) and TDRKH (P < 0.001) were upregulated and SBDS (P < 0.001) was downregulated in EC. Immunostaining showed the expression levels of CD3EAP, SBDS and TDRKH for each patient and these were multiplied by their respective coefficients of 0.860, 0.622 and 0.427 to obtain the risk scores. The AUCs of risk score for 1-, 3-, and 5-year OS were 0.888, 0.793, and 0.780 respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.790, 0.826, and 0.906, respectively. Cell functional experiments also confirmed the influence of the key RBPs on the malignant biologic behavior of EC. In summary, a characteristic model based on our three RBPs accurately predicted the prognosis of EC. Our in-depth analysis of these RBPs may inform the development of novel strategies for the diagnosis and treatment of EC.