Cancer Lett. 2026 May 16;653:218585. doi: 10.1016/j.canlet.2026.218585. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma is characterized by a fibrotic and metabolically active tumor microenvironment where cancer-associated fibroblasts (CAFs) mediate metabolic crosstalk, extracellular matrix (ECM) remodeling, and immune regulation. However, the metabolic and spatial heterogeneity of CAFs remains incompletely understood. We integrated spatial transcriptomics and spatial metabolomics data from PDAC tissues and performed SpatialGlue-based multimodal clustering to define CAF subtypes. To characterize metabolic communication, we developed an optimal transport (OT)-based metabolic inference framework to quantitatively model metabolite association between CAFs and tumor cells. Subtype-specific features were independently validated using an independent spatial metabolomics cohort and multiplex immunofluorescence (mIHC) staining. Furthermore, these features were correlated with clinical outcomes via TCGA-PAAD deconvolution. Spatial multi-omics integration identified three robust CAF subtypes with distinct signatures. OT analysis revealed differential metabolic interactions: CAF_C0 mediated amino acid/peptide transfer, CAF_C1 was the primary source of lipids, while CAF_C2 exhibited limited metabolic association but stronger immune and ECM signaling activity. Deconvolution confirmed that CAF composition was strongly associated with prognosis; CAF_C2 enrichment predicted poorer survival and gemcitabine resistance, whereas a higher CAF_C0/CAF_C1 balance correlated with improved outcomes. By combining spatial multi-omics with OT-based modeling, this study delineates metabolically and spatially distinct CAF states with clinical relevance. Our findings suggest CAFs act as both metabolic donors and immune-ECM regulators, providing new insights into stromal reprogramming and potential subtype-specific therapeutic targets in PDAC.

PMID:42144098 | DOI:10.1016/j.canlet.2026.218585