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Journal of Bioenergetics and Biomembranes

, Volume 39, Issue 3, pp 251–257 | Cite as

Adaptive landscapes and emergent phenotypes: why do cancers have high glycolysis?

  • Robert J. Gillies
  • Robert A. Gatenby
Mini Review

Abstract

Investigating the causes of increased aerobic glycolysis in tumors (Warburg Effect) has gone in and out of fashion many times since it was first described almost a century ago. The field is currently in ascendance due to two factors. Over a million FDG-PET studies have unequivocally identified increased glucose uptake as a hallmark of metastatic cancer in humans. These observations, combined with new molecular insights with HIF-1α and c-myc, have rekindled an interest in this important phenotype. A preponderance of work has been focused on the molecular mechanisms underlying this effect, with the expectation that a mechanistic understanding may lead to novel therapeutic approaches. There is also an implicit assumption that a mechanistic understanding, although fundamentally reductionist, will nonetheless lead to a more profound teleological understanding of the need for altered metabolism in invasive cancers. In this communication, we describe an alternative approach that begins with teleology; i.e. adaptive landscapes and selection pressures that promote emergence of aerobic glycolysis during the somatic evolution of invasive cancer. Mathematical models and empirical observations are used to define the adaptive advantage of aerobic glycolysis that would explain its remarkable prevalence in human cancers. These studies have led to the hypothesis that increased consumption of glucose in metastatic lesions is not used for substantial energy production via Embden-Meyerhoff glycolysis, but rather for production of acid, which gives the cancer cells a competitive advantage for invasion. Alternative hypotheses, wherein the glucose is used for generation of reducing equivalents (NADPH) or anabolic precursors (ribose) are also discussed.

Keywords

Aerobic glycolysis Acid-base Somatic evolution Math models 

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department of Radiology, Arizona Cancer CenterUniversity of Arizona Health Sciences CenterTucsonUSA

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