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Mapping the Functional Landscape of T Cell Receptor Repertoire by Single T Cell Transcriptomics

Many experimental and bioinformatics approaches have been developed to characterize the human T cell receptor (TCR) repertoire. However, the unknown functional relevance of TCR profiling significantly hinders unbiased interpretation of the biology of T cells. To address this inadequacy, we developed...

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Detalles Bibliográficos
Autores principales: Zhang, Ze, Xiong, Danyi, Wang, Xinlei, Liu, Hongyu, Wang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7799492/
https://www.ncbi.nlm.nih.gov/pubmed/33408405
http://dx.doi.org/10.1038/s41592-020-01020-3
Descripción
Sumario:Many experimental and bioinformatics approaches have been developed to characterize the human T cell receptor (TCR) repertoire. However, the unknown functional relevance of TCR profiling significantly hinders unbiased interpretation of the biology of T cells. To address this inadequacy, we developed tessa, a tool to integrate TCRs with gene expression of T cells, in order to estimate the effect that TCRs confer upon the phenotypes of T cells. Tessa leveraged techniques combining single cell RNA-sequencing with TCR-sequencing. We validated tessa and showed its superiority over existing approaches that investigate only the TCR sequences. With tessa, we demonstrated that TCR similarity constrains the phenotypes of T cells to be similar, and dictates a gradient in antigen targeting efficiency of T cell clonotypes with convergent TCRs. We showed this constraint could predict a functional dichotomization of T cells post-immunotherapy treatment, and is weakened in tumor contexts.