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Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer
Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012062/ https://www.ncbi.nlm.nih.gov/pubmed/33729159 http://dx.doi.org/10.7554/eLife.64522 |
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author | Chauhan, Lakshya Ram, Uday Hari, Kishore Jolly, Mohit Kumar |
author_facet | Chauhan, Lakshya Ram, Uday Hari, Kishore Jolly, Mohit Kumar |
author_sort | Chauhan, Lakshya |
collection | PubMed |
description | Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a ‘toggle switch’ between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their ‘latent’ design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor. |
format | Online Article Text |
id | pubmed-8012062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-80120622021-04-02 Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer Chauhan, Lakshya Ram, Uday Hari, Kishore Jolly, Mohit Kumar eLife Computational and Systems Biology Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a ‘toggle switch’ between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their ‘latent’ design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor. eLife Sciences Publications, Ltd 2021-03-17 /pmc/articles/PMC8012062/ /pubmed/33729159 http://dx.doi.org/10.7554/eLife.64522 Text en © 2021, Chauhan et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Chauhan, Lakshya Ram, Uday Hari, Kishore Jolly, Mohit Kumar Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title | Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title_full | Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title_fullStr | Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title_full_unstemmed | Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title_short | Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
title_sort | topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012062/ https://www.ncbi.nlm.nih.gov/pubmed/33729159 http://dx.doi.org/10.7554/eLife.64522 |
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