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Real-time activation profiles of a single T cell arrays following controlled interaction with antigen-presenting cells

Authors :
Desalvo, Anna
Elliott, Timothy
Morgan, Hywel
James, Edward
Publication Year :
2019
Publisher :
University of Southampton, 2019.

Abstract

The aim of this project was to develop a new microdevice to allow precise control of cellcell interactions, and to apply it to measure T cell signalling in arrays of single cells in realtime after stimulation by live antigen presenting cells. The specific T cell responses which underlie effective immunotherapy of cancer are mediated via cell-cell interactions and the formation of immune synapses. However, methods to study these interactions are limited by lack of control over single cell pairing and analysis methods. This project describes a new approach to track the activation profile of cytotoxic T cells against tumour cells in a high-throughput manner. A simple yet effective mechanism to pair the single T cells with antigen presenting cells was optimized to study cell-cell contact in a time-controlled manner. The cell-trap array is an open system consisting of thousands of microwells cast in an agarose block, which is biocompatible and permeable to nutrients allowing functional observations on viable cells to be carried out over a number of hours. T cells can be singularly isolated in the wells via passive sedimentation and size exclusion, achieving up to 90% occupancy. Activation profiles of thousands of single CD8+ cells could be screened in the same field of view using calcium-chelating fluorophore dyes to measure the early stages of T cell signalling. Custom software was developed to process experimental data and allow rapid detection of individual cells with the strongest activation signals defined by several different criteria. This capability could be used in future to identify and characterise single T-cells that have especially high propensity to be activated by immunotherapy such as vaccination or checkpoint blockade, in preclinical animal models and biopsy samples from human cancer patients.

Subjects

Subjects :
616.07

Details

Language :
English
Database :
British Library EThOS
Publication Type :
Dissertation/ Thesis
Accession number :
edsble.800796
Document Type :
Electronic Thesis or Dissertation