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Article ; Online: Very rapid cloning, expression and identifying specificity of T-cell receptors for T-cell engineering.

Zong, Shan / Mi, Tiejuan / Flores, Leo G / Alpert, Amir / Olivares, Simon / Patel, Krina / Maiti, Sourindra / Mcnamara, George / Cooper, Laurence J N / Torikai, Hiroki

PloS one

2020  Volume 15, Issue 2, Page(s) e0228112

Abstract: Neoantigens can be predicted and in some cases identified using the data obtained from the whole exome sequencing and transcriptome sequencing of tumor cells. These sequencing data can be coupled with single-cell RNA sequencing for the direct ... ...

Abstract Neoantigens can be predicted and in some cases identified using the data obtained from the whole exome sequencing and transcriptome sequencing of tumor cells. These sequencing data can be coupled with single-cell RNA sequencing for the direct interrogation of the transcriptome, surfaceome, and pairing of αβ T-cell receptors (TCRαβ) from hundreds of single T cells. Using these 2 large datasets, we established a platform for identifying antigens recognized by TCRαβs obtained from single T cells. Our approach is based on the rapid expression of cloned TCRαβ genes as Sleeping Beauty transposons and the determination of the introduced TCRαβs' antigen specificity and avidity using a reporter cell line. The platform enables the very rapid identification of tumor-reactive TCRs for the bioengineering of T cells with redirected specificity.
MeSH term(s) Cell Engineering/methods ; Cloning, Molecular/methods ; Gene Expression ; Gene Library ; Genes, MHC Class I/genetics ; Genes, MHC Class II/genetics ; HEK293 Cells ; Humans ; Kinetics ; Receptors, Antigen, T-Cell/genetics ; Receptors, Antigen, T-Cell, alpha-beta/genetics ; T-Lymphocytes/cytology ; T-Lymphocytes/metabolism
Chemical Substances Receptors, Antigen, T-Cell ; Receptors, Antigen, T-Cell, alpha-beta
Language English
Publishing date 2020-02-10
Publishing country United States
Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN 1932-6203
ISSN (online) 1932-6203
DOI 10.1371/journal.pone.0228112
Database MEDical Literature Analysis and Retrieval System OnLINE

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