Modeling cell death dynamics at the receptor level

Luis Pereira 1, 2, 3 Mickael Meyer 1 Paul Hofman 1 Jean-Luc Gouzé 2, 3 Madalena Chaves 2, 3 Jérémie Roux 1, 2, 3
2 BIOCORE - Biological control of artificial ecosystems
LOV - Laboratoire d'océanographie de Villefranche, CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique
Abstract : Initiating cell death in malignant cells through the activation of death receptors 4 and 5 (DR4/5) is a cancer therapeutic strategy re-entering a phase of intensive investigation due to recent advances that improved ligand activity, pharmacokinectics and lowered side effects (Wajant et al. Cancer Lett 2013). However, most drugs induce remarkable levels of heterogeneity in cellular response, leaving a subset of cancer cells repopulating the tumor. Although we have shown recently that complex receptor dynamics can predicts the sensitivity of tumor cells to several cancer therapeutics (Roux et al., Mol Syst Biol 2015), there is still no suitable mathematical model to understand in quantitative terms (a) the cell responses to the ~30 new DR4/5 ligands that have emerged with potential therapeutic value (de Miguel Cell Death Differ 2016) and (b) the role of cellular noise in the detailed molecular reactions at the receptor level. In the present study, we use experimental and theoretical approaches to evaluate the role of the death receptor subsystem of the apoptosis network, on cell death decision upon stimulation with novel ligands formulations and regimens.
Type de document :
Communication dans un congrès
CompSysBio, Advanced Lecture Course on Computational Systems Biology, Mar 2017, Aussois, France
Liste complète des métadonnées
Contributeur : Jean-Luc Gouzé <>
Soumis le : mardi 25 juillet 2017 - 12:39:26
Dernière modification le : mercredi 21 mars 2018 - 18:57:45


  • HAL Id : hal-01568506, version 1



Luis Pereira, Mickael Meyer, Paul Hofman, Jean-Luc Gouzé, Madalena Chaves, et al.. Modeling cell death dynamics at the receptor level. CompSysBio, Advanced Lecture Course on Computational Systems Biology, Mar 2017, Aussois, France. 〈hal-01568506〉



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