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Unraveling the Complex Regulatory Relationships Between Metabolism and Signal Transduction in Cancer

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Advances in Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 736))

Abstract

Cancer cells exhibit an altered metabolic phenotype, known as the Warburg effect, which is characterized by high rates of glucose uptake and glycolysis, even under aerobic conditions. The Warburg effect appears to be an intrinsic component of most cancers and there is evidence linking cancer progression to mutations, translocations, and alternative splicing of genes that directly code for or have downstream effects on key metabolic enzymes. Many of the same signaling pathways are routinely dysregulated in cancer and a number of important oncogenic signaling pathways play important regulatory roles in central carbon metabolism. Unraveling the complex regulatory relationship between cancer metabolism and signaling requires the application of systems biology approaches. Here we discuss computational approaches for modeling protein signal transduction and metabolism as well as how the regulatory relationship between these two important cellular processes can be combined into hybrid models.

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Notes

  1. 1.

    The idea of a Laplace Demon came from a thought experiment proposed by Pierre-Simon Laplace of a perfect entity who would know the precise location of each atom and of all forces in nature at any given moment. This entity (or demon, as it later came to be called) would have incredible predictive power because it could infer the past and determine the future from any set of initial conditions.

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Acknowledgements

This work was partially supported by the University of Michigan Center for Computational Medicine & Bioinformatics Pilot Grant 2010 and the National Science Foundation under Grant No. DMS-1135663. MLW acknowledges support from the Rackham Merit Fellowship, NIH T32 CA140044, and the Breast Cancer Research Foundation. SDM acknowledges support from the Burroughs Wellcome Fund, Breast Cancer Research Foundation, the Avon Foundation and NIH CA77612. SS acknowledges support from NIDDK R25 DK088752.

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Authors and Affiliations

  1. Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA

    Michelle L. Wynn

  2. Department of Internal Medicine and Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA

    Sofia D. Merajver

  3. Department of Molecular and Integrative Physiology, Center for Computational Medicine and Bioinformatics and Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI, USA

    Santiago Schnell

Authors
  1. Michelle L. Wynn
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  2. Sofia D. Merajver
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  3. Santiago Schnell
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Corresponding author

Correspondence to Santiago Schnell .

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Editors and Affiliations

  1. School of Informatics, University of Edinburgh, Crichton Street 10, Edinburgh, EH89AB, UK

    Igor I. Goryanin

  2. School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH93JR, UK

    Andrew B. Goryachev

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Wynn, M.L., Merajver, S.D., Schnell, S. (2012). Unraveling the Complex Regulatory Relationships Between Metabolism and Signal Transduction in Cancer. In: Goryanin, I.I., Goryachev, A.B. (eds) Advances in Systems Biology. Advances in Experimental Medicine and Biology, vol 736. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7210-1_9

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