Projet de thèse en MBS - Modèles, méthodes et algorithmes en biologie, santé et environnement
Sous la direction de Angélique Stéphanou et de Gibin Powathil.
Thèses en préparation à l'Université Grenoble Alpes en cotutelle avec Swansea University , dans le cadre de École doctorale ingénierie pour la santé, la cognition, l'environnement (Grenoble) , en partenariat avec Techniques de L'Ingénierie Médicale et de la Complexité - Inofrmatique, Mathématiques et Applications. (laboratoire) et de DyCTim : Dynamique Cellulaire/Tissulaire et microscopie fonctionnelle (equipe de recherche) depuis le 01-01-2018 .
Tumour growth models are numerous but they rarely (i) allow to follow the spatiotemporal evolution of the tumour and its microenvironment synergistically, (ii) integrate all the scales from intracellular events (protein activity) to the tissue/organ scale (alteration of tissue/organ functionality), (iii) integrate the combine effects and influences of the angiogenic and lymphangiogenic vascular networks. This hampers the use of the models to realistically test and assess the effects of drugs since the dispersion of the drugs through the vessels and diffusion through the tissue - that depends on these networks - are still disregarded. In this project we intend to develop such an integrated and multiscale model of the tumour and its vascular/lymphatic microenvironment and to our knowledge this will be the first of its kind. The model will thus give a mean to predict the outcome of treatment with an unprecedented level of accuracy. It will then make it possible to compute optimum treatment with regards to drug dose, scheduling and combination of molecules (specifically anti-cancer and anti-vascular molecules) for each individual patient.
Multiscale Modelling of Angiogenesis and Lymphangiogenesis: Towards developing virtual tumour models
Mathematical Oncology is currently an emerging and vibrant research area where we use mathematical and computational tools to study various aspects of cancer growth, invasion and associated multimodality treatments with an aim of providing better, individualised treatments to the patients. The vascular network is one of the most essential elements of the tumour and plays a vial role in tumour evolution, aggressiveness and invasiveness. Metastatic spreading is highly dependent upon angiogenesis and lymphangiogenesis, i.e. on the way the tumour acquires new vessels and lymphatic system. The processes by which the tumour cells are able to enter the vessels, to be carried by the bloodstream and to extravase to form distal metastases are now well documented, implicating the role of the vasculature in tumour metastasis. Historically, lymphatic vessels were considered passive participants in tumour metastasis by simply providing channels for tumour cells to transit through. However, recent experimental findings several key lymphatic-specific molecular markers and an increased availability of in vitro and in vivo experimental systems to study lymphatic biology have highlighted a significant and active role for the lymphatic vasculature in metastatic tumour spread. This project aims to develop a multiscale mathematical and computational model for tumour angiogenesis and lymphangiogenesis incorporating the fluid flow dynamics to study vascular tumour evolution, anticancer drug delivery and anti-vascular therapies. The model can be also used to study various hallmarks of metastatic tumour such as changing cellular metabolism and cell migration. Furthermore, it can be incorporated into other modules of tumour modelling project that aim towards developing an in silico patient-specific virtual tumour to aid in anticancer therapy planning. This is a multidisciplinary project with national and international collaborative partnerships from engineering, computational and experimental researchers. Successful candidate will develop, implement and analyse mathematical and computational models relevant to the project and he/she will also have opportunities to do related biological experiments at TIMC-IMAG lab in Grenoble.