Integrated spatial omics of metabolic reprogramming and the tumor microenvironment in pancreatic cancer

Hao Wu; Qiyao Zhang; Zhen Cao; Hongtao Cao; Mengwei Wu; Mengdi Fu; Tingping Huang; Xianlin Han; Xiaoyan Chang; Ziwen Liu

doi:10.1016/j.isci.2025.112681

Integrated spatial omics of metabolic reprogramming and the tumor microenvironment in pancreatic cancer

iScience. 2025 May 15;28(6):112681. doi: 10.1016/j.isci.2025.112681. eCollection 2025 Jun 20.

Authors

Hao Wu^{1

2}, Qiyao Zhang¹, Zhen Cao¹, Hongtao Cao¹, Mengwei Wu¹, Mengdi Fu³, Tingping Huang⁴, Xianlin Han¹, Xiaoyan Chang⁵, Ziwen Liu¹

Affiliations

¹ Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, P.R. China.
² Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China.
³ Department of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, P.R. China.
⁴ Lung Transplantation Center, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Nanjing 214000, P.R. China.
⁵ Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, P.R. China.

Abstract

Metabolic reprogramming is a defining feature of pancreatic cancer, influencing tumor progression and the tumor microenvironment. By integrating single-cell transcriptomics, spatial transcriptomics, and spatial metabolomics, this study visualized the spatial co-localization of metabolites and gene expression within tumor samples, uncovering metabolic heterogeneity and intercellular interactions. Spatial transcriptomics identified distinct pathological regions, which were further characterized using single-cell transcriptomic data and pathologist annotations. Pseudotime trajectory analysis revealed metabolic shifts along the malignant progression, while single-cell Metabolism (scMetabolism) delineated metabolic differences between pathological regions, classifying them as hypermetabolic or hypometabolic. Notably, aberrant cell communication between cancer cells, macrophages, and fibroblasts was observed, with key receptor-ligand pairs significantly co-expressed in malignant regions and correlated with poor prognosis. Spatial metabolomics imaging identified signature metabolites, highlighting metabolic alterations in amino acid metabolism, polyamine metabolism, fatty acid synthesis, and phospholipid metabolism. This integrated analysis provides critical insights into pancreatic cancer metabolism, offering potential avenues for targeted therapeutic interventions.

Keywords: Cancer; Metabolomics; Microenvironment; Transcriptomics.