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一种癌基因表达的随机模型及其与癌症治疗的相关性。

A stochastic model of oncogene expression and the relevance of this model to cancer therapy.

作者信息

Alfano Francis D

机构信息

The Harold Leever Cancer Center, 1075 Chase Parkway, Waterbury, Connecticut 06708, USA.

出版信息

Theor Biol Med Model. 2006 Jan 31;3:5. doi: 10.1186/1742-4682-3-5.

Abstract

BACKGROUND

Ablation of an oncogene or of the activity of the protein it encodes can result in apoptosis and/or inhibit tumor cell proliferation. Therefore, if the oncogene or set of oncogenes contributing maximally to a tumor cell's survival can be identified, such oncogene(s) are the most appropriate target(s) for maximizing tumor cell kill.

METHODS AND RESULTS

A mathematical model is presented that describes cellular phenotypic entropy as a function of cellular proliferation and/or survival, and states of transformation and differentiation. Oncogenes become part of the cellular machinery, block apoptosis and differentiation or promote proliferation and give rise to new states of cellular transformation. Our model gives a quantitative assessment of the amount of cellular death or growth inhibition that result from the ablation of an oncogene's protein product. We review data from studies of chronic myelogenous leukemia and K562 cells to illustrate these principles.

CONCLUSION

The model discussed in this paper has implications for oncogene-directed therapies and their use in combination with other therapeutic modalities.

摘要

背景

消除一个癌基因或其编码蛋白的活性可导致细胞凋亡和/或抑制肿瘤细胞增殖。因此,如果能够确定对肿瘤细胞存活贡献最大的一个或一组癌基因,那么此类癌基因就是实现最大程度杀死肿瘤细胞的最合适靶点。

方法与结果

本文提出了一个数学模型,该模型将细胞表型熵描述为细胞增殖和/或存活以及转化和分化状态的函数。癌基因成为细胞机制的一部分,阻断细胞凋亡和分化或促进增殖,并产生新的细胞转化状态。我们的模型对因消除癌基因蛋白产物而导致细胞死亡或生长抑制的量进行了定量评估。我们回顾了慢性粒细胞白血病和K562细胞研究的数据以阐明这些原理。

结论

本文讨论的模型对癌基因导向疗法及其与其他治疗方式联合使用具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/126f/1373613/10779ad1aea0/1742-4682-3-5-1.jpg

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