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The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy
Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059581/ https://www.ncbi.nlm.nih.gov/pubmed/33757357 http://dx.doi.org/10.1098/rspb.2021.0229 |
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author | Kimmel, Gregory J. Locke, Frederick L. Altrock, Philipp M. |
author_facet | Kimmel, Gregory J. Locke, Frederick L. Altrock, Philipp M. |
author_sort | Kimmel, Gregory J. |
collection | PubMed |
description | Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop a mathematical model of T cell–tumour cell interactions and demonstrate that expansion can be explained by immune reconstitution dynamics after LD and competition among T cells. CAR T cells rapidly grow and engage tumour cells but experience an emerging growth rate disadvantage compared to normal T cells. Since tumour eradication is deterministically unstable in our model, we define cure as a stochastic event, which, even when likely, can occur at variable times. However, we show that variability in timing is largely determined by patient variability. While cure events impacted by these fluctuations occur early and are narrowly distributed, progression events occur late and are more widely distributed in time. We parameterized our model using population-level CAR T cell and tumour data over time and compare our predictions with progression-free survival rates. We find that therapy could be improved by optimizing the tumour-killing rate and the CAR T cells' ability to adapt, as quantified by their carrying capacity. Our tumour extinction model can be leveraged to examine why therapy works in some patients but not others, and to better understand the interplay of deterministic and stochastic effects on outcomes. For example, our model implies that LD before a second CAR T injection is necessary. |
format | Online Article Text |
id | pubmed-8059581 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-80595812021-05-15 The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy Kimmel, Gregory J. Locke, Frederick L. Altrock, Philipp M. Proc Biol Sci Ecology Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop a mathematical model of T cell–tumour cell interactions and demonstrate that expansion can be explained by immune reconstitution dynamics after LD and competition among T cells. CAR T cells rapidly grow and engage tumour cells but experience an emerging growth rate disadvantage compared to normal T cells. Since tumour eradication is deterministically unstable in our model, we define cure as a stochastic event, which, even when likely, can occur at variable times. However, we show that variability in timing is largely determined by patient variability. While cure events impacted by these fluctuations occur early and are narrowly distributed, progression events occur late and are more widely distributed in time. We parameterized our model using population-level CAR T cell and tumour data over time and compare our predictions with progression-free survival rates. We find that therapy could be improved by optimizing the tumour-killing rate and the CAR T cells' ability to adapt, as quantified by their carrying capacity. Our tumour extinction model can be leveraged to examine why therapy works in some patients but not others, and to better understand the interplay of deterministic and stochastic effects on outcomes. For example, our model implies that LD before a second CAR T injection is necessary. The Royal Society 2021-03-31 2021-03-24 /pmc/articles/PMC8059581/ /pubmed/33757357 http://dx.doi.org/10.1098/rspb.2021.0229 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Ecology Kimmel, Gregory J. Locke, Frederick L. Altrock, Philipp M. The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title | The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title_full | The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title_fullStr | The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title_full_unstemmed | The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title_short | The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy |
title_sort | roles of t cell competition and stochastic extinction events in chimeric antigen receptor t cell therapy |
topic | Ecology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059581/ https://www.ncbi.nlm.nih.gov/pubmed/33757357 http://dx.doi.org/10.1098/rspb.2021.0229 |
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