Construction and Validation of A Novel Predictive Model Based on Chromatin Regulators in Endometrial Cancer

Abstract

Chromatin regulators (CRs) are substantially associated with the prognosis and immunotherapy responses in multiple cancers. However, comprehensive studies related to the prognostic prediction of CRs in endometrial cancer (UCEC) still remains lacking. Therefore, first, we constructed a prognostic model for UCEC associated with 23 CRs using a univariate Cox regression model as well as the glmnet R package. Then, based on the median risk scores, we separated the UCEC sufferers into the high risk set and low risk set, in which the proportion of sufferers with pathological grade G3 and clinical-stage III–IV is higher in the high risk one. Furthermore, we investigated the association of independent prognostic factors, immunotherapy-related scores, GO, KEGG pathways, and drug sensitivity between both groupings. We identified the high risk set tended to have lower IPS, microsatellite instability, and tumor mutational load. GO and KEGG suggested an enrichment of genes related to ribosome biogenesis, RNA processing and metabolism, viral defence, translational regulation, and calmodulin-binding in the high-risk one, while the other one related to cilia movement, microtubule movement, axonal components, and calmodulin-binding. Drug sensitivity assay showed sensitive doxorubicin could be applied to the high-risk patients. All in all, our team successfully built and validated a predictive model for CRs that predicts the overall survival of UCEC patients, which may provide a potential new direction for prognosis prediction and therapeutic target selection for UCEC patients.