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

Böttcher, M. A., Held-Feindt, J., Synowitz, M., Lucius, R., Traulsen, A., & Hattermann, K. (2018). Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation. BMC Cancer, 18: 376. doi:10.1186/s12885-018-4281-1.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-6C3D-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-F490-6
Genre: Journal Article

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Böttcher, Marvin A.1, Author              
Held-Feindt, Janka, Author
Synowitz, Michael, Author
Lucius, Ralph, Author
Traulsen, Arne1, Author              
Hattermann, Kirsten, Author
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 Abstract: 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. © 2018 The Author(s).

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Language(s): eng - English
 Dates: 2018-01-182018-03-212018-04-032018
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1186/s12885-018-4281-1
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Title: BMC Cancer
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 18 Sequence Number: 376 Start / End Page: - Identifier: ISSN: 1471-2407
CoNE: https://pure.mpg.de/cone/journals/resource/111000136906046