Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  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.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Zeitschriftenartikel

Dateien

einblenden: Dateien
ausblenden: Dateien
:
s12885-018-4281-1.pdf (Verlagsversion), 2MB
Name:
s12885-018-4281-1.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-

Externe Referenzen

einblenden:
ausblenden:
Beschreibung:
-
OA-Status:

Urheber

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

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: 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).

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2018-01-182018-03-212018-04-032018
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1186/s12885-018-4281-1
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: BMC Cancer
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: BioMed Central
Seiten: - Band / Heft: 18 Artikelnummer: 376 Start- / Endseite: - Identifikator: ISSN: 1471-2407
CoNE: https://pure.mpg.de/cone/journals/resource/111000136906046