Abstract 5203: Innovative and predictive models against cancer: an IMODI integrative approach
Authors: Mignard Caroline , Arnould Laurent , Bruno Alain , Calvet Loreley , Colombel Marc , Corre Jill , Cuvillier Olivier , Eckel Bénédicte , Forraz Nico , Gonzalez-Jouhanneaud Alexandra , Goetsch Liliane , Guenot Dominique , Iovanna Juan , Kuras Mariana , Lautrette Christophe , Le Vacon Françoise , Malavaud Bernard , Merle Philippe , Meyer-Losic Florence , Praz Françoise , Rosmorduc Olivier , Sarry Jean-Emmanuel , Tabone Séverine , Vaglio Philippe , Ysebaert Loïc , Duchamp Olivier ,   IMODI Consortium
Published: July 2016

Abstract
Many reports support that xenografts from patient-derived xenografts (PDXs) in mice or rats well recapitulate the molecular diversity, cellular heterogeneity, and histology seen in patient tumors. However, shortcomings including limited clinical diversity of the PDXs, absence of influence of human microbiome, absence of drug human metabolism and reduced immune system restrain the predictive values of these PDX models. To set-up a holistic integration of these criticisms, we have associated efforts from public hospitals, academic groups, biotechs and private pharmaceutical companies with the financial support of the French Ministry of Industry.
First, to improve the clinical cancer diversity, surgical specimens from patients obtained from 8 different tumor locations (lung, breast, ovary, pancreas, liver, prostate, AML, myelome) are collected to establish large collections of PDXs in mice. In addition, in vitro primary cultures of cells from these samples are conducted to establish a collection of cell lines from the stromal and the tumoral compartments. The established models are evaluated for ex vivo and in vivo sensitivities to relevant anticancer drugs, histological and molecular characteristics. All model characteristics are being compiled in a web-based database for efficient features search and interconnection. These tumor collection and model characterization were performed under specific procedures that are followed by all partners within the consortium, which allows to have harmonized results and high quality material. Second, to improve our knowledge on the role of the human gut microbiota, stools are collected from patients with cancer and from mice bearing PDXs before and after chemotherapeutic treatments allowing a comparison of the microbiota profiles. In order to increase the predictability of the models, we are generating mice with humanized liver showing distinct drug pharmacokinetic profiles as compared with parental mice. Finally, the humanization of the immune system in mice is developed by several approaches including the use of induced pluripotent stem cells from cancer patients.
We will present the first characterized models and will discuss their usefulness and chance to bring benefit to patients via this holistic strategy developed within the IMODI initiative.
Citation Format: Caroline Mignard, Laurent Arnould, Alain Bruno, Loreley Calvet, Marc Colombel, Jill Corre, Olivier Cuvillier, Bénédicte Eckel, Nico Forraz, Alexandra Gonzalez-Jouhanneaud, Liliane Goetsch, Dominique Guenot, Juan Iovanna, Mariana Kuras, Christophe Lautrette, Françoise Le Vacon, Bernard Malavaud, Philippe Merle, Florence Meyer-Losic, Françoise Praz, Olivier Rosmorduc, Jean-Emmanuel Sarry, Séverine Tabone, Philippe Vaglio, Loïc Ysebaert, Olivier Duchamp, IMODI Consortium. Innovative and predictive models against cancer: an IMODI integrative approach. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5203.