Deciphering the combinatorial landscape of immunity.
Animals
Databases as Topic
Dendritic Cells
/ drug effects
Humans
Immune Checkpoint Inhibitors
/ pharmacology
Immunity
/ drug effects
Immunologic Factors
/ pharmacology
Interferon-beta
/ metabolism
Interleukins
/ metabolism
Machine Learning
Mice
Software
T-Lymphocytes
/ drug effects
Tumor Necrosis Factor-alpha
/ metabolism
combination treatment experiment
computational biology
cytokine interactions
dendritic cell T cell cross-talk
human
immunology
inflammation
machine learning
mouse
signal integration
synergy antagonism
systems biology
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
23 11 2020
23 11 2020
Historique:
received:
15
08
2020
accepted:
05
11
2020
pubmed:
24
11
2020
medline:
19
3
2021
entrez:
23
11
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33225996
doi: 10.7554/eLife.62148
pii: 62148
pmc: PMC7748411
doi:
pii:
Substances chimiques
Immune Checkpoint Inhibitors
0
Immunologic Factors
0
Interleukins
0
Tumor Necrosis Factor-alpha
0
Interferon-beta
77238-31-4
Banques de données
GEO
['GSE134209']
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : European Research Council
ID : IT-DC 281987
Pays : International
Organisme : Agence Nationale de la Recherche
ID : ANR-11-LABX-0043 CIC IGR-Curie 1428
Pays : International
Organisme : NIAID NIH HHS
ID : U19 AI117873
Pays : United States
Organisme : European Research Council
ID : 680890
Pays : International
Organisme : Defense Advanced Research Projects Agency
ID : N6600119C4022
Pays : International
Informations de copyright
© 2020, Cappuccio et al.
Déclaration de conflit d'intérêts
AC, SJ, BH, SS, VS, EZ No competing interests declared
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