A 13-Gene Signature Based on Estrogen Response Pathway for Predicting Survival and Immune Responses of Patients With UCEC

Yimin Li; Ruotong Tian; Jiaxin Liu; Chunlin Ou; Qihui Wu; Xiaodan Fu

doi:10.3389/fmolb.2022.833910

A 13-Gene Signature Based on Estrogen Response Pathway for Predicting Survival and Immune Responses of Patients With UCEC

Front Mol Biosci. 2022 Apr 26:9:833910. doi: 10.3389/fmolb.2022.833910. eCollection 2022.

Authors

Yimin Li^{1

2}, Ruotong Tian³, Jiaxin Liu⁴, Chunlin Ou^{5

6}, Qihui Wu^{7

6}, Xiaodan Fu^{5

6}

Affiliations

¹ Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
² Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
³ Department of Pharmacology, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China.
⁴ Department of Pathology, School of Basic Medical Sciences, Central South University, Changsha, China.
⁵ Department of Pathology, Xiangya Hospital, Central South University, Changsha, China.
⁶ National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China.
⁷ Department of Obstetrics and Gynecology, Xiangya Hospital, Central South University, Changsha, China.

Abstract

Background: 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. Methods: 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 clinicopathological parameters. Next, UCEC patients from the TCGA dataset were divided into low- and high-risk groups according to the median risk score. To elucidate differences in biological characteristics between the two risk groups, pathway enrichment, immune landscape, genomic alterations, and therapeutic responses were evaluated to satisfy this objective. As for treatment, effective responses to anti-PD-1 therapy in the low-risk patients and sensitivity to six chemotherapy drugs in the high-risk patients were demonstrated. Results: The low-risk group with a relatively favorable prognosis was marked by increased immune cell infiltration, higher expression levels of HLA members and immune checkpoint biomarkers, higher tumor mutation burden, and lower copy number alterations. This UCEC prognostic signature, composed of 13 estrogen-response-related genes, has been identified and verified as effective. Conclusion: Our study provides molecular signatures for further functional and therapeutic investigations of estrogen-response-related genes in UCEC and represents a potential systemic approach to characterize key factors in UCEC pathogenesis and therapeutic responses.

Keywords: TCGA; UCEC; estrogens; immune infiltration; prognosis.