Effect of Cellular Quiescence on the Success of Targeted CML Therapy
Effect of Cellular Quiescence on the Success of Targeted CML Therapy
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DOI：
10.1371/journal.pone.0000990
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发表时间：
2007-10-03
期刊：
影响因子：
3.7
通讯作者：
Wodarz, Dominik
中科院分区：
文献类型：
--
作者：
Komarova, Natalia L.;Wodarz, Dominik
背景。与组织干细胞类似，慢性粒细胞白血病中的原始肿瘤细胞被发现处于静止状态。也就是说，细胞可以暂时停止分裂。使用数学模型，我们研究了细胞静止对靶向小分子抑制剂治疗结果的影响。方法和结果。根据模型，治疗的开始可能导致肿瘤细胞衰退的不同模式：双相衰退、单相衰退和反向双相衰退。双相下降涉及快速的初始阶段（大致相当于药物消除循环细胞），然后是第二个较慢的指数下降阶段（对应于休眠细胞的唤醒和死亡），这有助于解释临床数据。我们定义了切换到第二阶段的时间，并确定了决定治疗是否可以在合理的时间内使肿瘤消失的参数。我们进一步询问细胞静止如何影响耐药性的进化。我们发现，如果使用单一药物进行治疗，它对治疗前存在耐药突变体的概率没有影响，但如果患者接受两种或多种不同靶点药物的组合治疗，这种静止会增加出现耐药突变体的概率。有趣的是，虽然静止延长了治疗将细胞数量减少到低水平或灭绝的时间，但治疗阶段与耐药突变体的进化无关。如果治疗因耐药性而失败，突变体将在治疗开始之前的肿瘤生长阶段进化。因此，治疗期间减少静止细胞群（例如，通过细胞活化和药物介导的杀伤相结合）并不能促进耐药性的预防。结论。数学模型提供了关于静止对 CML 靶向治疗反应基本动力学的影响的见解。他们确定了在不存在耐药突变体的情况下成功的决定因素，并阐明了静止如何影响耐药突变体的出现。
Background. Similar to tissue stem cells, primitive tumor cells in chronic myelogenous leukemia have been observed to undergo quiescence; that is, the cells can temporarily stop dividing. Using mathematical models, we investigate the effect of cellular quiescence on the outcome of therapy with targeted small molecule inhibitors. Methods and Results. According to the models, the initiation of treatment can result in different patterns of tumor cell decline: a biphasic decline, a one-phase decline, and a reverse biphasic decline. A biphasic decline involves a fast initial phase (which roughly corresponds to the eradication of cycling cells by the drug), followed by a second and slower phase of exponential decline (corresponding to awakening and death of quiescent cells), which helps explain clinical data. We define the time when the switch to the second phase occurs, and identify parameters that determine whether therapy can drive the tumor extinct in a reasonable period of time or not. We further ask how cellular quiescence affects the evolution of drug resistance. We find that it has no effect on the probability that resistant mutants exist before therapy if treatment occurs with a single drug, but that quiescence increases the probability of having resistant mutants if patients are treated with a combination of two or more drugs with different targets. Interestingly, while quiescence prolongs the time until therapy reduces the number of cells to low levels or extinction, the therapy phase is irrelevant for the evolution of drug resistant mutants. If treatment fails as a result of resistance, the mutants will have evolved during the tumor growth phase, before the start of therapy. Thus, prevention of resistance is not promoted by reducing the quiescent cell population during therapy (e. g., by a combination of cell activation and drug-mediated killing). Conclusions. The mathematical models provide insights into the effect of quiescence on the basic kinetics of the response to targeted treatment of CML. They identify determinants of success in the absence of drug resistant mutants, and elucidate how quiescence influences the emergence of drug resistant mutants.