Metabolic Landscape of Endometrial Cancer: Insights into Pathway Dysregulation and Metabolic Features.

ABSTRACT: Background: Metabolic reprogramming is increasingly recognized as a hallmark of endometrial cancer, yet tissue-based metabolic signatures remain insufficiently defined. Methods: Untargeted metabolomics was performed on paired endometrial cancer (n = 10) and adjacent normal tissues (n = 10). Differential metabolites were identified through multivariate and univariate analyses. KEGG enrichment characterized altered pathways, while Random Forest and SVM were used for machine-learning-based feature prioritization. ROC analyses were conducted to evaluate the discriminative potential of selected metabolites. Results: 300 metabolites were significantly altered. Tumor tissues showed increased sphingolipid metabolism, glutathione metabolism, and arachidonic acid m

SUBMITTER: Yang Q 

PROVIDER: S-EPMC12838860 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature