Multiscale modeling of glioma pseudopalisades: contributions from the tumor microenvironment

  • Gliomas are primary brain tumors with a high invasive potential and infiltrative spread. Among them, glioblastoma multiforme (GBM) exhibits microvascular hyperplasia and pronounced necrosis triggered by hypoxia. Histological samples showing garland-like hypercellular structures (so-called pseudopalisades) centered around the occlusion site of a capillary are typical for GBM and hint on poor prognosis of patient survival. We propose a multiscale modeling approach in the kinetic theory of active particles framework and deduce by an upscaling process a reaction-diffusion model with repellent pH-taxis. We prove existence of a unique global bounded classical solution for a version of the obtained macroscopic system and investigate the asymptotic behavior of the solution. Moreover, we study two different types of scaling and compare the behavior of the obtained macroscopic PDEs by way of simulations. These show that patterns (not necessarily of Turing type), including pseudopalisades, can be formed for some parameter ranges, in accordance with the tumor grade. This is true when the PDEs are obtained via parabolic scaling (undirected tissue), while no such patterns are observed for the PDEs arising by a hyperbolic limit (directed tissue). This suggests that brain tissue might be undirected - at least as far as glioma migration is concerned. We also investigate two different ways of including cell level descriptions of response to hypoxia and the way they are related .

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Metadaten
Verfasser*innenangaben:Pawan Kumar, Jing Li, Christina Surulescu
URN:urn:nbn:de:hbz:386-kluedo-78489
DOI:https://doi.org/10.1007/s00285-021-01599-x
ISSN:1432-1416
Titel des übergeordneten Werkes (Englisch):Journal of Mathematical Biology
Verlag:Springer Nature - Springer
Dokumentart:Wissenschaftlicher Artikel
Sprache der Veröffentlichung:Englisch
Datum der Veröffentlichung (online):19.03.2024
Jahr der Erstveröffentlichung:2021
Veröffentlichende Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Datum der Publikation (Server):19.03.2024
Ausgabe / Heft:82
Seitenzahl:45
Quelle:https://link.springer.com/article/10.1007/s00285-021-01599-x
Fachbereiche / Organisatorische Einheiten:Kaiserslautern - Fachbereich Mathematik
DDC-Sachgruppen:5 Naturwissenschaften und Mathematik / 510 Mathematik
Sammlungen:Open-Access-Publikationsfonds
Lizenz (Deutsch):Zweitveröffentlichung