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Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme

hal.structure.identifierUniversity of Alabama at Birmingham [ Birmingham] [UAB]
dc.contributor.authorRAMAN, Fabio
hal.structure.identifierDepartment of neurology [Birmingham, Alabama]
hal.structure.identifierDepartment of Mathematics [Birmingham, Alabama]
dc.contributor.authorSCRIBNER, Elizabeth
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorSAUT, Olivier
hal.structure.identifierFaculdade de Ciências [Lisboa]
dc.contributor.authorWENGER, Cornelia
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorCOLIN, Thierry
hal.structure.identifierDepartment of neurology [Birmingham, Alabama]
hal.structure.identifierDepartment of Mathematics [Birmingham, Alabama]
dc.contributor.authorFATHALLAH-SHAYKH, Hassan
dc.date.accessioned2024-04-04T03:13:05Z
dc.date.available2024-04-04T03:13:05Z
dc.date.issued2016-01-12
dc.identifier.issn1932-6203
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193926
dc.description.abstractEnGlioblastoma multiforme is a malignant brain tumor with poor prognosis and high morbidity due to its invasiveness. Hypoxia-driven motility and concentration-driven motility are two mechanisms of glioblastoma multiforme invasion in the brain. The use of anti-angiogenic drugs has uncovered new progression patterns of glioblastoma multiforme associated with significant differences in overall survival. Here, we apply a mathematical model of glioblas- toma multiforme growth and invasion in humans and design computational trials using agents that target angiogenesis, tumor replication rates, or motility. The findings link highly- dispersive, moderately-dispersive, and hypoxia-driven tumors to the patterns observed in glioblastoma multiforme treated by anti-angiogenesis, consisting of progression by Expand- ing FLAIR, Expanding FLAIR + Necrosis, and Expanding Necrosis, respectively. Further- more, replication rate-reducing strategies (e.g. Tumor Treating Fields) appear to be effective in highly-dispersive and moderately-dispersive tumors but not in hypoxia-driven tumors. The latter may respond to motility-reducing agents. In a population computational trial, with all three phenotypes, a correlation was observed between the efficacy of the rate- reducing agent and the prolongation of overall survival times. This research highlights the potential applications of computational trials and supports new hypotheses on glioblastoma multiforme phenotypes and treatment options.
dc.language.isoen
dc.publisherPublic Library of Science
dc.title.enComputational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme
dc.typeArticle de revue
dc.identifier.doi10.1371/journal.pone.0146617
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halSciences du Vivant [q-bio]/Cancer
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
bordeaux.journalPLoS ONE
bordeaux.volume11
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue1
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01396271
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01396271v1
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