A survey of adaptive cell population dynamics models of emergence of drug resistance in cancer, and open questions about evolution and cancer

Q2 Agricultural and Biological Sciences Biomath Pub Date : 2019-05-24 DOI:10.11145/J.BIOMATH.2019.05.147
J. Clairambault, Camille Pouchol
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引用次数: 11

Abstract

This article is a proceeding survey (deepening a talk given by the first author at the Biomath 2019 International Conference on Mathematical Models and Methods, held in Bedlewo, Poland) of mathematical models of cancer and healthy cell population adaptive dynamics exposed to anticancer drugs, to describe how cancer cell populations evolve toward drug resistance.Such mathematical models consist of partial differential equations (PDEs) structured in continuous phenotypes coding for the expression of drug resistance genes; they involve different functions representing targets for different drugs, cytotoxic and cytostatic, with complementary effects in limiting tumour growth. These phenotypes evolve continuously under drug exposure, and their fate governs the evolution of the cell population under treatment. Methods of optimal control are used, taking inevitable emergence of drug resistance into account, to achieve the best strategies to contain the expansion of a tumour.This evolutionary point of view, which relies on biological observations and resulting modelling assumptions, naturally extends to questioning the very nature of cancer as evolutionary disease, seen not only at the short time scale of a human life, but also at the billion year-long time scale of Darwinian evolution, from unicellular organisms to evolved multicellular organs such as animals and man. Such questioning, not so recent, but recently revived, in cancer studies, may have consequences for understanding and treating cancer.Some open and challenging questions may thus be (non exhaustively) listed as:- May cancer be defined as a spatially localised loss of coherence between tissues in the same multicellular organism, `spatially localised' meaning initially starting from a given organ in the body, but also possibly due to flaws in an individual's rms of evolution towards drug resistance governed by the phenotypes which determine landscape such as imperfect epigenetic control of differentiation genes?- If one assumes that ''The genes of cellular cooperation that evolved with multicellularity about a billion years ago arethe same genes that malfunction in cancer.'', how can these genes besystematically investigated, looking for zones of fragility - that depend on individuals - in the 'tinkering' evolution is made of, tracking local defaults of coherence?- What is such coherence made of and to what extent is the immune system responsible for it (the self and differentiation within the self)?Related to this question of self, what parallelism can be established between the development of multicellularity in different species proceeding from the same origin and the development of the immune system in these different species?
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癌症耐药性出现的适应性细胞群动力学模型的调查,以及关于进化和癌症的开放性问题
本文是一项正在进行的调查(深化了第一作者在波兰贝德勒沃举行的Biomath 2019年国际数学模型与方法会议上的演讲),研究癌症和健康细胞群体暴露于抗癌药物下的适应动力学的数学模型,以描述癌细胞群体如何进化为耐药性。这些数学模型由偏微分方程(PDEs)组成,这些偏微分方程结构为连续表型,编码耐药基因的表达;它们涉及不同的功能,代表不同药物的目标,细胞毒性和细胞抑制剂,在限制肿瘤生长方面具有互补作用。这些表型在药物暴露下不断进化,它们的命运支配着治疗下细胞群的进化。使用最优控制方法,考虑到不可避免的耐药性的出现,以实现控制肿瘤扩张的最佳策略。这种基于生物学观察和由此产生的建模假设的进化观点,自然延伸到质疑癌症作为进化疾病的本质,不仅在人类生命的短时间尺度上,而且在达尔文进化的数十亿年时间尺度上,从单细胞生物到进化的多细胞器官,如动物和人。这样的问题,不是最近才出现的,但最近在癌症研究中重新出现,可能会对理解和治疗癌症产生影响。因此,一些开放和具有挑战性的问题可能被(非详尽地)列出:-癌症是否可以被定义为同一多细胞生物中组织之间空间局部一致性的丧失,“空间局部”意味着最初从体内的给定器官开始,但也可能是由于个体进化的rms中的缺陷,这些缺陷由决定景观的表型控制,例如分化基因的不完美表观遗传控制?如果有人假设“大约10亿年前随着多细胞进化而来的细胞合作基因与癌症中发生故障的基因是相同的。”,如何系统地研究这些基因,在构成进化的“修补”过程中寻找依赖于个体的脆弱区域,追踪局部一致性的默认值?-这种一致性是由什么构成的,免疫系统在多大程度上负责它(自我和自我内部的分化)?与这个自我问题相关的是,在不同物种的多细胞发展和这些不同物种的免疫系统发展之间,可以建立什么样的相似性?
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来源期刊
Biomath
Biomath Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
6
审稿时长
20 weeks
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