Glycolytic heterogeneity drives metabolic-targeted therapy in PDAC

Background: Pancreatic ductal adenocarcinoma is classically characterized as a glycolytic tumor. However, the extent and implications of metabolic heterogeneity within PDAC remain poorly defined. This study aimed to determine whether glycolytic activity follows a consistent expression pattern across PDAC patients and to explore how metabolic diversity influences therapeutic vulnerability. Methods: We employed spatial transcriptomics in six, ex vivo, primary human PDAC specimens, complemented by single-cell and bulk RNA sequencing, to map glycolytic heterogeneity in PDAC. Patient-derived cell models, representative of distinct glycolytic phenotypes, were used to assess metabolic and antiproliferative responses to glycolytic pathway inhibition. A comprehensive multi-omics strategy—including metabolomics, proteomics, and lipidomics—was integrated through a robust bioinformatics pipeline to dissect pathway-specific variations and integromics. Results: PDAC tumors displayed marked glycolytic heterogeneity, with distinct transcriptional profiles that preserved cell identity and spatial organization. These glycolytic patterns correlated with clinical outcomes, highlighting their potential prognostic value. Functional studies strengthen differential sensitivity to metabolic inhibitors in models with opposite glycolytic activity, demonstrating both the therapeutic relevance of PDAC glycolytic stratification and highlighting the potential of metabolic targeting. Conclusions: Our findings uncover a clinically relevant metabolic heterogeneity in PDAC, offering a novel stratification framework based on glycolytic profiling. This approach may allow the selection of patients for tailored metabolic therapies, advancing precision oncology in pancreatic cancer. Overall design: Pancreas samples have been acquired from patients with pancreatic ductal adenocarcinoma diagnosis, having a grade between 2-3, T and N, respectively, between 2-3 and 0-1.