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Analysis of Deregulated microRNAs and Their Target Genes in Gastric Cancer
MicroRNAs (miRNAs) are widely studied non-coding RNAs that modulate gene expression. MiRNAs are deregulated in different tumors including gastric cancer (GC) and have potential diagnostic and prognostic implications. The aim of our study was to determine miRNA profile in GC tissues, followed by eval...
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Published in: | PloS one 2015-07, Vol.10 (7), p.e0132327-e0132327 |
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creator | Juzėnas, Simonas Saltenienė, Violeta Kupcinskas, Juozas Link, Alexander Kiudelis, Gediminas Jonaitis, Laimas Jarmalaite, Sonata Kupcinskas, Limas Malfertheiner, Peter Skieceviciene, Jurgita |
description | MicroRNAs (miRNAs) are widely studied non-coding RNAs that modulate gene expression. MiRNAs are deregulated in different tumors including gastric cancer (GC) and have potential diagnostic and prognostic implications. The aim of our study was to determine miRNA profile in GC tissues, followed by evaluation of deregulated miRNAs in plasma of GC patients. Using available databases and bioinformatics methods we also aimed to evaluate potential target genes of confirmed differentially expressed miRNA and validate these findings in GC tissues.
The study included 51 GC patients and 51 controls. Initially, we screened miRNA expression profile in 13 tissue samples of GC and 12 normal gastric tissues with TaqMan low density array (TLDA). In the second stage, differentially expressed miRNAs were validated in a replication cohort using qRT-PCR in tissue and plasma samples. Subsequently, we analyzed potential target genes of deregulated miRNAs using bioinformatics approach, determined their expression in GC tissues and performed correlation analysis with targeting miRNAs.
Profiling with TLDA revealed 15 deregulated miRNAs in GC tissues compared to normal gastric mucosa. Replication analysis confirmed that miR-148a-3p, miR-204-5p, miR-223-3p and miR-375 were consistently deregulated in GC tissues. Analysis of GC patients' plasma samples showed significant down-regulation of miR-148a-3p, miR-375 and up-regulation of miR-223-3p compared to healthy subjects. Further, using bioinformatic tools we identified targets of replicated miRNAs and performed disease-associated gene enrichment analysis. Ultimately, we evaluated potential target gene BCL2 and DNMT3B expression by qRT-PCR in GC tissue, which correlated with targeting miRNA expression.
Our study revealed miRNA profile in GC tissues and showed that miR-148a-3p, miR-223-3p and miR-375 are deregulated in GC plasma samples, but these circulating miRNAs showed relatively weak diagnostic performance as sole biomarkers. Target gene analysis demonstrated that BCL2 and DNMT3B expression in GC tissue correlated with their targeting miRNA expression. |
doi_str_mv | 10.1371/journal.pone.0132327 |
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The study included 51 GC patients and 51 controls. Initially, we screened miRNA expression profile in 13 tissue samples of GC and 12 normal gastric tissues with TaqMan low density array (TLDA). In the second stage, differentially expressed miRNAs were validated in a replication cohort using qRT-PCR in tissue and plasma samples. Subsequently, we analyzed potential target genes of deregulated miRNAs using bioinformatics approach, determined their expression in GC tissues and performed correlation analysis with targeting miRNAs.
Profiling with TLDA revealed 15 deregulated miRNAs in GC tissues compared to normal gastric mucosa. Replication analysis confirmed that miR-148a-3p, miR-204-5p, miR-223-3p and miR-375 were consistently deregulated in GC tissues. Analysis of GC patients' plasma samples showed significant down-regulation of miR-148a-3p, miR-375 and up-regulation of miR-223-3p compared to healthy subjects. Further, using bioinformatic tools we identified targets of replicated miRNAs and performed disease-associated gene enrichment analysis. Ultimately, we evaluated potential target gene BCL2 and DNMT3B expression by qRT-PCR in GC tissue, which correlated with targeting miRNA expression.
Our study revealed miRNA profile in GC tissues and showed that miR-148a-3p, miR-223-3p and miR-375 are deregulated in GC plasma samples, but these circulating miRNAs showed relatively weak diagnostic performance as sole biomarkers. Target gene analysis demonstrated that BCL2 and DNMT3B expression in GC tissue correlated with their targeting miRNA expression.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0132327</identifier><identifier>PMID: 26172537</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aged ; Bioinformatics ; Biomarkers ; Biomarkers, Tumor - blood ; Biomarkers, Tumor - genetics ; Cancer ; Case-Control Studies ; Cell growth ; Computational Biology ; Correlation analysis ; Deregulation ; Diagnostic systems ; DNA (Cytosine-5-)-Methyltransferases - genetics ; DNA Methyltransferase 3B ; Female ; Gastric cancer ; Gastric mucosa ; Gastric Mucosa - metabolism ; Gastroenterology ; Gene expression ; Gene Expression Regulation, Neoplastic ; Genes ; Genes, Neoplasm - genetics ; Health sciences ; Helicobacter pylori ; Hepatology ; Humans ; Infectious diseases ; Male ; Medical diagnosis ; MicroRNAs ; MicroRNAs - blood ; MicroRNAs - genetics ; Middle Aged ; miRNA ; Patients ; Proto-Oncogene Proteins c-bcl-2 - genetics ; Replication ; Ribonucleic acid ; RNA ; Stomach cancer ; Stomach Neoplasms - blood ; Stomach Neoplasms - genetics ; Studies ; Target recognition ; Tissue analysis ; Tissues ; Tumors</subject><ispartof>PloS one, 2015-07, Vol.10 (7), p.e0132327-e0132327</ispartof><rights>2015 Juzėnas 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>2015 Juzėnas et al 2015 Juzėnas et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-8680c3d560e0fb56b7465a62b4e2719315d979f02f9d99fde7a8a583c32b3ce63</citedby><cites>FETCH-LOGICAL-c526t-8680c3d560e0fb56b7465a62b4e2719315d979f02f9d99fde7a8a583c32b3ce63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1696242863/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1696242863?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25731,27901,27902,36989,36990,44566,53766,53768,74869</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26172537$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Juzėnas, Simonas</creatorcontrib><creatorcontrib>Saltenienė, Violeta</creatorcontrib><creatorcontrib>Kupcinskas, Juozas</creatorcontrib><creatorcontrib>Link, Alexander</creatorcontrib><creatorcontrib>Kiudelis, Gediminas</creatorcontrib><creatorcontrib>Jonaitis, Laimas</creatorcontrib><creatorcontrib>Jarmalaite, Sonata</creatorcontrib><creatorcontrib>Kupcinskas, Limas</creatorcontrib><creatorcontrib>Malfertheiner, Peter</creatorcontrib><creatorcontrib>Skieceviciene, Jurgita</creatorcontrib><title>Analysis of Deregulated microRNAs and Their Target Genes in Gastric Cancer</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>MicroRNAs (miRNAs) are widely studied non-coding RNAs that modulate gene expression. MiRNAs are deregulated in different tumors including gastric cancer (GC) and have potential diagnostic and prognostic implications. The aim of our study was to determine miRNA profile in GC tissues, followed by evaluation of deregulated miRNAs in plasma of GC patients. Using available databases and bioinformatics methods we also aimed to evaluate potential target genes of confirmed differentially expressed miRNA and validate these findings in GC tissues.
The study included 51 GC patients and 51 controls. Initially, we screened miRNA expression profile in 13 tissue samples of GC and 12 normal gastric tissues with TaqMan low density array (TLDA). In the second stage, differentially expressed miRNAs were validated in a replication cohort using qRT-PCR in tissue and plasma samples. Subsequently, we analyzed potential target genes of deregulated miRNAs using bioinformatics approach, determined their expression in GC tissues and performed correlation analysis with targeting miRNAs.
Profiling with TLDA revealed 15 deregulated miRNAs in GC tissues compared to normal gastric mucosa. Replication analysis confirmed that miR-148a-3p, miR-204-5p, miR-223-3p and miR-375 were consistently deregulated in GC tissues. Analysis of GC patients' plasma samples showed significant down-regulation of miR-148a-3p, miR-375 and up-regulation of miR-223-3p compared to healthy subjects. Further, using bioinformatic tools we identified targets of replicated miRNAs and performed disease-associated gene enrichment analysis. Ultimately, we evaluated potential target gene BCL2 and DNMT3B expression by qRT-PCR in GC tissue, which correlated with targeting miRNA expression.
Our study revealed miRNA profile in GC tissues and showed that miR-148a-3p, miR-223-3p and miR-375 are deregulated in GC plasma samples, but these circulating miRNAs showed relatively weak diagnostic performance as sole biomarkers. Target gene analysis demonstrated that BCL2 and DNMT3B expression in GC tissue correlated with their targeting miRNA expression.</description><subject>Aged</subject><subject>Bioinformatics</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - blood</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Cancer</subject><subject>Case-Control Studies</subject><subject>Cell growth</subject><subject>Computational Biology</subject><subject>Correlation analysis</subject><subject>Deregulation</subject><subject>Diagnostic systems</subject><subject>DNA (Cytosine-5-)-Methyltransferases - genetics</subject><subject>DNA Methyltransferase 3B</subject><subject>Female</subject><subject>Gastric cancer</subject><subject>Gastric mucosa</subject><subject>Gastric Mucosa - metabolism</subject><subject>Gastroenterology</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Genes</subject><subject>Genes, Neoplasm - genetics</subject><subject>Health sciences</subject><subject>Helicobacter pylori</subject><subject>Hepatology</subject><subject>Humans</subject><subject>Infectious diseases</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>MicroRNAs</subject><subject>MicroRNAs - blood</subject><subject>MicroRNAs - genetics</subject><subject>Middle Aged</subject><subject>miRNA</subject><subject>Patients</subject><subject>Proto-Oncogene Proteins c-bcl-2 - genetics</subject><subject>Replication</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Stomach cancer</subject><subject>Stomach Neoplasms - blood</subject><subject>Stomach Neoplasms - genetics</subject><subject>Studies</subject><subject>Target recognition</subject><subject>Tissue analysis</subject><subject>Tissues</subject><subject>Tumors</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptUl1vEzEQPCEQLS3_AIElXnhJ6o-zffeCFAUIrSqQqvBs7dl7qaOLHew7pP57rsm1ahFPXtkzs7PeKYp3jM6Z0OxiG4cUoJvvY8A5ZYILrl8Up6wWfKY4FS-f1CfFm5y3lEpRKfW6OOGKaS6FPi2uFqPGXfaZxJZ8wYSboYMeHdl5m-LNj0UmEBxZ36JPZA1pgz1ZYcBMfCAryH3yliwhWEznxasWuoxvp_Os-PXt63r5fXb9c3W5XFzPrOSqn1WqolY4qSjStpGq0aWSoHhTItejYyZdreuW8rZ2dd061FCBrIQVvBEWlTgrPhx1913MZvqGbJiqFS95pcSIuDwiXISt2Se_g3RnInhzuIhpYyD13nZoqJTYSBCNU1XJHTQoQNQ1L3VJR0Ns1Po8dRuaHTqLoU_QPRN9_hL8rdnEP6aUlMmDmU-TQIq_B8y92flssesgYBwOvjVnjPNqhH78B_r_6cojalxQzgnbRzOMmvtoPLDMfTTMFI2R9v7pII-khyyIv69utX8</recordid><startdate>20150714</startdate><enddate>20150714</enddate><creator>Juzėnas, Simonas</creator><creator>Saltenienė, Violeta</creator><creator>Kupcinskas, Juozas</creator><creator>Link, Alexander</creator><creator>Kiudelis, Gediminas</creator><creator>Jonaitis, Laimas</creator><creator>Jarmalaite, Sonata</creator><creator>Kupcinskas, Limas</creator><creator>Malfertheiner, Peter</creator><creator>Skieceviciene, Jurgita</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>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>AEUYN</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>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20150714</creationdate><title>Analysis of Deregulated microRNAs and Their Target Genes in Gastric Cancer</title><author>Juzėnas, Simonas ; Saltenienė, Violeta ; Kupcinskas, Juozas ; Link, Alexander ; Kiudelis, Gediminas ; Jonaitis, Laimas ; Jarmalaite, Sonata ; Kupcinskas, Limas ; Malfertheiner, Peter ; Skieceviciene, Jurgita</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-8680c3d560e0fb56b7465a62b4e2719315d979f02f9d99fde7a8a583c32b3ce63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Aged</topic><topic>Bioinformatics</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - 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MiRNAs are deregulated in different tumors including gastric cancer (GC) and have potential diagnostic and prognostic implications. The aim of our study was to determine miRNA profile in GC tissues, followed by evaluation of deregulated miRNAs in plasma of GC patients. Using available databases and bioinformatics methods we also aimed to evaluate potential target genes of confirmed differentially expressed miRNA and validate these findings in GC tissues.
The study included 51 GC patients and 51 controls. Initially, we screened miRNA expression profile in 13 tissue samples of GC and 12 normal gastric tissues with TaqMan low density array (TLDA). In the second stage, differentially expressed miRNAs were validated in a replication cohort using qRT-PCR in tissue and plasma samples. Subsequently, we analyzed potential target genes of deregulated miRNAs using bioinformatics approach, determined their expression in GC tissues and performed correlation analysis with targeting miRNAs.
Profiling with TLDA revealed 15 deregulated miRNAs in GC tissues compared to normal gastric mucosa. Replication analysis confirmed that miR-148a-3p, miR-204-5p, miR-223-3p and miR-375 were consistently deregulated in GC tissues. Analysis of GC patients' plasma samples showed significant down-regulation of miR-148a-3p, miR-375 and up-regulation of miR-223-3p compared to healthy subjects. Further, using bioinformatic tools we identified targets of replicated miRNAs and performed disease-associated gene enrichment analysis. Ultimately, we evaluated potential target gene BCL2 and DNMT3B expression by qRT-PCR in GC tissue, which correlated with targeting miRNA expression.
Our study revealed miRNA profile in GC tissues and showed that miR-148a-3p, miR-223-3p and miR-375 are deregulated in GC plasma samples, but these circulating miRNAs showed relatively weak diagnostic performance as sole biomarkers. Target gene analysis demonstrated that BCL2 and DNMT3B expression in GC tissue correlated with their targeting miRNA expression.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26172537</pmid><doi>10.1371/journal.pone.0132327</doi><oa>free_for_read</oa></addata></record> |
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recordid | cdi_plos_journals_1696242863 |
source | Publicly Available Content Database; PubMed Central |
subjects | Aged Bioinformatics Biomarkers Biomarkers, Tumor - blood Biomarkers, Tumor - genetics Cancer Case-Control Studies Cell growth Computational Biology Correlation analysis Deregulation Diagnostic systems DNA (Cytosine-5-)-Methyltransferases - genetics DNA Methyltransferase 3B Female Gastric cancer Gastric mucosa Gastric Mucosa - metabolism Gastroenterology Gene expression Gene Expression Regulation, Neoplastic Genes Genes, Neoplasm - genetics Health sciences Helicobacter pylori Hepatology Humans Infectious diseases Male Medical diagnosis MicroRNAs MicroRNAs - blood MicroRNAs - genetics Middle Aged miRNA Patients Proto-Oncogene Proteins c-bcl-2 - genetics Replication Ribonucleic acid RNA Stomach cancer Stomach Neoplasms - blood Stomach Neoplasms - genetics Studies Target recognition Tissue analysis Tissues Tumors |
title | Analysis of Deregulated microRNAs and Their Target Genes in Gastric Cancer |
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