Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis

Dai,Fang‑Fang; Bao,An‑Yu; Luo,Bing; Zeng,Zi‑Hang; Pu,Xiao‑Li; Wang,Yan‑Qing; Zhang,Li; Xian,Shu; Yuan,Meng‑Qin; Yang,Dong‑Yong; Liu,Shi‑Yi; Cheng,Yan‑Xiang

doi:10.3892/etm.2019.8214

Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis

Authors:
- Fang‑Fang Dai
- An‑Yu Bao
- Bing Luo
- Zi‑Hang Zeng
- Xiao‑Li Pu
- Yan‑Qing Wang
- Li Zhang
- Shu Xian
- Meng‑Qin Yuan
- Dong‑Yong Yang
- Shi‑Yi Liu
- Yan‑Xiang Cheng
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Affiliations: Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China, Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China, Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China, Department of Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China, Department of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China
Published online on: November 18, 2019 https://doi.org/10.3892/etm.2019.8214
Pages: 264-272
Copyright: © Dai et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Endometriosis is a common gynecological disease characterized by the presence and growth of endometrial tissue outside the uterus, including the pelvis and abdominal cavity. This condition causes various clinical symptoms, such as non‑menstrual pelvic pain, dysmenorrhea and infertility, seriously affecting the health and quality of life of women. To date, the specific mechanism and the key molecules of endometriosis remain uncertain. The purpose of the present study was to elucidate the mechanisms involved in the development and persistence of the disease. A number of mRNA expression profile datasets (namely GSE11691, GSE23339, GSE25628 and GSE78851) were downloaded from the Gene Expression Omnibus (GEO) database. These gene expression profiles were normalized, and the differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis. A total of 103 DEGs were screened upon excluding the genes that exhibited inconsistency of expression (P<0.05). Furthermore, the Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and construction of protein‑protein interaction networks of DEGs were performed using online software. The results revealed that the DEGs were closely associated with cell migration, adherens junction and hypoxia‑inducible factor signaling. In addition, immunohistochemical assay results were found to be consistent with the bioinformatics results. The present study may help us understand underlying molecular mechanisms and the development of endometriosis, which has a great clinical significance for early diagnosis of the disease.

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