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Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential
Expansion of an initial population of T cells is essential for cellular immunotherapy. In Chronic Lymphocytic Leukemia (CLL), expansion is often complicated by lack of T cell proliferation, as these cells frequently show signs of exhaustion. This report seeks to identify specific biomarkers or measu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063612/ https://www.ncbi.nlm.nih.gov/pubmed/33898440 http://dx.doi.org/10.3389/fcell.2021.648925 |
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author | Lee, Joanne H. Shao, Shuai Kim, Michelle Fernandes, Stacey M. Brown, Jennifer R. Kam, Lance C. |
author_facet | Lee, Joanne H. Shao, Shuai Kim, Michelle Fernandes, Stacey M. Brown, Jennifer R. Kam, Lance C. |
author_sort | Lee, Joanne H. |
collection | PubMed |
description | Expansion of an initial population of T cells is essential for cellular immunotherapy. In Chronic Lymphocytic Leukemia (CLL), expansion is often complicated by lack of T cell proliferation, as these cells frequently show signs of exhaustion. This report seeks to identify specific biomarkers or measures of cell function that capture the proliferative potential of a starting population of cells. Mixed CD4+/CD8+ T cells from healthy donors and individuals previously treated for CLL were characterized on the basis of proliferative potential and in vitro cellular functions. Single-factor analysis found little correlation between the number of populations doublings reached during expansion and either Rai stage (a clinical measure of CLL spread) or PD-1 expression. However, inclusion of in vitro IL-2 secretion and the propensity of cells to align onto micropatterned features of activating proteins as factors identified three distinct groups of donors. Notably, these group assignments provided an elegant separation of donors with regards to proliferative potential. Furthermore, these groups exhibited different motility characteristics, suggesting a mechanism that underlies changes in proliferative potential. This study describes a new set of functional readouts that augment surface marker panels to better predict expansion outcomes and clinical prognosis. |
format | Online Article Text |
id | pubmed-8063612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80636122021-04-24 Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential Lee, Joanne H. Shao, Shuai Kim, Michelle Fernandes, Stacey M. Brown, Jennifer R. Kam, Lance C. Front Cell Dev Biol Cell and Developmental Biology Expansion of an initial population of T cells is essential for cellular immunotherapy. In Chronic Lymphocytic Leukemia (CLL), expansion is often complicated by lack of T cell proliferation, as these cells frequently show signs of exhaustion. This report seeks to identify specific biomarkers or measures of cell function that capture the proliferative potential of a starting population of cells. Mixed CD4+/CD8+ T cells from healthy donors and individuals previously treated for CLL were characterized on the basis of proliferative potential and in vitro cellular functions. Single-factor analysis found little correlation between the number of populations doublings reached during expansion and either Rai stage (a clinical measure of CLL spread) or PD-1 expression. However, inclusion of in vitro IL-2 secretion and the propensity of cells to align onto micropatterned features of activating proteins as factors identified three distinct groups of donors. Notably, these group assignments provided an elegant separation of donors with regards to proliferative potential. Furthermore, these groups exhibited different motility characteristics, suggesting a mechanism that underlies changes in proliferative potential. This study describes a new set of functional readouts that augment surface marker panels to better predict expansion outcomes and clinical prognosis. Frontiers Media S.A. 2021-04-09 /pmc/articles/PMC8063612/ /pubmed/33898440 http://dx.doi.org/10.3389/fcell.2021.648925 Text en Copyright © 2021 Lee, Shao, Kim, Fernandes, Brown and Kam. https://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 | Cell and Developmental Biology Lee, Joanne H. Shao, Shuai Kim, Michelle Fernandes, Stacey M. Brown, Jennifer R. Kam, Lance C. Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title | Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title_full | Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title_fullStr | Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title_full_unstemmed | Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title_short | Multi-Factor Clustering Incorporating Cell Motility Predicts T Cell Expansion Potential |
title_sort | multi-factor clustering incorporating cell motility predicts t cell expansion potential |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063612/ https://www.ncbi.nlm.nih.gov/pubmed/33898440 http://dx.doi.org/10.3389/fcell.2021.648925 |
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