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H 1 Mathematical modeling of targeted cancer therapeutics

Auteurs : Jackson, Trachette (Auteur de la Conférence)
CIRM (Editeur )

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    Résumé : Increased understanding of the molecular drivers of tumor initiation and progression has led to targeted manipulation of intracellular signaling pathways for patient-specific therapeutic benefit. In this talk, we outline a multiscale modeling strategy for linking intracellular signaling pathways critical to cell proliferation and apoptosis; receptor-ligand binding on the cell surface that triggers these intracellular signaling cascades; and population-level tumor growth dynamics and response to treatments targeting these pathways. Integration of these tiers of information is precisely the level of detail required to uncover possible hidden mechanisms that mediate both expected and potentially counter intuitive therapeutic effects of novel, targeted therapeutics on the multiple cell types responsible for tumor progression. We demonstrate the predictive therapeutic power of our multiscale computational approach with two specific examples. The first considers treatments targeting VEGF and its receptors. In this case, it is difficult to tease out the differential anti-angiogenic and anti-tumor effects of drug combinations experimentally due to the dynamic crosstalk between tumor cells and vascular endothelial cells, which impacts critical aspects of tumorigenesis, independent of angiogenesis. Our model predicts that certain therapeutic combinations result in antagonism in vivo, but not in vitro. In the second example, our computational approach is used to study the therapeutic impact of Tocilizumab, a competitive IL-6R inhibitor, on tumor growth and cancer stem cell fraction, alone and in combination with the traditional chemotherapeutic agent, Cisplatin. Targeting critical regulators of the cancer stem cell phenotype to overcome their acute influence on tumor growth is a promising new strategy for cancer treatment. Our results suggest that nonintuitive dose scheduling strategies will optimize the synergy of combination therapy. Both examples show that this predictive modeling framework can serve to evaluate strategies for signaling pathway modulation rapidly and can provide a basis for proposing optimized dose scheduling for combination treatments involving targeted therapeutics.

    Keywords : mathematical model; cancer; therapeutic

    Codes MSC :
    92-XX - Biology and other natural sciences

      Informations sur la Vidéo

      Réalisateur : Hennenfent, Guillaume
      Langue : Anglais
      Date de publication : 17/03/2020
      Date de captation : 24/02/2020
      Collection : Research talks ; Dynamical Systems and Ordinary Differential Equations
      Format : MP4
      Durée : 00:42:58
      Domaine : Dynamical Systems & ODE
      Audience : Chercheurs ; Doctorants , Post - Doctorants
      Download : https://videos.cirm-math.fr/2020-02-24_Jackson.mp4

    Informations sur la rencontre

    Nom de la rencontre : Thematic Month Week 4: Mathematics of Complex Systems in Biology and Medicine / Mois thématique Semaine 4 : Mathématiques des systèmes complexes en biologie et en médecine
    Organisateurs de la rencontre : Cristofol, Michel ; Freyermuth, Jean-Marc ; Gomez, Christophe ; Hubert, Florence ; Ryan, Shawn ; Tournus, Magali
    Dates : 24/02/2020 - 28/02/2020
    Année de la rencontre : 2020
    URL Congrès : https://conferences.cirm-math.fr/2304.html

    Citation Data

    DOI : 10.24350/CIRM.V.19616003
    Cite this video as: Jackson, Trachette (2020). Mathematical modeling of targeted cancer therapeutics. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19616003
    URI : http://dx.doi.org/10.24350/CIRM.V.19616003


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