Loading…
FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data
In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disea...
Saved in:
Published in: | Tumor biology 2014-03, Vol.35 (3), p.2607-2617 |
---|---|
Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3 |
---|---|
cites | cdi_FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3 |
container_end_page | 2617 |
container_issue | 3 |
container_start_page | 2607 |
container_title | Tumor biology |
container_volume | 35 |
creator | Zodro, Elżbieta Jaroszewski, Marcin Ida, Agnieszka Wrzesiński, Tomasz Kwias, Zbigniew Bluyssen, Hans Wesoly, Joanna |
description | In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as
TMEM213
,
SMIM5
, or ATPases:
ATP6V0A4
and
ATP6V1G3
, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with
EGLN3
,
AP-2
,
NR3C1
,
HIF1A
, and
EPAS1
(gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (
FUT11
) expression with non-symptomatic course of the disease, which suggests that
FUT11
's expression might be potentially used as a biomarker of disease progression. |
doi_str_mv | 10.1007/s13277-013-1344-4 |
format | article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3967067</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1639989348</sourcerecordid><originalsourceid>FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3</originalsourceid><addsrcrecordid>eNqFkk1rFTEUhgdR7If-ADcScOMmmpNk8rERpFgrFNy065DknntNnTsZk7nFgj_eTG9bqiCucuA85z0febvuFbB3wJh-X0FwrSkDQUFISeWT7hAkF5QJw562mAGjkhtx0B3VesUY9Naq590BlwKMNeaw-3V6eQFAfCWeTHnGcU5-ICHlrS_fsZC8JnFAX0jEYSAFx5a9DaMvMY0NI1PJm4K1pjyS4CuuSAu2OHvqG31TU11UNjgiwZ_TPbnys3_RPVv7oeLLu_e4uzz9dHFyRs-_fv5y8vGcxl7ZmVrUWssogzRrhtwr5ZkFw6EPkgXLrQ1BB6OMFEKqlVFa92BDFMgk1zGI4-7DXnfahS2uYtuy-MFNJbUtb1z2yf2ZGdM3t8nXTlilmdJN4O2dQMk_dlhnt011OYMfMe-qAyWsNVZI83-0BxC2Z_2i-uYv9CrvSrvZLcWEbu1Vo2BPxZJrLbh-mBuYW2zg9jZwzQZusYGTreb144UfKu7_vQF8D9SWGjdYHrX-p-pvy6u9Ng</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1510373966</pqid></control><display><type>article</type><title>FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data</title><source>Publicly Available Content Database</source><creator>Zodro, Elżbieta ; Jaroszewski, Marcin ; Ida, Agnieszka ; Wrzesiński, Tomasz ; Kwias, Zbigniew ; Bluyssen, Hans ; Wesoly, Joanna</creator><creatorcontrib>Zodro, Elżbieta ; Jaroszewski, Marcin ; Ida, Agnieszka ; Wrzesiński, Tomasz ; Kwias, Zbigniew ; Bluyssen, Hans ; Wesoly, Joanna</creatorcontrib><description>In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as
TMEM213
,
SMIM5
, or ATPases:
ATP6V0A4
and
ATP6V1G3
, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with
EGLN3
,
AP-2
,
NR3C1
,
HIF1A
, and
EPAS1
(gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (
FUT11
) expression with non-symptomatic course of the disease, which suggests that
FUT11
's expression might be potentially used as a biomarker of disease progression.</description><identifier>ISSN: 1010-4283</identifier><identifier>EISSN: 1423-0380</identifier><identifier>DOI: 10.1007/s13277-013-1344-4</identifier><identifier>PMID: 24318988</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Biomarkers ; Biomarkers, Tumor - analysis ; Biomarkers, Tumor - genetics ; Biomedical and Life Sciences ; Biomedicine ; Cancer Research ; Carcinoma, Renal Cell - genetics ; Disease Progression ; Fucosyltransferases - genetics ; Gene expression ; Humans ; Kidney cancer ; Kidney Neoplasms - genetics ; Meta-analysis ; Oligonucleotide Array Sequence Analysis ; Polymerase Chain Reaction ; Research Article ; Transcriptome</subject><ispartof>Tumor biology, 2014-03, Vol.35 (3), p.2607-2617</ispartof><rights>The Author(s) 2013</rights><rights>International Society of Oncology and BioMarkers (ISOBM) 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3</citedby><cites>FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1510373966?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,25753,27924,27925,37012,37013,44590</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24318988$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zodro, Elżbieta</creatorcontrib><creatorcontrib>Jaroszewski, Marcin</creatorcontrib><creatorcontrib>Ida, Agnieszka</creatorcontrib><creatorcontrib>Wrzesiński, Tomasz</creatorcontrib><creatorcontrib>Kwias, Zbigniew</creatorcontrib><creatorcontrib>Bluyssen, Hans</creatorcontrib><creatorcontrib>Wesoly, Joanna</creatorcontrib><title>FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data</title><title>Tumor biology</title><addtitle>Tumor Biol</addtitle><addtitle>Tumour Biol</addtitle><description>In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as
TMEM213
,
SMIM5
, or ATPases:
ATP6V0A4
and
ATP6V1G3
, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with
EGLN3
,
AP-2
,
NR3C1
,
HIF1A
, and
EPAS1
(gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (
FUT11
) expression with non-symptomatic course of the disease, which suggests that
FUT11
's expression might be potentially used as a biomarker of disease progression.</description><subject>Biomarkers</subject><subject>Biomarkers, Tumor - analysis</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cancer Research</subject><subject>Carcinoma, Renal Cell - genetics</subject><subject>Disease Progression</subject><subject>Fucosyltransferases - genetics</subject><subject>Gene expression</subject><subject>Humans</subject><subject>Kidney cancer</subject><subject>Kidney Neoplasms - genetics</subject><subject>Meta-analysis</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Polymerase Chain Reaction</subject><subject>Research Article</subject><subject>Transcriptome</subject><issn>1010-4283</issn><issn>1423-0380</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqFkk1rFTEUhgdR7If-ADcScOMmmpNk8rERpFgrFNy065DknntNnTsZk7nFgj_eTG9bqiCucuA85z0febvuFbB3wJh-X0FwrSkDQUFISeWT7hAkF5QJw562mAGjkhtx0B3VesUY9Naq590BlwKMNeaw-3V6eQFAfCWeTHnGcU5-ICHlrS_fsZC8JnFAX0jEYSAFx5a9DaMvMY0NI1PJm4K1pjyS4CuuSAu2OHvqG31TU11UNjgiwZ_TPbnys3_RPVv7oeLLu_e4uzz9dHFyRs-_fv5y8vGcxl7ZmVrUWssogzRrhtwr5ZkFw6EPkgXLrQ1BB6OMFEKqlVFa92BDFMgk1zGI4-7DXnfahS2uYtuy-MFNJbUtb1z2yf2ZGdM3t8nXTlilmdJN4O2dQMk_dlhnt011OYMfMe-qAyWsNVZI83-0BxC2Z_2i-uYv9CrvSrvZLcWEbu1Vo2BPxZJrLbh-mBuYW2zg9jZwzQZusYGTreb144UfKu7_vQF8D9SWGjdYHrX-p-pvy6u9Ng</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>Zodro, Elżbieta</creator><creator>Jaroszewski, Marcin</creator><creator>Ida, Agnieszka</creator><creator>Wrzesiński, Tomasz</creator><creator>Kwias, Zbigniew</creator><creator>Bluyssen, Hans</creator><creator>Wesoly, Joanna</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>C6C</scope><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>7T5</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</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>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</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>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope></search><sort><creationdate>20140301</creationdate><title>FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data</title><author>Zodro, Elżbieta ; Jaroszewski, Marcin ; Ida, Agnieszka ; Wrzesiński, Tomasz ; Kwias, Zbigniew ; Bluyssen, Hans ; Wesoly, Joanna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Biomarkers</topic><topic>Biomarkers, Tumor - analysis</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cancer Research</topic><topic>Carcinoma, Renal Cell - genetics</topic><topic>Disease Progression</topic><topic>Fucosyltransferases - genetics</topic><topic>Gene expression</topic><topic>Humans</topic><topic>Kidney cancer</topic><topic>Kidney Neoplasms - genetics</topic><topic>Meta-analysis</topic><topic>Oligonucleotide Array Sequence Analysis</topic><topic>Polymerase Chain Reaction</topic><topic>Research Article</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zodro, Elżbieta</creatorcontrib><creatorcontrib>Jaroszewski, Marcin</creatorcontrib><creatorcontrib>Ida, Agnieszka</creatorcontrib><creatorcontrib>Wrzesiński, Tomasz</creatorcontrib><creatorcontrib>Kwias, Zbigniew</creatorcontrib><creatorcontrib>Bluyssen, Hans</creatorcontrib><creatorcontrib>Wesoly, Joanna</creatorcontrib><collection>Springer_OA刊</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</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 (Proquest)</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)</collection><collection>ProQuest Central</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>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest research library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</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>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Tumor biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zodro, Elżbieta</au><au>Jaroszewski, Marcin</au><au>Ida, Agnieszka</au><au>Wrzesiński, Tomasz</au><au>Kwias, Zbigniew</au><au>Bluyssen, Hans</au><au>Wesoly, Joanna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data</atitle><jtitle>Tumor biology</jtitle><stitle>Tumor Biol</stitle><addtitle>Tumour Biol</addtitle><date>2014-03-01</date><risdate>2014</risdate><volume>35</volume><issue>3</issue><spage>2607</spage><epage>2617</epage><pages>2607-2617</pages><issn>1010-4283</issn><eissn>1423-0380</eissn><abstract>In this paper, we provide a comprehensive summary of available clear cell renal cell carcinoma (ccRCC) microarray data in the form of meta-analysis of genes differentially regulated in tumors as compared to healthy tissue, using effect size to measure the strength of a relationship between the disease and gene expression. We identified 725 differentially regulated genes, with a number of interesting targets, such as
TMEM213
,
SMIM5
, or ATPases:
ATP6V0A4
and
ATP6V1G3
, of which limited or no information is available in terms of their function in ccRCC pathology. Downregulated genes tended to represent pathways related to tissue remodeling, blood clotting, vasodilation, and energy metabolism, while upregulated genes were classified into pathways generally deregulated in cancers: immune system response, inflammatory response, angiogenesis, and apoptosis. One hundred fifteen deregulated genes were included in network analysis, with
EGLN3
,
AP-2
,
NR3C1
,
HIF1A
, and
EPAS1
(gene encoding HIF2-α) as points of functional convergence, but, interestingly, 610 genes failed to join previously identified molecular networks. Furthermore, we validated the expression of 14 top deregulated genes in independent sample set of 32 ccRCC tumors by qPCR and tested if it could serve as a marker of disease progression. We found a correlation of high fucosyltransferase 11 (
FUT11
) expression with non-symptomatic course of the disease, which suggests that
FUT11
's expression might be potentially used as a biomarker of disease progression.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>24318988</pmid><doi>10.1007/s13277-013-1344-4</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1010-4283 |
ispartof | Tumor biology, 2014-03, Vol.35 (3), p.2607-2617 |
issn | 1010-4283 1423-0380 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3967067 |
source | Publicly Available Content Database |
subjects | Biomarkers Biomarkers, Tumor - analysis Biomarkers, Tumor - genetics Biomedical and Life Sciences Biomedicine Cancer Research Carcinoma, Renal Cell - genetics Disease Progression Fucosyltransferases - genetics Gene expression Humans Kidney cancer Kidney Neoplasms - genetics Meta-analysis Oligonucleotide Array Sequence Analysis Polymerase Chain Reaction Research Article Transcriptome |
title | FUT11 as a potential biomarker of clear cell renal cell carcinoma progression based on meta-analysis of gene expression data |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T15%3A42%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=FUT11%20as%20a%20potential%20biomarker%20of%20clear%20cell%20renal%20cell%20carcinoma%20progression%20based%20on%20meta-analysis%20of%20gene%20expression%20data&rft.jtitle=Tumor%20biology&rft.au=Zodro,%20El%C5%BCbieta&rft.date=2014-03-01&rft.volume=35&rft.issue=3&rft.spage=2607&rft.epage=2617&rft.pages=2607-2617&rft.issn=1010-4283&rft.eissn=1423-0380&rft_id=info:doi/10.1007/s13277-013-1344-4&rft_dat=%3Cproquest_pubme%3E1639989348%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c569t-9e7774c4b48f0e2a66a0918215b40b9299bb7b86843346d8677519bc3e0427cb3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1510373966&rft_id=info:pmid/24318988&rfr_iscdi=true |