Evidence map›Paper›PMID 41377662›Full record

ArticleiScience2025

A systematic characterization of fibroblast subtypes and heterogeneity.

Xiuli Zhu, Hongen Kang, Zhongming Zhao, Peilin Jia

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Xiuli ZhuChina National Center for Bioinformation, Beijing, China.
Hongen KangChina National Center for Bioinformation, Beijing, China.
Zhongming ZhaoDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Peilin JiaChina National Center for Bioinformation, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fibroblasts are essential components in development, disease, and treatment response, yet their diversity and function remain incompletely understood. Here, we constructed a comprehensive fibroblast landscape by integrating large-scale single-cell and single-nucleus RNA sequencing datasets spanning 60 major human organs and tissues across various developmental stages and biological conditions. We identified 16 fibroblast subtypes and systematically characterized their tissue specificities, transcriptional heterogeneity, and cell states. Further analyses revealed distinct fibroblast subtypes associated with pluripotency and senescence across tissues. Leveraging the well-defined fibroblast atlas, we demonstrated that different fibroblast subtypes were associated with various complex traits such as anthropometric and immune diseases. Furthermore, analysis using the subtype-specific gene activities in bulk cancer data revealed that myoCAF was a risk factor for patient survival. Collectively, our study provides a comprehensive fibroblast atlas, offering insights into the functions, heterogeneity, and clinical applications of fibroblast subtypes.

Indexed as

CancerTechnical aspects of cell biologyTranscriptomics

Identifiers

PMID41377662
PMCPMC12686731

What OpenQuestion holds

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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.