Investigator
Nantong Maternity And Child Health Hospital
Integrative Analysis of Glycine, Serine, and Threonine Metabolism and the Immune Microenvironment in Endometrial Cancer: A Prognostic Model and Metabolic-Immune Framework for Precision Oncology
Background: Metabolic reprogramming is a hallmark of the pathogenesis and progression of endometrial carcinoma (EC). This study comprehensively analyzed the expression profiles of glycine, serine, and threonine (Gly/Ser/Thr) metabolism–related genes in EC. We also established a robust prognostic model and developed a molecular subtyping framework that integrates metabolic and immune characteristics based on the identified prognostic genes. The aims of this work are to enhance diagnostic precision and improve clinical management strategies for patients with EC. Methods: Untargeted metabolomic analysis was performed on 35 EC and 15 normal tissues. The Cancer Genome Atlas (TCGA) transcriptomic data were integrated with weighted gene co-expression network analysis (WGCNA) to identify EC-related metabolic genes and construct a prognostic model using Cox proportional hazards and least absolute shrinkage and selection operator (LASSO) regression analyses. The model was validated using an independent proteomic and single-cell dataset from our institution. Consensus clustering classified patients into three molecular subtypes, which were further characterized by gene set variation analysis (GSVA) and profiling of immune infiltration. Finally, key prognostic genes were validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in EC and normal endometrial epithelial cells. Results: Metabolomic analysis revealed significant enrichment of the Gly/Ser/Thr metabolic pathways. WGCNA identified a tumor-associated metabolic module among 1741 pathway-related genes. A prognostic model comprising methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), ribosomal protein S6 kinase A1 (RPS6KA1), and cyclin-dependent kinase inhibitor 2A (CDKN2A) was subsequently established. Consensus clustering based on risk scores stratified EC patients into three molecular subtypes: immunometabolic-suppressed (C1), proliferative-immunobalanced (C2), and immune-activated (C3). The C1 subtype had the poorest prognosis and was characterized by metabolic suppression and immune evasion. The C2 subtype showed a favorable prognosis and was defined by a “proliferation–immune balance” in which high proliferative activity coexisted with strong anti-tumor immunity. The C3 subtype was also associated with a favorable outcome, driven by upregulated DNA repair and oxidative phosphorylation pathways alongside infiltration of immune-active cells. RT-qPCR confirmed significant differences in the mRNA expression of MTHFD2, RPS6KA1, and CDKN2A between normal and EC cells (p < 0.05). Conclusion: This study developed a Gly/Ser/Thr pathway–based prognostic model for EC, based on the expression of MTHFD2, RPS6KA1, and CDKN2A as novel biomarkers. The resulting patient stratification framework holds significant clinical potential for guiding precise and personalized management of EC.
Antagonism of estrogen-related receptor-α inhibits mitochondrial oxidative phosphorylation and reduces M2 macrophage infiltration in endometrial cancer
Objective Endometrial cancer (EC) is a female malignancy closely linked to metabolic dysregulation. Most patients with EC exhibit poor responses to immunotherapy, underscoring the need to identify novel therapeutic targets at the intersection of metabolism and immune regulation. Methods In vitro: integrated proteomics, CUT&Tag (cleavage under targets and tag mentation) sequencing, dual-luciferase reporter assays, lipidomic profiling, and macrophage-tumor co-culture systems collectively demonstrated estrogen-related receptor (ERR) α’s dual metabolic-immunomodulatory role in KLE and HEC-1A human cell lines. Patient-derived organoids were used to validate the therapeutic efficacy of ERRα targeting. In vivo, the KLE cell xenograft model was used to evaluate tumorigenicity and therapeutic efficacy in mice. In humans, a retrospective cohort of 166 patients with EC was analyzed by immunohistochemistry (IHC) to quantify ERRα expression and macrophage infiltration, establishing clinical correlations and therapeutic implications. Spatial analysis of M2 macrophages in EC progression was performed using multiplex IHC. Results In EC cells, ERRα transcriptionally upregulates protein tyrosine phosphatase mitochondrial 1 through direct promoter binding (-624 to −609 bp). This interaction promotes cardiolipin biosynthesis, thereby stabilizing mitochondrial inner membrane ultrastructure, enhancing oxidative phosphorylation activity, and elevating reactive oxygen species (ROS) levels. Subsequently, ROS activates the NF-κB signaling axis, inducing CCL2 secretion to recruit M2 macrophages into the tumor microenvironment. Importantly, combined inhibition of ERRα (using XCT790) and CCL2 (using carlumab) significantly enhanced antitumor efficacy in EC. Additionally, ERRα expression in EC tissues may serve as a clinical indicator for disease evaluation. Conclusions This study uncovers a pivotal role of the ERRα metabolic axis in reshaping the EC immune microenvironment, providing the mechanistic evidence linking mitochondrial lipid metabolism to macrophage-driven immunosuppression. Our findings establish a theoretical foundation for developing combination therapies targeting metabolic-immune crosstalk, offering a strategy to overcome immunotherapy resistance in EC.
