Identification of Candidate Gene Signatures and Regulatory Networks in Endometriosis and its Related Infertility by Integrated Analysis

子宫内膜异位症 生物 候选基因 基因 基因调控网络 不育 计算生物学 小RNA 生物信息学 基因表达 遗传学 医学 病理 怀孕
作者
Qiutong Li,Min Xi,Fangrong Shen,Fengqing Fu,Juan Wang,Youguo Chen,Jinhua Zhou
出处
期刊:Reproductive Sciences [Springer Nature]
卷期号:29 (2): 411-426 被引量:4
标识
DOI:10.1007/s43032-021-00766-1
摘要

Endometriosis is a common gynecological disease associated with infertility, and it represents an economic burden worldwide. However, the molecular mechanisms underlying endometriosis development have not yet been fully elucidated. Here, we aimed to identify reliable key genes and the related regulatory network that may be involved in endometriosis. Differentially expressed genes (DEGs) were identified through integrated analysis of four expression datasets of endometriosis from Gene Expression Omnibus. Gene functional analysis and protein-protein interaction network construction were performed to reveal the potential function of DEGs. Subsequently, candidate hub genes were defined and validated in GSE105764 dataset, and the associated regulatory networks were constructed. Additionally, GSE120103 dataset was applied to identify the differential expression between the infertile and fertile groups of patients with stage IV endometriosis. Finally, real-time quantitative polymerase chain reaction analysis was performed to identify the differential expression of hub genes in the collected clinical specimens. Robust rank aggregation integrated analysis determined 158 DEGs. Epithelial cell differentiation was the most significantly enriched biological process, and leukocyte transendothelial migration was the most significantly enriched pathway. Eight hub genes including CLDN3, CLDN5, CLDN7, CLDN11, HOXC8, HOXC6, HOXB6, and HOXB7 were identified, and most of these were validated as abnormally expressed genes in both the infertile group and patients with endometriosis. Transcriptional factors and microRNAs related to these genes were identified. Altogether, our integrated analysis identified critical gene signatures, involved pathways, and regulatory networks, which could provide clinically significant insights into the molecular mechanisms underlying endometriosis and its related infertility.
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