Cargando…
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...
Autor principal: | |
---|---|
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 |
_version_ | 1782126798669086720 |
---|---|
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. |
format | Text |
id | pubmed-1373613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT alfanofrancisd astochasticmodelofoncogeneexpressionandtherelevanceofthismodeltocancertherapy AT alfanofrancisd stochasticmodelofoncogeneexpressionandtherelevanceofthismodeltocancertherapy |