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Quantifying the impact of antiangiogenic therapy on hypoxia and implications for radiation therapy in glioblastoma multiforme with a biomathematical model.

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e13028 Background: Glioblastoma multiforme (GBM) is the most aggressive form of primary brain tumor. As angiogenesis is a major hallmark of GBM, it can be inferred that hypoxia plays a prominent role in the progression of the disease. However, due to difficulty in assessing hypoxia, the development and evolution of hypoxia has not been well studied for GBM. 18F-Fluoromisonidazole (FMISO) PET indirectly measures hypoxia. It is known that hypoxia reduces the efficacy of radiation therapy, and one current strategy being explored is to combine anti-angiogenic therapy and radiation therapy. However, it is unclear whether anti-angiogenic therapy is ultimately reducing or increasing hypoxia nor is it clear how long the effects last. Methods: We have developed a spatio-temporal biomathematical model for glioma proliferation and invasion that incorporates the angiogenic cascade. In this context, we can simulate the action of anti-angiogenic treatment, such as bevacizumab, by modifying the availability of angiogenic factors. By applying a pharmacokinetic model for the uptake of FMISO to the simulation results, we can generate the corresponding FMISO-PET images during and after anti-angiogenic therapy to compare with what would be seen in the clinic. Results: Simulation results for a wide range of tumor kinetics demonstrated that hypoxia in general decreased during anti-angiogenic therapy. However, the rates at which it decreased and the time for the hypoxia to return to pre-treatment levels were not uniform. Conclusions: Dynamic understanding of anti-angiogenic therapy effects on vascular normalization and hypoxia suggest that optimal timing of radiation therapy and anti-angiogenic therapies would vary by patient. This biomathematical model can be tuned to individual patients’ tumors and provide similar information as a FMISO-PET image and also give insight into the dynamics of the hypoxia over time. Such insight could be invaluable to patient-specific treatment planning for combining radiation with antiangiogenics.
Title: Quantifying the impact of antiangiogenic therapy on hypoxia and implications for radiation therapy in glioblastoma multiforme with a biomathematical model.
Description:
e13028 Background: Glioblastoma multiforme (GBM) is the most aggressive form of primary brain tumor.
As angiogenesis is a major hallmark of GBM, it can be inferred that hypoxia plays a prominent role in the progression of the disease.
However, due to difficulty in assessing hypoxia, the development and evolution of hypoxia has not been well studied for GBM.
18F-Fluoromisonidazole (FMISO) PET indirectly measures hypoxia.
It is known that hypoxia reduces the efficacy of radiation therapy, and one current strategy being explored is to combine anti-angiogenic therapy and radiation therapy.
However, it is unclear whether anti-angiogenic therapy is ultimately reducing or increasing hypoxia nor is it clear how long the effects last.
Methods: We have developed a spatio-temporal biomathematical model for glioma proliferation and invasion that incorporates the angiogenic cascade.
In this context, we can simulate the action of anti-angiogenic treatment, such as bevacizumab, by modifying the availability of angiogenic factors.
By applying a pharmacokinetic model for the uptake of FMISO to the simulation results, we can generate the corresponding FMISO-PET images during and after anti-angiogenic therapy to compare with what would be seen in the clinic.
Results: Simulation results for a wide range of tumor kinetics demonstrated that hypoxia in general decreased during anti-angiogenic therapy.
However, the rates at which it decreased and the time for the hypoxia to return to pre-treatment levels were not uniform.
Conclusions: Dynamic understanding of anti-angiogenic therapy effects on vascular normalization and hypoxia suggest that optimal timing of radiation therapy and anti-angiogenic therapies would vary by patient.
This biomathematical model can be tuned to individual patients’ tumors and provide similar information as a FMISO-PET image and also give insight into the dynamics of the hypoxia over time.
Such insight could be invaluable to patient-specific treatment planning for combining radiation with antiangiogenics.

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