EN FR
EN FR
MONC - 2016
Overall Objectives
Bibliography
Overall Objectives
Bibliography


Section: New Results

Model-driven optimization of antiangiogenics + cytotoxics combination in breast cancer mice treated with bevacizumab and paclitaxel

Team participant: S. Benzekry. Other participants: S. Mollard (CRUK, Cambridge, UK), J. Ciccolini, D-C Imbs, R. El Cheikh, D. Barbolosi (SMARTc, Inserm, Marseille, FR)

Bevacizumab is the first-in-class antiangiogenic drug administrated concomitantly with cytotoxics. Several reports have shown that antiangiogenics could induce a transient phase of vascular normalization, thus ensuring a better drug delivery provided that cytotoxics administration is delayed. However, determining this best sequence is challenging. We have developed a simple mathematical model describing the impact of antiangiogenics on tumor vasculature. A 3.4 days delay between bevacizumab and paclitaxel was first proposed by the model as an optimal sequence. To test its relevance, 84 mice were orthotopically xenografted with human MDA-231Luc+ breast cancer cells. Two different sets of experiments were performed, based upon different bevacizumab dosing (10 or 20 mg/kg) and inter-cycle intervals (7 or 10 days), comprising several combinations with paclitaxel. Results showed that scheduling bevacizumab administration 3 days before paclitaxel improved antitumor efficacy (48% reduction in tumor growth as compared with concomitant dosing, p<0.05) while reducing metastatic spreading. Additionally, bevacizumab alone could lead to more aggressive metastatic disease with shorter survival in animals. Our phenomenological model was able to fit e perietal data a d provided insight o the underlying d a i s of as ulature’s a ilit to deliver the cytotoxic agent. Final simulations suggested a new, data-informed optimal sequence of 2.4 days. Our data suggest that concomitant dosing between bevacizumab and paclitaxel could be a sub-optimal strategy at bedside. In addition, this proof of concept study suggests that mathematical modelling could help to identify the best sequence among a variety of possible alternate treatment modalities, thus refining the way experimental or clinical studies are conducted.