A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy
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Published on: September 27, 2021
Yongjiang Zheng1, Jiguang Bao2, Qiyi Zhao3
1Department of Hematology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Abstract:
The emergence of drug resistance is often an inevitable obstacle that limits the long-term effectiveness of clinical cancer chemotherapeutics. Although various forms of cancer cell-intrinsic mechanisms of drug resistance have been experimentally revealed, the role and the underlying mechanism of tumor microenvironment in driving the development of acquired drug resistance remain elusive, which significantly impedes effective clinical cancer treatment. Recent experimental studies have revealed a macrophage-mediated drug resistance mechanism in which the tumor microenvironment undergoes adaptation in response to macrophage-targeted colony-stimulating factor-1 receptor (CSF1R) inhibition therapy in gliomas. In this study, we developed a spatio-temporal model to quantitatively describe the interplay between glioma cells and CSF1R inhibitor-targeted macrophages through CSF1 and IGF1 pathways. Our model was used to investigate the evolutionary kinetics of the tumor regrowth and the associated dynamic adaptation of the tumor microenvironment in response to the CSF1R inhibitor treatment. The simulation result obtained using this model was in agreement with the experimental data. The sensitivity analysis revealed the key parameters involved in the model, and their potential impacts on the model behavior were examined. Moreover, we demonstrated that the drug resistance is dose-dependent. In addition, we quantitatively evaluated the effects of combined CSFR inhibition and IGF1 receptor (IGF1R) inhibition with the goal of designing more effective therapies for gliomas. Our study provides quantitative and mechanistic insights into the microenvironmental adaptation mechanisms that operate during macrophage-targeted immunotherapy and has implications for drug dose optimization and the design of more effective combination therapies. Mol Cancer Ther; 17(4); 814-24. ©2018 AACR.
Insights
Drug resistance in cancer is a major challenge. This study models how tumor microenvironments adapt to therapies targeting macrophages, revealing dose-dependent resistance and informing new treatment strategies.
Area of Science:
- Oncology
- Immunology
- Computational Biology
Background:
- Drug resistance limits cancer chemotherapy effectiveness.
- Tumor microenvironment's role in acquired resistance is not fully understood.
- Macrophage-mediated resistance in gliomas is a newly identified mechanism.
Purpose of the Study:
- To develop a spatio-temporal model of glioma-macrophage interactions.
- To investigate tumor regrowth and microenvironment adaptation during CSF1R inhibition.
- To explore potential combination therapies for gliomas.
Main Methods:
- Developed a spatio-temporal model of glioma and macrophage interplay.
- Simulated tumor kinetics and microenvironment adaptation.
- Performed sensitivity analysis and evaluated combination therapies.
Main Results:
- Model simulations aligned with experimental data.
- Drug resistance was found to be dose-dependent.
- Identified key parameters influencing model behavior.
Conclusions:
- Provided quantitative insights into microenvironmental adaptation during immunotherapy.
- Highlighted implications for drug dose optimization.
- Suggested strategies for designing effective combination therapies for gliomas.
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