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将进化动力学纳入癌症治疗。

Integrating evolutionary dynamics into cancer therapy.

机构信息

Cancer Biology and Evolution Program, Moffitt Cancer Center, Tampa, FL, USA.

Integrated Mathematical Oncology Department, Moffitt Cancer Center, Tampa, FL, USA.

出版信息

Nat Rev Clin Oncol. 2020 Nov;17(11):675-686. doi: 10.1038/s41571-020-0411-1. Epub 2020 Jul 22.

Abstract

Many effective drugs for metastatic and/or advanced-stage cancers have been developed over the past decade, although the evolution of resistance remains the major barrier to disease control or cure. In large, diverse populations such as the cells that compose metastatic cancers, the emergence of cells that are resistant or that can quickly develop resistance is virtually inevitable and most likely cannot be prevented. However, clinically significant resistance occurs only when the pre-existing resistant phenotypes are able to proliferate extensively, a process governed by eco-evolutionary dynamics. Attempts to disrupt the molecular mechanisms of resistance have generally been unsuccessful in clinical practice. In this Review, we focus on the Darwinian processes driving the eco-evolutionary dynamics of treatment-resistant cancer populations. We describe a variety of evolutionarily informed strategies designed to increase the probability of disease control or cure by anticipating and steering the evolutionary dynamics of acquired resistance.

摘要

在过去十年中,已经开发出许多针对转移性和/或晚期癌症的有效药物,尽管耐药性的进化仍然是控制或治愈疾病的主要障碍。在像转移性癌症组成的细胞这样的大型、多样化的人群中,耐药性或能够快速产生耐药性的细胞的出现几乎是不可避免的,而且极有可能无法预防。然而,只有当预先存在的耐药表型能够广泛增殖时,临床上才会出现显著的耐药性,这是一个由生态进化动态控制的过程。在临床实践中,试图破坏耐药性的分子机制通常是不成功的。在这篇综述中,我们专注于驱动治疗耐药性癌症群体的生态进化动态的达尔文过程。我们描述了各种进化信息策略,旨在通过预测和引导获得性耐药性的进化动态,增加控制或治愈疾病的可能性。

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