Evidence map›Paper›PMID 37426659›Full record

ArticleFrontiers in immunology2023

Distinct subtypes of endometriosis identified based on stromal-immune microenvironment and gene expression: implications for hormone therapy.

Yuning Wang, Yun Chen, Yinping Xiao, Jingyao Ruan, Qi Tian, Qi Cheng, Kaikai Chang, Xiaofang Yi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
9.8field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 26 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Pain Phenotypes in Endometriosis: A Population-Based Study Using Latent Class Analysis.BJOG : an international journal of obstetrics and gynaecology · 2025
    Article
  8. Article
  9. New Potential Pharmacological Options for Endometriosis Associated Pain.International journal of molecular sciences · 2024
    Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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

8 authors at 1 institution in 1 country.

Yuning WangDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Yun ChenDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Yinping XiaoDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Jingyao RuanDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Qi TianDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Qi ChengDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Kaikai ChangDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Xiaofang YiDepartment of Gynecology, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Obstetrics and Gynecology Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Endometriosis (EMs) is a chronic inflammatory condition that is highly heterogeneous. Current clinical staging fails to accurately predict drug responses and prognosis. In this study, we aimed to reveal the heterogeneity of ectopic lesions and investigate the possible underlying mechanisms using transcriptomic data and clinical information. Methods: The EMs microarray dataset GSE141549 was obtained from the Gene Expression Omnibus database. Unsupervised hierarchical clustering was performed to identify EMs subtypes, which was followed by the functional enrichment analysis and estimation of immune infiltrates. Subtype-associated gene signatures were identified and further validated in other independent datasets, including GSE25628, E-MTAB-694, and GSE23339. Additionally, tissue microarrays (TMAs) were generated from premenopausal patients with EMs to investigate the potential clinical implications of the two identified subtypes. Results: The unsupervised clustering analysis revealed that ectopic EMs lesions can be classified into two distinct subtypes: stroma-enriched (S1) and immune-enriched (S2). The functional analysis revealed that S1 correlated with fibroblast activation and extracellular matrix remodeling in the ectopic milieu, whereas S2 was characterized by the upregulation of immune pathways and a higher positive correlation with the immunotherapy response. Moreover, we identified a subtype signature composed of FHL1 and SORBS1, and constructed a subtype diagnostic model. Based on the cohort data from the TMAs, we found that S2 was strongly associated with the failure of/intolerance to hormone therapy. Conclusions: This study identified two distinct subtypes that are varyingly associated with hormone resistance, stroma-immunity, and molecular features, thereby highlighting the importance of this stromal-immune heterogeneity in identifying EMs subtypes and providing novel insights into future personalized hormone-free therapy in EMs.

Indexed as

EndometriosisCluster AnalysisDatabases, FactualExtracellular MatrixFemaleHumansIntracellular Signaling Peptides and ProteinsLIM Domain ProteinsMuscle ProteinsTranscriptomeFHL1 protein, humanIntracellular Signaling Peptides and ProteinsLIM Domain ProteinsMuscle Proteinsendometriosisfibroblast activationheterogeneityimmune infiltrationsubtypeunsupervised hierarchical clustering

Identifiers

PMID37426659
PMCPMC10324653
OpenAlexW4381891869

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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.