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A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time-course of tumour responses to immune-checkpoint inhibitors. The model takes into account intrinsic tumour-growth rates,...

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Autores principales: Butner, Joseph D, Wang, Zhihui, Elganainy, Dalia, Al Feghali, Karine A, Plodinec, Marija, Calin, George A, Dogra, Prashant, Nizzero, Sara, Ramírez, Javier Ruiz, Martin, Geoffrey V, Tawbi, Hussein A, Chung, Caroline, Koay, Eugene J, Welsh, James W, Hong, David S, Cristini, Vittorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669771/
https://www.ncbi.nlm.nih.gov/pubmed/33398132
http://dx.doi.org/10.1038/s41551-020-00662-0
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author Butner, Joseph D
Wang, Zhihui
Elganainy, Dalia
Al Feghali, Karine A
Plodinec, Marija
Calin, George A
Dogra, Prashant
Nizzero, Sara
Ramírez, Javier Ruiz
Martin, Geoffrey V
Tawbi, Hussein A
Chung, Caroline
Koay, Eugene J
Welsh, James W
Hong, David S
Cristini, Vittorio
author_facet Butner, Joseph D
Wang, Zhihui
Elganainy, Dalia
Al Feghali, Karine A
Plodinec, Marija
Calin, George A
Dogra, Prashant
Nizzero, Sara
Ramírez, Javier Ruiz
Martin, Geoffrey V
Tawbi, Hussein A
Chung, Caroline
Koay, Eugene J
Welsh, James W
Hong, David S
Cristini, Vittorio
author_sort Butner, Joseph D
collection PubMed
description A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time-course of tumour responses to immune-checkpoint inhibitors. The model takes into account intrinsic tumour-growth rates, the rates of immune activation and of tumour–immune-cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug–cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug–cancer sensitivities in individual patients.
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spelling pubmed-86697712021-12-14 A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden Butner, Joseph D Wang, Zhihui Elganainy, Dalia Al Feghali, Karine A Plodinec, Marija Calin, George A Dogra, Prashant Nizzero, Sara Ramírez, Javier Ruiz Martin, Geoffrey V Tawbi, Hussein A Chung, Caroline Koay, Eugene J Welsh, James W Hong, David S Cristini, Vittorio Nat Biomed Eng Article A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time-course of tumour responses to immune-checkpoint inhibitors. The model takes into account intrinsic tumour-growth rates, the rates of immune activation and of tumour–immune-cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug–cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug–cancer sensitivities in individual patients. 2021-01-04 2021-04 /pmc/articles/PMC8669771/ /pubmed/33398132 http://dx.doi.org/10.1038/s41551-020-00662-0 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Butner, Joseph D
Wang, Zhihui
Elganainy, Dalia
Al Feghali, Karine A
Plodinec, Marija
Calin, George A
Dogra, Prashant
Nizzero, Sara
Ramírez, Javier Ruiz
Martin, Geoffrey V
Tawbi, Hussein A
Chung, Caroline
Koay, Eugene J
Welsh, James W
Hong, David S
Cristini, Vittorio
A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title_full A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title_fullStr A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title_full_unstemmed A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title_short A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
title_sort mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669771/
https://www.ncbi.nlm.nih.gov/pubmed/33398132
http://dx.doi.org/10.1038/s41551-020-00662-0
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