Mathematical modeling of tumor-immune system interactions: the effect of rituximab on breast cancer immune response

TL;DR

This paper develops a mathematical model to analyze how immune cells interact with breast cancer and assesses the impact of rituximab, a monoclonal antibody, on tumor-immune dynamics and therapy effectiveness.

Contribution

It introduces a novel mathematical framework incorporating rituximab effects and validates the functional response of NK cell-mediated lysis as ratio-dependent.

Findings

Rituximab influences immune cell interactions with breast cancer.

The model confirms ratio-dependent lysis of cancer cells by NK cells.

Simulations suggest optimal dosing strategies for rituximab.

Abstract

tBregs are a newly discovered subcategory of B regulatory cells, which are generated by breast cancer, resulting in the increase of Tregs and therefore in the death of NK cells. In this study, we use a mathematical and computational approach to investigate the complex interactions between the aforementioned cells as well as CD8$^+$ T cells, CD4$^+$ T cells and B cells. Furthermore, we use data fitting to prove that the functional response regarding the lysis of breast cancer cells by NK cells has a ratio-dependent form. Additionally, we include in our model the concentration of rituximab - a monoclonal antibody that has been suggested as a potential breast cancer therapy - and test its effect, when the standard, as well as experimental dosages, are administered.