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基于生物信息学分析鉴定与不孕性子宫内膜异位症相关的关键基因

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

作者信息

Chang Linlin, Ye Hongjuan, Hou Min, Xie Xin, Wang Yang, Cheng Jie, Wang Rongxiang, Chen Xiaocong, Quan Xinxin, Sun Lihua, Xue Songguo, Shi Liya

机构信息

Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.

The Shanghai Towako Hospital, Shanghai, China.

出版信息

Front Genet. 2025 Jul 23;16:1615268. doi: 10.3389/fgene.2025.1615268. eCollection 2025.

DOI:10.3389/fgene.2025.1615268
PMID:40772274
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12325009/
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.

摘要

背景

子宫内膜异位症是育龄期女性的常见疾病。然而，其背后的分子机制仍不清楚。因此，需要新的生物标志物和治疗靶点来改善对不孕女性的诊断和治疗。

方法

从基因表达综合数据库下载微阵列数据集GSE7305、GSE7307和GSE51981，以鉴定对照组和子宫内膜异位症之间的差异表达基因（DEGs）。STRING数据库和Cytoscape软件构建了蛋白质-蛋白质相互作用和枢纽基因网络。同时，对这三个数据集进行筛选，以找出与有丝分裂相关的共差异表达基因。随后，我们鉴定了与有丝分裂相关基因和枢纽基因均相关的有丝分裂相关枢纽基因（MRHGs）。接下来，通过基因本体论（GO）注释和京都基因与基因组百科全书（KEGG）通路对靶基因进行富集分析，并构建mRNA- miRNA网络。最后，分别使用GSE25628和GSE6364验证MRHGs的表达，同时使用GSE120103确定有丝分裂相关基因对女性生育能力的影响。

结果

在子宫内膜异位症数据集中共鉴定出93个DEGs。然后，我们确定了11个潜在的有丝分裂相关下调枢纽基因，其中8个显示出良好的子宫内膜异位症诊断特性，2个显示出良好的不孕子宫内膜异位症诊断特性。主要富集的GO功能表明，细胞周期有丝分裂途径可能是子宫内膜异位症的关键途径。同时，通过选择共表达的mRNA和miRNA构建了mRNA- miRNA相互作用网络。此外，虫草素在不孕子宫内膜异位症中显示出较高的药物靶向相关性。

结论

我们鉴定出8个有丝分裂相关枢纽基因作为诊断和治疗子宫内膜异位症的潜在生物标志物。CENPE和CCNA2可能通过影响子宫内膜分泌期转变而与不孕子宫内膜异位症相关。此外，虫草素可能是与不孕相关子宫内膜异位症患者的一种潜在临床治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/58e9c2c39226/fgene-16-1615268-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/b6dc0ae40413/fgene-16-1615268-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/46e8a7da8d8a/fgene-16-1615268-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/8df03cadfe14/fgene-16-1615268-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/97214908a4c7/fgene-16-1615268-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/e2e3bb15920c/fgene-16-1615268-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/d63979f52845/fgene-16-1615268-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/58e9c2c39226/fgene-16-1615268-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/b6dc0ae40413/fgene-16-1615268-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/46e8a7da8d8a/fgene-16-1615268-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/8df03cadfe14/fgene-16-1615268-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/97214908a4c7/fgene-16-1615268-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/e2e3bb15920c/fgene-16-1615268-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/d63979f52845/fgene-16-1615268-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12325009/58e9c2c39226/fgene-16-1615268-g007.jpg

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