Karima El Alaoui-Lasmaili
Glioblastoma is a highly angiogenic type of tumor and glioblastoma patients have a low survival rate in spite of all the therapeutic procedures unleashed (surgical resection, radio- and chemotherapy). According to the literature, anti-angiogenic therapies such as the anti-VEGF bevacizumab (Avastin®), can temporarily induce changes in the tumor vasculature that result in improved tissue oxygenation which is crucial to the success of oxygen-dependent radiation therapy.
Combining bevacizumab and radiation therapy seems to be a prospective way to improve patient survival. However, finding the best treatment sequence is not an easy task to achieve and no consensus has yet been established because of the lack of knowledge regarding the time and duration of the increased oxygenation window provided by bevacizumab. Hence it is indispensable to define the morphological and functional effects of bevacizumab on the tumor vascular network that impact on the oxygenation to find the perfect timing for its association with radiation therapy.
To achieve this aim, we used the skinfold chamber model on nude mice which allows us to observe the evolution of the vascularization of a glioblastoma tumor fragment for at most 5 to 6 weeks. To analyze the effects of bevacizumab on the vascular network, we combined the use of a mathematical tool created by our research team that characterizes morphologically the tumor blood vessels to an immunohistochemical morphological analysis of the tumor vasculature. To seek bevacizumab’s effects on the ability of the tumor blood vessels to deliver blood charged with nutrients and oxygen to the tumor, we evaluated the vascular permeability and the capacity of the blood vessels to perfuse the tumor tissue throughout treatment.
Additionally, we used some of the in vivo data of the tumor vascular network obtained with intravital microscopy to develop a mathematical model of the tumor response to the anti-angiogenic and hope to adapt it to clinically relevant data in order to optimize the treatment schedule .
 J.-B. Tylcz, K. El Alaoui-Lasmaili, E.-H. Djermoune, N. Thomas, B. Faivre, & T. Bastogne, Data-driven modeling and characterization of anti-angiogenic molecule effects on tumoral vascular density, Biomedical Signal Processing & Control, 20, 52-60, 2015. Online