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

authors

  • León-Triana, Odelaisy
  • SABIR, SOUKAINA
  • CALVO, GABRIEL F.
  • BELMONTE BEITIA, JUAN
  • CHULIAN, SALVADOR
  • MARTINEZ RUBIO, ALVARO
  • ROSA, MARIA
  • PEREZ MARTINEZ, ANTONIO
  • RAMIREZ ORELLANA, MANUEL
  • PEREZ GARCIA, VICTOR M.

publication date

  • March 2021

start page

  • 1

end page

  • 21

issue

  • 105570

volume

  • 94

International Standard Serial Number (ISSN)

  • 1007-5704

Electronic International Standard Serial Number (EISSN)

  • 1878-7274

abstract

  • 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.

subjects

  • Mathematics
  • Medicine

keywords

  • mathematical modelling; cancer dynamics; immunotherapy; tumour-immune system interactions; mathematical oncology