Project description
Predicting antigen recognition by T-cells
Our immune system comprises several T-cell subpopulations, each with a unique profile and function. There is great interest in T-cell recognition in relation to pathogens and cancer antigens for improved disease diagnosis. Funded by the European Research Council, the nextDART project will develop a novel technology based on the major histocompatibility complex I molecules. Researchers will focus on the detection of T-cell specificities in biological samples, and associate antigen specificity with the sequence of T-cell receptors. The technology will predict the recognition and specificity of T-cell receptors for specific epitopes, offering a means to forecast immune recognition by T-cells.
Objective
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.
Fields of science
- natural sciencesbiological sciencesgeneticsDNA
- medical and health sciencesclinical medicineoncologylung cancer
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesbasic medicineimmunologyimmunotherapy
- medical and health sciencesmedical biotechnologycells technologies
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting GrantHost institution
2800 Kongens Lyngby
Denmark