The importance of metabolism in cancer is becoming increasingly apparent with the identification of metabolic enzyme mutations and the growing awareness of the influence of metabolism on signaling, epigenetic markers, and transcription. However, the complexity of these processes has challenged our ability to make sense of the metabolic changes in cancer. Fortunately, constraint-based modeling, a systems biology approach, now enables one to study the entirety of cancer metabolism and simulate basic phenotypes. With the newness of this field, there has been a rapid evolution of both the scope of these models and their applications. Here we review the various constraint-based models built for cancer metabolism and how their predictions are shedding new light on basic cancer phenotypes, elucidating pathway differences between tumors, and dicovering putative anti-cancer targets. As the field continues to evolve, the scope of these genome-scale cancer models must expand beyond central metabolism to address questions related to the diverse processes contributing to tumor development and metastasis.
Keywords: cancer, metabolism, omics, systems biology, constraint-based modeling, data analysis, modeling and simulation, warburg effect
Citation: Lewis NE and Abdel-Haleem AM (2013) The evolution of genome-scale models of cancer metabolism. Front. Physiol. 4:237. doi: 10.3389/fphys.2013.00237
Received: 30 May 2013; Accepted: 13 August 2013;
Published online: 03 September 2013.
Edited by:Erwin Gianchandani, National Science Foundation, USA
Reviewed by:Jason Papin, University of Virginia, USA
Copyright © 2013 Lewis and Abdel-Haleem. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Nathan E. Lewis, Department of Biology, Brigham Young University, 401 WIDB, Provo, UT 84602, USA e-mail: email@example.com