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Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays

Representing a renewable source for cell replacement, neural stem cells have received substantial attention in recent years. The neurosphere assay represents a method to detect the presence of neural stem cells, however owing to a deficiency of specific and definitive markers to identify them, their...

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Autores principales: Deleyrolle, Loic P., Ericksson, Geoffery, Morrison, Brian J., Lopez, J. Alejandro, Burrage, Kevin, Burrage, Pamela, Vescovi, Angelo, Rietze, Rodney L., Reynolds, Brent A.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016423/
https://www.ncbi.nlm.nih.gov/pubmed/21246056
http://dx.doi.org/10.1371/journal.pone.0015844
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author Deleyrolle, Loic P.
Ericksson, Geoffery
Morrison, Brian J.
Lopez, J. Alejandro
Burrage, Kevin
Burrage, Pamela
Vescovi, Angelo
Rietze, Rodney L.
Reynolds, Brent A.
author_facet Deleyrolle, Loic P.
Ericksson, Geoffery
Morrison, Brian J.
Lopez, J. Alejandro
Burrage, Kevin
Burrage, Pamela
Vescovi, Angelo
Rietze, Rodney L.
Reynolds, Brent A.
author_sort Deleyrolle, Loic P.
collection PubMed
description Representing a renewable source for cell replacement, neural stem cells have received substantial attention in recent years. The neurosphere assay represents a method to detect the presence of neural stem cells, however owing to a deficiency of specific and definitive markers to identify them, their quantification and the rate they expand is still indefinite. Here we propose a mathematical interpretation of the neurosphere assay allowing actual measurement of neural stem cell symmetric division frequency. The algorithm of the modeling demonstrates a direct correlation between the overall cell fold expansion over time measured in the sphere assay and the rate stem cells expand via symmetric division. The model offers a methodology to evaluate specifically the effect of diseases and treatments on neural stem cell activity and function. Not only providing new insights in the evaluation of the kinetic features of neural stem cells, our modeling further contemplates cancer biology as cancer stem-like cells have been suggested to maintain tumor growth as somatic stem cells maintain tissue homeostasis. Indeed, tumor stem cell's resistance to therapy makes these cells a necessary target for effective treatment. The neurosphere assay mathematical model presented here allows the assessment of the rate malignant stem-like cells expand via symmetric division and the evaluation of the effects of therapeutics on the self-renewal and proliferative activity of this clinically relevant population that drive tumor growth and recurrence.
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spelling pubmed-30164232011-01-18 Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays Deleyrolle, Loic P. Ericksson, Geoffery Morrison, Brian J. Lopez, J. Alejandro Burrage, Kevin Burrage, Pamela Vescovi, Angelo Rietze, Rodney L. Reynolds, Brent A. PLoS One Research Article Representing a renewable source for cell replacement, neural stem cells have received substantial attention in recent years. The neurosphere assay represents a method to detect the presence of neural stem cells, however owing to a deficiency of specific and definitive markers to identify them, their quantification and the rate they expand is still indefinite. Here we propose a mathematical interpretation of the neurosphere assay allowing actual measurement of neural stem cell symmetric division frequency. The algorithm of the modeling demonstrates a direct correlation between the overall cell fold expansion over time measured in the sphere assay and the rate stem cells expand via symmetric division. The model offers a methodology to evaluate specifically the effect of diseases and treatments on neural stem cell activity and function. Not only providing new insights in the evaluation of the kinetic features of neural stem cells, our modeling further contemplates cancer biology as cancer stem-like cells have been suggested to maintain tumor growth as somatic stem cells maintain tissue homeostasis. Indeed, tumor stem cell's resistance to therapy makes these cells a necessary target for effective treatment. The neurosphere assay mathematical model presented here allows the assessment of the rate malignant stem-like cells expand via symmetric division and the evaluation of the effects of therapeutics on the self-renewal and proliferative activity of this clinically relevant population that drive tumor growth and recurrence. Public Library of Science 2011-01-05 /pmc/articles/PMC3016423/ /pubmed/21246056 http://dx.doi.org/10.1371/journal.pone.0015844 Text en Deleyrolle 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
Deleyrolle, Loic P.
Ericksson, Geoffery
Morrison, Brian J.
Lopez, J. Alejandro
Burrage, Kevin
Burrage, Pamela
Vescovi, Angelo
Rietze, Rodney L.
Reynolds, Brent A.
Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title_full Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title_fullStr Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title_full_unstemmed Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title_short Determination of Somatic and Cancer Stem Cell Self-Renewing Symmetric Division Rate Using Sphere Assays
title_sort determination of somatic and cancer stem cell self-renewing symmetric division rate using sphere assays
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016423/
https://www.ncbi.nlm.nih.gov/pubmed/21246056
http://dx.doi.org/10.1371/journal.pone.0015844
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