Integrated single-cell and bulk transcriptomics reveals an IGF2BP3-driven metabolic circuitry in endometrial cancer.

backgroundThis study investigates the epigenetic-metabolic interplay in endometrial cancer (EC) through integrated single-cell and bulk multi-omics analyses, aiming to identify prognostic biomarkers and elucidate mechanisms driving metabolic reprogramming.

methodsSingle-cell RNA sequencing (scRNA-seq) data from five EC patients and bulk RNA-seq data from TCGA/GTEx cohorts were analyzed. Non-negative matrix factorization (NMF) clustering, CellChat, and SCENIC were employed for subtyping, intercellular communication, and transcriptional network analysis. Prognostic models were constructed using LASSO-Cox regression. Functional validation included RIP-seq, ChIP-qPCR, luciferase assays, and in vivo tumor models. Metabolic activity was assessed via glucose/lactate measurements and extracellular acidification rate (ECAR).

resultsOur analysis identified 68 epigenetics-related genes, with 20 prognostic biomarkers. Analysis of scRNA-seq data from five EC patients identified major cell populations, including B cells, ciliated cells, endothelial cells, epithelial cells, fibroblasts, macrophages, monocytes, smooth muscle cells, and T cells. NMF clustering of malignant epithelial cells identified four epigenetically distinct subpopulations (Epigen-C1–C4) within tumors, rather than patient-level molecular subtypes. Bulk TCGA/GTEx analyses further supported prognostic modeling at the cohort level. Epigen-C2, characterized by hypermetabolic activity, exhibited advanced differentiation and poor prognosis. A six-gene prognostic signature (SDF2L1, ASPM, MUC1, MCM7, PHGDH, MSX1) derived from Epigen-C2-associated differentially expressed genes demonstrated robust risk stratification across training, testing, and full cohorts. Mechanistically, IGF2BP3, an m6A reader overexpressed in EC, may stabilize MUC1 mRNA by binding to m6A modification sites, thereby enhancing MUC1 protein expression. Upregulated MUC1 amplified HIF-1α levels, which transcriptionally activated the glycolytic enzyme ENO1 through promoter binding. Concurrently, IGF2BP3 stabilized ENO1 mRNA, forming a feed-forward loop that accelerated glycolysis, evidenced by increased glucose consumption, lactate production, and ECAR. In vivo, IGF2BP3 knockdown suppressed tumor growth, while overexpression exacerbated progression. These findings unveil the IGF2BP3/MUC1/HIF-1α/ENO1 axis as a critical driver of m6A-associated metabolic reprogramming in EC.

conclusionsThis study characterizes intra-tumoral malignant epithelial heterogeneity in EC using single-cell epigenetics, informing potential precision therapy hypotheses without establishing a stable patient-level molecular classification. It defines the IGF2BP3/MUC1/HIF-1α/ENO1 axis as a critical driver of m6A-associated metabolic reprogramming in EC.