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过渡疗法:攻克肿瘤表型可塑性的生态问题。

Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity.

机构信息

ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003, Barcelona, Spain.

Institut de Biologia Evolutiva, CSIC-UPF, 08003, Barcelona, Spain.

出版信息

Bull Math Biol. 2021 Dec 27;84(1):24. doi: 10.1007/s11538-021-00970-9.

DOI:10.1007/s11538-021-00970-9
PMID:34958403
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8712307/
Abstract

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.

摘要

癌症细胞表型转换已被发现在多种肿瘤类型中存在。最近关于胶质母细胞瘤的研究报告了一种非常常见的结构,即四种明确界定的表型在高水平的肿瘤内遗传异质性中共存。在乳腺癌和黑色素瘤中也显示出类似的动态,并且很可能在癌症类型中存在。鉴于表型转换(PHS)策略的适应潜力,了解它如何驱动肿瘤进化和治疗耐药性是一个主要优先事项。在这里,我们提出了一个数学框架,揭示了 PHS 背后的生态动力学。该模型能够重现实验结果,并且癌症进展的数学条件揭示了具有直接治疗耐药性后果的肿瘤的 PHS 特异性特征。特别是,我们的模型揭示了抵抗-敏感表型转换率的阈值,低于该阈值,任何细胞毒性或开关抑制治疗都可能失败。该模型能够捕获处于非线性生长动力学或更大 PHS 结构位置的癌症的治疗成功阈值,例如胶质母细胞瘤或黑色素瘤。通过这样做,该模型提出了一组新的条件,用于成功的联合治疗,能够同时针对复制和表型转换。根据我们的结果,我们讨论了转换治疗作为一种新的方案,不仅可以靶向联合细胞毒性,还可以靶向表型转换的速率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/76364b4bae29/11538_2021_970_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/9c3b14a43f3f/11538_2021_970_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/2031993949b1/11538_2021_970_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/c99efb126f32/11538_2021_970_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/3b4046ff545e/11538_2021_970_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/c36ddf544879/11538_2021_970_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/76364b4bae29/11538_2021_970_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/9c3b14a43f3f/11538_2021_970_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/2031993949b1/11538_2021_970_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/c99efb126f32/11538_2021_970_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/3b4046ff545e/11538_2021_970_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/c36ddf544879/11538_2021_970_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31d2/8712307/76364b4bae29/11538_2021_970_Fig6_HTML.jpg

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