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

INTRODUCTION: 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 comput...

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Autores principales: Yang, Grace, Huang, Shaoyang, Hu, Kevin, Lu, Alex, Yang, Jonathan, Meroueh, Noah, Dang, Pengtao, Wang, Yijie, Zhu, Haiqi, Cao, Sha, Zhang, Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291142/
https://www.ncbi.nlm.nih.gov/pubmed/37377905
http://dx.doi.org/10.3389/fonc.2023.1117810
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author Yang, Grace
Huang, Shaoyang
Hu, Kevin
Lu, Alex
Yang, Jonathan
Meroueh, Noah
Dang, Pengtao
Wang, Yijie
Zhu, Haiqi
Cao, Sha
Zhang, Chi
author_facet Yang, Grace
Huang, Shaoyang
Hu, Kevin
Lu, Alex
Yang, Jonathan
Meroueh, Noah
Dang, Pengtao
Wang, Yijie
Zhu, Haiqi
Cao, Sha
Zhang, Chi
author_sort Yang, Grace
collection PubMed
description INTRODUCTION: 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.
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spelling pubmed-102911422023-06-27 Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer Yang, Grace Huang, Shaoyang Hu, Kevin Lu, Alex Yang, Jonathan Meroueh, Noah Dang, Pengtao Wang, Yijie Zhu, Haiqi Cao, Sha Zhang, Chi Front Oncol Oncology INTRODUCTION: 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. Frontiers Media S.A. 2023-06-12 /pmc/articles/PMC10291142/ /pubmed/37377905 http://dx.doi.org/10.3389/fonc.2023.1117810 Text en Copyright © 2023 Yang, Huang, Hu, Lu, Yang, Meroueh, Dang, Wang, Zhu, Cao and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Yang, Grace
Huang, Shaoyang
Hu, Kevin
Lu, Alex
Yang, Jonathan
Meroueh, Noah
Dang, Pengtao
Wang, Yijie
Zhu, Haiqi
Cao, Sha
Zhang, Chi
Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title_full Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title_fullStr Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title_full_unstemmed Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title_short Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
title_sort flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291142/
https://www.ncbi.nlm.nih.gov/pubmed/37377905
http://dx.doi.org/10.3389/fonc.2023.1117810
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