Evidence map›Paper›PMID 41120378›Full record

ArticleScientific reports2025

Integrative transcriptomic analysis identifies shared EndMT-related gene signatures in endometriosis and recurrent miscarriage.

Yue Liang, Liangcheng Yu, Qingde Zhou, Danjie Su, Lu Wang, Cong Li, Jingjing Wang, Haihui Wang, Jie Dong, Xifeng Xiao and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Yue Liang *Department of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Liangcheng Yu *Reproductive Medicine Center and Prenatal Diagnosis Center, 901st Hospital of PLA Joint Logistic Support Force, Hefei, Anhui, People's Republic of China.
Qingde ZhouDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Danjie SuDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Lu WangDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Cong LiDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Jingjing WangDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Haihui WangSchool of Basic Medical Sciences, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China.
Jie DongDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China. dongjie2020@fmmu.edu.cn.
Xifeng XiaoDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China. xxfeng926@163.com.
Xiaohong WangDepartment of Gynecology and Obstetrics and Reproductive Medicine Center, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China. wangxh919@fmmu.edu.cn.

Funding

National Natural Science Foundation of China 82101794National Natural Science Foundation of China 82271734
6 · The paper itself

Abstract

Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, focusing on the dysregulation of EndMT-related genes (EndMTRGs). Transcriptomic datasets of EMs and RM were retrieved from the gene expression omnibus (GEO) database. Specifically, GSE120103 includes 18 endometriosis and 18 control samples, and GSE165004 includes 24 recurrent miscarriage and 24 control samples. Differentially expressed gene (DEG) analysis and EndMTRG profiling were performed to identify key pathways and hub genes associated with EndMT. Functional enrichment analyses, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and gene set enrichment analysis (GSEA), were conducted. A protein-protein interaction (PPI) network was constructed via the STRING database, and hub genes were identified using cytoHubba algorithms. Immune cell infiltration patterns were evaluated through single-sample GSEA (ssGSEA). Additionally, support vector machine recursive feature elimination (SVM-RFE) was applied as a supplementary method to assist key gene selection, and nomograms were developed for preliminary risk prediction modeling. A total of 13 EndMTRGs were identified, with key genes such as FGF2, ITGB1, VIM, NR4A1, MAPK1, SMAD1, TUBB3, and CDH11 validated across external datasets. ROC curve analysis demonstrated high diagnostic performance of these genes. Regulatory networks involving RNA-binding proteins and transcription factors were delineated. Immune cell-related gene set enrichment analysis (ssGSEA) revealed distinct immune signatures, notably involving gamma-delta T (γδ T) cells and monocytes in EMs, and T follicular helper (Tfh) cells and natural killer (NK) cells in RM. Nomograms based on key genes exhibited reasonable predictive performance. This study elucidates the dysregulated EndMT landscape shared by endometriosis and recurrent miscarriage, identifying common gene signatures and immune features. These findings provide molecular insights into the shared pathogenesis of these conditions and highlight potential targets for future translational research.

Indexed as

Abortion, HabitualEndometriosisEpithelial-Mesenchymal TransitionGene Expression ProfilingTranscriptomeComputational BiologyEndothelial-Mesenchymal TransitionFemaleGene OntologyGene Regulatory NetworksHumansPregnancyProtein Interaction MapsBiomarkerEndometriosisEndothelial-mesenchymal transitionImmune infiltrationMachine learningRecurrent miscarriage

Identifiers

PMID41120378
PMCPMC12540761

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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.