Dataset Information

Transcriptional response modules characterize IL-1β and IL-6 activity in COVID-19.

ABSTRACT: Dysregulated IL-1β and IL-6 responses have been implicated in the pathogenesis of severe Coronavirus Disease 2019 (COVID-19). Innovative approaches for evaluating the biological activity of these cytokines in vivo are urgently needed to complement clinical trials of therapeutic targeting of IL-1β and IL-6 in COVID-19. We show that the expression of IL-1β or IL-6 inducible transcriptional signatures (modules) reflects the bioactivity of these cytokines in immunopathology modelled by juvenile idiopathic arthritis (JIA) and rheumatoid arthritis. In COVID-19, elevated expression of IL-1β and IL-6 response modules, but not the cytokine transcripts themselves, is a feature of infection in the nasopharynx and blood but is not associated with severity of COVID-19 disease, length of stay, or mortality. We propose that IL-1β and IL-6 transcriptional response modules provide a dynamic readout of functional cytokine activity in vivo, aiding quantification of the biological effects of immunomodulatory therapies in COVID-19.

SUBMITTER: Bell LCK

PROVIDER: S-EPMC7721347 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcriptional response modules characterize IL-1β and IL-6 activity in COVID-19.

Bell Lucy C K LCK Meydan Cem C Kim Jacob J Foox Jonathan J Butler Daniel D Mason Christopher E CE Shapira Sagi D SD Noursadeghi Mahdad M Pollara Gabriele G

iScience 20201207 1

Dysregulated IL-1β and IL-6 responses have been implicated in the pathogenesis of severe Coronavirus Disease 2019 (COVID-19). Innovative approaches for evaluating the biological activity of these cytokines <i>in vivo</i> are urgently needed to complement clinical trials of therapeutic targeting of IL-1β and IL-6 in COVID-19. We show that the expression of IL-1β or IL-6 inducible transcriptional signatures (modules) reflects the bioactivity of these cytokines in immunopathology modelled by juveni ...[more]

PMID: 33319166

Similar Datasets

Project description:BackgroundAnticancer therapies that target single signal transduction pathways often fail to prevent proliferation of cancer cells because of overlapping functions and cross-talk between different signaling pathways. Recent research has identified that balanced multi-component therapies might be more efficacious than highly specific single component therapies in certain cases. Ideally, synergistic combinations can provide 1) increased efficacy of the therapeutic effect 2) reduced toxicity as a result of decreased dosage providing equivalent or increased efficacy 3) the avoidance or delayed onset of drug resistance. Therefore, the interest in combinatorial drug discovery based on systems-oriented approaches has been increasing steadily in recent years.MethodologyHere we describe the development of Combinatorial Drug Assembler (CDA), a genomics and bioinformatics system, whereby using gene expression profiling, multiple signaling pathways are targeted for combinatorial drug discovery. CDA performs expression pattern matching of signaling pathway components to compare genes expressed in an input cell line (or patient sample data), with expression patterns in cell lines treated with different small molecules. Then it detects best pattern matching combinatorial drug pairs across the input gene set-related signaling pathways to detect where gene expression patterns overlap and those predicted drug pairs could likely be applied as combination therapy. We carried out in vitro validations on non-small cell lung cancer cells and triple-negative breast cancer (TNBC) cells. We found two combinatorial drug pairs that showed synergistic effect on lung cancer cells. Furthermore, we also observed that halofantrine and vinblastine were synergistic on TNBC cells.ConclusionsCDA provides a new way for rational drug combination. Together with phExplorer, CDA also provides functional insights into combinatorial drugs. CDA is freely available at http://cda.i-pharm.org.

Dataset Information

Transcriptional response modules characterize IL-1β and IL-6 activity in COVID-19.

Publications

Transcriptional response modules characterize IL-1β and IL-6 activity in COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets