Evidence map›Paper›PMID 37355548›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Dissecting Interleukin-6 Classic and Trans-signaling in Inflammation and Cancer.

Christoph Garbers, Stefan Rose-John

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
6.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Christoph GarbersMedical Faculty, Department of Pathology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany. christoph.garbers@med.ovgu.de.
Stefan Rose-JohnInstitute of Biochemistry, Kiel University, Kiel, Germany.
Kiel University · DEOtto-von-Guericke University Magdeburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interleukin-6 (IL-6) is a cytokine synthesized by many cells in the human body. IL-6 binds to a membrane-bound receptor (IL-6R), which is only present on hepatocytes, some epithelial cells, and some leukocytes. The complex of IL-6 and IL-6R binds to the ubiquitously expressed receptor subunit gp130, which forms a homodimer and thereby initiates intracellular signaling, e.g., the JAK/STAT and MAPK pathways. Proteases can cleave the membrane-bound IL-6R from the cell surface and generate a soluble IL-6R (sIL-6R), which retains its ability to bind IL-6. The IL-6/sIL-6R complex associates with gp130 and induces signaling even on cells which do not express the IL-6R. This paradigm has been called IL-6 trans-signaling, whereas signaling via the membrane-bound IL-6R is referred to as classic signaling. We have generated several molecular tools to differentiate between both pathways and to analyze the consequences of cellular IL-6 signaling in vivo. One of these tools is soluble gp130Fc, which selectively inhibits IL-6 trans-signaling. This protein under the WHO name Olamkicept has successfully undergone phase II clinical trials in patients with autoimmune diseases. Here, in this chapter, we describe several molecular tools to differentiate between IL-6 classic and trans-signaling and to analyze the consequences of cellular IL-6 signaling in vivo.

Indexed as

Interleukin-6NeoplasmsCytokine Receptor gp130CytokinesHumansInflammationReceptors, Interleukin-6Cytokine Receptor gp130CytokinesInterleukin-6Receptors, Interleukin-6CancerIL-6 trans-signalingInflammationInterleukin-6Interleukin-6 receptorSoluble gp130

Identifiers

PMID37355548
OpenAlexW4381851507

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.