Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis
Barrett's esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE fr...
Gespeichert in:
Veröffentlicht in: | PloS one 2021-11, Vol.16 (11), p.e0260353-e0260353 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | e0260353 |
---|---|
container_issue | 11 |
container_start_page | e0260353 |
container_title | PloS one |
container_volume | 16 |
creator | Yao, Chengjiao Li, Yilin Luo, Lihong Xiong, Qin Zhong, Xiaowu Xie, Fengjiao Feng, Peimin |
description | Barrett's esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein-protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival. |
doi_str_mv | 10.1371/journal.pone.0260353 |
format | Article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2602244598</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A683695297</galeid><doaj_id>oai_doaj_org_article_3c17ff7a0e3d470faf53d3ef7603db8c</doaj_id><sourcerecordid>A683695297</sourcerecordid><originalsourceid>FETCH-LOGICAL-c571t-5d32364c43833c7b84bb1755d33fa097c14ba53eae83a42ab7ca48c7a07b5a5f3</originalsourceid><addsrcrecordid>eNqNk22L1DAQx4so3nn6DUQLgg8vdm2bpmnfCOvhw8LhwfnwNkzTSTdHm6xJKt7n8Aub7naPrdwLCTRh5jf_aSYzUfQ0TZYpYenbazNYDd1yazQuk6xICCX3otO0ItmiyBJy_-h8Ej1y7jpJKCmL4mF0QvIyLQN_Gv1ZN6i9kkqAV0bHRsa9uvqycjHoJm5Ro4ulsfHWYqOEV7qN34O16P0rF6Mz2w20gwtu01p0bvR7c3AgdDEEfSPACqVND_GwQ3YpFn34xEp7bC14bEJG6G6cco-jBxI6h0-m_Sz6_vHDt_PPi4vLT-vz1cVCUJb6BW1IRopc5KQkRLC6zOs6ZTSYiYSkYiLNa6AEAUsCeQY1E5CXgkHCagpUkrPo-V532xnHp3o6HkqZZXlOqzIQ6z3RGLjmW6t6sDfcgOI7g7EtB-uV6JATkTIpgziSJmeJBElJQ1Cy8DBNXYqg9W7KNtQ9NiKU3UI3E517tNrw1vziZZFmlLAg8HoSsObngM7zXjmBXQcazbD_7yIvKKsC-uIf9O7bTVQL4QJKSxPyilGUr4qSFBXNqjHt8g4qrAZ7JULzSRXss4A3s4DAePztWxic4-uvV__PXv6Ysy-P2E1oLr9xphvGvnVzMN-DwhrnLMrbIqcJH2fnUA0-zg6fZieEPTt-oNugw7CQv4hdFxc</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2602244598</pqid></control><display><type>article</type><title>Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Public Library of Science (PLoS)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Yao, Chengjiao ; Li, Yilin ; Luo, Lihong ; Xiong, Qin ; Zhong, Xiaowu ; Xie, Fengjiao ; Feng, Peimin</creator><contributor>Andrés-León, Eduardo</contributor><creatorcontrib>Yao, Chengjiao ; Li, Yilin ; Luo, Lihong ; Xiong, Qin ; Zhong, Xiaowu ; Xie, Fengjiao ; Feng, Peimin ; Andrés-León, Eduardo</creatorcontrib><description>Barrett's esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein-protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0260353</identifier><identifier>PMID: 34818353</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adenocarcinoma ; Adenocarcinoma - diagnosis ; Adenocarcinoma - genetics ; Adenocarcinoma - pathology ; Analysis ; Barrett Esophagus - diagnosis ; Barrett Esophagus - genetics ; Barrett Esophagus - pathology ; Biology and life sciences ; Biomarkers ; Chinese medicine ; Data collection ; Datasets ; Disease Progression ; DNA microarrays ; E-cadherin ; Epithelium ; Epstein-Barr virus ; Esophageal cancer ; Esophageal Neoplasms - diagnosis ; Esophageal Neoplasms - genetics ; Esophageal Neoplasms - pathology ; Esophagus ; Gene expression ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Genes ; Genetic aspects ; Genomes ; Hospitals ; Humans ; IL-1β ; Infections ; Intercellular adhesion molecule 1 ; Interleukin 1 ; Kinases ; Laboratories ; Medical schools ; Medicine and Health Sciences ; MicroRNA ; MicroRNAs ; MicroRNAs - genetics ; miRNA ; Prognosis ; Proteins ; Research and Analysis Methods ; Ribonucleic acid ; RNA ; Survival ; Survival analysis ; Throat cancer ; Transcriptome ; Viruses</subject><ispartof>PloS one, 2021-11, Vol.16 (11), p.e0260353-e0260353</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Yao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Yao et al 2021 Yao et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c571t-5d32364c43833c7b84bb1755d33fa097c14ba53eae83a42ab7ca48c7a07b5a5f3</cites><orcidid>0000-0002-7716-368X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612537/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612537/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34818353$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Andrés-León, Eduardo</contributor><creatorcontrib>Yao, Chengjiao</creatorcontrib><creatorcontrib>Li, Yilin</creatorcontrib><creatorcontrib>Luo, Lihong</creatorcontrib><creatorcontrib>Xiong, Qin</creatorcontrib><creatorcontrib>Zhong, Xiaowu</creatorcontrib><creatorcontrib>Xie, Fengjiao</creatorcontrib><creatorcontrib>Feng, Peimin</creatorcontrib><title>Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Barrett's esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein-protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival.</description><subject>Adenocarcinoma</subject><subject>Adenocarcinoma - diagnosis</subject><subject>Adenocarcinoma - genetics</subject><subject>Adenocarcinoma - pathology</subject><subject>Analysis</subject><subject>Barrett Esophagus - diagnosis</subject><subject>Barrett Esophagus - genetics</subject><subject>Barrett Esophagus - pathology</subject><subject>Biology and life sciences</subject><subject>Biomarkers</subject><subject>Chinese medicine</subject><subject>Data collection</subject><subject>Datasets</subject><subject>Disease Progression</subject><subject>DNA microarrays</subject><subject>E-cadherin</subject><subject>Epithelium</subject><subject>Epstein-Barr virus</subject><subject>Esophageal cancer</subject><subject>Esophageal Neoplasms - diagnosis</subject><subject>Esophageal Neoplasms - genetics</subject><subject>Esophageal Neoplasms - pathology</subject><subject>Esophagus</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene Regulatory Networks</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Hospitals</subject><subject>Humans</subject><subject>IL-1β</subject><subject>Infections</subject><subject>Intercellular adhesion molecule 1</subject><subject>Interleukin 1</subject><subject>Kinases</subject><subject>Laboratories</subject><subject>Medical schools</subject><subject>Medicine and Health Sciences</subject><subject>MicroRNA</subject><subject>MicroRNAs</subject><subject>MicroRNAs - genetics</subject><subject>miRNA</subject><subject>Prognosis</subject><subject>Proteins</subject><subject>Research and Analysis Methods</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Survival</subject><subject>Survival analysis</subject><subject>Throat cancer</subject><subject>Transcriptome</subject><subject>Viruses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk22L1DAQx4so3nn6DUQLgg8vdm2bpmnfCOvhw8LhwfnwNkzTSTdHm6xJKt7n8Aub7naPrdwLCTRh5jf_aSYzUfQ0TZYpYenbazNYDd1yazQuk6xICCX3otO0ItmiyBJy_-h8Ej1y7jpJKCmL4mF0QvIyLQN_Gv1ZN6i9kkqAV0bHRsa9uvqycjHoJm5Ro4ulsfHWYqOEV7qN34O16P0rF6Mz2w20gwtu01p0bvR7c3AgdDEEfSPACqVND_GwQ3YpFn34xEp7bC14bEJG6G6cco-jBxI6h0-m_Sz6_vHDt_PPi4vLT-vz1cVCUJb6BW1IRopc5KQkRLC6zOs6ZTSYiYSkYiLNa6AEAUsCeQY1E5CXgkHCagpUkrPo-V532xnHp3o6HkqZZXlOqzIQ6z3RGLjmW6t6sDfcgOI7g7EtB-uV6JATkTIpgziSJmeJBElJQ1Cy8DBNXYqg9W7KNtQ9NiKU3UI3E517tNrw1vziZZFmlLAg8HoSsObngM7zXjmBXQcazbD_7yIvKKsC-uIf9O7bTVQL4QJKSxPyilGUr4qSFBXNqjHt8g4qrAZ7JULzSRXss4A3s4DAePztWxic4-uvV__PXv6Ysy-P2E1oLr9xphvGvnVzMN-DwhrnLMrbIqcJH2fnUA0-zg6fZieEPTt-oNugw7CQv4hdFxc</recordid><startdate>20211124</startdate><enddate>20211124</enddate><creator>Yao, Chengjiao</creator><creator>Li, Yilin</creator><creator>Luo, Lihong</creator><creator>Xiong, Qin</creator><creator>Zhong, Xiaowu</creator><creator>Xie, Fengjiao</creator><creator>Feng, Peimin</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-7716-368X</orcidid></search><sort><creationdate>20211124</creationdate><title>Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis</title><author>Yao, Chengjiao ; Li, Yilin ; Luo, Lihong ; Xiong, Qin ; Zhong, Xiaowu ; Xie, Fengjiao ; Feng, Peimin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c571t-5d32364c43833c7b84bb1755d33fa097c14ba53eae83a42ab7ca48c7a07b5a5f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adenocarcinoma</topic><topic>Adenocarcinoma - diagnosis</topic><topic>Adenocarcinoma - genetics</topic><topic>Adenocarcinoma - pathology</topic><topic>Analysis</topic><topic>Barrett Esophagus - diagnosis</topic><topic>Barrett Esophagus - genetics</topic><topic>Barrett Esophagus - pathology</topic><topic>Biology and life sciences</topic><topic>Biomarkers</topic><topic>Chinese medicine</topic><topic>Data collection</topic><topic>Datasets</topic><topic>Disease Progression</topic><topic>DNA microarrays</topic><topic>E-cadherin</topic><topic>Epithelium</topic><topic>Epstein-Barr virus</topic><topic>Esophageal cancer</topic><topic>Esophageal Neoplasms - diagnosis</topic><topic>Esophageal Neoplasms - genetics</topic><topic>Esophageal Neoplasms - pathology</topic><topic>Esophagus</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene Regulatory Networks</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Hospitals</topic><topic>Humans</topic><topic>IL-1β</topic><topic>Infections</topic><topic>Intercellular adhesion molecule 1</topic><topic>Interleukin 1</topic><topic>Kinases</topic><topic>Laboratories</topic><topic>Medical schools</topic><topic>Medicine and Health Sciences</topic><topic>MicroRNA</topic><topic>MicroRNAs</topic><topic>MicroRNAs - genetics</topic><topic>miRNA</topic><topic>Prognosis</topic><topic>Proteins</topic><topic>Research and Analysis Methods</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>Survival</topic><topic>Survival analysis</topic><topic>Throat cancer</topic><topic>Transcriptome</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yao, Chengjiao</creatorcontrib><creatorcontrib>Li, Yilin</creatorcontrib><creatorcontrib>Luo, Lihong</creatorcontrib><creatorcontrib>Xiong, Qin</creatorcontrib><creatorcontrib>Zhong, Xiaowu</creatorcontrib><creatorcontrib>Xie, Fengjiao</creatorcontrib><creatorcontrib>Feng, Peimin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yao, Chengjiao</au><au>Li, Yilin</au><au>Luo, Lihong</au><au>Xiong, Qin</au><au>Zhong, Xiaowu</au><au>Xie, Fengjiao</au><au>Feng, Peimin</au><au>Andrés-León, Eduardo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-11-24</date><risdate>2021</risdate><volume>16</volume><issue>11</issue><spage>e0260353</spage><epage>e0260353</epage><pages>e0260353-e0260353</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Barrett's esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein-protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34818353</pmid><doi>10.1371/journal.pone.0260353</doi><tpages>e0260353</tpages><orcidid>https://orcid.org/0000-0002-7716-368X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-11, Vol.16 (11), p.e0260353-e0260353 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2602244598 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Adenocarcinoma Adenocarcinoma - diagnosis Adenocarcinoma - genetics Adenocarcinoma - pathology Analysis Barrett Esophagus - diagnosis Barrett Esophagus - genetics Barrett Esophagus - pathology Biology and life sciences Biomarkers Chinese medicine Data collection Datasets Disease Progression DNA microarrays E-cadherin Epithelium Epstein-Barr virus Esophageal cancer Esophageal Neoplasms - diagnosis Esophageal Neoplasms - genetics Esophageal Neoplasms - pathology Esophagus Gene expression Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genes Genetic aspects Genomes Hospitals Humans IL-1β Infections Intercellular adhesion molecule 1 Interleukin 1 Kinases Laboratories Medical schools Medicine and Health Sciences MicroRNA MicroRNAs MicroRNAs - genetics miRNA Prognosis Proteins Research and Analysis Methods Ribonucleic acid RNA Survival Survival analysis Throat cancer Transcriptome Viruses |
title | Identification of miRNAs and genes for predicting Barrett's esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T17%3A12%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Identification%20of%20miRNAs%20and%20genes%20for%20predicting%20Barrett's%20esophagus%20progressing%20to%20esophageal%20adenocarcinoma%20using%20miRNA-mRNA%20integrated%20analysis&rft.jtitle=PloS%20one&rft.au=Yao,%20Chengjiao&rft.date=2021-11-24&rft.volume=16&rft.issue=11&rft.spage=e0260353&rft.epage=e0260353&rft.pages=e0260353-e0260353&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0260353&rft_dat=%3Cgale_plos_%3EA683695297%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2602244598&rft_id=info:pmid/34818353&rft_galeid=A683695297&rft_doaj_id=oai_doaj_org_article_3c17ff7a0e3d470faf53d3ef7603db8c&rfr_iscdi=true |