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Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer
BACKGROUND: Cancer reversion, converting the phenotypes of a cancer cell into those of a normal cell, has been sporadically observed throughout history. However, no systematic analysis has been attempted so far. RESULTS: To investigate this from a systems biological perspective, we have constructed...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382366/ https://www.ncbi.nlm.nih.gov/pubmed/28381275 http://dx.doi.org/10.1186/s12918-017-0424-2 |
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author | Kim, Yunseong Choi, Sea Shin, Dongkwan Cho, Kwang-Hyun |
author_facet | Kim, Yunseong Choi, Sea Shin, Dongkwan Cho, Kwang-Hyun |
author_sort | Kim, Yunseong |
collection | PubMed |
description | BACKGROUND: Cancer reversion, converting the phenotypes of a cancer cell into those of a normal cell, has been sporadically observed throughout history. However, no systematic analysis has been attempted so far. RESULTS: To investigate this from a systems biological perspective, we have constructed a logical network model of colorectal tumorigenesis by integrating key regulatory molecules and their interactions from previous experimental data. We identified molecular targets that can reverse cancerous cellular states to a normal state by systematically perturbing each molecular activity in the network and evaluating the resulting changes of the attractor landscape with respect to uncontrolled proliferation, EMT, and stemness. Intriguingly, many of the identified targets were well in accord with previous studies. We further revealed that the identified targets constitute stable network motifs that contribute to enhancing the robustness of attractors in cancerous cellular states against diverse regulatory signals. CONCLUSIONS: The proposed framework for systems analysis is applicable to the study of tumorigenesis and reversion of other types of cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-017-0424-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5382366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53823662017-04-10 Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer Kim, Yunseong Choi, Sea Shin, Dongkwan Cho, Kwang-Hyun BMC Syst Biol Research Article BACKGROUND: Cancer reversion, converting the phenotypes of a cancer cell into those of a normal cell, has been sporadically observed throughout history. However, no systematic analysis has been attempted so far. RESULTS: To investigate this from a systems biological perspective, we have constructed a logical network model of colorectal tumorigenesis by integrating key regulatory molecules and their interactions from previous experimental data. We identified molecular targets that can reverse cancerous cellular states to a normal state by systematically perturbing each molecular activity in the network and evaluating the resulting changes of the attractor landscape with respect to uncontrolled proliferation, EMT, and stemness. Intriguingly, many of the identified targets were well in accord with previous studies. We further revealed that the identified targets constitute stable network motifs that contribute to enhancing the robustness of attractors in cancerous cellular states against diverse regulatory signals. CONCLUSIONS: The proposed framework for systems analysis is applicable to the study of tumorigenesis and reversion of other types of cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-017-0424-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-04-05 /pmc/articles/PMC5382366/ /pubmed/28381275 http://dx.doi.org/10.1186/s12918-017-0424-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Kim, Yunseong Choi, Sea Shin, Dongkwan Cho, Kwang-Hyun Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title | Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title_full | Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title_fullStr | Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title_full_unstemmed | Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title_short | Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
title_sort | quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382366/ https://www.ncbi.nlm.nih.gov/pubmed/28381275 http://dx.doi.org/10.1186/s12918-017-0424-2 |
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