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Yizhak K, Chaneton B, Gottlieb E, et al. Modeling cancer metabolism on a genome scale. Mol Syst Biol. 2015;11(6):817doi: 10.15252/msb.20145307.
Yizhak, K., Chaneton, B., Gottlieb, E., & Ruppin, E. (2015). Modeling cancer metabolism on a genome scale. Molecular systems biology, 11(6), 817. https://doi.org/10.15252/msb.20145307
Yizhak, Keren, et al. "Modeling cancer metabolism on a genome scale." Molecular systems biology vol. 11,6 (2015): 817. doi: https://doi.org/10.15252/msb.20145307
Yizhak K, Chaneton B, Gottlieb E, Ruppin E. Modeling cancer metabolism on a genome scale. Mol Syst Biol. 2015 Jun 30;11(6):817. doi: 10.15252/msb.20145307. PMID: 26130389; PMCID: PMC4501850.
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Mol Syst Biol. 2015 Jun 30;11(6):817. doi: 10.15252/msb.20145307.

Modeling cancer metabolism on a genome scale.

Molecular systems biology

Keren Yizhak, Barbara Chaneton, Eyal Gottlieb, Eytan Ruppin

Affiliations

  1. The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel [email protected] [email protected].
  2. Cancer Research UK, Beatson Institute, Glasgow, UK.
  3. The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA [email protected] [email protected].

PMID: 26130389 PMCID: PMC4501850 DOI: 10.15252/msb.20145307

Abstract

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field.

© 2015 The Authors. Published under the terms of the CC BY 4.0 license.

Keywords: Cancer metabolism; Genome‐scale simulations; Metabolic modeling

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