Abstract 2047: Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer

Abstract

Abstract Background: Glucose and glutamine are major carbon and energy sources that promote the fast proliferation of cancer cells. The Warburg effect, characterized by shifted flux ratio between aerobic and anaerobic respirations, is considered as a common metabolic reprogramming mechanism in cancer. The further discovery of glutaminolysis pathway elucidated the role of glutamate in providing energy and carbon source in cancer metabolism. Variations in the branches of the central metabolism of glucose and glutamate have also been observed. However, most of these observations were made on cell line or mouse systems, which cannot mimic the dysbalanced nutrient, redox, pH and oxygen levels in a real tumor microenvironment (TME), which may heavily shift in a TME and determines the metabolic phenotypes of a cancer. Analysis: In this study, we conducted a systematic evaluation of the metabolic reprogramming and characteristics via a computational analysis by using pan-cancer transcriptomics data of 11 cancer subtypes and 9 matched adjacent normal tissue types. We focused on the flux distribution and variations of the central energy metabolism and its key branches. We first reconstructed the central metabolism pathway in a subcellular resolution by including glycolytic pathway, production of lactate, TCA cycle, nucleic acids synthesis, glutaminolysis, glutaminate, glutamine and glutathione metabolism, and other amino acids synthesis. We applied our in-house developed scFEA method on TCGA pan-cancer transcriptomics data. Results: Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of TCA cycle, i.e., Warburg effect in almost all the analyzed cancer types. However, increased lactate production and the second half of TCA cycle were only seen in certain cancer types. More interestingly, we did not see cancer tissues have highly shifted glutaminolysis compared to their adjacent normal tissues. A systems biology model of metabolic shifts through cancer and tissue types is further developed and analyzed. We observed that (1) normal tissues have distinct metabolic phenotypes, (2) cancer types have drastically different metabolic shifts compared to their adjacent normal controls, and (3) the different shifts happened to tissue specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. This study strongly suggests the possibility to have a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors. Citation Format: Alex Lu, Haiqi Zhu, Kevin Hu, Grace Yang, Shaoyang Huang, Pengtao Dang, Sha Cao, Chi Zhang. Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2047.