Mathematical analysis and classification of tumor immune dynamics in T cell transfer treatment

Abstract

Immunotherapy for cancer is a forthcoming therapeutic option in cancer treatment. A variety of approaches, including adoptive cell transfer, adjuvant therapy, and monoclonal antibody therapy, are currently used as complementary or alternative cancer treatments. Since immunity against tumors is established as a result of complex interactions among tumors and immune cells, a theoretical framework to elucidate the dynamics of tumor killing by immune cells initiated by clinical intervention needs to be developed. We construct a simple mathematical model that describes the killing of tumors by T cells. We focus on a mathematical characterization of the effect of adoptive cell transfer therapy, the injection of a patient's own ex vivo activated T cells to initiate tumor immunity. On the basis of rigorous mathematical analyses and numerical computations, we provide biological interpretations for the possible outcomes of adoptive cell transfer under three different scenarios in terms of proliferation. In our modeling framework, adoptive cell transfer therapy can be understood as a driving force that potentially operates to shift the state of an immune response from inactive to active. On the other hand, our modeling framework suggests the possibility that a tumor can exploit a self-augmenting proliferation of T cells mediated by autocrine/paracrine signaling as an escape strategy from an immune response.