Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis
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 af...
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| Veröffentlicht in: | Experimental and therapeutic medicine 2020-01, Vol.19 (1), p.264-272 |
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| creator | 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 |
| description | 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 |
| doi_str_mv | 10.3892/etm.2019.8214 |
| format | Article |
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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.</description><identifier>ISSN: 1792-0981</identifier><identifier>EISSN: 1792-1015</identifier><identifier>DOI: 10.3892/etm.2019.8214</identifier><identifier>PMID: 31853298</identifier><language>eng</language><publisher>Greece: Spandidos Publications</publisher><subject>Anopheles ; Biochemistry ; Bioinformatics ; Biotechnology industries ; Cancer ; Cell adhesion & migration ; Computational biology ; Data processing ; Datasets ; Disease ; Diseases ; Dysmenorrhea ; Endometriosis ; Gene expression ; Genes ; Genomes ; Genomics ; Gynecological diseases ; Infertility ; Medical diagnosis ; Messenger RNA ; Pelvic pain ; Protein-protein interactions ; Proteins ; RNA ; Software ; Visualization ; Women</subject><ispartof>Experimental and therapeutic medicine, 2020-01, Vol.19 (1), p.264-272</ispartof><rights>Copyright: © Dai et al.</rights><rights>COPYRIGHT 2020 Spandidos Publications</rights><rights>Copyright Spandidos Publications UK Ltd. 2020</rights><rights>Copyright: © Dai et al. 2019</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-5a9370affafb6fb85c945f30a7566d8b235a40a9c73575350da45e326edc27ba3</citedby><cites>FETCH-LOGICAL-c412t-5a9370affafb6fb85c945f30a7566d8b235a40a9c73575350da45e326edc27ba3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909483/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909483/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27922,27923,53789,53791</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31853298$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dai, Fang-Fang</creatorcontrib><creatorcontrib>Bao, An-Yu</creatorcontrib><creatorcontrib>Luo, Bing</creatorcontrib><creatorcontrib>Zeng, Zi-Hang</creatorcontrib><creatorcontrib>Pu, Xiao-Li</creatorcontrib><creatorcontrib>Wang, Yan-Qing</creatorcontrib><creatorcontrib>Zhang, Li</creatorcontrib><creatorcontrib>Xian, Shu</creatorcontrib><creatorcontrib>Yuan, Meng-Qin</creatorcontrib><creatorcontrib>Yang, Dong-Yong</creatorcontrib><creatorcontrib>Liu, Shi-Yi</creatorcontrib><creatorcontrib>Cheng, Yan-Xiang</creatorcontrib><title>Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis</title><title>Experimental and therapeutic medicine</title><addtitle>Exp Ther Med</addtitle><description>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.</description><subject>Anopheles</subject><subject>Biochemistry</subject><subject>Bioinformatics</subject><subject>Biotechnology industries</subject><subject>Cancer</subject><subject>Cell adhesion & migration</subject><subject>Computational biology</subject><subject>Data processing</subject><subject>Datasets</subject><subject>Disease</subject><subject>Diseases</subject><subject>Dysmenorrhea</subject><subject>Endometriosis</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Gynecological diseases</subject><subject>Infertility</subject><subject>Medical diagnosis</subject><subject>Messenger RNA</subject><subject>Pelvic pain</subject><subject>Protein-protein interactions</subject><subject>Proteins</subject><subject>RNA</subject><subject>Software</subject><subject>Visualization</subject><subject>Women</subject><issn>1792-0981</issn><issn>1792-1015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNptkk1v1DAQhiMEolXpkSuKxIXLLv6IHfuCVFVAK1XiAmdr4oxTV4m92NmF_AL-No66LRRhH2yNn3lHM36r6jUlW640e4_ztGWE6q1itHlWndJWsw0lVDw_3olW9KQ6z_mOlCUkVUq8rE44VYIzrU6rX9c9htk7b2H2MdTR1b13DtMahXFcavy5S5gz9vWAAXMNoa-zHwKMPgz1DubbH7Dk2odDHA-F8qHG0McJ5-Rj9rnulhKbcUgwl-fORx9cTFOpZ1c1GJdCvapeOBgznh_Ps-rbp49fL682N18-X19e3GxsQ9m8EaB5S8A5cJ10nRJWN8JxAq2Qslcd4wIaAtq2XLSCC9JDI5Azib1lbQf8rPpwr7vbd1MJljYTjGaX_ARpMRG8efoS_K0Z4sFITXSjeBF4dxRI8fse82wmny2OIwSM-2wYZ6oVLdUr-vYf9C7uU2l4pXj5wFbK5g81wIhmnU2pa1dRcyGp4JJzqQu1_Q9Vdo-TtzGg8yX-JGFzn2BTzDmhe-yRErOaxxTzmNU8ZjVP4d_8PZhH-sEq_DfnHsMh</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Dai, Fang-Fang</creator><creator>Bao, An-Yu</creator><creator>Luo, Bing</creator><creator>Zeng, Zi-Hang</creator><creator>Pu, Xiao-Li</creator><creator>Wang, Yan-Qing</creator><creator>Zhang, Li</creator><creator>Xian, Shu</creator><creator>Yuan, Meng-Qin</creator><creator>Yang, Dong-Yong</creator><creator>Liu, Shi-Yi</creator><creator>Cheng, Yan-Xiang</creator><general>Spandidos Publications</general><general>Spandidos Publications UK Ltd</general><general>D.A. 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Experimental and therapeutic medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dai, Fang-Fang</au><au>Bao, An-Yu</au><au>Luo, Bing</au><au>Zeng, Zi-Hang</au><au>Pu, Xiao-Li</au><au>Wang, Yan-Qing</au><au>Zhang, Li</au><au>Xian, Shu</au><au>Yuan, Meng-Qin</au><au>Yang, Dong-Yong</au><au>Liu, Shi-Yi</au><au>Cheng, Yan-Xiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis</atitle><jtitle>Experimental and therapeutic medicine</jtitle><addtitle>Exp Ther Med</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>19</volume><issue>1</issue><spage>264</spage><epage>272</epage><pages>264-272</pages><issn>1792-0981</issn><eissn>1792-1015</eissn><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.</abstract><cop>Greece</cop><pub>Spandidos Publications</pub><pmid>31853298</pmid><doi>10.3892/etm.2019.8214</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Anopheles Biochemistry Bioinformatics Biotechnology industries Cancer Cell adhesion & migration Computational biology Data processing Datasets Disease Diseases Dysmenorrhea Endometriosis Gene expression Genes Genomes Genomics Gynecological diseases Infertility Medical diagnosis Messenger RNA Pelvic pain Protein-protein interactions Proteins RNA Software Visualization Women |
| title | Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis |
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