Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes
Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play...
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Veröffentlicht in: | Human mutation 2008-11, Vol.29 (11), p.1273-1281 |
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creator | Greenblatt, Marc S Brody, Lawrence C Foulkes, William D Genuardi, Maurizio Hofstra, Robert M.W Olivier, Magali Plon, Sharon E Sijmons, Rolf H Sinilnikova, Olga Spurdle, Amanda B |
description | Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded. Hum Mutat 29(11), 1273-1281, 2008. Published 2008 Wiley-Liss, Inc. |
doi_str_mv | 10.1002/humu.20889 |
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LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded. Hum Mutat 29(11), 1273-1281, 2008. Published 2008 Wiley-Liss, Inc.</description><identifier>ISSN: 1059-7794</identifier><identifier>EISSN: 1098-1004</identifier><identifier>DOI: 10.1002/humu.20889</identifier><identifier>PMID: 18951438</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>BIC ; cancer ; Computational Biology - methods ; Data Collection - methods ; Databases, Genetic - standards ; Genes, Neoplasm ; Genetic Predisposition to Disease ; Genetic Variation ; Humans ; locus-specific databases ; LSDBs ; mismatch repair ; Neoplastic Syndromes, Hereditary - classification ; Neoplastic Syndromes, Hereditary - genetics ; pathogenic ; unclassified variant ; variant of unknown significance</subject><ispartof>Human mutation, 2008-11, Vol.29 (11), p.1273-1281</ispartof><rights>This article is a US Government work and, as such, is in the public domain in the United States of America. Published in 2008 by Wiley‐Liss, Inc.</rights><rights>Published 2008 Wiley-Liss, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5139-3cb948c326c33699c621a1d4eafeaa3f835809befd50e31b0d2cc9273a41123b3</citedby><cites>FETCH-LOGICAL-c5139-3cb948c326c33699c621a1d4eafeaa3f835809befd50e31b0d2cc9273a41123b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fhumu.20889$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fhumu.20889$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18951438$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Greenblatt, Marc S</creatorcontrib><creatorcontrib>Brody, Lawrence C</creatorcontrib><creatorcontrib>Foulkes, William D</creatorcontrib><creatorcontrib>Genuardi, Maurizio</creatorcontrib><creatorcontrib>Hofstra, Robert M.W</creatorcontrib><creatorcontrib>Olivier, Magali</creatorcontrib><creatorcontrib>Plon, Sharon E</creatorcontrib><creatorcontrib>Sijmons, Rolf H</creatorcontrib><creatorcontrib>Sinilnikova, Olga</creatorcontrib><creatorcontrib>Spurdle, Amanda B</creatorcontrib><creatorcontrib>IARC Unclassified Genetic Variants Working Group</creatorcontrib><creatorcontrib>for the IARC Unclassified Genetic Variants Working Group</creatorcontrib><title>Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes</title><title>Human mutation</title><addtitle>Hum. Mutat</addtitle><description>Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded. Hum Mutat 29(11), 1273-1281, 2008. Published 2008 Wiley-Liss, Inc.</description><subject>BIC</subject><subject>cancer</subject><subject>Computational Biology - methods</subject><subject>Data Collection - methods</subject><subject>Databases, Genetic - standards</subject><subject>Genes, Neoplasm</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Variation</subject><subject>Humans</subject><subject>locus-specific databases</subject><subject>LSDBs</subject><subject>mismatch repair</subject><subject>Neoplastic Syndromes, Hereditary - classification</subject><subject>Neoplastic Syndromes, Hereditary - genetics</subject><subject>pathogenic</subject><subject>unclassified variant</subject><subject>variant of unknown significance</subject><issn>1059-7794</issn><issn>1098-1004</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc1u1DAUhSMEoj-w4QHAK4SQUuw4_tsgoQo6SAMs6MDScpybGUNiD3bSMi_BM-N0hgKbbmzr-LtH9-gUxROCzwjG1avNNExnFZZS3SuOCVayzHJ9f34zVQqh6qPiJKVvGGPJGH1YHBGpGKmpPC5-LYOdUpm2YF3nLGrNaBqTICHjWxTBhmEAn1UXfEJjQGmM4NfjBjzKh4vIBj9G10wzMQNZRbY3Kc1-N3ModOjKRGf8mJDzyBpvIaI0JQvb0TWud-MOrcFDelQ86Eyf4PHhPi1W795eni_K5aeL9-dvlqVlhKqS2kbV0tKKW0q5UpZXxJC2BtOBMbSTlEmsGuhahoGSBreVtaoS1NSEVLShp8Xrve92agZoLeQMptfb6AYTdzoYp___8W6j1-FK07rmklXZ4PnBIIYfE6RRDy7H6XvjIUxJcyXqGlOawRd3gkQIzrkQhGf05R61MaQUobvdh2A9N63npvVN0xl--m-Cv-ih2gyQPXDtetjdYaUXqw-rP6blfsalEX7ezpj4XXNBBdNfP17oSnCyEF8W-jLzz_Z8Z4I26-iSXn2uMKGYMMaZkPQ3B-7Rbw</recordid><startdate>200811</startdate><enddate>200811</enddate><creator>Greenblatt, Marc S</creator><creator>Brody, Lawrence C</creator><creator>Foulkes, William D</creator><creator>Genuardi, Maurizio</creator><creator>Hofstra, Robert M.W</creator><creator>Olivier, Magali</creator><creator>Plon, Sharon E</creator><creator>Sijmons, Rolf H</creator><creator>Sinilnikova, Olga</creator><creator>Spurdle, Amanda B</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>FBQ</scope><scope>BSCLL</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>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>200811</creationdate><title>Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes</title><author>Greenblatt, Marc S ; Brody, Lawrence C ; Foulkes, William D ; Genuardi, Maurizio ; Hofstra, Robert M.W ; Olivier, Magali ; Plon, Sharon E ; Sijmons, Rolf H ; Sinilnikova, Olga ; Spurdle, Amanda B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5139-3cb948c326c33699c621a1d4eafeaa3f835809befd50e31b0d2cc9273a41123b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>BIC</topic><topic>cancer</topic><topic>Computational Biology - methods</topic><topic>Data Collection - methods</topic><topic>Databases, Genetic - standards</topic><topic>Genes, Neoplasm</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Variation</topic><topic>Humans</topic><topic>locus-specific databases</topic><topic>LSDBs</topic><topic>mismatch repair</topic><topic>Neoplastic Syndromes, Hereditary - classification</topic><topic>Neoplastic Syndromes, Hereditary - genetics</topic><topic>pathogenic</topic><topic>unclassified variant</topic><topic>variant of unknown significance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Greenblatt, Marc S</creatorcontrib><creatorcontrib>Brody, Lawrence C</creatorcontrib><creatorcontrib>Foulkes, William D</creatorcontrib><creatorcontrib>Genuardi, Maurizio</creatorcontrib><creatorcontrib>Hofstra, Robert M.W</creatorcontrib><creatorcontrib>Olivier, Magali</creatorcontrib><creatorcontrib>Plon, Sharon E</creatorcontrib><creatorcontrib>Sijmons, Rolf H</creatorcontrib><creatorcontrib>Sinilnikova, Olga</creatorcontrib><creatorcontrib>Spurdle, Amanda B</creatorcontrib><creatorcontrib>IARC Unclassified Genetic Variants Working Group</creatorcontrib><creatorcontrib>for the IARC Unclassified Genetic Variants Working Group</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Human mutation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Greenblatt, Marc S</au><au>Brody, Lawrence C</au><au>Foulkes, William D</au><au>Genuardi, Maurizio</au><au>Hofstra, Robert M.W</au><au>Olivier, Magali</au><au>Plon, Sharon E</au><au>Sijmons, Rolf H</au><au>Sinilnikova, Olga</au><au>Spurdle, Amanda B</au><aucorp>IARC Unclassified Genetic Variants Working Group</aucorp><aucorp>for the IARC Unclassified Genetic Variants Working Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes</atitle><jtitle>Human mutation</jtitle><addtitle>Hum. Mutat</addtitle><date>2008-11</date><risdate>2008</risdate><volume>29</volume><issue>11</issue><spage>1273</spage><epage>1281</epage><pages>1273-1281</pages><issn>1059-7794</issn><eissn>1098-1004</eissn><abstract>Locus-specific databases (LSDBs) are curated collections of sequence variants in genes associated with disease. LSDBs of cancer-related genes often serve as a critical resource to researchers, diagnostic laboratories, clinicians, and others in the cancer genetics community. LSDBs are poised to play an important role in disseminating clinical classification of variants. The IARC Working Group on Unclassified Genetic Variants has proposed a new system of five classes of variants in cancer susceptibility genes. However, standards are lacking for reporting and analyzing the multiple data types that assist in classifying variants. By adhering to standards of transparency and consistency in the curation and annotation of data, LSDBs can be critical for organizing our understanding of how genetic variation relates to disease. In this article we discuss how LSDBs can accomplish these goals, using existing databases for BRCA1, BRCA2, MSH2, MLH1, TP53, and CDKN2A to illustrate the progress and remaining challenges in this field. We recommend that: 1) LSDBs should only report a conclusion related to pathogenicity if a consensus has been reached by an expert panel. 2) The system used to classify variants should be standardized. The Working Group encourages use of the five class system described in this issue by Plon and colleagues. 3) Evidence that supports a conclusion should be reported in the database, including sources and criteria used for assignment. 4) Variants should only be classified as pathogenic if more than one type of evidence has been considered. 5) All instances of all variants should be recorded. Hum Mutat 29(11), 1273-1281, 2008. Published 2008 Wiley-Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>18951438</pmid><doi>10.1002/humu.20889</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | BIC cancer Computational Biology - methods Data Collection - methods Databases, Genetic - standards Genes, Neoplasm Genetic Predisposition to Disease Genetic Variation Humans locus-specific databases LSDBs mismatch repair Neoplastic Syndromes, Hereditary - classification Neoplastic Syndromes, Hereditary - genetics pathogenic unclassified variant variant of unknown significance |
title | Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes |
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