Reliable estrogen-related prognostic signature for uterine corpus endometrial carcinoma

Background: Uterine corpus endometrial carcinoma (UCEC) is a predominant gynecological malignancy worldwide. Overdosed estrogen exposure has been widely known as a crucial risk factor for UCEC patients. The purpose of this work is to explore crucial estrogen-related genes (ERGs) in UCEC. Methods: UCEC scRNA-seq data, bulk RNA data, and ERGs were obtained from GEO, TCGA, and Molecular Signature Database, respectively. Differential expression analysis and cross analysis determined the candidate genes, and optimal genes in risk score were obtained after univariate Cox regression analysis, LASSO Cox regression analysis, and multivariate Cox regression analysis. The functional information was revealed by GO, KEGG, and GSVA enrichment analyses. CCK8 assay was used to detect the drug sensitivity. Results: After cross analysis of the differentially expressed genes and the 8734 ERGs, 86 differentially expressed ERGs were identified in UCEC, which were significantly enriched in some immune related pathways and microbiota related pathways. Of them, the most optimal 8 ERGs were obtained to build prognostic risk score, including GAL, PHGDH, SLC7A2, HNMT, CLU, AREG, MACC1, and HMGA1. The risk score could reliably predict patient prognosis, and high-risk patients had worse prognosis. Higher HMGA1 gene expression exhibited higher sensitivity to Osimertinib. Conclusions: Predictive risk score based on 8 ERGs exhibited excellent prognostic value in UCEC patients, and high-risk patients had inferior survival. UCEC patients with distinct prognoses showed different tumor immune microenvironment.