Modeling continuous levels of resistance to multidrug therapy in cancer

被引:15
作者
Cho, Heyrim [1 ]
Levy, Doron [1 ,2 ]
机构
[1] Univ Maryland, Dept Math, College Pk, MD 20742 USA
[2] Univ Maryland, CSCAMM, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
Multidrug resistance; Tumor growth; Phenotype structured model; Epimutation; RNA-SEQUENCING REVEALS; DRUG-RESISTANCE; HEMATOPOIETIC STEM; MATHEMATICAL-MODEL; PHENOTYPIC HETEROGENEITY; PROLIFERATION KINETICS; NONGENETIC INSTABILITY; GROWTH-RATES; EVOLUTION; DIFFERENTIATION;
D O I
10.1016/j.apm.2018.07.025
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Multidrug resistance consists of a series of genetic and epigenetic alternations that involve multifactorial and complex processes, which are a challenge to successful cancer treatments. Accompanied by advances in biotechnology and high-dimensional data analysis techniques that are bringing in new opportunities in modeling biological systems with continuous phenotypic structured models, we investigate multidrug resistance by studying a cancer cell population model that considers a multi-dimensional continuous resistance trait to multiple drugs. We compare our continuous resistance trait model with classical models that assume a discrete resistance state and classify the cases when the continuum and discrete models yield different dynamical patterns in the emerging heterogeneity in response to drugs. We also compute the maximal fitness resistance trait for various continuum models and study the effect of epimutations. Finally, we demonstrate how our approach can be used to study tumor growth with respect to the turnover rate and the proliferating fraction. We show that a continuous resistance level model may result in different dynamics compared with the predictions of other discrete models. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:733 / 751
页数:19
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