A multispecies framework for modeling adaptive immunity and immunotherapy in cancer

Author:

Qi TimothyORCID,Vincent Benjamin G.,Cao YanguangORCID

Abstract

Predator-prey theory is commonly used to describe tumor growth in the presence of selective pressure from the adaptive immune system. These interactions are mediated by the tumor immunopeptidome (what the tumor “shows” the body) and the T-cell receptor (TCR) repertoire (how well the body “sees” cancer cells). The tumor immunopeptidome comprises neoantigens which can be gained and lost throughout tumorigenesis and treatment. Heterogeneity in the immunopeptidome is predictive of poor response to immunotherapy in some tumor types, suggesting that the TCR repertoire is unable to support a fully polyclonal response against every neoantigen. Importantly, while tumor and T-cell populations are known to compete with each other for intratumoral resources, whether between-lineage competition among peripheral T cells influences the TCR repertoire is unknown and difficult to interrogate experimentally. Computational models may offer a way to investigate these phenomena and deepen our understanding of the tumor-immune axis. Here, we construct a predator-prey-like model and calibrate it to preclinical and clinical data to describe tumor growth and immunopeptidome diversification. Simultaneously, we model the expansion of antigen-specific T-cell lineages and their consumption of both lineage-specific antigenic resources and lineage-agnostic, shared resources. This predator-prey-like framework accurately described clinically observed immunopeptidomes; recapitulated response-associated effects of immunotherapy, including immunoediting; and allowed exploration of treatment of tumors with varying growth and mutation rates.

Funder

National Institute of General Medical Sciences

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

Reference59 articles.

1. Tumour immunotherapy: lessons from predator–prey theory;PT Hamilton;Nat Rev Immunol,2022

2. Evolutionary dynamics of neoantigens in growing tumors;E Lakatos;Nat Genet,2020

3. Alternative tumour-specific antigens;CC Smith;Nat Rev Cancer,2019

4. Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction;DK Wells;Cell,2020

5. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade;N McGranahan;Science,2016

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