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

  • Endometrios: Original Article
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Abstract

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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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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Acknowledgements

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

  1. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China

    Qiutong Li, Min Xi, Fangrong Shen, Fengqing Fu, Juan Wang, Youguo Chen & Jinhua Zhou

  2. Clinical Research Center of Obstetrics and Gynecology, Jiangsu Key Laboratory of Clinical Immunology, Soochow University, Suzhou, People’s Republic of China

    Qiutong Li, Min Xi, Fangrong Shen, Fengqing Fu, Juan Wang, Youguo Chen & Jinhua Zhou

  3. Jiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China

    Qiutong Li, Min Xi, Fangrong Shen, Fengqing Fu, Juan Wang, Youguo Chen & Jinhua Zhou

  4. Jiangsu Key Laboratory of Clinical Immunology, Soochow University, Suzhou, People’s Republic of China

    Qiutong Li, Min Xi, Fangrong Shen, Fengqing Fu, Juan Wang, Youguo Chen & Jinhua Zhou

Authors
  1. Qiutong Li
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  2. Min Xi
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  3. Fangrong Shen
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  4. Fengqing Fu
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  5. Juan Wang
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  6. Youguo Chen
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  7. Jinhua Zhou
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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

Correspondence to Juan Wang, Youguo Chen or Jinhua Zhou.

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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.

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Not applicable.

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All the co-authors have agreed to publication in the journal.

Conflict of Interest

The authors declare no competing interests.

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Qiutong Li and Min Xi contributed equally to this work.

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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

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  • DOI: https://doi.org/10.1007/s43032-021-00766-1

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