Evidence map›Paper›PMID 24705941›Full record

ReviewCellular and molecular life sciences : CMLS2014

Discoidin domain receptors: a proteomic portrait.

Leo K Iwai, Maciej T Luczynski, Paul H Huang

Abstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

  1. Article
  2. Review
  3. Therapeutic advances of targeting receptor tyrosine kinases in cancer.Signal transduction and targeted therapy · 2024
    Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. 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

3 authors.

Leo K IwaiProtein Networks Team, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.
Maciej T Luczynski
Paul H Huang

Funding

Biotechnology and Biological Sciences Research Council BB/I014276/1Wellcome TrustWellcome Trust WT089028
6 · The paper itself

Abstract

The discoidin domain receptors (DDRs) are collagen-binding receptor tyrosine kinases that have been implicated in a number of fundamental biological processes ranging from growth and development to immunoregulation. In this review, we examine how recent proteomic technologies have enriched our understanding of DDR signaling mechanisms. We provide an overview on the use of large-scale proteomic profiling and chemical proteomics to reveal novel insights into DDR therapeutics, signaling networks, and receptor crosstalk. A perspective of how proteomics may be harnessed to answer outstanding fundamental questions including the dynamic regulation of receptor activation kinetics is presented. Collectively, these studies present an emerging molecular portrait of these unique receptors and their functional role in health and disease.

Indexed as

Protein Processing, Post-TranslationalAnimalsAntineoplastic AgentsCell Physiological PhenomenaDiscoidin Domain ReceptorsEnzyme ActivationEpithelial CellsEpithelial-Mesenchymal TransitionHSP90 Heat-Shock ProteinsHumansIntracellular Signaling Peptides and ProteinsMesodermMolecular Targeted TherapyNeoplasm ProteinsNeoplasmsPhosphorylationAntineoplastic AgentsDiscoidin Domain ReceptorsHSP90 Heat-Shock ProteinsIntracellular Signaling Peptides and ProteinsNeoplasm ProteinsProtein Kinase InhibitorsReceptor Protein-Tyrosine KinasesReceptors, Mitogen

Identifiers

PMID24705941
PMCPMC11113481

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.