biostudies-literatureUnknown9Li YNational Natural Science Foundation of China<b>Background:</b> Accumulating evidence suggests that anti-estrogens have been effective against multiple gynecological diseases, especially advanced uterine corpus endometrial carcinoma (UCEC), highlighting the contribution of the estrogen response pathway in UCEC progression. This study aims to identify a reliable prognostic signature for potentially aiding in the comprehensive management of UCEC. <b>Methods:</b> Firstly, univariate Cox and LASSO regression were performed to identify a satisfying UCEC prognostic model quantifying patients' risk, constructed from estrogen-response-related genes and verified to be effective by Kaplan-Meier curves, ROC curves, univariate and multivariate Cox regression. Additionally, a nomogram was constructed integrating the prognostic model and other cliFrontiers in molecular biosciences833910https://www.ebi.ac.uk/biostudies/studies/S-EPMC9087353biostudies-literatureA 13-Gene Signature Based on Estrogen Response Pathway for Predicting Survival and Immune Responses of Patients With UCEC.PMC9087353Li YLiu JWu QFu XTian ROu CfalseA 13-Gene Signature Based on Estrogen Response Pathway for Predicting Survival and Immune Responses of Patients With UCEC.<b>Background:</b> Accumulating evidence suggests that anti-estrogens have been effective against multiple gynecological diseases, especially advanced uterine corpus endometrial carcinoma (UCEC), highlighting the contribution of the estrogen response pathway in UCEC progression. This study aims to identify a reliable prognostic signature for potentially aiding in the comprehensive management of UCEC. <b>Methods:</b> Firstly, univariate Cox and LASSO regression were performed to identify a satisfying UCEC prognostic model quantifying patients' risk, constructed from estrogen-response-related genes and verified to be effective by Kaplan-Meier curves, ROC curves, univariate and multivariate Cox regression. Additionally, a nomogram was constructed integrating the prognostic model and other cli2022-01-01T00:00:00Z20222025-06-01T02:26:09.029Z2024-11-15T01:24:21.803ZS-EPMC90873533555856410.3389/fmolb.2022.833910