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Overcoming chemotherapy resistance in low-grade gliomas: A computational approach
Thibault Delobel1,2, Luis E Ayala-Hernández1,3, Jesús J Bosque1
1Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain.
Abstract:
Low-grade gliomas are primary brain tumors that arise from glial cells and are usually treated with temozolomide (TMZ) as a chemotherapeutic option. They are often incurable, but patients have a prolonged survival. One of the shortcomings of the treatment is that patients eventually develop drug resistance. Recent findings show that persisters, cells that enter a dormancy state to resist treatment, play an important role in the development of resistance to TMZ. In this study we constructed a mathematical model of low-grade glioma response to TMZ incorporating a persister population. The model was able to describe the volumetric longitudinal dynamics, observed in routine FLAIR 3D sequences, of low-grade glioma patients acquiring TMZ resistance. We used the model to explore different TMZ administration protocols, first on virtual clones of real patients and afterwards on virtual patients preserving the relationships between parameters of real patients. In silico clinical trials showed that resistance development was deferred by protocols in which individual doses are administered after rest periods, rather than the 28-days cycle standard protocol. This led to median survival gains in virtual patients of more than 15 months when using resting periods between two and three weeks and agreed with recent experimental observations in animal models. Additionally, we tested adaptive variations of these new protocols, what showed a potential reduction in toxicity, but no survival gain. Our computational results highlight the need of further clinical trials that could obtain better results from treatment with TMZ in low grade gliomas.
Insights
Mathematical modeling reveals that altering temozolomide (TMZ) administration schedules can delay drug resistance in low-grade gliomas. Intermittent dosing with rest periods significantly improves survival in virtual patient models.
Area of Science:
- Neuro-oncology
- Mathematical Biology
- Computational Medicine
Background:
- Low-grade gliomas are primary brain tumors often treated with temozolomide (TMZ).
- Patients frequently develop resistance to TMZ, limiting treatment efficacy.
- Persister cells, entering dormancy, are implicated in TMZ resistance development.
Purpose of the Study:
- To develop a mathematical model of low-grade glioma response to TMZ, incorporating persister cells.
- To investigate novel TMZ administration protocols to overcome drug resistance.
- To evaluate the impact of modified dosing schedules on patient survival and toxicity.
Main Methods:
- Construction of a mathematical model simulating low-grade glioma dynamics under TMZ treatment.
- Inclusion of a persister cell population within the model to represent dormancy.
- In silico clinical trials using virtual patient models to test various TMZ administration protocols.
Main Results:
- The model accurately described tumor volume changes in patients developing TMZ resistance.
- Protocols with intermittent TMZ dosing and rest periods deferred resistance development compared to standard cycles.
- Virtual patients showed median survival gains exceeding 15 months with 2-3 week rest periods.
- Adaptive protocol variations reduced toxicity but did not increase survival gains.
Conclusions:
- Mathematical modeling provides insights into optimizing TMZ treatment for low-grade gliomas.
- Intermittent TMZ dosing strategies show promise in delaying resistance and improving survival.
- Further clinical trials are warranted to validate these computational findings in real-world patient populations.
