CAR T cell therapy in B-cell acute lymphoblastic leukaemia: Insights from mathematical models

•A mathematical model of leukaemia response to CAR-T cell treatment is built and studied.•Tumour relapse is a dynamical phenomenon and can be controlled.•The mathematical model allows obtaining a formula for the relapse time.•Persistence of the disease depends on the generation of B-cells in the bon...

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Veröffentlicht in:Communications in nonlinear science & numerical simulation 2021-03, Vol.94, p.105570, Article 105570
Hauptverfasser: León-Triana, Odelaisy, Sabir, Soukaina, Calvo, Gabriel F., Belmonte-Beitia, Juan, Chulián, Salvador, Martínez-Rubio, Álvaro, Rosa, María, Pérez-Martínez, Antonio, Ramirez-Orellana, Manuel, Pérez-García, Víctor M.
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creator León-Triana, Odelaisy
Sabir, Soukaina
Calvo, Gabriel F.
Belmonte-Beitia, Juan
Chulián, Salvador
Martínez-Rubio, Álvaro
Rosa, María
Pérez-Martínez, Antonio
Ramirez-Orellana, Manuel
Pérez-García, Víctor M.
description •A mathematical model of leukaemia response to CAR-T cell treatment is built and studied.•Tumour relapse is a dynamical phenomenon and can be controlled.•The mathematical model allows obtaining a formula for the relapse time.•Persistence of the disease depends on the generation of B-cells in the bone marrow. Immunotherapies use components of the patient immune system to selectively target cancer cells. The use of chimeric antigenic receptor (CAR) T cells to treat B-cell malignancies –leukaemias and lymphomas– is one of the most successful examples, with many patients experiencing long-lasting full responses to this therapy. This treatment works by extracting the patient’s T cells and transducing them with the CAR, enabling them to recognize and target cells carrying the antigen CD19+, which is expressed in these haematological cancers. Here we put forward a mathematical model describing the time response of leukaemias to the injection of CAR T cells. The model accounts for mature and progenitor B-cells, leukaemic cells, CAR T cells and side effects by including the main biological processes involved. The model explains the early post-injection dynamics of the different compartments and the fact that the number of CAR T cells injected does not critically affect the treatment outcome. An explicit formula is found that gives the maximum CAR T cell expansion in vivo and the severity of side effects. Our mathematical model captures other known features of the response to this immunotherapy. It also predicts that CD19+ cancer relapses could be the result of competition between leukaemic and CAR T cells, analogous to predator-prey dynamics. We discuss this in the light of the available evidence and the possibility of controlling relapses by early re-challenging of the leukaemia cells with stored CAR T cells.
doi_str_mv 10.1016/j.cnsns.2020.105570
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An explicit formula is found that gives the maximum CAR T cell expansion in vivo and the severity of side effects. Our mathematical model captures other known features of the response to this immunotherapy. It also predicts that CD19+ cancer relapses could be the result of competition between leukaemic and CAR T cells, analogous to predator-prey dynamics. 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Immunotherapies use components of the patient immune system to selectively target cancer cells. The use of chimeric antigenic receptor (CAR) T cells to treat B-cell malignancies –leukaemias and lymphomas– is one of the most successful examples, with many patients experiencing long-lasting full responses to this therapy. This treatment works by extracting the patient’s T cells and transducing them with the CAR, enabling them to recognize and target cells carrying the antigen CD19+, which is expressed in these haematological cancers. Here we put forward a mathematical model describing the time response of leukaemias to the injection of CAR T cells. The model accounts for mature and progenitor B-cells, leukaemic cells, CAR T cells and side effects by including the main biological processes involved. The model explains the early post-injection dynamics of the different compartments and the fact that the number of CAR T cells injected does not critically affect the treatment outcome. 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subjects Antigens
Biological activity
Biological models (mathematics)
Cancer
Cancer dynamics
Immune system
Immunotherapy
Leukemia
Lymphocytes
Lymphoma
Mathematical analysis
Mathematical modelling
Mathematical models
Mathematical oncology
Mathematics
Mathematics, Applied
Mathematics, Interdisciplinary Applications
Mechanics
Physical Sciences
Physics
Physics, Fluids & Plasmas
Physics, Mathematical
Science & Technology
Side effects
T cell receptors
Target recognition
Technology
Time response
Tumour-immune system interactions
title CAR T cell therapy in B-cell acute lymphoblastic leukaemia: Insights from mathematical models
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