Peer-reviewedCC BY-NC-ND 4.0Proceedings of the National Academy of Sciences of the United States of America
Modeling a continuum of drug-induced persistence during targeted cancer therapy
- 1Department of Physics, Northeastern University, Boston, MA 02115
- 2Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115
- 3Department of Bioengineering, Northeastern University, Boston, MA 02115
Abstract
We introduce a general phenomenological framework for understanding how phenotypic plasticity gives rise to drug persisters. These persisters, often quiescent but which sometimes return to cycling, survive in the presence of targeted therapy and eventually can lead to mutants with true resistance. Our framework builds on recent experimental observations regarding variations between and among single-cell clones and the possible role of the drug itself in enhancing the survival strategy. Predictions of our approach include the existence of an optimum drug concentration as well as an optimum drug holiday schedule to minimize the persistence-based threat.
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BibTeX
@article{park2026modeling,
title = {{Modeling a continuum of drug-induced persistence during targeted cancer therapy}},
author = {Ji Tae Park and Herbert Levine},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
year = {2026},
month = oct,
doi = {10.1073/pnas.2617783123},
url = {https://doi.org/10.1073/pnas.2617783123},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Modeling a continuum of drug-induced persistence during targeted cancer therapy
AU - Ji Tae Park
AU - Herbert Levine
PY - 2026
DA - 2026/10/27
JO - Proceedings of the National Academy of Sciences of the United States of America
DO - 10.1073/pnas.2617783123
UR - https://doi.org/10.1073/pnas.2617783123
AB - We introduce a general phenomenological framework for understanding how phenotypic plasticity gives rise to drug persisters. These persisters, often quiescent but which sometimes return to cycling, survive in the presence of targeted therapy and eventually can lead to mutants with true resistance. Our framework builds on recent experimental observations regarding variations between and among single-cell clones and the possible role of the drug itself in enhancing the survival strategy. Predictions of our approach include the existence of an optimum drug concentration as well as an optimum drug holiday schedule to minimize the persistence-based threat.
SN - 0027-8424
SN - 1091-6490
ER -