Evidence map›Paper›PMID 39875570›Full record

ReviewNature reviews. Drug discovery2025

FGF-based drug discovery: advances and challenges.

Gaozhi Chen, Lingfeng Chen, Xiaokun Li, Moosa Mohammadi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
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  6. Article
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  10. Article
  11. Article
  12. Review
  13. FGF family in health and disease.Molecular biomedicine · 2026
    Review
  14. Article
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  16. Article
  17. Article
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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

4 authors.

Gaozhi Chen *School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Lingfeng Chen *School of Pharmaceutical Sciences, Hangzhou Medical College, Hangzhou, Zhejiang, China.ORCID 0000-0003-0089-6559
Xiaokun LiSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China. xiaokunli@wmu.edu.cn.ORCID 0000-0002-6556-6262
Moosa MohammadiInstitute of Cell Growth Factor, Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision, and Brain Health, Wenzhou, Zhejiang, China. mohammadimoosa@gmail.com.ORCID 0000-0003-2434-9437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fibroblast growth factor (FGF) family comprises 15 paracrine-acting and 3 endocrine-acting polypeptides, which govern a multitude of processes in human development, metabolism and tissue homeostasis. Therapeutic endocrine FGFs have recently advanced in clinical trials, with FGF19 and FGF21-based therapies on the cusp of approval for the treatment of primary sclerosing cholangitis and metabolic syndrome-associated steatohepatitis, respectively. By contrast, while paracrine FGFs were once thought to be promising drug candidates for wound healing, burns, tissue repair and ischaemic ailments based on their potent mitogenic and angiogenic properties, repeated failures in clinical trials have led to the widespread perception that the development of paracrine FGF-based drugs is not feasible. However, the observation that paracrine FGFs can exert FGF hormone-like metabolic activities has restored interest in these FGFs. The recent structural elucidation of the FGF cell surface signalling machinery and the formulation of a new threshold model for FGF signalling specificity have paved the way for therapeutically harnessing paracrine FGFs for the treatment of a range of metabolic diseases.

Indexed as

Drug DiscoveryFibroblast Growth FactorsAnimalsHumansSignal TransductionFibroblast Growth Factors

Identifiers

What Socratic 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 Socratic graph.