Optimal dosing of anti-cancer treatment under drug-induced plasticity.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Einar Bjarki Gunnarsson, Benedikt Vilji Magnússon, Jasmine Foo
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引用次数: 0

Abstract

While cancer has traditionally been considered a genetic disease, mounting evidence indicates an important role for non-genetic (epigenetic) mechanisms. Common anti-cancer drugs have recently been observed to induce the adoption of non-genetic drug-tolerant cell states, thereby accelerating the evolution of drug resistance. This confounds conventional high-dose treatment strategies aimed at maximal tumor reduction, since high doses can simultaneously promote non-genetic resistance. In this work, we study optimal dosing of anti-cancer treatment under drug-induced cell plasticity. We show that the optimal dosing strategy steers the tumor to a fixed equilibrium composition between sensitive and tolerant cells, while precisely balancing the trade-off between cell kill and tolerance induction. The optimal equilibrium strategy ranges from applying a low dose continuously to applying the maximum dose intermittently, depending on the dynamics of tolerance induction. We finally discuss how our approach can be integrated with in vitro data to derive patient-specific treatment insights.

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Abstract Image

药物诱导可塑性下抗癌治疗的最佳剂量。
虽然癌症传统上被认为是一种遗传性疾病,但越来越多的证据表明,非遗传(表观遗传)机制也起着重要作用。常见的抗癌药物最近被观察到诱导采用非遗传耐药细胞状态,从而加速耐药性的进化。这使传统的旨在最大限度减少肿瘤的高剂量治疗策略感到困惑,因为高剂量可以同时促进非遗传耐药性。在这项工作中,我们研究了药物诱导细胞可塑性下抗癌治疗的最佳剂量。我们发现,最佳给药策略使肿瘤在敏感细胞和耐受细胞之间达到固定的平衡组成,同时精确地平衡细胞杀伤和耐受诱导之间的权衡。最佳平衡策略的范围从连续施加低剂量到间歇施加最大剂量,取决于耐受诱导的动态。我们最后讨论了我们的方法如何与体外数据相结合,以获得针对患者的治疗见解。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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