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...

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Veröffentlicht in:PloS one 2021-11, Vol.16 (11), p.e0260353-e0260353
Hauptverfasser: Yao, Chengjiao, Li, Yilin, Luo, Lihong, Xiong, Qin, Zhong, Xiaowu, Xie, Fengjiao, Feng, Peimin
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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.
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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. 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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 - 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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>
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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
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