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Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses

Immunotherapies have revolutionized cancer treatment. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. However, the majority of treated patients do not respond. Understanding immune mechanisms that underlie responsiveness to ICT will help...

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Autores principales: Kidman, Joel, Principe, Nicola, Watson, Mark, Lassmann, Timo, Holt, Robert A., Nowak, Anna K., Lesterhuis, Willem Joost, Lake, Richard A., Chee, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591700/
https://www.ncbi.nlm.nih.gov/pubmed/33163002
http://dx.doi.org/10.3389/fimmu.2020.587014
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author Kidman, Joel
Principe, Nicola
Watson, Mark
Lassmann, Timo
Holt, Robert A.
Nowak, Anna K.
Lesterhuis, Willem Joost
Lake, Richard A.
Chee, Jonathan
author_facet Kidman, Joel
Principe, Nicola
Watson, Mark
Lassmann, Timo
Holt, Robert A.
Nowak, Anna K.
Lesterhuis, Willem Joost
Lake, Richard A.
Chee, Jonathan
author_sort Kidman, Joel
collection PubMed
description Immunotherapies have revolutionized cancer treatment. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. However, the majority of treated patients do not respond. Understanding immune mechanisms that underlie responsiveness to ICT will help identify predictive biomarkers of response and develop treatments to convert non-responding patients to responding ones. ICT primarily acts at the level of adaptive immunity. The specificity of adaptive immune cells, such as T and B cells, is determined by antigen-specific receptors. T cell repertoires can be comprehensively profiled by high-throughput sequencing at the bulk and single-cell level. T cell receptor (TCR) sequencing allows for sensitive tracking of dynamic changes in antigen-specific T cells at the clonal level, giving unprecedented insight into the mechanisms by which ICT alters T cell responses. Here, we review how the repertoire influences response to ICT and conversely how ICT affects repertoire diversity. We will also explore how changes to the repertoire in different anatomical locations can better correlate and perhaps predict treatment outcome. We discuss the advantages and limitations of current metrics used to characterize and represent TCR repertoire diversity. Discovery of predictive biomarkers could lie in novel analysis approaches, such as network analysis of amino acids similarities between TCR sequences. Single-cell sequencing is a breakthrough technology that can link phenotype with specificity, identifying T cell clones that are crucial for successful ICT. The field of immuno-sequencing is rapidly developing and cross-disciplinary efforts are required to maximize the analysis, application, and validation of sequencing data. Unravelling the dynamic behavior of the TCR repertoire during ICT will be highly valuable for tracking and understanding anti-tumor immunity, biomarker discovery, and ultimately for the development of novel strategies to improve patient outcomes.
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spelling pubmed-75917002020-11-05 Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses Kidman, Joel Principe, Nicola Watson, Mark Lassmann, Timo Holt, Robert A. Nowak, Anna K. Lesterhuis, Willem Joost Lake, Richard A. Chee, Jonathan Front Immunol Immunology Immunotherapies have revolutionized cancer treatment. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. However, the majority of treated patients do not respond. Understanding immune mechanisms that underlie responsiveness to ICT will help identify predictive biomarkers of response and develop treatments to convert non-responding patients to responding ones. ICT primarily acts at the level of adaptive immunity. The specificity of adaptive immune cells, such as T and B cells, is determined by antigen-specific receptors. T cell repertoires can be comprehensively profiled by high-throughput sequencing at the bulk and single-cell level. T cell receptor (TCR) sequencing allows for sensitive tracking of dynamic changes in antigen-specific T cells at the clonal level, giving unprecedented insight into the mechanisms by which ICT alters T cell responses. Here, we review how the repertoire influences response to ICT and conversely how ICT affects repertoire diversity. We will also explore how changes to the repertoire in different anatomical locations can better correlate and perhaps predict treatment outcome. We discuss the advantages and limitations of current metrics used to characterize and represent TCR repertoire diversity. Discovery of predictive biomarkers could lie in novel analysis approaches, such as network analysis of amino acids similarities between TCR sequences. Single-cell sequencing is a breakthrough technology that can link phenotype with specificity, identifying T cell clones that are crucial for successful ICT. The field of immuno-sequencing is rapidly developing and cross-disciplinary efforts are required to maximize the analysis, application, and validation of sequencing data. Unravelling the dynamic behavior of the TCR repertoire during ICT will be highly valuable for tracking and understanding anti-tumor immunity, biomarker discovery, and ultimately for the development of novel strategies to improve patient outcomes. Frontiers Media S.A. 2020-10-14 /pmc/articles/PMC7591700/ /pubmed/33163002 http://dx.doi.org/10.3389/fimmu.2020.587014 Text en Copyright © 2020 Kidman, Principe, Watson, Lassmann, Holt, Nowak, Lesterhuis, Lake and Chee http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Kidman, Joel
Principe, Nicola
Watson, Mark
Lassmann, Timo
Holt, Robert A.
Nowak, Anna K.
Lesterhuis, Willem Joost
Lake, Richard A.
Chee, Jonathan
Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title_full Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title_fullStr Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title_full_unstemmed Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title_short Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses
title_sort characteristics of tcr repertoire associated with successful immune checkpoint therapy responses
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591700/
https://www.ncbi.nlm.nih.gov/pubmed/33163002
http://dx.doi.org/10.3389/fimmu.2020.587014
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