Cargando…

Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation

BACKGROUND: Tumors comprise a variety of specialized cell phenotypes adapted to different ecological niches that massively influence the tumor growth and its response to treatment. METHODS: In the background of glioblastoma multiforme, a highly malignant brain tumor, we consider a rapid proliferatin...

Descripción completa

Detalles Bibliográficos
Autores principales: Böttcher, Marvin A., Held-Feindt, Janka, Synowitz, Michael, Lucius, Ralph, Traulsen, Arne, Hattermann, Kirsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5883287/
https://www.ncbi.nlm.nih.gov/pubmed/29614985
http://dx.doi.org/10.1186/s12885-018-4281-1
_version_ 1783311617981677568
author Böttcher, Marvin A.
Held-Feindt, Janka
Synowitz, Michael
Lucius, Ralph
Traulsen, Arne
Hattermann, Kirsten
author_facet Böttcher, Marvin A.
Held-Feindt, Janka
Synowitz, Michael
Lucius, Ralph
Traulsen, Arne
Hattermann, Kirsten
author_sort Böttcher, Marvin A.
collection PubMed
description BACKGROUND: Tumors comprise a variety of specialized cell phenotypes adapted to different ecological niches that massively influence the tumor growth and its response to treatment. METHODS: In the background of glioblastoma multiforme, a highly malignant brain tumor, we consider a rapid proliferating phenotype that appears susceptible to treatment, and a dormant phenotype which lacks this pronounced proliferative ability and is not affected by standard therapeutic strategies. To gain insight in the dynamically changing proportions of different tumor cell phenotypes under different treatment conditions, we develop a mathematical model and underline our assumptions with experimental data. RESULTS: We show that both cell phenotypes contribute to the distinct composition of the tumor, especially in cycling low and high dose treatment, and therefore may influence the tumor growth in a phenotype specific way. CONCLUSION: Our model of the dynamic proportions of dormant and rapidly growing glioblastoma cells in different therapy settings suggests that phenotypically different cells should be considered to plan dose and duration of treatment schedules.
format Online
Article
Text
id pubmed-5883287
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-58832872018-04-10 Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation Böttcher, Marvin A. Held-Feindt, Janka Synowitz, Michael Lucius, Ralph Traulsen, Arne Hattermann, Kirsten BMC Cancer Research Article BACKGROUND: Tumors comprise a variety of specialized cell phenotypes adapted to different ecological niches that massively influence the tumor growth and its response to treatment. METHODS: In the background of glioblastoma multiforme, a highly malignant brain tumor, we consider a rapid proliferating phenotype that appears susceptible to treatment, and a dormant phenotype which lacks this pronounced proliferative ability and is not affected by standard therapeutic strategies. To gain insight in the dynamically changing proportions of different tumor cell phenotypes under different treatment conditions, we develop a mathematical model and underline our assumptions with experimental data. RESULTS: We show that both cell phenotypes contribute to the distinct composition of the tumor, especially in cycling low and high dose treatment, and therefore may influence the tumor growth in a phenotype specific way. CONCLUSION: Our model of the dynamic proportions of dormant and rapidly growing glioblastoma cells in different therapy settings suggests that phenotypically different cells should be considered to plan dose and duration of treatment schedules. BioMed Central 2018-04-03 /pmc/articles/PMC5883287/ /pubmed/29614985 http://dx.doi.org/10.1186/s12885-018-4281-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Böttcher, Marvin A.
Held-Feindt, Janka
Synowitz, Michael
Lucius, Ralph
Traulsen, Arne
Hattermann, Kirsten
Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title_full Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title_fullStr Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title_full_unstemmed Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title_short Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
title_sort modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5883287/
https://www.ncbi.nlm.nih.gov/pubmed/29614985
http://dx.doi.org/10.1186/s12885-018-4281-1
work_keys_str_mv AT bottchermarvina modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation
AT heldfeindtjanka modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation
AT synowitzmichael modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation
AT luciusralph modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation
AT traulsenarne modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation
AT hattermannkirsten modelingtreatmentdependentgliomagrowthincludingadormanttumorcellsubpopulation