Title |
Modeling treatment-dependent glioma growth including a dormant tumor cell subpopulation
|
---|---|
Published in |
BMC Cancer, April 2018
|
DOI | 10.1186/s12885-018-4281-1 |
Pubmed ID | |
Authors |
Marvin A. Böttcher, Janka Held-Feindt, Michael Synowitz, Ralph Lucius, Arne Traulsen, Kirsten Hattermann |
Abstract |
Tumors comprise a variety of specialized cell phenotypes adapted to different ecological niches that massively influence the tumor growth and its response to treatment. 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. 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. 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. |
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Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 7% |
Portugal | 1 | 7% |
Germany | 1 | 7% |
Unknown | 11 | 79% |
Demographic breakdown
Type | Count | As % |
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Scientists | 7 | 50% |
Members of the public | 6 | 43% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 30 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 17% |
Student > Ph. D. Student | 4 | 13% |
Student > Doctoral Student | 3 | 10% |
Lecturer | 2 | 7% |
Student > Bachelor | 2 | 7% |
Other | 5 | 17% |
Unknown | 9 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Mathematics | 5 | 17% |
Agricultural and Biological Sciences | 3 | 10% |
Biochemistry, Genetics and Molecular Biology | 3 | 10% |
Medicine and Dentistry | 3 | 10% |
Physics and Astronomy | 2 | 7% |
Other | 1 | 3% |
Unknown | 13 | 43% |