Literature DB >> 29922569

Mass Spectrometry-Based Method to Study Inhibitor-Induced Metabolic Redirection in the Central Metabolism of Cancer Cells.

Chie Araki1, Nobuyuki Okahashi1, Kousuke Maeda1, Hiroshi Shimizu1, Fumio Matsuda1.   

Abstract

Cancer cells often respond to chemotherapeutic inhibitors by redirecting carbon flow in the central metabolism. To understand the metabolic redirections of inhibitor treatment on cancer cells, this study established a 13C-metabolic flux analysis (13C-MFA)-based method to evaluate metabolic redirection in MCF-7 breast cancer cells using mass spectrometry. A metabolic stationary state necessary for accurate 13C-MFA was confirmed during an 8-24 h window using low-dose treatments of various metabolic inhibitors. Further 13C-labeling experiments using [1-13C]glucose and [U-13C]glutamine, combined with gas chromatography-mass spectrometry (GC-MS) analysis of mass isotopomer distributions (MIDs), confirmed that an isotopic stationary state of intracellular metabolites was reached 24 h after treatment with paclitaxel (Taxol), an inhibitor of mitosis used for cancer treatment. Based on these metabolic and isotopic stationary states, metabolic flux distribution in the central metabolism of paclitaxel-treated MCF-7 cells was determined by 13C-MFA. Finally, estimations of the 95% confidence intervals showed that tricarboxylic acid cycle metabolic flux increased after paclitaxel treatment. Conversely, anaerobic glycolysis metabolic flux decreased, revealing metabolic redirections by paclitaxel inhibition. The gap between total regeneration and consumption of ATP in paclitaxel-treated cells was also found to be 1.2 times greater than controls, suggesting ATP demand was increased by paclitaxel treatment, likely due to increased microtubule polymerization. These data confirm that 13C-MFA can be used to investigate inhibitor-induced metabolic redirection in cancer cells. This will contribute to future pharmaceutical developments and understanding variable patient response to treatment.

Entities:  

Keywords:  13C-metabolic flux analysis; cancer cells; central metabolism; isotope abundance; metabolic redirection

Year:  2018        PMID: 29922569      PMCID: PMC6002601          DOI: 10.5702/massspectrometry.A0067

Source DB:  PubMed          Journal:  Mass Spectrom (Tokyo)        ISSN: 2186-5116


  47 in total

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Authors:  Peter C Hinkle
Journal:  Biochim Biophys Acta       Date:  2005-01-07

2.  Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus.

Authors:  Kashif Sheikh; Jochen Förster; Lars K Nielsen
Journal:  Biotechnol Prog       Date:  2005 Jan-Feb

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Authors:  Maciek R Antoniewicz; Joanne K Kelleher; Gregory Stephanopoulos
Journal:  Metab Eng       Date:  2006-09-17       Impact factor: 9.783

4.  Metabolic characterization of cultured mammalian cells by mass balance analysis, tracer labeling experiments and computer-aided simulations.

Authors:  Nobuyuki Okahashi; Susumu Kohno; Shunsuke Kitajima; Fumio Matsuda; Chiaki Takahashi; Hiroshi Shimizu
Journal:  J Biosci Bioeng       Date:  2015-04-27       Impact factor: 2.894

5.  Metabolic profiling of gemcitabine- and paclitaxel-treated immortalized human pancreatic cell lines with K-RASG12D.

Authors:  Akiko Todaka; Rina Umehara; Keiko Sasaki; Masakuni Serizawa; Kenichi Urakami; Masatoshi Kusuhara; Ken Yamaguchi; Hirofumi Yasui
Journal:  Biomed Res       Date:  2017       Impact factor: 1.203

Review 6.  MYC, Metabolism, and Cancer.

Authors:  Zachary E Stine; Zandra E Walton; Brian J Altman; Annie L Hsieh; Chi V Dang
Journal:  Cancer Discov       Date:  2015-09-17       Impact factor: 39.397

Review 7.  Metabolic flux rewiring in mammalian cell cultures.

Authors:  Jamey D Young
Journal:  Curr Opin Biotechnol       Date:  2013-05-28       Impact factor: 9.740

8.  Inhibition of malic enzyme 1 disrupts cellular metabolism and leads to vulnerability in cancer cells in glucose-restricted conditions.

Authors:  S Murai; A Ando; S Ebara; M Hirayama; Y Satomi; T Hara
Journal:  Oncogenesis       Date:  2017-05-08       Impact factor: 7.485

9.  Quantitative flux analysis reveals folate-dependent NADPH production.

Authors:  Jing Fan; Jiangbin Ye; Jurre J Kamphorst; Tomer Shlomi; Craig B Thompson; Joshua D Rabinowitz
Journal:  Nature       Date:  2014-05-04       Impact factor: 49.962

10.  How Taxol/paclitaxel kills cancer cells.

Authors:  Beth A Weaver
Journal:  Mol Biol Cell       Date:  2014-09-15       Impact factor: 4.138

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  1 in total

1.  Isotope Calculation Gadgets: A Series of Software for Isotope-Tracing Experiments in Garuda Platform.

Authors:  Nobuyuki Okahashi; Yuki Yamada; Junko Iida; Fumio Matsuda
Journal:  Metabolites       Date:  2022-07-14
  1 in total

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