97381 20240219135522.0 doi 10.1038/s41598-020-78215-3 sideral 121766 ART-2020-121766 eng Ayensa-Jiménez, J. Universidad de Zaragoza (orcid)0000-0003-2564-6038 Mathematical formulation and parametric analysis of in vitro cell models in microfluidic devices: application to different stages of glioblastoma evolution 2020 Access copy available to the general public Unrestricted In silico models and computer simulation are invaluable tools to better understand complex biological processes such as cancer evolution. However, the complexity of the biological environment, with many cell mechanisms in response to changing physical and chemical external stimuli, makes the associated mathematical models highly non-linear and multiparametric. One of the main problems of these models is the determination of the parameters’ values, which are usually fitted for specific conditions, making the conclusions drawn difficult to generalise. We analyse here an important biological problem: the evolution of hypoxia-driven migratory structures in Glioblastoma Multiforme (GBM), the most aggressive and lethal primary brain tumour. We establish a mathematical model considering the interaction of the tumour cells with oxygen concentration in what is called the go or grow paradigm. We reproduce in this work three different experiments, showing the main GBM structures (pseudopalisade and necrotic core formation), only changing the initial and boundary conditions. We prove that it is possible to obtain versatile mathematical tools which, together with a sound parametric analysis, allow to explain complex biological phenomena. We show the utility of this hybrid “biomimetic in vitro-in silico” platform to help to elucidate the mechanisms involved in cancer processes, to better understand the role of the different phenomena, to test new scientific hypotheses and to design new data-driven experiments. info:eu-repo/grantAgreement/ES/DGA-ISCIII-EDRF/CIBER-BBN info:eu-repo/grantAgreement/ES/MINECO-AEI-FEDER/PID2019-106099RB-C44 info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-097257-B-C31 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 4.379 2020 MULTIDISCIPLINARY SCIENCES 17 / 72 = 0.236 2020 Q1 T1 1.24 2020 Multidisciplinary 2020 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Pérez-Aliacar, M. (orcid)0000-0002-7909-4446 Randelovic, T. (orcid)0000-0001-7232-7588 Oliván, S. Universidad de Zaragoza (orcid)0000-0003-0156-4230 Fernández, L. (orcid)0000-0002-4220-2722 Sanz-Herrera, J.A. Ochoa, I. Universidad de Zaragoza (orcid)0000-0003-2410-5678 Doweidar, M.H. Universidad de Zaragoza (orcid)0000-0003-0088-7222 Doblaré, M. Universidad de Zaragoza (orcid)0000-0001-8741-6452 1003 443 Universidad de Zaragoza Dpto. Anatom.Histolog.Humanas Area Histología 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 10, 1 (2020), 21193 [21 pp] Sci. rep. (Nat. Publ. Group) Scientific reports (Nature Publishing Group) 2045-2322 3945003 http://zaguan.unizar.es/record/97381/files/texto_completo.pdf Versión publicada 280507 http://zaguan.unizar.es/record/97381/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:97381 articulos driver 2024-02-19-13:52:10 ARTICLE