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Computational and Mathematical Methods in Medicine
Volume 2014 (2014), Article ID 437094, 14 pages
Research Article

Identification of Crucial Parameters in a Mathematical Multiscale Model of Glioblastoma Growth

1Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
2Graduate School for Computing in Medicine and Life Sciences, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
3Institute for Computational Engineering and Sciences, University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229, USA
4Centre of Excellence for Technology and Engineering in Medicine (TANDEM), Ratzeburger Allee 160, 23562 Luebeck, Germany

Received 16 January 2014; Accepted 22 March 2014; Published 8 May 2014

Academic Editor: Volkhard Helms

Copyright © 2014 Tina A. Schuetz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Glioblastomas are highly malignant brain tumours. Mathematical models and their analysis provide a tool to support the understanding of the development of these tumours as well as the design of more effective treatment strategies. We have previously developed a multiscale model of glioblastoma progression that covers processes on the cellular and molecular scale. Here, we present a novel nutrient-dependent multiscale sensitivity analysis of this model that helps to identify those reaction parameters of the molecular interaction network that influence the tumour progression on the cellular scale the most. In particular, those parameters are identified that essentially determine tumour expansion and could be therefore used as potential therapy targets. As indicators for the success of a potential therapy target, a deceleration of the tumour expansion and a reduction of the tumour volume are employed. From the results, it can be concluded that no single parameter variation results in a less aggressive tumour. However, it can be shown that a few combined perturbations of two systematically selected parameters cause a slow-down of the tumour expansion velocity accompanied with a decrease of the tumour volume. Those parameters are primarily linked to the reactions that involve the microRNA-451 and the thereof regulated protein MO25.