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Computational modelling of perivascular-niche dynamics for the optimization of treatment schedules for glioblastoma.
- Source :
-
Nature biomedical engineering [Nat Biomed Eng] 2021 Apr; Vol. 5 (4), pp. 346-359. Date of Electronic Publication: 2021 Apr 16. - Publication Year :
- 2021
-
Abstract
- Glioblastoma stem-like cells dynamically transition between a chemoradiation-resistant state and a chemoradiation-sensitive state. However, physical barriers in the tumour microenvironment restrict the delivery of chemotherapy to tumour compartments that are distant from blood vessels. Here, we show that a massively parallel computational model of the spatiotemporal dynamics of the perivascular niche that incorporates glioblastoma stem-like cells and differentiated tumour cells as well as relevant tissue-level phenomena can be used to optimize the administration schedules of concurrent radiation and temozolomide-the standard-of-care treatment for glioblastoma. In mice with platelet-derived growth factor (PDGF)-driven glioblastoma, the model-optimized treatment schedule increased the survival of the animals. For standard radiation fractionation in patients, the model predicts that chemotherapy may be optimally administered about one hour before radiation treatment. Computational models of the spatiotemporal dynamics of the tumour microenvironment could be used to predict tumour responses to a broader range of treatments and to optimize treatment regimens.
- Subjects :
- Animals
Brain Neoplasms mortality
Disease Models, Animal
Drug Administration Schedule
Drug Resistance, Neoplasm
Glioblastoma mortality
Glioblastoma radiotherapy
Humans
Mice
Platelet-Derived Growth Factor genetics
Platelet-Derived Growth Factor metabolism
Radiation, Ionizing
Survival Rate
Treatment Outcome
Tumor Microenvironment
Antineoplastic Agents, Alkylating administration & dosage
Brain Neoplasms drug therapy
Glioblastoma drug therapy
Models, Biological
Temozolomide administration & dosage
Subjects
Details
- Language :
- English
- ISSN :
- 2157-846X
- Volume :
- 5
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Nature biomedical engineering
- Publication Type :
- Academic Journal
- Accession number :
- 33864039
- Full Text :
- https://doi.org/10.1038/s41551-021-00710-3