The impact of competition between cancer cells and healthy cells on optimal drug delivery

The impact of competition between cancer cells and healthy cells on optimal drug delivery
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DOI:
10.1051/mmnp/2019043
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发表时间:
2020-09-22
影响因子:
2.2
通讯作者:
Levy, Doron
Levy, Doron
中科院分区:
数学4区
文献类型:
--
作者:
Cho, Heyrim;Levy, Doron

文献摘要

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细胞竞争被认为是有助于在侵袭性癌症中的肿瘤-宿主界面的动力学和结构。在温和的竞争情况下,健康组织和癌细胞可以共存。当竞争激烈时,竞争细胞,所谓的超级竞争者,通过杀死其他细胞来扩张。新型化疗药物和分子靶向药物通常作为癌症治疗的一部分施用。这两种类型的药物都容易受到各种耐药性机制的影响,阻碍或阻止成功的结果。在本文中,我们开发了一个癌症生长模型,该模型考虑了癌细胞和健康细胞之间的竞争。该模型结合了对化疗和靶向药物的耐药性。在这两种情况下,耐药性水平被假定为从完全敏感到完全耐药的连续变量。使用我们的模型,我们证明,当竞争是温和的,使用两种药物的治疗方法比单一药物治疗更有效。然而,当癌细胞高度竞争时,靶向药物变得更有效。研究结果强调了根据治疗前的耐药水平调整治疗的重要性。最后,我们研究了在竞争环境中耐药性的时空传播,验证了在空间异质性情况下同样的结论。
Cell competition is recognized to be instrumental to the dynamics and structure of the tumor-host interface in invasive cancers. In mild competition scenarios, the healthy tissue and cancer cells can coexist. When the competition is aggressive, competitive cells, the so called super-competitors, expand by killing other cells. Novel chemotherapy drugs and molecularly targeted drugs are commonly administered as part of cancer therapy. Both types of drugs are susceptible to various mechanisms of drug resistance, obstructing or preventing a successful outcome. In this paper, we develop a cancer growth model that accounts for the competition between cancer cells and healthy cells. The model incorporates resistance to both chemotherapy and targeted drugs. In both cases, the level of drug resistance is assumed to be a continuous variable ranging from fully-sensitive to fully-resistant. Using our model we demonstrate that when the competition is moderate, therapies using both drugs are more effective compared with single drug therapies. However, when cancer cells are highly competitive, targeted drugs become more effective. The results of the study stress the importance of adjusting the therapy to the pre-treatment resistance levels. We conclude with a study of the spatiotemporal propagation of drug resistance in a competitive setting, verifying that the same conclusions hold in the spatially heterogeneous case.