Dataset Information

Sontag2017 - Dynamic model of immune responses to antigen presentation by tumor or pathogen

ABSTRACT: This model of the immune system response to antigen presentation is based on the publication: Eduardo D.Sontag (2017) 'A Dynamic Model of Immune Responses to Antigen Presentation Predicts Different Regions of Tumor or Pathogen Elimination', Cell Systems, 4(2) DOI: 10.1016/j.cels.2016.12.003 Comment: This model is based on the "toy model" as described by Equations 1A-1C from the manuscript and the system represented by Equation 2, which exhibits a type of incoherent feedforward loop (IFFL). 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.

SUBMITTER: Rahuman Sheriff

PROVIDER: BIOMD0000001030 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000001030?filename=Sontag2017%20-%20Fig%201D%20new%20constant%20value%20simulation.sedml	Other
	BIOMD0000001030?filename=Sontag2017%20-%20Fig%201D%20shifted%20exponential%20simulation.sedml	Other
	BIOMD0000001030?filename=Sontag2017%20-%20Fig%201D%20shifted%20ramp%20simulation.sedml	Other
	BIOMD0000001030?filename=Sontag2017-biopax2.owl	Owl
	BIOMD0000001030?filename=Sontag2017-biopax3.owl	Owl

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Publications

A Dynamic Model of Immune Responses to Antigen Presentation Predicts Different Regions of Tumor or Pathogen Elimination.

Sontag Eduardo D ED

Cell systems 20170126 2

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 immun ...[more]

PMID: 28131824

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Project description:All nucleated mammalian cells express major histocompatibility complex (MHC) proteins that present peptides on cell surfaces for immune surveillance. These MHC-presented peptides (pMHC) can convey non-self antigens derived from pathogens or mutations to amount T-cell responses. Alterations in tumor-specific antigens – particularly mutation-bearing peptides (neoantigens) presented by MHC — can serve as potent substrates for anti-tumor immune responses. Here we employed an integrated genomic and proteomic antigen discovery strategy aimed at measuring interferon gamma (IFN-γ) induced alterations to antigen presentation, using a lymphoma cell line. IFN-γ treatment resulted in a set of differentially expressed proteins (2 % of all quantified proteins) including components of antigen presentation machinery or interferon signaling pathways. In addition, several proteasome subunits were found to be modulated, consistent with previous reports of immunoproteasome induction by IFN-γ exposure. This finding suggests that a modest proteomic response to IFN-γ could create larger alteration to cells antigen repertoires. Accordingly, by surveying immunopeptides, distinct peptide repertoires were exclusively observed in the IFN-γ induced samples. Furthermore, an additional set of presented peptides distinguished control and the IFN-γ samples by their altered relative abundances including neoantigens. Accordingly, we developed a classification system to distinguish peptides which are differentially presented due to altered expression from novel peptides resulting from changes in antigen processing. Taken together, these data demonstrate that IFN-γ can re-shape antigen repertoires by identity and by abundance. Extending this approach to models with greater clinical relevance should help develop strategies by which immunopeptide repertoires are intentionally reshaped to improve endogenous or vaccine-induced anti-tumor immune responses and potentially anti-viral immune responses.