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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...

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Autores principales: Chauhan, Lakshya, Ram, Uday, Hari, Kishore, Jolly, Mohit Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
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.
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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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