Competition delays multi-drug resistance evolution during combination therapy
Competition delays multi-drug resistance evolution during combination therapy
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DOI：
10.1016/j.jtbi.2020.110524
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发表时间：
2021-01-21
影响因子：
2
通讯作者：
Galla, Tobias
中科院分区：
文献类型：
--
作者：
Berrios-Caro, Ernesto;Gifford, Danna R.;Galla, Tobias
联合疗法在防止对多种药物（包括艾滋病毒、结核病和癌症）产生耐药性方面取得了显著成功。然而，耐药性的上升仍然是一个重要的挑战。准确预测对一种或多种药物产生耐药性的能力可能有助于改善治疗方案。现有的理论方法往往侧重于指数增长规律，当稀缺资源和竞争限制增长时，这可能不现实。在这项工作中，我们研究了两种药物联合治疗模型中单药和双药耐药的出现。该模型描述了一种敏感菌株、两种单耐药菌株和一种双耐药菌株。我们比较了三种生长规律：指数增长、无株间竞争的logistic增长和有株间竞争的logistic增长出现耐药性的概率。通过数学估计和数值模拟，我们发现菌株间竞争仅在资源稀缺时影响单一抗性的出现。相比之下，双重抗性的概率受到在更广泛的资源可用空间上的种间竞争的影响。这表明不同耐药菌株之间的竞争可能与确定抑制耐药性的策略有关，并且指数模型可能高估了对多种药物的耐药性的出现。我们工作的副产品是一种有效的策略来评估具有多个序列突变的模型中单抗性和双抗性的概率。这可能对一系列其他的问题是有用的，其中阻力的可能性是感兴趣的。(C) 2020作者。Elsevier Ltd.出版。
Combination therapies have shown remarkable success in preventing the evolution of resistance to multiple drugs, including HIV, tuberculosis, and cancer. Nevertheless, the rise in drug resistance still remains an important challenge. The capability to accurately predict the emergence of resistance, either to one or multiple drugs, may help to improve treatment options. Existing theoretical approaches often focus on exponential growth laws, which may not be realistic when scarce resources and competition limit growth. In this work, we study the emergence of single and double drug resistance in a model of combination therapy of two drugs. The model describes a sensitive strain, two types of single-resistant strains, and a double-resistant strain. We compare the probability that resistance emerges for three growth laws: exponential growth, logistic growth without competition between strains, and logistic growth with competition between strains. Using mathematical estimates and numerical simulations, we show that between-strain competition only affects the emergence of single resistance when resources are scarce. In contrast, the probability of double resistance is affected by between-strain competition over a wider space of resource availability. This indicates that competition between different resistant strains may be pertinent to identifying strategies for suppressing drug resistance, and that exponential models may overestimate the emergence of resistance to multiple drugs. A by-product of our work is an efficient strategy to evaluate probabilities of single and double resistance in models with multiple sequential mutations. This may be useful for a range of other problems in which the probability of resistance is of interest. (C) 2020 The Authors. Published by Elsevier Ltd.