Protein ubiquitination is closely related to tumor occurrence and development. The specific role of ubiquitination in endometrial cancer remains largely unclear. Therefore, we constructed a novel endometrial cancer prognostic model based on ubiquitination-related genes. We extracted the expression matrices of ubiquitination-related genes from the Cancer Genome Atlas database, upon which we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to obtain 22 ubiquitination-related genes for the construction of the prognostic model. Survival, regression, clinical correlation, and principal component analyses were performed to assess the performance of the model. Drug sensitivity analysis was performed based on these ubiquitination-related genes. Finally, a prognostic nomogram was constructed based on the prognostic model to quantify patient outcomes. Survival, regression, clinical correlation, and principal component analyses revealed that the performance of the prognostic model was satisfactory. Drug sensitivity analysis provided a potential direction for the treatment of endometrial cancer. The prognostic nomogram could be used to effectively estimate the survival rate of patients with endometrial cancer. In summary, we constructed a new endometrial cancer prognostic model and identified 5 differentially expressed, prognosis-associated, ubiquitination-related genes. These 5 genes are potential diagnostic and treatment targets for endometrial cancer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.