Construction And Verification of A Prognostic Model Related To RNA-Binding Proteins In Uterine Corpus Endometrial Carcinoma
Abstract Background: RNA binding proteins (RBP) plays an important role in post-transcriptional regulation. Although the dysregulation of RBP expression is closely related to the occurrence and metastasis of a variety of tumors, there are few reports on RBP in endometrial carcinoma (UCEC). This study aims to establish a RBP-related prognostic model of UCEC. Methods: We downloaded UCEC gene expression and clinical information data from the Cancer Genome Atlas (TCGA) and GEO database, and determined RBPs that are differentially expressed between tumors and normal tissues. Then, used functional enrichment analysis to analyze the biological functions of the differentially expressed RBP. Used univariate Cox regression analysis to screen prognostic-related RBP and construct a prognostic model. Subsequently, Kaplan-Meier and recipient operating characteristic (ROC) curves were drawn to evaluate the model. Finally, established a nomogram. Results: This study identified 531 differentially expressed RBPs, including 325 up-regulated and 206 down-regulated RBPs, respectively. Then six independent prognostic-related RBPs (REXO2, MARS2, XPO5, YBX1, YBX2, and CELF4) were used to construct a prognostic model. According to this model, the overall survival (OS) of patients in the high-risk score group was significantly lower than that of the low-risk score group. In the training queue and the test queue, the areas under the ROC curve were 0.799 and 0.669, respectively, showing the moderate predictive value of the model. Conclusion: We have developed and validated the RBP-related prognostic model.