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J R Soc Interface. 2015 Aug 6;12(109):20150388. doi: 10.1098/rsif.2015.0388.

In silico analysis suggests differential response to bevacizumab and radiation combination therapy in newly diagnosed glioblastoma.

Author information

1
Department of Neurological Surgery, Northwestern University, Chicago, IL 60611, USA.
2
Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612, USA.
3
Department of Radiology, University of Washington, Seattle, WA 98195-7987, USA.
4
Department of Neurological Surgery, Northwestern University, Chicago, IL 60611, USA kraeswanson@gmail.com.

Abstract

Recently, two phase III studies of bevacizumab, an anti-angiogenic, for newly diagnosed glioblastoma (GBM) patients were released. While they were unable to statistically significantly demonstrate that bevacizumab in combination with other therapies increases the overall survival of GBM patients, there remains a question of potential benefits for subpopulations of patients. We use a mathematical model of GBM growth to investigate differential benefits of combining surgical resection, radiation and bevacizumab across observed tumour growth kinetics. The differential hypoxic burden after gross total resection (GTR) was assessed along with the change in radiation cell kill from bevacizumab-induced tissue re-normalization when starting therapy for tumours at different diagnostic sizes. Depending on the tumour size at the time of treatment, our model predicted that GTR would remove a variable portion of the hypoxic burden ranging from 11% to 99.99%. Further, our model predicted that the combination of bevacizumab with radiation resulted in an additional cell kill ranging from 2.6×10(7) to 1.1×10(10) cells. By considering the outcomes given individual tumour kinetics, our results indicate that the subpopulation of patients who would receive the greatest benefit from bevacizumab and radiation combination therapy are those with large, aggressive tumours and who are not eligible for GTR.

KEYWORDS:

bevacizumab; glioblastoma; hypoxia; mathematical model; radiation; surgery

PMID:
26202682
PMCID:
PMC4535409
DOI:
10.1098/rsif.2015.0388
[Indexed for MEDLINE]
Free PMC Article

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