Integrative network modeling reveals mechanisms underlying T cell exhaustion

Failure to clear antigens causes CD8 T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpi...

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Bibliographic Details
Published in:Scientific reports 2020-02, Vol.10 (1), p.1915, Article 1915
Main Authors: Bolouri, Hamid, Young, Mary, Beilke, Joshua, Johnson, Rebecca, Fox, Brian, Huang, Lu, Santini, Cristina Costa, Hill, Christopher Mark, Vries, Anne-Renee van der Vuurst de, Shannon, Paul T, Dervan, Andrew, Sivakumar, Pallavur, Trotter, Matthew, Bassett, Douglas, Ratushny, Alexander
Format: Article
Language:English
Subjects:
Animals
Antigens
CD8 antigen
CD8-Positive T-Lymphocytes - immunology
CD8-Positive T-Lymphocytes - metabolism
Computer Simulation
Datasets as Topic
Enhancer of Zeste Homolog 2 Protein - antagonists & inhibitors
Enhancer of Zeste Homolog 2 Protein - metabolism
Gene expression
Gene Regulatory Networks - drug effects
Gene Regulatory Networks - immunology
Humans
Immunologic Memory - drug effects
Immunologic Memory - immunology
Lymphocyte Activation - drug effects
Lymphocyte Activation - immunology
Lymphocytes T
Mice
Models, Immunological
Oligonucleotide Array Sequence Analysis
RNA-Seq
Signal Transduction - drug effects
Signal Transduction - genetics
Signal Transduction - immunology
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Summary:Failure to clear antigens causes CD8 T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8 T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-58600-8