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A Dynamic Model of Immune Responses to Antigen Presentation Predicts Different Regions of Tumor or Pathogen
1Department of Mathematics and Center for Quantitative Biology, Rutgers University, New Brunswick, NJ 08903, USA.
Abstract:
The immune system must discriminate between agents of disease and an organism's healthy cells. While the identification of an antigen as self/non-self is critically important, the dynamic features of antigen presentation may also determine the immune system's response. Here, we use a simple mathematical model of immune activation to explore the idea of antigen discrimination through dynamics. We propose that antigen presentation is coupled to two nodes, one regulatory and one effecting the immune response, through an incoherent feedforward loop and repressive feedback. This circuit would allow the immune system to effectively estimate the increase of antigens with respect to time, a key determinant of immune reactivity in vivo. Our model makes the prediction that tumors growing at specific rates evade the immune system despite the continuous presence of antigens indicating disease, a phenomenon closely related to clinically observed "two-zone tolerance." Finally, we discuss a plausible biological instantiation of our circuit using combinations of regulatory and effector T cells.
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