Evidence map›Paper›PMID 30761269›Full record

ArticleFrontiers in oncology2019

Inhibition of FAK Signaling Elicits Lamin A/C-Associated Nuclear Deformity and Cellular Senescence.

Hsiang-Hao Chuang, Pei-Hui Wang, Sheng-Wen Niu, Yen-Yi Zhen, Ming-Shyan Huang, Michael Hsiao, Chih-Jen Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

19 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
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  4. Review
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  6. Review
  7. Article
  8. Genome-wide screening for genetic variants in polyadenylation signal (PAS) sites in mouse selection lines for fatness and leanness.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Article
  9. Review
  10. Gaussian curvature-driven direction of cell fate toward osteogenesis with triply periodic minimal surface scaffolds.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. FAK in Cancer: From Mechanisms to Therapeutic Strategies.International journal of molecular sciences · 2022
    Review
  15. Article
  16. The Effect of Terpenoid Natural Chinese Medicine Molecular Compound on Lung Cancer Treatment.Evidence-based complementary and alternative medicine : eCAM · 2021
    Review
  17. Review
  18. Review
  19. 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

7 authors at 4 institutions in 1 country.

Hsiang-Hao ChuangDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Pei-Hui WangDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Sheng-Wen NiuDivision of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Yen-Yi ZhenDivision of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Ming-Shyan HuangDepartment of Internal Medicine, E-Da Cancer Hospital, School of Medicine, I-Shou University, Kaohsiung, Taiwan.
Michael HsiaoGenomics Research Center, Academia Sinica, Taipei, Taiwan.
Chih-Jen YangDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Kaohsiung Medical University Chung-Ho Memorial Hospital · TWKaohsiung Medical University · TWGenomics Research Center, Academia Sinica · TWI-Shou University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Focal adhesion kinase (FAK) is a non-receptor kinase that facilitates tumor aggressiveness. The effects of FAK inhibition include arresting proliferation, limiting metastasis, and inhibiting angiogenesis. PF-573228 is an ATP-competitive inhibitor of FAK. Treating lung cancer cells with PF-573228 resulted in FAK inactivation and changes in the expressions of lamin A/C and nuclear deformity. Since lamin A/C downregulation or deficiency was associated with cellular senescence, the senescence-associated β-galactosidase (SA-β-gal) assay was used to investigate whether PF-573228 treatment drove cellular senescence, which showed more SA-β-gal-positive cells in culture. p53 is known to play a pivotal role in mediating the progression of cellular senescence, and the PF-573228-treated lung cancer cells resulted in a higher p53 expression level. Subsequently, the FAK depletion in lung cancer cells was employed to confirm the role of FAK inhibition on cellular senescence. FAK depletion and pharmacological inhibition of lung cancer cells elicited similar patterns of cellular senescence, lamin A/C downregulation, and p53 upregulation, implying that FAK signaling is associated with the expression of p53 and the maintenance of lamin A/C levels to shape regular nuclear morphology and manage anti-senescence. Conversely, FAK inactivation led to p53 upregulation, disorganization of the nuclear matrix, and consequently cellular senescence. Our data suggest a new FAK signaling pathway, in that abolishing FAK signaling can activate the senescence program in cells. Triggering cellular senescence could be a new therapeutic approach to limit tumor growth.

Indexed as

focal adhesion kinaselamin A/Cnon-small cell lung cancernuclear deformitysenescence

Identifiers

PMID30761269
PMCPMC6363943
OpenAlexW2913572059

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.