Mathematical models suggest ways to improve CAR-T cell leukaemia treatments
MOLAB
Wednesday October 28, 2020
Mathematical Oncology Laboratory

Immunotherapies use components of the patient immune system to selectively target cancer cells. The use of CAR T cells to treat B-cell malignancies --leukaemias and lymphomas-- is one of the most successful examples, with many patients experiencing long-lasting complete responses to this therapy. This treatment works by extracting the patient's T cells and adding them the CAR group, which enables them to recognize and target cells carrying the antigen CD19+, that is expressed in these haematological tumors. 

In a recent work published in the prestigious mathematical journal Communications in Nonlinear Science and Numerical Simulation (ranked 3rd journal of 260 in the Web of Science), MOLAB researchers have 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, tumor cells, CAR T cells and side effects by incorporating 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 provides the maximum CAR T cell expansion in-vivo and the severity of side effects. The mathematical model captures other known features of the response to this immunotherapy. 

Interestingly, the model predicts that CD19+ tumor relapses observed in a fraction of patients could be the result of the competition between tumor and CAR T cells analogous to predator-prey dynamics and thus a transient phenomenon. Also MOLAB researchers show the possibility of controlling relapses by early re-challenging of the tumor with stored CAR T cells.

 

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

O. León-Triana, S. Sabir, GF Calvo, J Belmonte-Beitia, S Chulian, A Martínez-Rubio, M Rosa, A Pérez-Martínez, M Ramírez-Orellana, VM Pérez-García 

Comm Nonlin Sci Numer Simul 94, 105570 (2021)

Journal website