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T cell receptor sequence clustering and antigen specificity
There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473833/ https://www.ncbi.nlm.nih.gov/pubmed/32952933 http://dx.doi.org/10.1016/j.csbj.2020.06.041 |
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author | Vujovic, Milena Degn, Kristine Fredlund Marin, Frederikke Isa Schaap-Johansen, Anna-Lisa Chain, Benny Andresen, Thomas Lars Kaplinsky, Joseph Marcatili, Paolo |
author_facet | Vujovic, Milena Degn, Kristine Fredlund Marin, Frederikke Isa Schaap-Johansen, Anna-Lisa Chain, Benny Andresen, Thomas Lars Kaplinsky, Joseph Marcatili, Paolo |
author_sort | Vujovic, Milena |
collection | PubMed |
description | There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering. |
format | Online Article Text |
id | pubmed-7473833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-74738332020-09-17 T cell receptor sequence clustering and antigen specificity Vujovic, Milena Degn, Kristine Fredlund Marin, Frederikke Isa Schaap-Johansen, Anna-Lisa Chain, Benny Andresen, Thomas Lars Kaplinsky, Joseph Marcatili, Paolo Comput Struct Biotechnol J Review Article There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering. Research Network of Computational and Structural Biotechnology 2020-08-05 /pmc/articles/PMC7473833/ /pubmed/32952933 http://dx.doi.org/10.1016/j.csbj.2020.06.041 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Article Vujovic, Milena Degn, Kristine Fredlund Marin, Frederikke Isa Schaap-Johansen, Anna-Lisa Chain, Benny Andresen, Thomas Lars Kaplinsky, Joseph Marcatili, Paolo T cell receptor sequence clustering and antigen specificity |
title | T cell receptor sequence clustering and antigen specificity |
title_full | T cell receptor sequence clustering and antigen specificity |
title_fullStr | T cell receptor sequence clustering and antigen specificity |
title_full_unstemmed | T cell receptor sequence clustering and antigen specificity |
title_short | T cell receptor sequence clustering and antigen specificity |
title_sort | t cell receptor sequence clustering and antigen specificity |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473833/ https://www.ncbi.nlm.nih.gov/pubmed/32952933 http://dx.doi.org/10.1016/j.csbj.2020.06.041 |
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