Ontology highlight
ABSTRACT: Objective
While T lymphocytes have been employed as a cancer immunotherapy, the development of effective and specific T-cell-based therapeutics remains challenging. A key obstacle is the difficulty in identifying T cells reactive to cancer-associated antigens. The objective of this research was to develop a versatile platform for single cell analysis and isolation that can be applied in immunology research and clinical therapy development.Methods
An automated microscopy and cell sorting system was developed to track the proliferative behavior of single-cell human primary CD4+ lymphocytes in response to stimulation using allogeneic lymphoblastoid feeder cells.Results
The system identified single human T lymphocytes with a sensitivity of 98% and specificity of 99% and possessed a cell collection efficiency of 86%. Time-lapse imaging simultaneously tracked 4,534 alloreactive T cells on a single array; 19% of the arrayed cells formed colonies of ≥2 cells. From the array, 130 clonal colonies were isolated and 7 grew to colony sizes of >10,000 cells, consistent with the known proliferative capacity of T cells in vitro and their tendency to become exhausted with prolonged stimulation. The isolated colonies underwent ELISA assay to detect interferon-γ secretion and Sanger sequencing to determine T cell receptor β sequences with a 100% success rate.Conclusion
The platform is capable of both identification and isolation of proliferative T cells in an automated manner.Significance
This novel technology enables the identification of TCR sequences based on T cell proliferation which is expected to speed the development of future cancer immunotherapies.
SUBMITTER: LaBelle CA
PROVIDER: S-EPMC7247929 | biostudies-literature |
REPOSITORIES: biostudies-literature