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癌症中有利于和不利于基因不稳定的选择压力:一个随时间变化的问题。

Selective pressures for and against genetic instability in cancer: a time-dependent problem.

作者信息

Komarova Natalia L, Sadovsky Alexander V, Wan Frederic Y M

机构信息

Department of Mathematics, University of California, Irvine, CA 92697, USA.

出版信息

J R Soc Interface. 2008 Jan 6;5(18):105-21. doi: 10.1098/rsif.2007.1054.

Abstract

Genetic instability in cancer is a two-edge sword. It can both increase the rate of cancer progression (by increasing the probability of cancerous mutations) and decrease the rate of cancer growth (by imposing a large death toll on dividing cells). Two of the many selective pressures acting upon a tumour, the need for variability and the need to minimize deleterious mutations, affect the tumour's 'choice' of a stable or unstable 'strategy'. As cancer progresses, the balance of the two pressures will change. In this paper, we examine how the optimal strategy of cancerous cells is shaped by the changing selective pressures. We consider the two most common patterns in multistage carcinogenesis: the activation of an oncogene (a one-step process) and an inactivation of a tumour-suppressor gene (a two-step process). For these, we formulate an optimal control problem for the mutation rate in cancer cells. We then develop a method to find optimal time-dependent strategies. It turns out that for a wide range of parameters, the most successful strategy is to start with a high rate of mutations and then switch to stability. This agrees with the growing biological evidence that genetic instability, prevalent in early cancers, turns into stability later on in the progression. We also identify parameter regimes where it is advantageous to keep stable (or unstable) constantly throughout the growth.

摘要

癌症中的基因不稳定性是一把双刃剑。它既可以提高癌症进展的速度(通过增加致癌突变的概率),也可以降低癌症生长的速度(通过对分裂细胞造成大量死亡)。作用于肿瘤的众多选择压力中的两个,即对变异性的需求和将有害突变降至最低的需求,影响着肿瘤对稳定或不稳定“策略”的“选择”。随着癌症的进展,这两种压力的平衡会发生变化。在本文中,我们研究癌细胞的最优策略是如何由不断变化的选择压力塑造的。我们考虑多阶段致癌过程中两种最常见的模式:癌基因的激活(一个一步过程)和肿瘤抑制基因的失活(一个两步过程)。对于这些情况,我们为癌细胞的突变率制定了一个最优控制问题。然后我们开发了一种方法来找到最优的时间依赖策略。结果表明,对于广泛的参数范围,最成功的策略是开始时具有高突变率,然后转向稳定。这与越来越多的生物学证据一致,即在早期癌症中普遍存在的基因不稳定性在进展后期会转变为稳定性。我们还确定了在整个生长过程中始终保持稳定(或不稳定)有利的参数范围。

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