Journal Article Epublish
PubMed: 40772274 DOI: 10.3389/fgene.2025.1615268
Identification of key genes associated with infertile endometriosis based on bioinformatic analysis.
Front Genet 16:1615268
Authors: Linlin Chang, Hongjuan Ye, Min Hou, Xin Xie, Yang Wang, Jie Cheng, Rongxiang Wang, Xiaocong Chen, Xinxin Quan, Lihua Sun, Songguo Xue, Liya Shi
Affiliations
- Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
- The Shanghai Towako Hospital, Shanghai, China.
- Department of Reproductive Medicine, International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University, Shanghai, China.
- Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
- Center for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
- Department of Reproductive Medicine Center, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
- Department of Reproductive Medicine Center, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China. Department of Obstetrics and Gynecology, Ji 'an Hospital, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Abstract
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 database to identify differentially expressed genes (DEGs) between control and endometriosis. The STRING database and Cytoscape software constructed protein-protein interaction 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 co-expressed mRNAs and miRNAs. Furthermore, cordycepin showed high drug-targeting relevance in infertile endometriosis.
Conclusion
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 infertility-related endometriosis.
MeSH
Endometriosis, Genes, Fertility, Mitosis, Micrornas, Infertility, Biomarkers, Therapeutics