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Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis.


ABSTRACT: Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

SUBMITTER: Nilsson A 

PROVIDER: S-EPMC7229649 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis.

Nilsson Avlant A   Haanstra Jurgen R JR   Engqvist Martin M   Gerding Albert A   Bakker Barbara M BM   Klingmüller Ursula U   Teusink Bas B   Nielsen Jens J  

Proceedings of the National Academy of Sciences of the United States of America 20200427 19


Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for  ...[more]

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