ORIGINAL RESEARCH article

Front. Genet.

Sec. Cytogenomics

Volume 16 - 2025 | doi: 10.3389/fgene.2025.1615268

Identification of key genes associated with infertile endometriosis based on bioinformatic analysis

Provisionally accepted
Liya  ShiLiya Shi1,2*Xiaocong  ChenXiaocong Chen1Ye  HongjuanYe Hongjuan3Xin  XieXin Xie4Yang  WangYang Wang5Jie  ChengJie Cheng6Linlin  ChangLinlin Chang7Songguo  XueSongguo Xue1*
  • 1Department of Reproductive Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
  • 2b Department of Obstetrics and Gynecology, Ji 'an Hospital, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China., Ji 'an, China
  • 3Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
  • 4Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, Shanghai Municipality, China
  • 5Department of Obstetrics and Gynecology, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
  • 6Center for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
  • 7Department of Obstetrics and Gynecology, Department of Obstetrics & Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China

The final, formatted version of the article will be published soon.

Background: Endometriosis is a common disease among women of childbearing age. However, the molecular mechanism behind it is still unknown. Therefore, new biomarkers and therapeutic targets are needed to improve the diagnosis and treatment of infertile women. Methods: Microarray datasets GSE7305, GSE7307, and GSE51981 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between control and endometriosis. The STRING database and Cytoscape software constructed protein-protein interaction (PPI) and hub gene networks. At the same time, the three data sets were screened for co-differentially expressed genes related to mitosis. Subsequently, we identified mitosis-related hub genes (MRHGs) associated with both mitosis-related genes and hub genes. Next, enrichment analysis for target genes was performed by Gene Ontology (GO) annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the mRNA-miRNA network was constructed. Finally, GSE25628 and GSE6364 were used to verify the expression of MRHGs individually, while GSE120103 was employed to ascertain the influence of mitosis-related genes on female fertility. Results: A total of 93 DEGs were identified in the endometriosis datasets. Then, we placed 11 potential mitosis-related downregulated hub genes, among which eight showed good diagnostic properties of endometriosis, and two showed good diagnostic properties of infertile endometriosis. The main enriched GO functions revealed that the cell cycle mitotic pathway may be the critical pathway in endometriosis. Meanwhile, mRNA-miRNA interaction networks were constructed by choosing coexpressed mRNAs and miRNAs. Furthermore, cordycepin showed high drugtargeting relevance in infertile endometriosis. Conclusions: We identified eight mitosis-related hub genes as potential biomarkers for diagnosing and treating endometriosis. CENPE and CCNA2 might be associated with infertile endometriosis by affecting the endometrial secretory phase transition. In addition, cordycepin may be a potential clinical treatment for people with infertilityrelated endometriosis. Keywords Endometriosis; infertility; differentially expressed genes; biomarkers; DEGs Highlights • This article uses bioinformatic methods to identify target genes for the treatment of endometriosis.• This article adopts a new search method for target genes based on the common characteristics of infertility and endometriosis.• Scan suitable therapeutic agents for target genes from the drug database.

Keywords: Endometriosis, Infertility, Differentially expressed genes, biomarkers, DEGs

Received: 21 Apr 2025; Accepted: 02 Jul 2025.

Copyright: © 2025 Shi, Chen, Hongjuan, Xie, Wang, Cheng, Chang and Xue. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Liya Shi, Department of Reproductive Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
Songguo Xue, Department of Reproductive Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China

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