Proteomic identification of potential cancer markers in human urine using subtractive analysis
Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative...
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| Veröffentlicht in: | International journal of oncology 2016-05, Vol.48 (5), p.1921-1932 |
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| container_title | International journal of oncology |
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| creator | HUSI, HOLGER SKIPWORTH, RICHARD J.E CRONSHAW, ANDREW FEARON, KENNETH C.H ROSS, JAMES A |
| description | Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org). |
| doi_str_mv | 10.3892/ijo.2016.3424 |
| format | Article |
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Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org).</description><identifier>ISSN: 1019-6439</identifier><identifier>EISSN: 1791-2423</identifier><identifier>DOI: 10.3892/ijo.2016.3424</identifier><identifier>PMID: 26984763</identifier><language>eng</language><publisher>Greece: D.A. Spandidos</publisher><subject>Adult ; Aged ; Biomarkers ; Biomarkers, Tumor - blood ; Biomarkers, Tumor - urine ; Breast cancer ; cancer marker ; Chromatography ; Chromatography, Liquid ; Composition ; Databases, Protein ; Datasets ; Enzymes ; Female ; Humans ; Identification and classification ; Innovations ; Intellectual disabilities ; Kidney - metabolism ; Kinases ; Liver cancer ; Male ; Mass spectrometry ; Meta-analysis ; Neoplasms - blood ; Neoplasms - diagnosis ; Neoplasms - urine ; Organ Specificity ; Ovarian cancer ; Particle size ; Peptides ; Proteins ; Proteomics ; Proteomics - methods ; Scientific imaging ; Software ; Tandem Mass Spectrometry ; Tumor proteins ; Urine</subject><ispartof>International journal of oncology, 2016-05, Vol.48 (5), p.1921-1932</ispartof><rights>Copyright © 2016, Spandidos Publications</rights><rights>COPYRIGHT 2016 Spandidos Publications</rights><rights>Copyright Spandidos Publications UK Ltd. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c556t-9262604e00c8440c27a0ddca55987433fe434859d3713b44b7d2974d3576fa073</citedby><cites>FETCH-LOGICAL-c556t-9262604e00c8440c27a0ddca55987433fe434859d3713b44b7d2974d3576fa073</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,782,786,5577,27933,27934</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26984763$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>HUSI, HOLGER</creatorcontrib><creatorcontrib>SKIPWORTH, RICHARD J.E</creatorcontrib><creatorcontrib>CRONSHAW, ANDREW</creatorcontrib><creatorcontrib>FEARON, KENNETH C.H</creatorcontrib><creatorcontrib>ROSS, JAMES A</creatorcontrib><title>Proteomic identification of potential cancer markers in human urine using subtractive analysis</title><title>International journal of oncology</title><addtitle>Int J Oncol</addtitle><description>Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org).</description><subject>Adult</subject><subject>Aged</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - blood</subject><subject>Biomarkers, Tumor - urine</subject><subject>Breast cancer</subject><subject>cancer marker</subject><subject>Chromatography</subject><subject>Chromatography, Liquid</subject><subject>Composition</subject><subject>Databases, Protein</subject><subject>Datasets</subject><subject>Enzymes</subject><subject>Female</subject><subject>Humans</subject><subject>Identification and classification</subject><subject>Innovations</subject><subject>Intellectual disabilities</subject><subject>Kidney - metabolism</subject><subject>Kinases</subject><subject>Liver cancer</subject><subject>Male</subject><subject>Mass spectrometry</subject><subject>Meta-analysis</subject><subject>Neoplasms - blood</subject><subject>Neoplasms - diagnosis</subject><subject>Neoplasms - urine</subject><subject>Organ Specificity</subject><subject>Ovarian cancer</subject><subject>Particle size</subject><subject>Peptides</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Proteomics - methods</subject><subject>Scientific imaging</subject><subject>Software</subject><subject>Tandem Mass Spectrometry</subject><subject>Tumor proteins</subject><subject>Urine</subject><issn>1019-6439</issn><issn>1791-2423</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNptkU1rHSEUhqWkNB_tMtsgBNKVt347LkNI2kKgXbTbiledXG9m9EZnAvn3dbhp2kBxceSc5xyP7wvAKcEr1mn6KW7zimIiV4xT_gYcEaUJopyyg3bHRCPJmT4Ex7VuMaZCYPIOHFKpO64kOwK_vpc8hTxGB6MPaYp9dHaKOcHcw10rtZQdoLPJhQJHW-5DqTAmuJlHm-BcYgpwrjHdwTqvp2LdFB8DtMkOTzXW9-Btb4caPjzHE_Dz5vrH1Rd0--3z16vLW-SEkBPSVFKJecDYdZxjR5XF3jsrhO4UZ6wPnPFOaM8UYWvO18pTrbhnQsneYsVOwPl-7q7khznUyWzzXNoS1RDNKGOEM_mXurNDMDH1eVl4jNWZSy4k7bSkpFGr_1Dt-NBkyin0seVfNVz807AJdpg2NQ_zImN9DaI96EqutYTe7Epsmj4Zgs3ipmlumsVNs7jZ-LPnX83rMfgX-o99Dfi4B-rOJh99ri9Mm4R4h7BARLenfwPIPqVF</recordid><startdate>20160501</startdate><enddate>20160501</enddate><creator>HUSI, HOLGER</creator><creator>SKIPWORTH, RICHARD J.E</creator><creator>CRONSHAW, ANDREW</creator><creator>FEARON, KENNETH C.H</creator><creator>ROSS, JAMES A</creator><general>D.A. 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blood</topic><topic>Biomarkers, Tumor - urine</topic><topic>Breast cancer</topic><topic>cancer marker</topic><topic>Chromatography</topic><topic>Chromatography, Liquid</topic><topic>Composition</topic><topic>Databases, Protein</topic><topic>Datasets</topic><topic>Enzymes</topic><topic>Female</topic><topic>Humans</topic><topic>Identification and classification</topic><topic>Innovations</topic><topic>Intellectual disabilities</topic><topic>Kidney - metabolism</topic><topic>Kinases</topic><topic>Liver cancer</topic><topic>Male</topic><topic>Mass spectrometry</topic><topic>Meta-analysis</topic><topic>Neoplasms - blood</topic><topic>Neoplasms - diagnosis</topic><topic>Neoplasms - urine</topic><topic>Organ Specificity</topic><topic>Ovarian cancer</topic><topic>Particle size</topic><topic>Peptides</topic><topic>Proteins</topic><topic>Proteomics</topic><topic>Proteomics - methods</topic><topic>Scientific imaging</topic><topic>Software</topic><topic>Tandem Mass Spectrometry</topic><topic>Tumor proteins</topic><topic>Urine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>HUSI, HOLGER</creatorcontrib><creatorcontrib>SKIPWORTH, RICHARD J.E</creatorcontrib><creatorcontrib>CRONSHAW, ANDREW</creatorcontrib><creatorcontrib>FEARON, KENNETH C.H</creatorcontrib><creatorcontrib>ROSS, JAMES A</creatorcontrib><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>ProQuest Nursing and Allied Health Journals</collection><collection>ProQuest_Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Nursing & Allied Health Premium</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><jtitle>International journal of oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>HUSI, HOLGER</au><au>SKIPWORTH, RICHARD J.E</au><au>CRONSHAW, ANDREW</au><au>FEARON, KENNETH C.H</au><au>ROSS, JAMES A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Proteomic identification of potential cancer markers in human urine using subtractive analysis</atitle><jtitle>International journal of oncology</jtitle><addtitle>Int J Oncol</addtitle><date>2016-05-01</date><risdate>2016</risdate><volume>48</volume><issue>5</issue><spage>1921</spage><epage>1932</epage><pages>1921-1932</pages><issn>1019-6439</issn><eissn>1791-2423</eissn><abstract>Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org).</abstract><cop>Greece</cop><pub>D.A. Spandidos</pub><pmid>26984763</pmid><doi>10.3892/ijo.2016.3424</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | International journal of oncology, 2016-05, Vol.48 (5), p.1921-1932 |
| issn | 1019-6439 1791-2423 |
| language | eng |
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| source | Spandidos Publications Journals; MEDLINE; Free E-Journal (出版社公開部分のみ）; Alma/SFX Local Collection |
| subjects | Adult Aged Biomarkers Biomarkers, Tumor - blood Biomarkers, Tumor - urine Breast cancer cancer marker Chromatography Chromatography, Liquid Composition Databases, Protein Datasets Enzymes Female Humans Identification and classification Innovations Intellectual disabilities Kidney - metabolism Kinases Liver cancer Male Mass spectrometry Meta-analysis Neoplasms - blood Neoplasms - diagnosis Neoplasms - urine Organ Specificity Ovarian cancer Particle size Peptides Proteins Proteomics Proteomics - methods Scientific imaging Software Tandem Mass Spectrometry Tumor proteins Urine |
| title | Proteomic identification of potential cancer markers in human urine using subtractive analysis |
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