Evidence map›Paper›PMID 40575954›Full record

ArticleLiver international : official journal of the International Association for the Study of the Liver2025

Amelioration of Liver Fibrosis via In Situ Hepatic Stellate Cell Conversion Through Co-Inhibition of TGF-β and GSK-3 Signalling.

Xiang-Jie Zhu, Zhi Zhong, Jiang-Chuan Du, Jiu-Yu Zhang, Xu Zhang, Xiu-Liang Cui, Ling-Ting Guan, Yan-Yu Hu, Can Chen, Han Wang and 4 more

Abstract read
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In one paragraph

Article in Liver international : official journal of the International Association for the Study of the Liver, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Amelioration of Liver Fibrosis via In Situ Hepatic Stellate Cell Conversion Through Co-Inhibition of TGF-β and GSK-3 Signalling.Liver international : official journal of the International Association for the Study of the Liver · 2025
    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

14 authors.

Xiang-Jie ZhuInstitute of Metabolism & Integrative Biology, Fudan University, Shanghai, China.
Zhi ZhongNational Center for Liver Cancer, Shanghai, China.
Jiang-Chuan DuNational Center for Liver Cancer, Shanghai, China.
Jiu-Yu ZhangInstitute of Metabolism & Integrative Biology, Fudan University, Shanghai, China.
Xu ZhangNational Center for Liver Cancer, Shanghai, China.
Xiu-Liang CuiNational Center for Liver Cancer, Shanghai, China.
Ling-Ting GuanNational Center for Liver Cancer, Shanghai, China.
Yan-Yu HuNational Center for Liver Cancer, Shanghai, China.
Can ChenInternational Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute, Naval Medical University, Shanghai, China.
Han WangDepartment of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China.ORCID 0000-0002-4709-3334
Xiang-Yu WuNational Center for Liver Cancer, Shanghai, China.
Wei-Jia ZhangNational Center for Liver Cancer, Shanghai, China.
Pei-Lin ZhangNational Center for Liver Cancer, Shanghai, China.
Hong-Yang WangInstitute of Metabolism & Integrative Biology, Fudan University, Shanghai, China.

Funding

National Natural Science Foundation of China 81472772National Science and Technology Major Project 2018ZX10302207Natural Science Foundation of Shanghai Municipality 14ZR1408900
6 · The paper itself

Abstract

BACKGROUND AND

aimsLiver fibrosis, a progressive condition driven by chronic liver injury and excessive scar tissue formation, can lead to cirrhosis, a life-threatening disease. Activation of hepatic stellate cells (HSCs) is central to fibrosis progression, yet current therapies fail to halt or reverse this process. This study evaluated a combination therapy targeting HSCs to ameliorate fibrosis and promote liver repair.

methodsA small molecule cocktail, SBCH (SB431542, a TGF-β inhibitor, and CHIR99021, a GSK-3 inhibitor), was tested in three fibrosis models: CCl

resultsSBCH significantly reduced fibrosis in all models by inhibiting HSC activation and fibrogenic activity. The suppression of PI3K/Akt pathway and EMT cascade contribute to the fibrosis-ameliorating effect of SBCH treatment. Furthermore, in vivo tracing and single-cell RNA sequencing revealed that SBCH induced the conversion of activated HSCs into hepatocyte-like cells (ciHeps), which integrated into liver tissue, repaired liver damage and restored liver integrity and function.

conclusionsSBCH mitigates liver fibrosis through multifaceted mechanisms, including the inhibition of HSC activation, suppression of fibrogenic activity and regulation of key signalling pathways such as PI3K/Akt and EMT. In addition, SBCH induces the trans-differentiation of activated HSCs into hepatocyte-like cells (ciHeps), effectively reducing pathogenic HSCs while increasing functional ciHeps. This dual-target approach not only facilitates liver tissue repair but also restores liver function, offering a promising therapeutic strategy for liver fibrosis and cirrhosis, with potential applications in conditions arising from various aetiologies of liver injury.

Indexed as

BenzamidesDioxolesGlycogen Synthase Kinase 3Hepatic Stellate CellsLiver CirrhosisPyridinesPyrimidinesTransforming Growth Factor betaAnimalsCarbon TetrachlorideCell TransdifferentiationDiethylnitrosamineDisease Models, AnimalLiverMaleMice4-(5-benzo(1,3)dioxol-5-yl-4-pyridin-2-yl-1H-imidazol-2-yl)benzamideBenzamidesCarbon TetrachlorideChir 99021DiethylnitrosamineDioxolesGlycogen Synthase Kinase 3PyridinesPyrimidinesTransforming Growth Factor betahepatic stellate cellshepatocyteslineage tracingliver fibrosis and cirrhosistrans‐differentiation

Identifiers

PMID40575954
PMCPMC12203458

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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.