In Vitro/In Silico Study on the Role of Doubling Time Heterogeneity among Primary Glioblastoma Cell Lines.

The application of accurate cancer predictive algorithms validated with experimental data is a field concerning both basic researchers and clinicians, especially regarding a highly aggressive form of cancer, such as Glioblastoma. In an aim to enhance prediction accuracy in realistic patient-specific...

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Publicado en:BioMed Research International Vol. 2017; pp. 1 - 13
Autores principales: Oraiopoulou, M.-E., Tzamali, E., Tzedakis, G., Vakis, A., Papamatheakis, J., Sakkalis, V.
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 10/31/2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 10/31/2017
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      pub: Wiley-Blackwell
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        10.1155/2017/8569328
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        atl: In Vitro/In Silico Study on the Role of Doubling Time Heterogeneity among Primary Glioblastoma Cell Lines.
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        au:
          Oraiopoulou, M.-E.
          Tzamali, E.
          Tzedakis, G.
          Vakis, A.
          Papamatheakis, J.
          Sakkalis, V.
        affil: Department of Medicine, University of Crete, Heraklion, Greece
      sug:
        subj:
          Glioma
          Cell Line, Tumor
          Human
          In Vitro Studies
          Research Methodology
          Algorithms
          Time Factors
      ab: The application of accurate cancer predictive algorithms validated with experimental data is a field concerning both basic researchers and clinicians, especially regarding a highly aggressive form of cancer, such as Glioblastoma. In an aim to enhance prediction accuracy in realistic patient-specific environments, accounting for both inter- and intratumoral heterogeneity, we use patient-derived Glioblastoma cells from different patients. We focus on cell proliferation using in vitro experiments to estimate cell doubling times and sizes for established primary Glioblastoma cell lines. A preclinically driven mathematical model parametrization is accomplished by taking into account the experimental measurements. As a control cell line we use the well-studied U87MG cells. Both in vitro and in silico results presented support that the variance between tumor staging can be attributed to the differential proliferative capacity of the different Glioblastoma cells. More specifically, the intratumoral heterogeneity together with the overall proliferation reflected in both the proliferation rate and the mechanical cell contact inhibition can predict the in vitro evolution of different Glioblastoma cell lines growing under the same conditions. Undoubtedly, additional imaging techniques capable of providing spatial information of tumor cell physiology and microenvironment will enhance our understanding regarding Glioblastoma nature and verify and further improve our predictability.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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