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

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. Similar content being viewed by others Data Availability The datasets (GSE7305, GSE11691, GSE25628, GSE23339, GSE105764, and GSE120103) used for this study can be found in the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/). Code Availability All code used during the study are available from the corresponding author by request. Abbreviations - GO: - Gene Ontology - KEGG: - Kyoto Encyclopedia of Genes and Genomes - DEG: - Differentially expressed gene - PPI: - Protein–protein interaction - TF: - Transcription factor - MCODE: - Molecular complex detection - RRA: - Robust rank aggregation - RT-qPCR: - Real-time quantitative polymerase chain reaction - SNP: - Single-nucleotide polymorphism - GWAS: - Genome-wide association study

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The authors would like to acknowledge the GEO database for the gene expression profiles of endometriosis. Funding This work was supported by the National Natural Science Foundation of China (No.81302275, 81672560), the GuSu Medical Youth Talent (No. GSWS2019034), and the Project of Jiangsu Provincial Maternal and Child Health Association (No. FYX201709). Author information Authors and Affiliations Contributions All the listed authors have made essential contributions to the work. Qiutong Li and Min Xi analyzed the data and drafted the original manuscript. Fangrong Shen and Fengqing Fu interpreted and validated the results. Juan Wang conceived the study and participated in its design and coordination. Jinhua Zhou and Youguo Chen supervised the project design and reviewed the manuscript. All authors have read and approved the final manuscript for publication. Corresponding authors Ethics declarations Ethics Approval The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from all the patients and the retrospective study involving human participants was approved by The Ethics Committee of The First Affiliated Hospital of Soochow University (Soochow, China). All the data from the public databases were not involved. Consent to Participate Not applicable. Consent for Publication All the co-authors have agreed to publication in the journal. Conflict of Interest The authors declare no competing interests. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Qiutong Li and Min Xi contributed equally to this work. Supplementary Information Below is the link to the electronic supplementary material. Rights and permissions About this article Cite this article Li, Q., Xi, M., Shen, F. et al. Identification of Candidate Gene Signatures and Regulatory Networks in Endometriosis and its Related Infertility by Integrated Analysis. Reprod. Sci. 29, 411–426 (2022). https://doi.org/10.1007/s43032-021-00766-1 Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1007/s43032-021-00766-1