Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets

Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer,...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Functional & integrative genomics 2019-07, Vol.19 (4), p.645-658
Hauptverfasser: He, Kan, Li, Wen-Xing, Guan, Daogang, Gong, Mengting, Ye, Shoudong, Fang, Zekun, Huang, Jing-Fei, Lu, Aiping
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 658
container_issue 4
container_start_page 645
container_title Functional & integrative genomics
container_volume 19
creator He, Kan
Li, Wen-Xing
Guan, Daogang
Gong, Mengting
Ye, Shoudong
Fang, Zekun
Huang, Jing-Fei
Lu, Aiping
description Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.
doi_str_mv 10.1007/s10142-019-00670-7
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2190483405</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2189893843</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-8397433c5b88eefc024430983fecca56be08c78913329c6d005e62b383de02723</originalsourceid><addsrcrecordid>eNp9kc9u1DAQxi0EomXhBTggS1y4BCaZZGMfq6r8kVYgVSBxixxnsnJJ7MXjbNkX4XnxsqVIHDh5NP5939jzCfG8hNclQPuGSyjrqoBSFwDrFor2gTgva1RFq2v18L7Gr2fiCfMNADSg8bE4Q1CNxqY-Fz-vabtMJoV4kJ7SbYjfZCQbPKe42OSCl2GUo9uTJGbyyZlJzs7GcP3xguUYouQl7t0-t40304EdS-dlH8lwktZ4S1H2h9xLtI0mOb_N-izO-CDnY0E_djGbH2cNJhmmxE_Fo9FMTM_uzpX48vbq8-X7YvPp3YfLi01hsW1SoVC3NaJteqWIRgtVXSNohSNZa5p1T6Bsq3SJWGm7HvICaF31qHAgqNoKV-LVyXcXw_eFOHWzY0vTZDyFhbuq1FArrKHJ6Mt_0JuwxPzlI6W00qjyU1aiOlF5Q8yRxm4X3WzioSuhO6bWnVLrcmrd79S6Note3Fkv_UzDveRPTBnAE8D5ym8p_p39H9tf-KWkgg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2189893843</pqid></control><display><type>article</type><title>Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets</title><source>SpringerLink Journals</source><creator>He, Kan ; Li, Wen-Xing ; Guan, Daogang ; Gong, Mengting ; Ye, Shoudong ; Fang, Zekun ; Huang, Jing-Fei ; Lu, Aiping</creator><creatorcontrib>He, Kan ; Li, Wen-Xing ; Guan, Daogang ; Gong, Mengting ; Ye, Shoudong ; Fang, Zekun ; Huang, Jing-Fei ; Lu, Aiping</creatorcontrib><description>Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.</description><identifier>ISSN: 1438-793X</identifier><identifier>EISSN: 1438-7948</identifier><identifier>DOI: 10.1007/s10142-019-00670-7</identifier><identifier>PMID: 30859354</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Animal Genetics and Genomics ; Biochemistry ; Bioinformatics ; Biomedical and Life Sciences ; Breast cancer ; Cell Biology ; Gene expression ; Gene regulation ; Genomics ; Histocompatibility antigen HLA ; Interferon ; Life Sciences ; Microbial Genetics and Genomics ; MicroRNAs ; miRNA ; Original Article ; Plant Genetics and Genomics ; Precision medicine ; Stat1 protein ; Survival ; Survival analysis ; Transcription</subject><ispartof>Functional &amp; integrative genomics, 2019-07, Vol.19 (4), p.645-658</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Functional &amp; Integrative Genomics is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-8397433c5b88eefc024430983fecca56be08c78913329c6d005e62b383de02723</citedby><cites>FETCH-LOGICAL-c375t-8397433c5b88eefc024430983fecca56be08c78913329c6d005e62b383de02723</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10142-019-00670-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10142-019-00670-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30859354$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>He, Kan</creatorcontrib><creatorcontrib>Li, Wen-Xing</creatorcontrib><creatorcontrib>Guan, Daogang</creatorcontrib><creatorcontrib>Gong, Mengting</creatorcontrib><creatorcontrib>Ye, Shoudong</creatorcontrib><creatorcontrib>Fang, Zekun</creatorcontrib><creatorcontrib>Huang, Jing-Fei</creatorcontrib><creatorcontrib>Lu, Aiping</creatorcontrib><title>Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets</title><title>Functional &amp; integrative genomics</title><addtitle>Funct Integr Genomics</addtitle><addtitle>Funct Integr Genomics</addtitle><description>Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.</description><subject>Animal Genetics and Genomics</subject><subject>Biochemistry</subject><subject>Bioinformatics</subject><subject>Biomedical and Life Sciences</subject><subject>Breast cancer</subject><subject>Cell Biology</subject><subject>Gene expression</subject><subject>Gene regulation</subject><subject>Genomics</subject><subject>Histocompatibility antigen HLA</subject><subject>Interferon</subject><subject>Life Sciences</subject><subject>Microbial Genetics and Genomics</subject><subject>MicroRNAs</subject><subject>miRNA</subject><subject>Original Article</subject><subject>Plant Genetics and Genomics</subject><subject>Precision medicine</subject><subject>Stat1 protein</subject><subject>Survival</subject><subject>Survival analysis</subject><subject>Transcription</subject><issn>1438-793X</issn><issn>1438-7948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kc9u1DAQxi0EomXhBTggS1y4BCaZZGMfq6r8kVYgVSBxixxnsnJJ7MXjbNkX4XnxsqVIHDh5NP5939jzCfG8hNclQPuGSyjrqoBSFwDrFor2gTgva1RFq2v18L7Gr2fiCfMNADSg8bE4Q1CNxqY-Fz-vabtMJoV4kJ7SbYjfZCQbPKe42OSCl2GUo9uTJGbyyZlJzs7GcP3xguUYouQl7t0-t40304EdS-dlH8lwktZ4S1H2h9xLtI0mOb_N-izO-CDnY0E_djGbH2cNJhmmxE_Fo9FMTM_uzpX48vbq8-X7YvPp3YfLi01hsW1SoVC3NaJteqWIRgtVXSNohSNZa5p1T6Bsq3SJWGm7HvICaF31qHAgqNoKV-LVyXcXw_eFOHWzY0vTZDyFhbuq1FArrKHJ6Mt_0JuwxPzlI6W00qjyU1aiOlF5Q8yRxm4X3WzioSuhO6bWnVLrcmrd79S6Note3Fkv_UzDveRPTBnAE8D5ym8p_p39H9tf-KWkgg</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>He, Kan</creator><creator>Li, Wen-Xing</creator><creator>Guan, Daogang</creator><creator>Gong, Mengting</creator><creator>Ye, Shoudong</creator><creator>Fang, Zekun</creator><creator>Huang, Jing-Fei</creator><creator>Lu, Aiping</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PADUT</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20190701</creationdate><title>Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets</title><author>He, Kan ; Li, Wen-Xing ; Guan, Daogang ; Gong, Mengting ; Ye, Shoudong ; Fang, Zekun ; Huang, Jing-Fei ; Lu, Aiping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-8397433c5b88eefc024430983fecca56be08c78913329c6d005e62b383de02723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Animal Genetics and Genomics</topic><topic>Biochemistry</topic><topic>Bioinformatics</topic><topic>Biomedical and Life Sciences</topic><topic>Breast cancer</topic><topic>Cell Biology</topic><topic>Gene expression</topic><topic>Gene regulation</topic><topic>Genomics</topic><topic>Histocompatibility antigen HLA</topic><topic>Interferon</topic><topic>Life Sciences</topic><topic>Microbial Genetics and Genomics</topic><topic>MicroRNAs</topic><topic>miRNA</topic><topic>Original Article</topic><topic>Plant Genetics and Genomics</topic><topic>Precision medicine</topic><topic>Stat1 protein</topic><topic>Survival</topic><topic>Survival analysis</topic><topic>Transcription</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>He, Kan</creatorcontrib><creatorcontrib>Li, Wen-Xing</creatorcontrib><creatorcontrib>Guan, Daogang</creatorcontrib><creatorcontrib>Gong, Mengting</creatorcontrib><creatorcontrib>Ye, Shoudong</creatorcontrib><creatorcontrib>Fang, Zekun</creatorcontrib><creatorcontrib>Huang, Jing-Fei</creatorcontrib><creatorcontrib>Lu, Aiping</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nucleic Acids Abstracts</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</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 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>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</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>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Research Library China</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Functional &amp; integrative genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>He, Kan</au><au>Li, Wen-Xing</au><au>Guan, Daogang</au><au>Gong, Mengting</au><au>Ye, Shoudong</au><au>Fang, Zekun</au><au>Huang, Jing-Fei</au><au>Lu, Aiping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets</atitle><jtitle>Functional &amp; integrative genomics</jtitle><stitle>Funct Integr Genomics</stitle><addtitle>Funct Integr Genomics</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>19</volume><issue>4</issue><spage>645</spage><epage>658</epage><pages>645-658</pages><issn>1438-793X</issn><eissn>1438-7948</eissn><abstract>Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>30859354</pmid><doi>10.1007/s10142-019-00670-7</doi><tpages>14</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1438-793X
ispartof Functional & integrative genomics, 2019-07, Vol.19 (4), p.645-658
issn 1438-793X
1438-7948
language eng
recordid cdi_proquest_miscellaneous_2190483405
source SpringerLink Journals
subjects Animal Genetics and Genomics
Biochemistry
Bioinformatics
Biomedical and Life Sciences
Breast cancer
Cell Biology
Gene expression
Gene regulation
Genomics
Histocompatibility antigen HLA
Interferon
Life Sciences
Microbial Genetics and Genomics
MicroRNAs
miRNA
Original Article
Plant Genetics and Genomics
Precision medicine
Stat1 protein
Survival
Survival analysis
Transcription
title Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T04%3A24%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Regulatory%20network%20reconstruction%20of%20five%20essential%20microRNAs%20for%20survival%20analysis%20in%20breast%20cancer%20by%20integrating%20miRNA%20and%20mRNA%20expression%20datasets&rft.jtitle=Functional%20&%20integrative%20genomics&rft.au=He,%20Kan&rft.date=2019-07-01&rft.volume=19&rft.issue=4&rft.spage=645&rft.epage=658&rft.pages=645-658&rft.issn=1438-793X&rft.eissn=1438-7948&rft_id=info:doi/10.1007/s10142-019-00670-7&rft_dat=%3Cproquest_cross%3E2189893843%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2189893843&rft_id=info:pmid/30859354&rfr_iscdi=true