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

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 app...

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Detalles Bibliográficos
Autor principal: Alfano, Francis D
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1373613/
https://www.ncbi.nlm.nih.gov/pubmed/16448558
http://dx.doi.org/10.1186/1742-4682-3-5
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author Alfano, Francis D
author_facet Alfano, Francis D
author_sort Alfano, Francis D
collection PubMed
description 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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spelling pubmed-13736132006-02-18 A stochastic model of oncogene expression and the relevance of this model to cancer therapy Alfano, Francis D Theor Biol Med Model Research 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. BioMed Central 2006-01-31 /pmc/articles/PMC1373613/ /pubmed/16448558 http://dx.doi.org/10.1186/1742-4682-3-5 Text en Copyright © 2006 Alfano; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Alfano, Francis D
A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title_full A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title_fullStr A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title_full_unstemmed A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title_short A stochastic model of oncogene expression and the relevance of this model to cancer therapy
title_sort stochastic model of oncogene expression and the relevance of this model to cancer therapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1373613/
https://www.ncbi.nlm.nih.gov/pubmed/16448558
http://dx.doi.org/10.1186/1742-4682-3-5
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