Abstract

Anti CTLA-4 therapy is aimed at blocking the Cytotoxic T-lymphocyte antigen-4 (CTLA-4), a key cancer immunity cycle checkpoint. The mechanism of action of CTLA-4 may be described as a dynamic competition for the B7 ligand which, subsequently, interferes with the CD28-B7 costimulatory pathway. Anti CTLA-4 blockade enhances the process of cognate T cell activation and leads to a broadening of the T cell repertoire. In the present work, we used an agent-based modeling (ABM) platform of T cell immune response development, to explore hypothetical modes of anti CTLA-4 action. The model features a selected number of activated T cell clones, calculated based on combined random and chemotactically-driven encounters with antigen-presenting dendritic cells (DCs) and a distribution of individual T cell affinities to the antigen of interest. The proposed model can be used as a quantitative tool to explore various hypotheses on T cell immunity regulation and validate these against experimental data. A comprehensive ABM model analysis of immune response dynamic simulations revealed several putative anti CTLA-4 mechanisms of action, including: (i) an increase in the probability of primary activation of lymphocytes; (ii) T cell activation enhancement via a prolongation of short contacts with dendritic cells; and (iii) an increase in the maximum level of activation signal (or saturation), accumulated through a series of short contacts with DCs. The modeling work further demonstrates that it is only when considering jointly these various modes of anti CTLA-4 effects on the T cell immune response dynamics that a biologically meaningful increase in both the production of activated cells and the expansion of the T cell repertoire is observed. These model-based results are overall consistent with the collective biological knowledge on the functional role of CTLA-4. Furthermore, the ABM presented here may allow to interrogate various mechanistic scenarios underlying adverse events mediated by anti CTLA-4 pharmacologic therapies.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call