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Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance

Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbat...

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Autores principales: Su, Yapeng, Bintz, Marcus, Yang, Yezi, Robert, Lidia, Ng, Alphonsus H. C., Liu, Victoria, Ribas, Antoni, Heath, James R., Wei, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6576794/
https://www.ncbi.nlm.nih.gov/pubmed/31166947
http://dx.doi.org/10.1371/journal.pcbi.1007034
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author Su, Yapeng
Bintz, Marcus
Yang, Yezi
Robert, Lidia
Ng, Alphonsus H. C.
Liu, Victoria
Ribas, Antoni
Heath, James R.
Wei, Wei
author_facet Su, Yapeng
Bintz, Marcus
Yang, Yezi
Robert, Lidia
Ng, Alphonsus H. C.
Liu, Victoria
Ribas, Antoni
Heath, James R.
Wei, Wei
author_sort Su, Yapeng
collection PubMed
description Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbations. This, in turn, can confound interpretations of drug responses and resistance development. Using BRAF-mutant melanoma cell lines as the prototype, we report on a joint theoretical and experimental investigation of the cell-state transition dynamics associated with BRAF inhibitor drug tolerance. Thermodynamically motivated surprisal analysis of transcriptome data was used to treat the cell population as an entropy maximizing system under the influence of time-dependent constraints. This permits the extraction of an epigenetic potential landscape for drug-induced phenotypic evolution. Single-cell flow cytometry data of the same system were modeled with a modified Fokker-Planck-type kinetic model. The two approaches yield a consistent picture that accounts for the phenotypic heterogeneity observed over the course of drug tolerance development. The results reveal that, in certain plastic cancers, the population heterogeneity and evolution of cell phenotypes may be understood by accounting for the competing interactions of the epigenetic potential landscape and state-dependent cell proliferation. Accounting for such competition permits accurate, experimentally verifiable predictions that can potentially guide the design of effective treatment strategies.
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spelling pubmed-65767942019-06-28 Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance Su, Yapeng Bintz, Marcus Yang, Yezi Robert, Lidia Ng, Alphonsus H. C. Liu, Victoria Ribas, Antoni Heath, James R. Wei, Wei PLoS Comput Biol Research Article Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbations. This, in turn, can confound interpretations of drug responses and resistance development. Using BRAF-mutant melanoma cell lines as the prototype, we report on a joint theoretical and experimental investigation of the cell-state transition dynamics associated with BRAF inhibitor drug tolerance. Thermodynamically motivated surprisal analysis of transcriptome data was used to treat the cell population as an entropy maximizing system under the influence of time-dependent constraints. This permits the extraction of an epigenetic potential landscape for drug-induced phenotypic evolution. Single-cell flow cytometry data of the same system were modeled with a modified Fokker-Planck-type kinetic model. The two approaches yield a consistent picture that accounts for the phenotypic heterogeneity observed over the course of drug tolerance development. The results reveal that, in certain plastic cancers, the population heterogeneity and evolution of cell phenotypes may be understood by accounting for the competing interactions of the epigenetic potential landscape and state-dependent cell proliferation. Accounting for such competition permits accurate, experimentally verifiable predictions that can potentially guide the design of effective treatment strategies. Public Library of Science 2019-06-05 /pmc/articles/PMC6576794/ /pubmed/31166947 http://dx.doi.org/10.1371/journal.pcbi.1007034 Text en © 2019 Su et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Su, Yapeng
Bintz, Marcus
Yang, Yezi
Robert, Lidia
Ng, Alphonsus H. C.
Liu, Victoria
Ribas, Antoni
Heath, James R.
Wei, Wei
Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title_full Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title_fullStr Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title_full_unstemmed Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title_short Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
title_sort phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6576794/
https://www.ncbi.nlm.nih.gov/pubmed/31166947
http://dx.doi.org/10.1371/journal.pcbi.1007034
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