Description du projet
Détournement métabolique des cellules immunitaires par les tumeurs
Malgré ses grandes promesses, l’immunothérapie dans la pratique clinique ne s’est avérée bénéfique que pour une fraction des patients atteints de cancer. De nouvelles approches sont indispensables pour améliorer les résultats cliniques. Financé par le Conseil européen de la recherche, le projet SpatialTMEMetabolism se penchera sur le métabolisme des cellules immunitaires humaines. Les chercheurs travailleront sur l’hypothèse selon laquelle les tumeurs créent des niches métaboliques définies pour supprimer les réponses immunitaires. En utilisant le profilage métabolique d’une seule cellule, les chercheurs mettront en lumière la manière dont les différents cancers influencent le métabolisme des cellules immunitaires et identifieront les états prédictifs des cellules immunitaires en réponse à l’immunothérapie. Ces travaux permettront d’identifier de nouvelles cibles moléculaires susceptibles d’être exploitées à des fins thérapeutiques.
Objectif
The success of cancer immunotherapy, especially immune checkpoint inhibition (ICI), demonstrates the ability of the immune system to fight tumors. However, only a fraction of patients benefit from currently available therapies, and we need to find novel approaches to improve clinical responses. Cellular metabolism has emerged as a key determinant of multiple aspects of immune cell function, especially T cell exhaustion and anti-inflammatory macrophage polarization. However, we currently do not have a good understanding of the metabolic states of human immune cells since no technology has been available to quantify them directly in clinical tumor tissues.
I hypothesize that tumors create spatially defined metabolic environments, also called metabolic niches, to suppress immune cells and that this mechanism can be targeted to improve cancer immunotherapy. To test this, we will (1) quantify the metabolic states of immune cells in solid human cancers, (2) identify metabolic immune cell states that predict response to ICI, and (3) reveal the mechanism of metabolic niche formation in tumor organoids. We will quantify cellular metabolism and phenotype directly in human tumor tissues, using the innovative single-cell metabolic profiling (scMEP) approach I have recently developed. We will combine this with multiplexed ion beam imaging (MIBI), a technology that enables 40-dimensional proteomic imaging. MIBI imaging will be complemented by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and machine learning frameworks for the analysis of these multi-omic datasets.
Taken together, this project will uncover generalizable concepts of how different tumor entities influence the cellular metabolism of immune cells to modulate their function. The potential therapeutic targets that will emerge from this analysis could thus contribute to improved treatment options for various types of human cancer.
Champ scientifique
- medical and health sciencesclinical medicineoncology
- medical and health sciencesbasic medicineimmunologyimmunotherapy
- natural scienceschemical sciencesanalytical chemistrymass spectrometry
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencesphysical sciencesopticslaser physics
Mots‑clés
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thème(s)
Régime de financement
HORIZON-ERC - HORIZON ERC GrantsInstitution d’accueil
69120 Heidelberg
Allemagne