Differential selective pressure alters rate of drug resistance acquisition in heterogeneous tumor populations
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Differential selective.pdf
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Author(s)
Sun, Daphne S.
Dalin, Simona
Hemann, Michael
Lauffenburger, Douglas A
Zhao, Boyang
Date Issued
November 2016
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Sun, Daphne, Simona Dalin, Michael T. Hemann, Douglas A. Lauffenburger, and Boyang Zhao. “Differential Selective Pressure Alters Rate of Drug Resistance Acquisition in Heterogeneous Tumor Populations.” Scientific Reports 6, no. 1 (November 7, 2016).
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Final published version
Abstract
Recent drug discovery and development efforts have created a large arsenal of targeted and chemotherapeutic drugs for precision medicine. However, drug resistance remains a major challenge as minor pre-existing resistant subpopulations are often found to be enriched at relapse. Current drug design has been heavily focused on initial efficacy, and we do not fully understand the effects of drug selective pressure on long-term drug resistance potential. Using a minimal two-population model, taking into account subpopulation proportions and growth/kill rates, we modeled long-term drug treatment and performed parameter sweeps to analyze the effects of each parameter on therapeutic efficacy. We found that drugs with the same overall initial kill may exert differential selective pressures, affecting long-term therapeutic outcome. We validated our conclusions experimentally using a preclinical model of Burkitt’s lymphoma. Furthermore, we highlighted an intrinsic tradeoff between drug-imposed overall selective pressure and rate of adaptation. A principled approach in understanding the effects of distinct drug selective pressures on short-term and long-term tumor response enables better design of therapeutics that ultimately minimize relapse.
MIT Department
Koch Institute for Integrative Cancer Research at MIT
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
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/srep36198
