4.6 Article

Assay and Isolation of Single Proliferating CD4+Lymphocytes Using an Automated Microraft Array Platform

Journal

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 67, Issue 8, Pages 2166-2175

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2019.2956081

Keywords

Immune system; Media; Optical filters; Magnetic resonance imaging; Microscopy; Sorting; Cancer; Microarrays; lymphocyte; proliferation; cell sorting; immunology

Funding

  1. National Institute of Health (NIH) [R42 AI126905, R01 EY024556]

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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-gamma secretion and Sanger sequencing to determine T cell receptor beta 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.

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