Massively parallel interrogation and mining of natively paired human TCRαβ repertoires

被引:0
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作者
Matthew J. Spindler
Ayla L. Nelson
Ellen K. Wagner
Natasha Oppermans
John S. Bridgeman
James M. Heather
Adam S. Adler
Michael A. Asensio
Robert C. Edgar
Yoong Wearn Lim
Everett H. Meyer
Robert E. Hawkins
Mark Cobbold
David S. Johnson
机构
[1] GigaMune,Division of Cancer Sciences
[2] Inc.,Stanford Diabetes Research Center
[3] University of Manchester,Stanford Cancer Institute
[4] Immetacyte Ltd,undefined
[5] Massachusetts General Hospital Cancer Center and Department of Medicine,undefined
[6] Harvard Medical School,undefined
[7] Boston,undefined
[8] Stanford University Medical Center,undefined
[9] Stanford University Medical Center,undefined
[10] AstraZeneca,undefined
来源
Nature Biotechnology | 2020年 / 38卷
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摘要
T cells engineered to express antigen-specific T cell receptors (TCRs) are potent therapies for viral infections and cancer. However, efficient identification of clinical candidate TCRs is complicated by the size and complexity of T cell repertoires and the challenges of working with primary T cells. Here we present a high-throughput method to identify TCRs with high functional avidity from diverse human T cell repertoires. The approach used massively parallel microfluidics to generate libraries of natively paired, full-length TCRαβ clones, from millions of primary T cells, which were then expressed in Jurkat cells. The TCRαβ–Jurkat libraries enabled repeated screening and panning for antigen-reactive TCRs using peptide major histocompatibility complex binding and cellular activation. We captured more than 2.9 million natively paired TCRαβ clonotypes from six healthy human donors and identified rare (<0.001% frequency) viral-antigen-reactive TCRs. We also mined a tumor-infiltrating lymphocyte sample from a patient with melanoma and identified several tumor-specific TCRs, which, after expression in primary T cells, led to tumor cell killing.
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页码:609 / 619
页数:10
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