title: Identification of crucial parameters in a mathematical multiscale model of glioblastoma growth.
abstract: 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.
authors.affiliation: Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany ; Graduate School for Computing in Medicine and Life Sciences, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany.
authors.forename: Tina A
authors.initials: TA
authors.lastname: Schuetz
authors.affiliation: Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany ; Institute for Computational Engineering and Sciences, University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229, USA.
authors.forename: Andreas
authors.initials: A
authors.lastname: Mang
authors.affiliation: Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany ; Centre of Excellence for Technology and Engineering in Medicine (TANDEM), Ratzeburger Allee 160, 23562 Luebeck, Germany.
authors.forename: Stefan
authors.identifier: 0000-0002-5333-3162
authors.initials: S
authors.lastname: Becker
authors.affiliation: Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany ; Centre of Excellence for Technology and Engineering in Medicine (TANDEM), Ratzeburger Allee 160, 23562 Luebeck, Germany.
authors.forename: Alina
authors.identifier: 0000-0003-2212-2896
authors.initials: A
authors.lastname: Toma
authors.affiliation: Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany.
authors.forename: Thorsten M
authors.initials: TM
authors.lastname: Buzug
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000503:physiopathology; D002135:Calcium-Binding Proteins / Q000502:physiology; D002465:Cell Movement; D049109:Cell Proliferation; D003198:Computer Simulation; D018450:Disease Progression; D005909:Glioblastoma / Q000175:diagnosis* / Q000503:physiopathology; D005947:Glucose / Q000378:metabolism; D006801:Humans; D035683:MicroRNAs / Q000378:metabolism*; D008962:Models, Theoretical; D010641:Phenotype; D010766:Phosphorylation; D012680:Sensitivity and Specificity; D012984:Software; D013997:Time Factors
chemical_list: D001786:Blood Glucose; C540569:CAB39 protein, human; D002135:Calcium-Binding Proteins; C531201:MIRN451 microRNA, human; D035683:MicroRNAs; D005947:Glucose