On optimal temozolomide scheduling for slowly growing glioblastomas
2022
Аутори:
Segura-Collar, BertaJiménez-Sánchez, Juan
Gargini, Ricardo
Dragoj, Miodrag
Sepúlveda-Sánchez, Juan M
Pešić, Milica
Ramírez, María A
Ayala-Hernández, Luis E
Sánchez-Gómez, Pilar
Pérez-García, Víctor M
Тип документа:
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт:
Background 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.
Кључне речи:
in-silico trials; mathematical oncology; optimal drug scheduling; temozolomide resistance; tumor phenotypeИзвор:
Neuro-Oncology Advances, 2022, 4, 1, vdac155-Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200007 (Универзитет у Београду, Институт за биолошка истраживања 'Синиша Станковић') (RS-MESTD-inst-2020-200007)
- 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)
- Ministerio de Ciencia e Innovacion and FEDER funds, Spain (grant number PID2019110895RB-I00, doi: 10.13039/501100011033 to VMP-G, and RTI2018093596 and PI21CIII/00002 to PS-G)
- Universidad de Castilla-La Mancha (grant number 2020-PREDUCLM-15634 to JJ-S)
DOI: 10.1093/noajnl/vdac155
ISSN: 2632-2498
PubMed: 36325374
WoS: 000875672100004
Scopus: 2-s2.0-85145400021
URI
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC9616068https://academic.oup.com/noa/article/doi/10.1093/noajnl/vdac155/6722624
http://radar.ibiss.bg.ac.rs/handle/123456789/5182