Publication:
On optimal temozolomide scheduling for slowly growing glioblastomas

Simple item page
dc.contributor.authorSegura-Collar, Berta
dc.contributor.authorJiménez-Sánchez, Juan
dc.contributor.authorGargini, Ricardo
dc.contributor.authorDragoj, Miodrag
dc.contributor.authorSepúlveda-Sánchez, Juan M
dc.contributor.authorPešić, Milica
dc.contributor.authorRamírez-González, María A
dc.contributor.authorAyala-Hernández, Luis E
dc.contributor.authorSánchez-Gómez, Pilar
dc.contributor.authorPérez-García, Víctor M
dc.contributor.funderJames S. McDonnell Foundationes_ES
dc.contributor.funderMinistry of Education, Science and Technological Development (Serbia)es_ES
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es_ES
dc.contributor.funderUnión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF)es_ES
dc.contributor.funderInstituto de Salud Carlos IIIes_ES
dc.contributor.funderUniversity of Castilla-La Mancha (España)es_ES
dc.date.accessioned2023-04-26T13:39:22Z
dc.date.available2023-04-26T13:39:22Z
dc.date.issued2022-09
dc.description.abstractBackground: Temozolomide (TMZ) is an oral alkylating agent active against gliomas with a favorable toxicity profile. It is part of the standard of care in the management of glioblastoma (GBM), and is commonly used in low-grade gliomas (LGG). In-silico mathematical models can potentially be used to personalize treatments and to accelerate the discovery of optimal drug delivery schemes. Methods: Agent-based mathematical models fed with either mouse or patient data were developed for the in-silico studies. The experimental test beds used to confirm the results were: mouse glioma models obtained by retroviral expression of EGFR-wt/EGFR-vIII in primary progenitors from p16/p19 ko mice and grown in-vitro and in-vivo in orthotopic allografts, and human GBM U251 cells immobilized in alginate microfibers. The patient data used to parametrize the model were obtained from the TCGA/TCIA databases and the TOG clinical study. Results: Slow-growth "virtual" murine GBMs benefited from increasing TMZ dose separation in-silico. In line with the simulation results, improved survival, reduced toxicity, lower expression of resistance factors, and reduction of the tumor mesenchymal component were observed in experimental models subject to long-cycle treatment, particularly in slowly growing tumors. Tissue analysis after long-cycle TMZ treatments revealed epigenetically driven changes in tumor phenotype, which could explain the reduction in GBM growth speed. In-silico trials provided support for implementation methods in human patients. Conclusions: In-silico simulations, in-vitro and in-vivo studies show that TMZ administration schedules with increased time between doses may reduce toxicity, delay the appearance of resistances and lead to survival benefits mediated by changes in the tumor phenotype in slowly-growing GBMs.es_ES
dc.description.peerreviewedSíes_ES
dc.description.sponsorshipThis research was funded by the James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer (Collaborative award 220020560, doi:10.37717/220020560); Ministry of Education, Science and Technological Development, Republic of Serbia (ref. number 451-03-9/2021-14/200007); Ministerio de Ciencia e Innovación and FEDER funds, Spain (grant number PID2019-110895RB-I00, doi: 10.13039/501100011033 to VMP-G, and RTI2018-093596 and PI21CIII/00002 to PS-G); and Universidad de Castilla-La Mancha (grant number 2020-PREDUCLM-15634 to JJ-S).es_ES
dc.format.number1es_ES
dc.format.pagevdac155es_ES
dc.format.volume4es_ES
dc.identifier.citationNeurooncol Adv. 2022 Sep 27;4(1):vdac155.es_ES
dc.identifier.doi10.1093/noajnl/vdac155es_ES
dc.identifier.e-issn2632-2498es_ES
dc.identifier.journalNeuro-oncology advanceses_ES
dc.identifier.pubmedID36325374es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/15900
dc.language.isoenges_ES
dc.publisherOxford University Presses_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/RTI2018-093596es_ES
dc.relation.projectFECYTinfo:eu-repo/grantAgreement/ES/PID2019-110895RB-I00es_ES
dc.relation.projectFISinfo:fis/Instituto de Salud Carlos III///PI21-ISCIII Modalidad Proyectos de Investigacion en Salud Intramurales. (2021)/PI21CIII/00002es_ES
dc.relation.publisherversionhttps://doi.org/10.1093/noajnl/vdac155es_ES
dc.repisalud.centroISCIII::Unidad Funcional de Investigación de Enfermedades Crónicas (UFIEC)es_ES
dc.repisalud.institucionISCIIIes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.licenseAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectIn-silico trialses_ES
dc.subjectMathematical oncologyes_ES
dc.subjectOptimal drug schedulinges_ES
dc.subjectTemozolomide resistancees_ES
dc.subjectTumor phenotypees_ES
dc.titleOn optimal temozolomide scheduling for slowly growing glioblastomases_ES
dc.typejournal articlees_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication1a36f06c-e520-427d-90a4-53617c60d520
relation.isAuthorOfPublication7e71ffd7-1cca-494f-b9ae-684e04d9746e
relation.isAuthorOfPublication291622f0-9a6d-4f4c-a0cf-3896780f9c28
relation.isAuthorOfPublication5149e567-93ff-423f-86af-68545f9abee7
relation.isAuthorOfPublication.latestForDiscovery1a36f06c-e520-427d-90a4-53617c60d520
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
OnOptimalTemozolomideScheduling_2022.pdf
Size:
13.15 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Unidad Funcional de Investigación de Enfermedades Crónicas (UFIEC)
i+12 - Instituto de Investigación Hospital 12 de Octubre (Madrid)