Evidence map›Paper›PMID 18493017›Full record

ReviewScience signaling2008

Focal adhesion kinase versus p53: apoptosis or survival?

William G Cance, Vita M Golubovskaya

Abstract readReview
In one paragraph

Review in Science signaling, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 97 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. FAK in Cancer: From Mechanisms to Therapeutic Strategies.International journal of molecular sciences · 2022
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. The Role of microRNAs in Epithelial Ovarian Cancer Metastasis.International journal of molecular sciences · 2020
    Review
  15. Article
  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

2 authors at 1 institution in 1 country.

William G CanceDepartment of Surgery, University of Florida, School of Medicine, Gainesville, FL 32610, USA. cance@surgery.ufl.edu
Vita M Golubovskaya
University of Florida · US

Funding

FOCAL ADHESION KINASE--TUMOR BIOLOGY AND THERAPEUTICSR01CA065910 · NCI · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI MARLOWE, TIMOTHY A · 1996 to 2019
$6.3M
NCI NIH HHS R01 CA065910
6 · The paper itself

Abstract

Focal adhesion kinase (FAK) is a tyrosine kinase that interacts with a multitude of signaling partners and helps cells to survive in the face of various proapoptotic signals. One of the most important interactions for FAK is with the tumor suppressor protein p53. p53 binds not only to the amino-terminal domain of FAK but also to the FAK promoter to inhibit its transcription. A study now reports the biological implications of the kinase-independent interaction of FAK with p53, which opens up future perspectives in cell signaling and cancer research. We focus on FAK and p53 signaling, which link signal transduction pathways from the extracellular matrix and cytoplasm to the nucleus, in human and mouse cells. FAK is proposed to be a critical scaffold protein that sequesters proapoptotic proteins, such as p53, to mediate cell survival.

Indexed as

ApoptosisAnimalsCell SurvivalFocal Adhesion Protein-Tyrosine KinasesHumansMiceProtein BindingSignal TransductionTumor Suppressor Protein p53Focal Adhesion Protein-Tyrosine KinasesTumor Suppressor Protein p53

Identifiers

PMID18493017
PMCPMC4560103
OpenAlexW2171664463

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.