Abstract A060: Metabolic patterns in pancreatic cancer cachexia

Abstract

Abstract Cachexia is a multi-organ pathological state characterized by physical wasting and tissue catabolism. It occurs in 80% of pancreatic cancer patients, and to date there are no preventative or early detection methods. Cachexia leads to limited tolerance to anti-cancer therapy and is a lethal disease. Here, we have characterized a mouse model of cachexia in pancreatic ductal adenocarcinoma (PDAC) in order to better understand disease progression: the physiology across stages of cachexia in the model recaptures well the progressive disease in humans. We present the first-of-its-kind systemic metabolomic analysis across cachectic stages in the tumor, interstitial fluid, liver, fats, muscles, and blood plasma. The primary source of variation in the data is the tissue type, indicating that each tissue has a unique metabolome and trajectory across cachexia stages. We use mathematical modeling to identify metabolites that may be participating in cross-tissue networks in pre-, early-, and late-stage cachexia. Pathway analysis shows a particular emphasis on lipid alterations. Strikingly, we find systemic metabolic changes prior to weight loss or other disease symptoms, and use feature selection algorithms to identify potential predictive markers of cachexia progression. Overall, we hope our work is a valuable resource for the field and will lay the foundation for metabolic insights into pancreatic cancer cachexia and its prevention and treatment. Citation Format: Deepti Mathur, Blanca Majem, Nada Kalaany. Metabolic patterns in pancreatic cancer cachexia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A060.