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

dc.contributor.authorYang, Grace
dc.contributor.authorHuang, Shaoyang
dc.contributor.authorHu, Kevin
dc.contributor.authorLu, Alex
dc.contributor.authorYang, Jonathan
dc.contributor.authorMeroueh, Noah
dc.contributor.authorDang, Pengtao
dc.contributor.authorWang, Yijie
dc.contributor.authorZhu, Haiqi
dc.contributor.authorCao, Sha
dc.contributor.authorZhang, Chi
dc.contributor.departmentElectrical and Computer Engineering, School of Engineering and Technology
dc.date.accessioned2024-01-26T11:59:47Z
dc.date.available2024-01-26T11:59:47Z
dc.date.issued2023-06-12
dc.description.abstractIntroduction: Glucose and glutamine are major carbon and energy sources that promote the rapid proliferation of cancer cells. Metabolic shifts observed on cell lines or mouse models may not reflect the general metabolic shifts in real human cancer tissue. Method: In this study, we conducted a computational characterization of the flux distribution and variations of the central energy metabolism and key branches in a pan-cancer analysis, including the glycolytic pathway, production of lactate, tricarboxylic acid (TCA) cycle, nucleic acid synthesis, glutaminolysis, glutamate, glutamine, and glutathione metabolism, and amino acid synthesis, in 11 cancer subtypes and nine matched adjacent normal tissue types using TCGA transcriptomics data. Result: Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of the TCA cycle, i.e., the Warburg effect, in almost all the analyzed cancer. However, increased lactate production and the second half of the TCA cycle were only seen in certain cancer types. More interestingly, we failed to detect significantly altered glutaminolysis in cancer tissues 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 in tissue-specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. Discussion: This study strongly suggests the possibility of having a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors.
dc.eprint.versionFinal published version
dc.identifier.citationYang G, Huang S, Hu K, et al. Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer. Front Oncol. 2023;13:1117810. Published 2023 Jun 12. doi:10.3389/fonc.2023.1117810
dc.identifier.urihttps://hdl.handle.net/1805/38212
dc.language.isoen_US
dc.publisherFrontiers Media
dc.relation.isversionof10.3389/fonc.2023.1117810
dc.relation.journalFrontiers in Oncology
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectTCA cycle
dc.subjectCancer metabolism
dc.subjectFlux estimation
dc.subjectGlutaminolysis
dc.subjectSystems biology
dc.titleFlux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
dc.typeArticle
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