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Next generation Detection of Antigen Responsive T cells

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 bo... ver más

31/05/2021

TECHNICAL UNIVERSI...

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

DANMARKS TEKNISKE UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-05-31

ERC-StG-2015: ERC Starting Grant

I+D

Cerrada hace 9 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

TECHNICAL UNIVERSITY OF DENM...

1.50M€ | Lider

BODEGA MATARROMERA

1.05M€ | Participante

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Duración del proyecto: 60 meses Fecha Inicio: 2016-05-10
Fecha Fin: 2021-05-31

Líder del proyecto

DANMARKS TEKNISKE UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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