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

癌基因表达的随机模型及其与癌症治疗的相关性

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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.

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