Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin
Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for ~3–5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor t...
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Veröffentlicht in: | Modern pathology 2016-06, Vol.29 (6), p.546-556 |
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creator | Xu, Qinghua Chen, Jinying Ni, Shujuan Tan, Cong Xu, Midie Dong, Lei Yuan, Lin Wang, Qifeng Du, Xiang |
description | Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for ~3–5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics. Previous studies have paved the way for gene expression-based tumor type classification. In this study, we have established a comprehensive database integrating microarray- and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, we identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, we tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, we have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. This gene panel may hold a promise to be a useful additional tool for the determination of the tumor origin. |
doi_str_mv | 10.1038/modpathol.2016.60 |
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Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics. Previous studies have paved the way for gene expression-based tumor type classification. In this study, we have established a comprehensive database integrating microarray- and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, we identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, we tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, we have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. This gene panel may hold a promise to be a useful additional tool for the determination of the tumor origin.</description><identifier>ISSN: 0893-3952</identifier><identifier>EISSN: 1530-0285</identifier><identifier>DOI: 10.1038/modpathol.2016.60</identifier><identifier>PMID: 26990976</identifier><identifier>CODEN: MODPEO</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>38/39 ; 38/91 ; 631/67/1680 ; 692/53/2421 ; Biomarkers, Tumor - genetics ; Cancer therapies ; Computational Biology ; Databases, Genetic ; Female ; Gene expression ; Gene Expression Profiling - methods ; Genomes ; Genomics ; High-Throughput Nucleotide Sequencing ; Humans ; Identification ; Laboratory Medicine ; Male ; Medical prognosis ; Medicine ; Medicine & Public Health ; Metastasis ; Neoplasms, Unknown Primary - classification ; Neoplasms, Unknown Primary - genetics ; Oligonucleotide Array Sequence Analysis ; original-article ; Pathology ; Predictive Value of Tests ; Reproducibility of Results ; Transcriptome ; Tumors</subject><ispartof>Modern pathology, 2016-06, Vol.29 (6), p.546-556</ispartof><rights>United States & Canadian Academy of Pathology 2016</rights><rights>Copyright Nature Publishing Group Jun 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-b5437e32d11d0f858060818e8a6537672a43c508c99d040833ddec94713fe823</citedby><cites>FETCH-LOGICAL-c415t-b5437e32d11d0f858060818e8a6537672a43c508c99d040833ddec94713fe823</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1792585158?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26990976$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, Qinghua</creatorcontrib><creatorcontrib>Chen, Jinying</creatorcontrib><creatorcontrib>Ni, Shujuan</creatorcontrib><creatorcontrib>Tan, Cong</creatorcontrib><creatorcontrib>Xu, Midie</creatorcontrib><creatorcontrib>Dong, Lei</creatorcontrib><creatorcontrib>Yuan, Lin</creatorcontrib><creatorcontrib>Wang, Qifeng</creatorcontrib><creatorcontrib>Du, Xiang</creatorcontrib><title>Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin</title><title>Modern pathology</title><addtitle>Mod Pathol</addtitle><addtitle>Mod Pathol</addtitle><description>Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for ~3–5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics. Previous studies have paved the way for gene expression-based tumor type classification. In this study, we have established a comprehensive database integrating microarray- and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, we identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, we tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, we have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. 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Academic</collection><jtitle>Modern pathology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Qinghua</au><au>Chen, Jinying</au><au>Ni, Shujuan</au><au>Tan, Cong</au><au>Xu, Midie</au><au>Dong, Lei</au><au>Yuan, Lin</au><au>Wang, Qifeng</au><au>Du, Xiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin</atitle><jtitle>Modern pathology</jtitle><stitle>Mod Pathol</stitle><addtitle>Mod Pathol</addtitle><date>2016-06-01</date><risdate>2016</risdate><volume>29</volume><issue>6</issue><spage>546</spage><epage>556</epage><pages>546-556</pages><issn>0893-3952</issn><eissn>1530-0285</eissn><coden>MODPEO</coden><abstract>Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for ~3–5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics. Previous studies have paved the way for gene expression-based tumor type classification. In this study, we have established a comprehensive database integrating microarray- and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, we identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, we tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, we have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. This gene panel may hold a promise to be a useful additional tool for the determination of the tumor origin.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>26990976</pmid><doi>10.1038/modpathol.2016.60</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 38/39 38/91 631/67/1680 692/53/2421 Biomarkers, Tumor - genetics Cancer therapies Computational Biology Databases, Genetic Female Gene expression Gene Expression Profiling - methods Genomes Genomics High-Throughput Nucleotide Sequencing Humans Identification Laboratory Medicine Male Medical prognosis Medicine Medicine & Public Health Metastasis Neoplasms, Unknown Primary - classification Neoplasms, Unknown Primary - genetics Oligonucleotide Array Sequence Analysis original-article Pathology Predictive Value of Tests Reproducibility of Results Transcriptome Tumors |
title | Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin |
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