Projektbeschreibung
Antigenerkennung durch T-Zellen vorhersagen
Unser Immunsystem besteht aus mehreren T-Zell-Subpopulationen, die jeweils ein eigenes Profil und eine eigene Funktion aufweisen. Es besteht großes Interesse an der Erkennung von T-Zellen in Bezug auf Krankheitserreger und Krebsantigene, um die Diagnose von Erkrankungen zu verbessern. Im vom Europäischen Forschungsrat finanzierten Projekt nextDART wird eine neuartige Technologie entwickelt, die auf den Molekülen des Haupthistokompatibilitätskomplexes I basiert. Die Forschenden werden sich auf den Nachweis von T-Zell-Spezifitäten in biologischen Proben konzentrieren und die Antigenspezifität mit der Sequenz der T-Zell-Rezeptoren in Verbindung bringen. Die Technologie wird die Erkennung und Spezifität von T-Zell-Rezeptoren für bestimmte Epitope vorausberechnen und damit ein Mittel zur Prognose der Immunerkennung durch T-Zellen bieten.
Ziel
Our current ability to map T-cell reactivity to certain molecular patterns poorly matches the huge diversity of T-cell recognition in humans. Our immune system holds approximately 107 different T-cell populations patrolling our body to fight intruding pathogens. Current state-of-the-art T-cell detection enables the detection of 45 different T-cell specificities in a given sample. Therefore comprehensive analysis of T-cell recognition against intruding pathogens, auto-immune attacked tissues or cancer is virtually impossible.
To gain insight into immune recognition and allow careful target selection for disease intervention, also on a personalized basis, we need technologies that allow detection of vast numbers of different T-cell specificities with high sensitivity in small biological samples.
I propose here a new technology based on multimerised peptide-major histocompatibility complex I (MHC I) reagents that allow detection of >1000 different T-cell specificities with high sensitivity in small biological samples. I will use this new technology to gain insight into the T-cell recognition of cancer cells and specifically assess the impact of mutation-derived neo-epitopes on T cell-mediated cancer cell recognition.
A major advantage of this new technology relates to the ability of coupling the antigen specificity to the T-cell receptor sequence. This will enable us to retrieve information about T-cell receptor sequences coupled with their molecular recognition pattern, and develop a predictor of binding between T-cell receptors and specific epitopes. It will ultimately enable us to predict immune recognition based on T-cell receptor sequences, and has the potential to truly transform our understanding of T cell immunology.
Advances in our understanding of T cell immunology are leading to massive advances in the treatment of cancer. The technologies I propose to develop and validate will greatly aid this process and have application for all immune related diseases.
Wissenschaftliches Gebiet
- natural sciencesbiological sciencesgeneticsDNA
- medical and health sciencesclinical medicineoncologylung cancer
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesbasic medicineimmunologyimmunotherapy
- medical and health sciencesmedical biotechnologycells technologies
Programm/Programme
Thema/Themen
Finanzierungsplan
ERC-STG - Starting GrantGastgebende Einrichtung
2800 Kongens Lyngby
Dänemark