Modeling Tumor Clonal Evolution for Drug Combinations Design
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nihms759499.pdf
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Author(s)
Zhao, Boyang
Hemann, Michael
Lauffenburger, Douglas A
Date Issued
March 2016
Journal
Trends in Cancer
Publisher
Elsevier BV
Citation
Zhao, Boyang, Michael T. Hemann, and Douglas A. Lauffenburger. “Modeling Tumor Clonal Evolution for Drug Combinations Design.” Trends in Cancer 2, no. 3 (March 2016): 144–158.
Version
Author's final manuscript
Abstract
Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure toward drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review we discuss the promising opportunities that these interdisciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.
Subjects
intratumoral heterogeneity tumor clonal evolution mathematical/computational modeling drug combinations drug resistance
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.TRECAN.2016.02.001
