Modeling cell-specific dynamics and regulation of the common gamma chain cytokines

The gamma-chain receptor dimerizes with complexes of the cytokines interleukin-2 (IL-2), IL-4, IL-7, IL-9, IL-15, and IL-21 and their corresponding private'' receptors. These cytokines have existing uses and future potential as immune therapies because of their ability to regulate the abundance and function of specific immune cell populations. Here, we build a binding reaction model for the ligand-receptor interactions of common gamma-chain cytokines, which includes receptor trafficking dynamics, enabling quantitative predictions of cell-type-specific response to natural and engineered cytokines. We then show that tensor factorization is a powerful tool to visualize changes in the input-output behavior of the family across time, cell types, ligands, and concentrations. These results present a more accurate model of ligand response validated across a panel of immune cell types as well as a general approach for generating interpretable guidelines for manipulation of cell-type-specific targeting of engineered ligands.

Automated summary

The study introduces a binding reaction model for common gamma-chain cytokines, enabling quantitative predictions of cell type-specific responses to natural and engineered cytokines. Tensor factorization is shown to be a powerful tool in visualizing changes in the input-output behavior of the cytokine family across various parameters like time, cell types, ligands, and concentrations. This results in a more accurate ligand response model validated across immune cell types, as well as a general approach for generating interpretable guidelines for manipulating cell type-specific targeting of engineered ligands.