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Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model
SIMPLE SUMMARY: Treatment with chimeric antigen receptor (CAR)-T cells has improved the prognosis of patients with non-Hodgkin lymphoma (NHL) substantially. Yet, as up to 60% of patients eventually relapse, insights into factors determining treatment response are highly warranted. We used mathematic...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199881/ https://www.ncbi.nlm.nih.gov/pubmed/34205020 http://dx.doi.org/10.3390/cancers13112782 |
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author | Mueller-Schoell, Anna Puebla-Osorio, Nahum Michelet, Robin Green, Michael R. Künkele, Annette Huisinga, Wilhelm Strati, Paolo Chasen, Beth Neelapu, Sattva S. Yee, Cassian Kloft, Charlotte |
author_facet | Mueller-Schoell, Anna Puebla-Osorio, Nahum Michelet, Robin Green, Michael R. Künkele, Annette Huisinga, Wilhelm Strati, Paolo Chasen, Beth Neelapu, Sattva S. Yee, Cassian Kloft, Charlotte |
author_sort | Mueller-Schoell, Anna |
collection | PubMed |
description | SIMPLE SUMMARY: Treatment with chimeric antigen receptor (CAR)-T cells has improved the prognosis of patients with non-Hodgkin lymphoma (NHL) substantially. Yet, as up to 60% of patients eventually relapse, insights into factors determining treatment response are highly warranted. We used mathematical modeling to characterize typical and individual concentration–time profiles of four different CAR-T cell subtypes and tumor burden in 19 NHL patients and investigated patient-/therapy-related factors associated with poor survival. A low CAR-T cell maximum expansion capacity and no previous autologous stem cell transplantation were associated with a poor prognosis. We next translated our most important model parameter into a clinical composite score, which leverages but does not require the use of the model. Based on our clinical data, we propose a clinical composite score cut-off value for early survival prediction. Additional data will be needed to update and refine the developed model and the proposed clinical composite score cut-off value. ABSTRACT: Chimeric antigen receptor (CAR)-T cell therapy has revolutionized treatment of relapsed/refractory non-Hodgkin lymphoma (NHL). However, since 36–60% of patients relapse, early response prediction is crucial. We present a novel population quantitative systems pharmacology model, integrating literature knowledge on physiology, immunology, and adoptive cell therapy together with 133 CAR-T cell phenotype, 1943 cytokine, and 48 metabolic tumor measurements. The model well described post-infusion concentrations of four CAR-T cell phenotypes and CD19(+) metabolic tumor volume over 3 months after CAR-T cell infusion. Leveraging the model, we identified a low expansion subpopulation with significantly lower CAR-T cell expansion capacities amongst 19 NHL patients. Together with two patient-/therapy-related factors (autologous stem cell transplantation, CD4(+)/CD8(+) T cells), the low expansion subpopulation explained 2/3 of the interindividual variability in the CAR-T cell expansion capacities. Moreover, the low expansion subpopulation had poor prognosis as only 1/4 of the low expansion subpopulation compared to 2/3 of the reference population were still alive after 24 months. We translated the expansion capacities into a clinical composite score (CCS) of ‘Maximum naïve CAR-T cell concentrations/Baseline tumor burden’ ratio and propose a CCS(TN)-value > 0.00136 (cells·µL(−1)·mL(−1) as predictor for survival. Once validated in a larger cohort, the model will foster refining survival prediction and solutions to enhance NHL CAR-T cell therapy response. |
format | Online Article Text |
id | pubmed-8199881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81998812021-06-14 Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model Mueller-Schoell, Anna Puebla-Osorio, Nahum Michelet, Robin Green, Michael R. Künkele, Annette Huisinga, Wilhelm Strati, Paolo Chasen, Beth Neelapu, Sattva S. Yee, Cassian Kloft, Charlotte Cancers (Basel) Article SIMPLE SUMMARY: Treatment with chimeric antigen receptor (CAR)-T cells has improved the prognosis of patients with non-Hodgkin lymphoma (NHL) substantially. Yet, as up to 60% of patients eventually relapse, insights into factors determining treatment response are highly warranted. We used mathematical modeling to characterize typical and individual concentration–time profiles of four different CAR-T cell subtypes and tumor burden in 19 NHL patients and investigated patient-/therapy-related factors associated with poor survival. A low CAR-T cell maximum expansion capacity and no previous autologous stem cell transplantation were associated with a poor prognosis. We next translated our most important model parameter into a clinical composite score, which leverages but does not require the use of the model. Based on our clinical data, we propose a clinical composite score cut-off value for early survival prediction. Additional data will be needed to update and refine the developed model and the proposed clinical composite score cut-off value. ABSTRACT: Chimeric antigen receptor (CAR)-T cell therapy has revolutionized treatment of relapsed/refractory non-Hodgkin lymphoma (NHL). However, since 36–60% of patients relapse, early response prediction is crucial. We present a novel population quantitative systems pharmacology model, integrating literature knowledge on physiology, immunology, and adoptive cell therapy together with 133 CAR-T cell phenotype, 1943 cytokine, and 48 metabolic tumor measurements. The model well described post-infusion concentrations of four CAR-T cell phenotypes and CD19(+) metabolic tumor volume over 3 months after CAR-T cell infusion. Leveraging the model, we identified a low expansion subpopulation with significantly lower CAR-T cell expansion capacities amongst 19 NHL patients. Together with two patient-/therapy-related factors (autologous stem cell transplantation, CD4(+)/CD8(+) T cells), the low expansion subpopulation explained 2/3 of the interindividual variability in the CAR-T cell expansion capacities. Moreover, the low expansion subpopulation had poor prognosis as only 1/4 of the low expansion subpopulation compared to 2/3 of the reference population were still alive after 24 months. We translated the expansion capacities into a clinical composite score (CCS) of ‘Maximum naïve CAR-T cell concentrations/Baseline tumor burden’ ratio and propose a CCS(TN)-value > 0.00136 (cells·µL(−1)·mL(−1) as predictor for survival. Once validated in a larger cohort, the model will foster refining survival prediction and solutions to enhance NHL CAR-T cell therapy response. MDPI 2021-06-03 /pmc/articles/PMC8199881/ /pubmed/34205020 http://dx.doi.org/10.3390/cancers13112782 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mueller-Schoell, Anna Puebla-Osorio, Nahum Michelet, Robin Green, Michael R. Künkele, Annette Huisinga, Wilhelm Strati, Paolo Chasen, Beth Neelapu, Sattva S. Yee, Cassian Kloft, Charlotte Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title | Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title_full | Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title_fullStr | Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title_full_unstemmed | Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title_short | Early Survival Prediction Framework in CD19-Specific CAR-T Cell Immunotherapy Using a Quantitative Systems Pharmacology Model |
title_sort | early survival prediction framework in cd19-specific car-t cell immunotherapy using a quantitative systems pharmacology model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199881/ https://www.ncbi.nlm.nih.gov/pubmed/34205020 http://dx.doi.org/10.3390/cancers13112782 |
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