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Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts

Tumors are often heterogeneous in which tumor cells of different phenotypes have distinct properties. For scientific and clinical interests, it is of fundamental importance to understand their properties and the dynamic variations among different phenotypes, specifically under radio- and/or chemo-th...

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Autores principales: Wang, Weikang, Quan, Yi, Fu, Qibin, Liu, Yu, Liang, Ying, Wu, Jingwen, Yang, Gen, Luo, Chunxiong, Ouyang, Qi, Wang, Yugang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886990/
https://www.ncbi.nlm.nih.gov/pubmed/24416258
http://dx.doi.org/10.1371/journal.pone.0084654
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author Wang, Weikang
Quan, Yi
Fu, Qibin
Liu, Yu
Liang, Ying
Wu, Jingwen
Yang, Gen
Luo, Chunxiong
Ouyang, Qi
Wang, Yugang
author_facet Wang, Weikang
Quan, Yi
Fu, Qibin
Liu, Yu
Liang, Ying
Wu, Jingwen
Yang, Gen
Luo, Chunxiong
Ouyang, Qi
Wang, Yugang
author_sort Wang, Weikang
collection PubMed
description Tumors are often heterogeneous in which tumor cells of different phenotypes have distinct properties. For scientific and clinical interests, it is of fundamental importance to understand their properties and the dynamic variations among different phenotypes, specifically under radio- and/or chemo-therapy. Currently there are two controversial models describing tumor heterogeneity, the cancer stem cell (CSC) model and the stochastic model. To clarify the controversy, we measured probabilities of different division types and transitions of cells via in situ immunofluorescence. Based on the experiment data, we constructed a model that combines the CSC with the stochastic concepts, showing the existence of both distinctive CSC subpopulations and the stochastic transitions from NSCCs to CSCs. The results showed that the dynamic variations between CSCs and non-stem cancer cells (NSCCs) can be simulated with the model. Further studies also showed that the model can be used to describe the dynamics of the two subpopulations after radiation treatment. More importantly, analysis demonstrated that the experimental detectable equilibrium CSC proportion can be achieved only when the stochastic transitions from NSCCs to CSCs occur, indicating that tumor heterogeneity may exist in a model coordinating with both the CSC and the stochastic concepts. The mathematic model based on experimental parameters may contribute to a better understanding of the tumor heterogeneity, and provide references on the dynamics of CSC subpopulation during radiotherapy.
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spelling pubmed-38869902014-01-10 Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts Wang, Weikang Quan, Yi Fu, Qibin Liu, Yu Liang, Ying Wu, Jingwen Yang, Gen Luo, Chunxiong Ouyang, Qi Wang, Yugang PLoS One Research Article Tumors are often heterogeneous in which tumor cells of different phenotypes have distinct properties. For scientific and clinical interests, it is of fundamental importance to understand their properties and the dynamic variations among different phenotypes, specifically under radio- and/or chemo-therapy. Currently there are two controversial models describing tumor heterogeneity, the cancer stem cell (CSC) model and the stochastic model. To clarify the controversy, we measured probabilities of different division types and transitions of cells via in situ immunofluorescence. Based on the experiment data, we constructed a model that combines the CSC with the stochastic concepts, showing the existence of both distinctive CSC subpopulations and the stochastic transitions from NSCCs to CSCs. The results showed that the dynamic variations between CSCs and non-stem cancer cells (NSCCs) can be simulated with the model. Further studies also showed that the model can be used to describe the dynamics of the two subpopulations after radiation treatment. More importantly, analysis demonstrated that the experimental detectable equilibrium CSC proportion can be achieved only when the stochastic transitions from NSCCs to CSCs occur, indicating that tumor heterogeneity may exist in a model coordinating with both the CSC and the stochastic concepts. The mathematic model based on experimental parameters may contribute to a better understanding of the tumor heterogeneity, and provide references on the dynamics of CSC subpopulation during radiotherapy. Public Library of Science 2014-01-09 /pmc/articles/PMC3886990/ /pubmed/24416258 http://dx.doi.org/10.1371/journal.pone.0084654 Text en © 2014 Wang 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wang, Weikang
Quan, Yi
Fu, Qibin
Liu, Yu
Liang, Ying
Wu, Jingwen
Yang, Gen
Luo, Chunxiong
Ouyang, Qi
Wang, Yugang
Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title_full Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title_fullStr Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title_full_unstemmed Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title_short Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts
title_sort dynamics between cancer cell subpopulations reveals a model coordinating with both hierarchical and stochastic concepts
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886990/
https://www.ncbi.nlm.nih.gov/pubmed/24416258
http://dx.doi.org/10.1371/journal.pone.0084654
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