Abstract / Summary
Abstract Background High-grade (FIGO Grade 3) uterine corpus endometrial carcinoma (UCEC) is an aggressive malignancy with limited therapeutic options and a poor prognosis. While ferroptosis is implicated in various cancers, its specific role within the tumor immune microenvironment of high-grade UCEC remains unclear. Methods We analyzed transcriptomic and clinical data from 314 Grade 3 UCEC patients in The Cancer Genome Atlas (TCGA). Clustering analysis was used to identify molecular subtypes. A prognostic model based on ferroptosis-related genes was constructed and internally validated using 1000-time bootstrap resampling. Protein-level dysregulation of candidate model genes was corroborated using the CPTAC proteomic cohort. ssGSEA and CIBERSORT algorithms were applied to evaluate immune enrichment across clusters and continuous risk scores, respectively. Single-cell RNA-seq via TISCH2 resolved cell-type-specific marker expression. Results We identified two distinct ferroptosis-related molecular subtypes in high-grade UCEC with divergent clinical outcomes, immune profiles, and pathway activities. A robust prognostic model based on seven genes (ANXA1, DDB1, HSDL2, LINC01139, MGST1, PRNP, PTEN) was constructed. It demonstrated strong predictive accuracy, yielding bootstrap-corrected area under the curve (AUC) values of 0.763, 0.844, and 0.882 for 1-, 3-, and 5-year overall survival, respectively. Patients in the high-risk group exhibited a dysregulated immune microenvironment characterized by increased M2 macrophage infiltration. Exploratory in silico pharmacogenomic profiling identified candidate targeted agents with higher predicted drug sensitivity associated with the high-risk transcriptomic signature. Furthermore, single-cell analysis confirmed the overexpression of ANXA1 in tumor-associated immune and malignant cells. Conclusion We developed a novel ferroptosis-related prognostic model specifically tailored for risk stratification in high-grade UCEC. This study links ferroptosis to immune dysregulation and uncovers potential therapeutic vulnerabilities, providing a foundation for future targeted treatment strategies.