Xiaodan Mao

High glucose levels promote glycolysis and cholesterol synthesis via ERRα and suppress the autophagy–lysosomal pathway in endometrial cancer

Abstract Endometrial cancer (EC) patients with Diabetes Mellitus (DM) always have a poor prognosis. Estrogen-related receptor α (ERRα) is known as the metabolic-related prognostic factor for EC. However, the mechanism linking glycolipid metabolism dysfunction mediated by ERRα to poor prognosis of EC with DM is still unclear. In vitro, high-glucose (HG) levels showed enhancement of ERRα expression, cell proliferation, and inhibition of the autophagic lysosomes and apoptosis by flow cytometry analysis, transmission electron microscopy, and CCK-8 assays. Mechanistically, lose-and-gain function assay, DNA sequencing, and CO-IP revealed HG increased ERRα expression to promote the transcription of HK2 and HMGCS1, which were the key rate-limiting enzyme of glycolysis-cholesterol synthesis and their metabolites suppressed the autophagy–lysosomal pathway in an ERRα-dependent manner. Furthermore, CO-IP and molecular dynamics simulation uncovered the protein residues (ARG 769HK2 vs. ARG 313HMGCS1) of HK2 and HMGCS1 could bind to p62 to form stable protein complexes involved in the autophagy–lysosomal pathway. In EC tissue from patients with comorbid DM, ERRα was significantly higher expressed compared to EC tissue from patients without evidence for DM (p < 0.05). The 3D EC organoid model with HG stimulation showed that the cell viability of XCT790 + carboplatin treatment was similar to that of metformin+carboplatin treatment, while the obviously bigger volume of organoids was more visible in the metformin+carboplatin group, indicating the therapy of XCT790 + carboplatin had the better inhibition of EC organoids with the same carboplatin dose. Besides insights into the interaction of HG and the autophagy–lysosomal pathway via ERRα, our present study points out the potential benefit of targeting ERRα in patients with EC with dysregulation of glucose and cholesterol metabolism.

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.