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Abstract Cachexia or body wasting is a significant contributing factor to the morbidity and mortality of pancreatic cancer. Despite an unmet need, its metabolic underpinnings remain poorly understood. Here, we characterize an inducible mouse model of pancreatic cancer cachexia that recaptures human disease progression. We present longitudinal systemic metabolic profiling analyses through pre-, early and late cachexia stages in male and female pancreas, its interstitial fluid (IF), plasma, liver, adipose and skeletal muscle. We find that each tissue has a unique metabolome and trajectory across stages, and reveal metabolic signatures with marked lipid enrichment in the pancreatic IF. Using mathematical modeling, we identify metabolites participating in cross-tissue networks and in vivo validate a lactate-hexose connection. We find systemic metabolic changes prior to weight loss, and use feature selection algorithms to identify potential predictive markers of cachexia progression. Our study provides a resource for system-wide metabolic network evolution of pancreatic cancer cachexia, highlighting the potential for prevention and therapy. Citation Format: Blanca Majem, Min-Sik Lee, Kyung Cheul Shin, Insia Naqvi, Courtney Dennis, Lucas Dailey, Sarah Jeanfavre, Mari Mino-Kenudson, Joao B Xavier, Clary B Clish, Deepti Mathur, Nada Y Kalaany. Spatiotemporal metabolic networks in pancreatic cancer and associated cachexia abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84 (17 Suppl₂): Abstract nr IA-09.
Majem et al. (2024) studied this question.