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Massively parallel interrogation and mining of natively paired human TCRαβ repertoires

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...

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Autores principales: Spindler, Matthew J., Nelson, Ayla L., Wagner, Ellen K., Oppermans, Natasha, Bridgeman, John S., Heather, James M., Adler, Adam S., Asensio, Michael A., Edgar, Robert C., Lim, Yoong Wearn, Meyer, Everett H., Hawkins, Robert E., Cobbold, Mark, Johnson, David S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224336/
https://www.ncbi.nlm.nih.gov/pubmed/32393905
http://dx.doi.org/10.1038/s41587-020-0438-y
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author Spindler, Matthew J.
Nelson, Ayla L.
Wagner, Ellen K.
Oppermans, Natasha
Bridgeman, John S.
Heather, James M.
Adler, Adam S.
Asensio, Michael A.
Edgar, Robert C.
Lim, Yoong Wearn
Meyer, Everett H.
Hawkins, Robert E.
Cobbold, Mark
Johnson, David S.
author_facet Spindler, Matthew J.
Nelson, Ayla L.
Wagner, Ellen K.
Oppermans, Natasha
Bridgeman, John S.
Heather, James M.
Adler, Adam S.
Asensio, Michael A.
Edgar, Robert C.
Lim, Yoong Wearn
Meyer, Everett H.
Hawkins, Robert E.
Cobbold, Mark
Johnson, David S.
author_sort Spindler, Matthew J.
collection PubMed
description 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 uses massively parallel microfluidics to generate libraries of natively paired, full-length TCRαβ clones, from millions of primary T cells, which are then expressed in Jurkat cells. The TCRαβ-Jurkat libraries enable repeated screening and panning for antigen-reactive TCRs using peptide:MHC binding and cellular activation. We captured >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 (TIL) sample from a melanoma patient and identified several tumor-specific TCRs, which, after expression in primary T cells, led to tumor cell killing.
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spelling pubmed-72243362020-09-16 Massively parallel interrogation and mining of natively paired human TCRαβ repertoires Spindler, Matthew J. Nelson, Ayla L. Wagner, Ellen K. Oppermans, Natasha Bridgeman, John S. Heather, James M. Adler, Adam S. Asensio, Michael A. Edgar, Robert C. Lim, Yoong Wearn Meyer, Everett H. Hawkins, Robert E. Cobbold, Mark Johnson, David S. Nat Biotechnol Article 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 uses massively parallel microfluidics to generate libraries of natively paired, full-length TCRαβ clones, from millions of primary T cells, which are then expressed in Jurkat cells. The TCRαβ-Jurkat libraries enable repeated screening and panning for antigen-reactive TCRs using peptide:MHC binding and cellular activation. We captured >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 (TIL) sample from a melanoma patient and identified several tumor-specific TCRs, which, after expression in primary T cells, led to tumor cell killing. 2020-03-16 2020-05 /pmc/articles/PMC7224336/ /pubmed/32393905 http://dx.doi.org/10.1038/s41587-020-0438-y Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Spindler, Matthew J.
Nelson, Ayla L.
Wagner, Ellen K.
Oppermans, Natasha
Bridgeman, John S.
Heather, James M.
Adler, Adam S.
Asensio, Michael A.
Edgar, Robert C.
Lim, Yoong Wearn
Meyer, Everett H.
Hawkins, Robert E.
Cobbold, Mark
Johnson, David S.
Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title_full Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title_fullStr Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title_full_unstemmed Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title_short Massively parallel interrogation and mining of natively paired human TCRαβ repertoires
title_sort massively parallel interrogation and mining of natively paired human tcrαβ repertoires
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224336/
https://www.ncbi.nlm.nih.gov/pubmed/32393905
http://dx.doi.org/10.1038/s41587-020-0438-y
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