Deciphering the combinatorial landscape of immunity
From cellular activation to drug combinations, immunological responses are shaped by the action of multiple stimuli. Synergistic and antagonistic interactions between stimuli play major roles in shaping immune processes. To understand combinatorial regulation, we present the immune Synergistic/Antagonistic Interaction Learner (iSAIL). iSAIL includes a machine learning classifier to map and interpret interactions, a curated compendium of immunological combination treatment datasets, and their global integration into a landscape of ~30,000 interactions. The landscape is mined to reveal combinatorial control of interleukins, checkpoints, and other immune modulators. The resource helps elucidate the modulation of a stimulus by interactions with other cofactors, showing that TNF has strikingly different effects depending on co-stimulators. We discover new functional synergies between TNF and IFNβ controlling dendritic cell-T cell crosstalk. Analysis of laboratory or public combination treatment studies with this user-friendly web-based resource will help resolve the complex role of interaction effects on immune processes.
Gene expression data generated for this study have been deposited in GEO under accession code GSE134209. All other dataset accession codes analysed in this study are included in the manuscript (Table 1). All the analyses have been implemented in R. An interactive R Shiny application of iSAIL can be found at https://isail.shinyapps.io/test_app/. The site also contains downloadable code and documentation to run the software locally.
Microarray data of human moDC treated with IFNβ and TNFαNCBI Gene Expression Omnibus, GSE134209.
Article and author information
National Institute of Allergy and Infectious Diseases (5U19AI117873)
- Stuart C Sealfon
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Alfonso Valencia, Barcelona Supercomputing Center - BSC, Spain
- Received: August 15, 2020
- Accepted: November 5, 2020
- Accepted Manuscript published: November 23, 2020 (version 1)
- Version of Record published: December 18, 2020 (version 2)
© 2020, Cappuccio et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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