Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation
Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation
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DOI：
10.1016/j.bbagen.2016.06.009
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发表时间：
2016-11-01
影响因子：
3
通讯作者：
Clairambault, Jean
中科院分区：
文献类型：
--
作者：
Chisholm, Rebecca H.;Lorenzi, Tommaso;Clairambault, Jean
背景资料：药物诱导的癌症耐药性已被归因于不同的生物学机制，在单个细胞或细胞群体的规模，依赖于随机或表观遗传学上不同的表型表达在单细胞水平上，和肿瘤的适应性在细胞群体level.Scope的审查：我们专注于肿瘤内的异质性，即癌细胞群体内的细胞间变异性，占耐药性。为了阐明这种异质性，我们回顾了进化机制，包括设计多细胞生物的伟大进化，以及人类疾病时间尺度上较小的进化窗口。我们还提出了用于预测癌症耐药性的数学模型和在联合治疗策略中可以规避耐药性的最佳控制方法。主要结论：癌细胞的可塑性，即，在单个细胞中部分逆转为干细胞样状态以及由此产生的癌细胞群体的适应性可被视为使癌细胞群体对药物损伤具有抗性的后向进化。这种可逆的可塑性被数学模型所捕获，该模型通过连续的表型变量将细胞间的异质性纳入其中。这样的模型具有与用于设计优化的治疗方案的最佳控制方法兼容的益处，所述治疗方案涉及细胞毒性和细胞抑制治疗与表观遗传药物和免疫疗法的组合。从癌症和进化生物学中收集知识，并利用基于生理学的细胞群体动力学数学模型，应该为肿瘤学家提供设计优化治疗策略以规避药物治疗的基本原理。耐药性，这仍然是癌症治疗的主要陷阱。本文是特刊《系统遗传学》的一部分，客座编辑：蔡玉东博士和黄涛博士。(C)2016爱思唯尔B.V.保留所有权利。
Background: Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level.Scope of review: We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies.Major conclusions: Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies.General significance: Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. (C) 2016 Elsevier B.V. All rights reserved.