Evidence map›Paper›PMID 31222112›Full record

ArticleScientific reports2019

A sensitive and simple targeted proteomics approach to quantify transcription factor and membrane proteins of the unfolded protein response pathway in glioblastoma cells.

Chi D L Nguyen, Sebastian Malchow, Stefan Reich, Sascha Steltgens, Konstantin V Shuvaev, Stefan Loroch, Christin Lorenz, Albert Sickmann, Christiane B Knobbe-Thomsen, Björn Tews and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

20 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
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  5. Proteomics Applications inPathogens (Basel, Switzerland) · 2023
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  10. ERK1/2 Activity Is Critical for the Outcome of Ischemic Stroke.International journal of molecular sciences · 2022
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  15. An Introduction to Advanced Targeted Acquisition Methods.Molecular & cellular proteomics : MCP · 2021
    Review
  16. Nano-liquid chromatography-mass spectrometry and recent applications in omics investigations.Analytical methods : advancing methods and applications · 2020
    Review
  17. Article
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  19. Sugar Beet (International journal of molecular sciences · 2020
    Article
  20. Article
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

12 authors at 5 institutions in 2 countries.

Chi D L NguyenLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Sebastian MalchowLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Stefan ReichTranslational Control Group, Biochemistry I, University of Regensburg, 93053, Regensburg, Germany.
Sascha SteltgensInstitute of Neuropathology, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225, Düsseldorf, Germany.
Konstantin V ShuvaevLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Stefan LorochLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Christin LorenzLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Albert SickmannLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany.
Christiane B Knobbe-ThomsenInstitute of Neuropathology, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225, Düsseldorf, Germany.ORCID http://orcid.org/0000-0003-1231-0076
Björn TewsSchaller Research Group, University of Heidelberg and DKFZ, 69120, Heidelberg, Germany.
Jan MedenbachTranslational Control Group, Biochemistry I, University of Regensburg, 93053, Regensburg, Germany.
Robert AhrendsLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227, Dortmund, Germany. robert.ahrends@isas.de.ORCID http://orcid.org/0000-0003-0232-3375
Leibniz Institute for Analytical Sciences - ISAS · DEHeinrich Heine University Düsseldorf · DEUniversity of Regensburg · DEHeidelberg University · DEUniversity of Aberdeen · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many cellular events are driven by changes in protein expression, measurable by mass spectrometry or antibody-based assays. However, using conventional technology, the analysis of transcription factor or membrane receptor expression is often limited by an insufficient sensitivity and specificity. To overcome this limitation, we have developed a high-resolution targeted proteomics strategy, which allows quantification down to the lower attomol range in a straightforward way without any prior enrichment or fractionation approaches. The method applies isotope-labeled peptide standards for quantification of the protein of interest. As proof of principle, we applied the improved workflow to proteins of the unfolded protein response (UPR), a signaling pathway of great clinical importance, and could for the first time detect and quantify all major UPR receptors, transducers and effectors that are not readily detectable via antibody-based-, SRM- or conventional PRM assays. As transcription and translation is central to the regulation of UPR, quantification and determination of protein copy numbers in the cell is important for our understanding of the signaling process as well as how pharmacologic modulation of these pathways impacts on the signaling. These questions can be answered using our newly established workflow as exemplified in an experiment using UPR perturbation in a glioblastoma cell lines.

Indexed as

Unfolded Protein ResponseCell Line, TumorGene DosageGlioblastomaHumansIsotope LabelingMembrane ProteinsPeptidesProteomicsTranscription FactorsMembrane ProteinsPeptidesTranscription Factors

Identifiers

PMID31222112
PMCPMC6586633
OpenAlexW2950345178

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.