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通过一种非达尔文主义和非拉马克主义的适应性进化机制连接肿瘤发生与治疗抗性

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution.

作者信息

Catania Francesco, Ujvari Beata, Roche Benjamin, Capp Jean-Pascal, Thomas Frédéric

机构信息

Institute for Evolution and Biodiversity, University of Münster, Münster, Germany.

Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Deakin, VIC, Australia.

出版信息

Front Oncol. 2021 Sep 10;11:732081. doi: 10.3389/fonc.2021.732081. eCollection 2021.

DOI:10.3389/fonc.2021.732081
PMID:34568068
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8462274/
Abstract

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple or rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

摘要

尽管新达尔文主义(以及较少被提及的拉马克主义)动力学经常被用来解释癌症的多种分子特征,但它们对于肿瘤发生如何展开几乎没有提供什么线索,而且往往无法充分捕捉耐药机制的频率和广度。这种不确定性构成了现代科学与实践之间最具问题的差距之一。在此,我们提出一种适应性癌症进化理论,该理论建立在一种新达尔文主义和拉马克主义框架之外的分子机制之上。这种机制连贯地整合了非遗传和遗传变化、生态和进化时间尺度,并将焦点从正向选择转移到纯化选择、遗传漂变以及环境变化的创造性破坏力量上。所提出理论令人惊讶的简单原理有助于预测肿瘤发生过程中的分子动力学。它还提供了一些简单的经验法则,应该有助于改进癌症的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eae2/8462274/e0e7dae7ec21/fonc-11-732081-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eae2/8462274/e0e7dae7ec21/fonc-11-732081-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eae2/8462274/e0e7dae7ec21/fonc-11-732081-g001.jpg

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Weak selection on synonymous codons substantially inflates estimates in bacteria.同义密码子的弱选择极大地夸大了细菌中的估计值。
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