Related Experiment Video
Updated: Jul 8, 2025

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma
Hannah G Anderson1, Gregory P Takacs2, Duane C Harris3
1Department of Mathematics, University of Florida, Gainesville, FL, USA.
Abstract:
Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the approximate Bayesian computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended fourier amplitude sensitivity test. Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.
Insights
Glioblastoma (GBM) treatments are improved by targeting immune suppression. Combining immune checkpoint inhibitors with therapies for myeloid-derived suppressor cells (MDSCs) may lead to tumor-free equilibrium in GBM.
Area of Science:
- Oncology
- Immunology
- Mathematical Biology
Background:
- Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options.
- Tumor-induced immunosuppression via PD-L1-PD-1 interactions and myeloid-derived suppressor cells (MDSCs) hinders anti-tumor immunity.
- Understanding these complex cellular interactions is crucial for developing effective therapies.
Purpose of the Study:
- To develop a mathematical model simulating GBM, T cells, and MDSCs.
- To analyze the theoretical impact of immune suppression on tumor dynamics.
- To identify potential therapeutic strategies for GBM treatment.
Main Methods:
- Ordinary differential equations (ODEs) model for glioma cells, T cells, and MDSCs.
- Equilibrium and stability analysis to determine system states.
- Bifurcation analysis to assess treatment effects.
- Approximate Bayesian computation (ABC) and Fourier Amplitude Sensitivity Test (FAST) for parameter estimation and sensitivity analysis.
Main Results:
- The model identified conditions for stable tumorous and tumor-free equilibria.
- Tumor-free equilibrium is achievable when T cell activity surpasses tumor growth and immunosuppression.
- Bifurcation analysis indicated that combined surgical resection and targeting PD-L1-PD-1 and MDSC suppression promotes a tumor-free state.
- Sensitivity analysis revealed significant interactions between tumor growth drivers and immunosuppressive mechanisms.
Conclusions:
- Targeting both PD-L1-PD-1 immune checkpoints and MDSC-mediated immunosuppression is a promising therapeutic strategy for GBM.
- Mathematical modeling provides valuable insights into GBM tumor-immune dynamics.
- Combined immunotherapies hold potential for achieving durable tumor eradication in glioblastoma.

