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2007-10-26 13:53:15

PLoS ONE:抗癌药物趁细胞“苏醒”时清除肿瘤细胞

    美国加利福尼亚大学学者研究认为,抗癌药物清除肿瘤细胞于它们“苏醒”时而非细胞休眠时。(《公共科学图书馆·综合》(PLoS  ONE)  2(10):  e990)

    细胞休眠,即细胞暂时停止分裂。研究人员建立了一个数学模型来分析细胞休眠对伊马替尼靶向治疗慢性粒细胞性白血病(CML)的影响。Komarova等明确了治疗反应中第一时相(大致对应于药物清除循环中的癌细胞)向第二时相(对应于休眠细胞的苏醒和死亡)发生转化的时间,确立起一些参数用以判断药物治疗在合理的时间范围内能否消除肿瘤细胞,并进一步对细胞休眠状态如何影响其药物耐药性加以研究。

    研究者对休眠的肿瘤细胞施用化疗药物治疗发现,如果肿瘤细胞在进行单一药物治疗之前已经发生了耐药突变,则细胞休眠对耐药突变率没有影响;但如果接受了两种或者多种不同靶标的药物联合治疗,则细胞休眠会增加耐药突变率。有趣的是,虽然细胞休眠延长了药物减少或清除肿瘤细胞所需的时间,但治疗时相与耐药突变的演变无关。

    该研究提示,因细胞耐药而导致的治疗失败,细胞耐药突变发生于肿瘤细胞生长期。因此,通过在细胞休眠期减少肿瘤细胞的数量(例如,联合使用细胞激活药物和药物介导的杀细胞药物)并不能阻止肿瘤细胞耐药的发生。(中国医学论坛报)

原始出处:

PLoS  ONE

Received: April 13, 2007; Accepted: September 4, 2007; Published: October 3, 2007

Effect of Cellular Quiescence on the Success of Targeted CML Therapy

Natalia L. Komarova1,2, Dominik Wodarz1,2*

1 Department of Mathematics, University of California Irvine, Irvine, California, United States of America, 2 Department of Ecology and Evolution, University of California Irvine, Irvine, California, United States of America

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.

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新型抗癌药物威力大 切断肿瘤营养通道

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