A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration

Keren Yizhak*, Sylvia E. Le Dévédec, Vasiliki Maria Rogkoti, Franziska Baenke, Vincent C. De Boer, Christian Frezza, Almut Schulze, Bob Van De Water, Eytan Ruppin

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

105 Citations (Scopus)

Abstract

Over the last decade, the field of cancer metabolism has mainly focused on studying the role of tumorigenic metabolic rewiring in supporting cancer proliferation. Here, we perform the first genome-scale computational study of the metabolic underpinnings of cancer migration. We build genome-scale metabolic models of the NCI-60 cell lines that capture the Warburg effect (aerobic glycolysis) typically occurring in cancer cells. The extent of the Warburg effect in each of these cell line models is quantified by the ratio of glycolytic to oxidative ATP flux (AFR), which is found to be highly positively associated with cancer cell migration. We hence predicted that targeting genes that mitigate the Warburg effect by reducing the AFR may specifically inhibit cancer migration. By testing the anti-migratory effects of silencing such 17 top predicted genes in four breast and lung cancer cell lines, we find that up to 13 of these novel predictions significantly attenuate cell migration either in all or one cell line only, while having almost no effect on cell proliferation. Furthermore, in accordance with the predictions, a significant reduction is observed in the ratio between experimentally measured ECAR and OCR levels following these perturbations. Inhibiting anti-migratory targets is a promising future avenue in treating cancer since it may decrease cytotoxic-related side effects that plague current anti-proliferative treatments. Furthermore, it may reduce cytotoxic-related clonal selection of more aggressive cancer cells and the likelihood of emerging resistance. Synopsis A computational analysis based on genome-scale metabolic models shows that the extent of the Warburg effect is highly associated with cancer cell migration across different cell lines and identifies anti-migratory targets. Genome-scale metabolic models of each the NCI-60 cell lines correctly capture the Warburg effect. The extent of the Warburg effect, as quantified by the ratio between glycolytic and oxidative ATP flux rate (AFR), positively associates with cancer cell migration across the different cell lines. siRNA knockdown of 13 genes predicted to reduce the AFR attenuates cell migration while having almost no effect on cell proliferation. In agreement with the predictions, a significant reduction in the ratio of glycolytic/oxidative capacity is observed following these gene perturbations. A computational analysis based on genome-scale metabolic models shows that the extent of the Warburg effect is highly associated with cancer cell migration across different cell lines and identifies anti-migratory targets.
Original languageEnglish
Article number744
JournalMolecular Systems Biology
Volume10
Issue number8
DOIs
Publication statusPublished - Aug 2014
Externally publishedYes

Keywords

  • cancer cell migration
  • cellular metabolism
  • genome-scale metabolic modeling

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