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A dynamical framework for complex fractional killing
When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5556027/ https://www.ncbi.nlm.nih.gov/pubmed/28808338 http://dx.doi.org/10.1038/s41598-017-07422-2 |
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author | Ballweg, Richard Paek, Andrew L. Zhang, Tongli |
author_facet | Ballweg, Richard Paek, Andrew L. Zhang, Tongli |
author_sort | Ballweg, Richard |
collection | PubMed |
description | When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies. |
format | Online Article Text |
id | pubmed-5556027 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55560272017-08-16 A dynamical framework for complex fractional killing Ballweg, Richard Paek, Andrew L. Zhang, Tongli Sci Rep Article When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies. Nature Publishing Group UK 2017-08-14 /pmc/articles/PMC5556027/ /pubmed/28808338 http://dx.doi.org/10.1038/s41598-017-07422-2 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ballweg, Richard Paek, Andrew L. Zhang, Tongli A dynamical framework for complex fractional killing |
title | A dynamical framework for complex fractional killing |
title_full | A dynamical framework for complex fractional killing |
title_fullStr | A dynamical framework for complex fractional killing |
title_full_unstemmed | A dynamical framework for complex fractional killing |
title_short | A dynamical framework for complex fractional killing |
title_sort | dynamical framework for complex fractional killing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5556027/ https://www.ncbi.nlm.nih.gov/pubmed/28808338 http://dx.doi.org/10.1038/s41598-017-07422-2 |
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