Caractérisation au moyen d'outils mathématiques des effets vasculaires du bevacizumab à des fins d'optimisation des protocoles thérapeutiques dans le cas des tumeurs cérébrales

Abstract : The main aim of this work was to characterize the effects of the anti-VEGF Bevacizumab (Avastin) on the tumor vascular network, in vivo, over time, thanks to the skin fold chamber model on the nude mouse. Images of the vascular network obtained using intravital microscopy were analyzed par a dedicated image processing algorithm developed within our research team, allowing to highlight the morphological modifications induced by the treatment and to isolate discriminating parameters of the vascular "normalization", by comparison to healthy vascular networks. Le vascular "normalization" period detected with our tool was comforted by the analysis of the functionality of the blood vessels over time, in vivo and by an immunohistochemical analysis of the blood vessels and of the tumor tissue. In preliminary in vivo experiments, we tried to verify the hypothesis of the benefits of an anti-VEGF treatment prior to photodynamic therapy (PDT) on glioblastoma xenografts implanted subcutaneously or in the skin fold chamber. The efficacy of PDT is described as being dependent on tumor oxygenation and on the distribution of the photosensitizing agent within the tumor. In paralel to this work, we tried as a pluridisciplinary team to develop a mathematical model of the tumor response to bevacizumab using biological data obtained on the same in vivo model et that will allow in the future to simulate the response for different doses and different treatment durations, for the optimization of therapeutic protocols
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https://hal.univ-lorraine.fr/tel-01753330
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  • HAL Id : tel-01753330, version 1

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Karima El Alaoui-Lasmaili. Caractérisation au moyen d'outils mathématiques des effets vasculaires du bevacizumab à des fins d'optimisation des protocoles thérapeutiques dans le cas des tumeurs cérébrales. Sciences du Vivant [q-bio]. Université de Lorraine, 2017. Français. ⟨NNT : 2017LORR0023⟩. ⟨tel-01753330⟩

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