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癌症生物学是否依赖于帕隆多原理?

Does Cancer Biology Rely on Parrondo's Principles?

作者信息

Capp Jean-Pascal, Nedelcu Aurora M, Dujon Antoine M, Roche Benjamin, Catania Francesco, Ujvari Beata, Alix-Panabières Catherine, Thomas Frédéric

机构信息

Toulouse Biotechnology Institute, University of Toulouse, INSA, CNRS, INRAE, 31400 Toulouse, France.

Department of Biology, University of New Brunswick, P.O. Box 4400, Fredericton, NB E3B 5A3, Canada.

出版信息

Cancers (Basel). 2021 May 3;13(9):2197. doi: 10.3390/cancers13092197.

Abstract

Many aspects of cancer biology remain puzzling, including the proliferative and survival success of malignant cells in spite of their high genetic and epigenetic instability as well as their ability to express migrating phenotypes and/or enter dormancy despite possible fitness loss. Understanding the potential adaptive value of these phenotypic traits is confounded by the fact that, when considered separately, they seem to be rather detrimental at the cell level, at least in the short term. Here, we argue that cancer's biology and success could frequently be governed by processes underlying Parrondo's paradox, whereby combinations of intrinsically losing strategies may result in winning outcomes. Oncogenic selection would favor Parrondo's dynamics because, given the environmental adversity in which malignant cells emerge and evolve, alternating between various less optimal strategies would represent the sole viable option to counteract the changing and deleterious environments cells are exposed to during tumorigenesis. We suggest that malignant processes could be viewed through this lens, and we discuss how Parrondo's principles are also important when designing therapies against cancer.

摘要

癌症生物学的许多方面仍然令人困惑,包括恶性细胞尽管具有高度的遗传和表观遗传不稳定性却能成功增殖和存活,以及它们尽管可能会损失适应性却仍能表达迁移表型和/或进入休眠状态的能力。这些表型特征的潜在适应性价值难以理解,因为单独来看,它们似乎在细胞水平上是相当有害的,至少在短期内是这样。在这里,我们认为癌症的生物学特性和成功常常可能受帕隆多悖论背后的过程所支配,即内在失败策略的组合可能会导致成功的结果。致癌选择会青睐帕隆多动力学,因为鉴于恶性细胞出现和进化的环境逆境,在各种不太理想的策略之间交替可能是应对肿瘤发生过程中细胞所面临的不断变化且有害环境的唯一可行选择。我们建议可以通过这个视角来看待恶性过程,并且我们讨论了在设计抗癌疗法时帕隆多原理为何也很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e3fc/8125342/2516085ff2d9/cancers-13-02197-g001.jpg

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