Evidence map›Paper›PMID 34699385›Full record

ArticleJCI insight2021

GATA4 induces liver fibrosis regression by deactivating hepatic stellate cells.

Noelia Arroyo, Laura Villamayor, Irene Díaz, Rita Carmona, Mireia Ramos-Rodríguez, Ramón Muñoz-Chápuli, Lorenzo Pasquali, Miguel G Toscano, Franz Martín, David A Cano and 1 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
4.3field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 49 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Mouse Models for the Study of Liver Fibrosis RegressionJournal of clinical and translational hepatology · 2024
    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

11 authors at 5 institutions in 1 country.

Noelia ArroyoCentro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Universidad Pablo de Olavide, Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain.
Laura VillamayorCentro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Universidad Pablo de Olavide, Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain.
Irene DíazCentro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Universidad Pablo de Olavide, Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain.
Rita CarmonaUniversidad de Málaga y Centro Andaluz de Nanomedicina, Málaga, Spain.
Mireia Ramos-RodríguezEndocrine Regulatory Genomics, Department of Experimental & Health Sciences, University Pompeu Fabra, Barcelona, Spain.
Ramón Muñoz-ChápuliUniversidad de Málaga y Centro Andaluz de Nanomedicina, Málaga, Spain.
Lorenzo PasqualiEndocrine Regulatory Genomics, Department of Experimental & Health Sciences, University Pompeu Fabra, Barcelona, Spain.
Miguel G ToscanoAmarna Therapeutics, Sevilla, Spain.
Franz MartínCentro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Universidad Pablo de Olavide, Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain.
David A CanoInstituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.
Anabel RojasCentro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), Universidad Pablo de Olavide, Universidad de Sevilla, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain.
Consejo Superior de Investigaciones Científicas · ESAndalusian Centre for Nanomedicine and Biotechnology · ESUniversitat Pompeu Fabra · ESInstituto de Biomedicina de Sevilla · ESUniversidad de Sevilla · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In response to liver injury, hepatic stellate cells activate and acquire proliferative and contractile features. The regression of liver fibrosis appears to involve the clearance of activated hepatic stellate cells, either by apoptosis or by reversion toward a quiescent-like state, a process called deactivation. Thus, deactivation of active hepatic stellate cells has emerged as a novel and promising therapeutic approach for liver fibrosis. However, our knowledge of the master regulators involved in the deactivation and/or activation of fibrotic hepatic stellate cells is still limited. The transcription factor GATA4 has been previously shown to play an important role in embryonic hepatic stellate cell quiescence. In this work, we show that lack of GATA4 in adult mice caused hepatic stellate cell activation and, consequently, liver fibrosis. During regression of liver fibrosis, Gata4 was reexpressed in deactivated hepatic stellate cells. Overexpression of Gata4 in hepatic stellate cells promoted liver fibrosis regression in CCl4-treated mice. GATA4 induced changes in the expression of fibrogenic and antifibrogenic genes, promoting hepatic stellate cell deactivation. Finally, we show that GATA4 directly repressed EPAS1 transcription in hepatic stellate cells and that stabilization of the HIF2α protein in hepatic stellate cells leads to liver fibrosis.

Indexed as

AnimalsGATA4 Transcription FactorHepatic Stellate CellsHumansLiver CirrhosisMiceTransfectionGata4 protein, mouseGATA4 Transcription FactorCell BiologyFibrosisGastroenterologyMouse models

Identifiers

PMID34699385
PMCPMC8675192
OpenAlexW3209127942

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.