ArticleSignal transduction and targeted therapy2026
Glycolytic heterogeneity drives metabolic-targeted therapy in pancreatic ductal adenocarcinoma.
Article in Signal transduction and targeted therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Exploiting Metabolic Vulnerabilities in Acute Myeloid Leukemia: Rationale and Evidence for Combining Metabolic Modulators with Conventional Chemotherapy.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Microbiome and pancreatic ductal adenocarcinoma: mechanistic insights, microenvironmental interactions, and therapeutic implications.Molecular biology reports · 2026Review
- The Metabolic Rheostat Index Uncovers Pathway-Level Coordination, Immunosuppressive Microenvironment Remodeling, and Therapeutic Co-Vulnerabilities in Pancreatic Ductal Adenocarcinoma.Current issues in molecular biology · 2026Article
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Authors and funding
19 authors.
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Abstract
Pancreatic ductal adenocarcinoma is traditionally characterized as a glycolytic tumor. However, the extent and clinical relevance of its metabolic heterogeneity remain poorly understood. In this study, we investigated whether glycolytic activity follows a consistent expression pattern across pancreatic ductal adenocarcinoma patients and explored how metabolic diversity influences therapeutic responses. Using spatial transcriptomics of ex vivo primary human pancreatic ductal adenocarcinoma specimens, along with single-cell and bulk RNA sequencing, we mapped glycolytic heterogeneity within the tumor microenvironment. Patient-derived cell models representing distinct glycolytic phenotypes were employed to assess metabolic profiles and responses to glycolytic pathway inhibition. A multiomics approach-including metabolomics, proteomics, and lipidomics-was integrated through a robust bioinformatics pipeline to identify pathway-specific variations. Our findings revealed pronounced glycolytic heterogeneity across pancreatic ductal adenocarcinoma tumors, with distinct transcriptional profiles that maintained cellular identity and spatial architecture. These glycolytic patterns are associated with clinical outcomes, suggesting their potential as prognostic indicators. Functional studies confirmed differential sensitivity to metabolic inhibitors in organoids and demonstrated their safety across models, supporting the therapeutic relevance of glycolytic stratification. Overall, this study reveals clinically significant metabolic heterogeneity in pancreatic ductal adenocarcinoma and proposes a glycolysis-based framework for patient stratification, which could guide personalized metabolic therapies and advance precision oncology in pancreatic cancer.
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