Anti-VEGF treatment reduces blood supply and increases tumor cell invasion in glioblastoma

By O. Keunen, M. Johansson, A. Oudin, Morgane Sanzey, S. A. Rahim, F. Fack, F. Thorsen, T. Taxt, Michal Bartoš, R. Jiřík and 8 more. Proceedings of the National Academy of Sciences of the United States of America, 2011

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Bevacizumab, an antibody against vascular endothelial growth factor (VEGF), is a promising, yet controversial, drug in human glioblastoma treatment (GBM). Its effects on tumor burden, recurrence, and vascular physiology are unclear. We therefore determined the tumor response to bevacizumab at the phenotypic, physiological, and molecular level in a clinically relevant intracranial GBM xenograft model derived from patient tumor spheroids. Using anatomical and physiological magnetic resonance imaging (MRI), we show that bevacizumab causes a strong decrease in contrast enhancement while having only a marginal effect on tumor growth. Interestingly, dynamic contrast-enhanced MRI revealed a significant reduction of the vascular supply, as evidenced by a decrease in intratumoral blood flow and volume and, at the morphological level, by a strong reduction of large- and medium-sized blood vessels. Electron microscopy revealed fewer mitochondria in the treated tumor cells. Importantly, this was accompanied by a 68% increase in infiltrating tumor cells in the brain parenchyma. At the molecular level we observed an increase in lactate and alanine metabolites, together with an induction of hypoxia-inducible factor 1α and an activation of the phosphatidyl-inositol-3-kinase pathway. These data strongly suggest that vascular remodeling induced by anti-VEGF treatment leads to a more hypoxic tumor microenvironment. This favors a metabolic change in the tumor cells toward glycolysis, which leads to enhanced tumor cell invasion into the normal brain. The present work underlines the need to combine anti-angiogenic treatment in GBMs with drugs targeting specific signaling or metabolic pathways linked to the glycolytic phenotype.

Subfields: Cancer Research, Genetics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/b4b8fb15ad897801559a1e2d6a5d62a5f91a1021

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