Project description
Predicting the binding specificity of T cells against cancer antigens
T lymphocytes are key cells of the immune system that recognise antigens on infected cells and directly kill them or prime other cells to mount an immune response. However, many aspects regarding the mechanisms of T cell-mediated immunity remain unresolved. The EU-funded MT-PoINT project aims to understand the binding specificity of T cells. Researchers will analyse sequencing data to identify patterns predictive of the interaction of the T cell receptor with a given antigenic epitope. Results will significantly improve the design and development of personalised immunotherapies involving engineered T cells.
Objective
T cells are a key element of the human immune system. Upon binding to antigenic peptides (called T cell epitopes), T cells can induce the death of infected cells or prime and regulate other immune cells. In cancer immunotherapy treatments, T cells are genetically re-engineered to recognize cancer epitopes and destroy malignant cells. Unfortunately, it still remains challenging to determine which T cells can target a specific epitope, both from a computational and experimental point of view. This limits mechanistic understanding of T-cell-mediated immunity and translational applications for disease treatments.
Thanks to advances in high-throughput sequencing technologies, sequence data of T cells coupled with their cognate epitopes are accumulating at an unprecedented pace, offering unique opportunities to develop data-driven T cell-epitope interaction predictors.
The goal of the MT-PoINT project (Motif in T cells for the Prediction of INTeractions) is to identify patterns in T cells sequences that underlie the binding specificity, interpret them at the structural level, and to develop sequence-based predictors of T cell-epitope interactions (Aim1) with a special focus on T cells targeting cancer epitopes (Aim2). My project will capitalize on a unique dataset of publicly available and in-house generated data that was not available in previous studies, and T cell sequence data from cancer patients of Lausanne University Hospital will allow me to benchmark the in-silico predictors in a clinically relevant setting.
Accurate predictions of TCR-epitope interactions can narrow down the list of T cell candidates for personalized cancer immunotherapies, and significantly accelerate cancer immunotherapy clinical developments.
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Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
1015 LAUSANNE
Switzerland