Evidence map›Paper›PMID 28092656›Full record

ArticleNature biotechnology2017

Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry.

Xiao-Kang Lun, Vito R T Zanotelli, James D Wade, Denis Schapiro, Marco Tognetti, Nadine Dobberstein, Bernd Bodenmiller

Open access · greenAbstract read
In one paragraph

Article in Nature biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
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  5. spillR: spillover compensation in mass cytometry data.Bioinformatics (Oxford, England) · 2024
    Article
  6. Article
  7. Article
  8. Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
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  12. Review
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  15. Profiling Cell Signaling Networks at Single-cell Resolution.Molecular & cellular proteomics : MCP · 2020
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

7 authors at 3 institutions in 2 countries.

Xiao-Kang LunInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
Vito R T ZanotelliInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
James D WadeInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
Denis SchapiroInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
Marco TognettiInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
Nadine DobbersteinInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
Bernd BodenmillerInstitute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
University of Zurich · CHETH Zurich · CHThe Wallace H. Coulter Department of Biomedical Engineering · US

Funding

European Research Council 336921
6 · The paper itself

Abstract

Signaling networks are key regulators of cellular function. Although the concentrations of signaling proteins are perturbed in disease states, such as cancer, and are modulated by drug therapies, our understanding of how such changes shape the properties of signaling networks is limited. Here we couple mass-cytometry-based single-cell analysis with overexpression of tagged signaling proteins to study the dependence of signaling relationships and dynamics on protein node abundance. Focusing on the epidermal growth factor receptor (EGFR) signaling network in HEK293T cells, we analyze 20 signaling proteins during a 1-h EGF stimulation time course using a panel of 35 antibodies. Data analysis with BP-R

Indexed as

Models, BiologicalComputer SimulationEpidermal Growth FactorErbB ReceptorsFlow CytometryGene Expression ProfilingGene Expression RegulationHEK293 CellsHumansProteomeSignal TransductionEGFR protein, humanEpidermal Growth FactorErbB ReceptorsProteome

Identifiers

PMID28092656
PMCPMC5617104
OpenAlexW2574795978

What OpenQuestion holds

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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.