Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes-Reference-Cited by-同舟云学术

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Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes

Published:2022-10 Issue:5 Volume:15 Page:521-533
ISSN:1865-5025
Container-title:Cellular and Molecular Bioengineering
language:en
Short-container-title:Cel. Mol. Bioeng.

Author:

Leighow Scott M.,Landry Ben,Lee Michael J.,Peyton Shelly R.,Pritchard Justin R.

Funder

National Cancer Institute

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation

Link

https://link.springer.com/content/pdf/10.1007/s12195-022-00748-6.pdf

Reference65 articles.

1. Bacevic, K., et al. Spatial competition constrains resistance to targeted cancer therapy. Nat. Commun. 2017. https://doi.org/10.1038/s41467-017-01516-1

2. Beltran, H., et al. Challenges in recognizing treatment-related neuroendocrine prostate cancer. J. Clin. Oncol. 30:e386, 2012

3. Boelens, M. C., et al. Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways. Cell. 159:499–513, 2014

4. Bozic, I., et al. Evolutionary dynamics of cancer in response to targeted combination therapy. Elife. 2:e00747, 2013

5. Cao, Y., D. T. Gillespie, and L. R. Petzold. Efficient step size selection for the tau-leaping simulation method. J Chem Phys. 124(4):044109, 2006

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