000144260 001__ 144260
000144260 005__ 20240229112620.0
000144260 0247_ $$2doi$$a10.3390/cancers11070912
000144260 0247_ $$2pmid$$apmid:31261771
000144260 037__ $$aDKFZ-2019-01780
000144260 041__ $$aeng
000144260 082__ $$a610
000144260 1001_ $$0P:(DE-HGF)0$$aRaut, Janhavi R$$b0$$eFirst author
000144260 245__ $$aWhole-blood DNA Methylation Markers for Risk Stratification in Colorectal Cancer Screening: A Systematic Review.
000144260 260__ $$aBasel$$bMDPI$$c2019
000144260 3367_ $$2DRIVER$$aarticle
000144260 3367_ $$2DataCite$$aOutput Types/Journal article
000144260 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1562749525_1740$$xReview Article
000144260 3367_ $$2BibTeX$$aARTICLE
000144260 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000144260 3367_ $$00$$2EndNote$$aJournal Article
000144260 520__ $$aDNA methylation profiles within whole-blood samples have been reported to be associated with colorectal cancer (CRC) occurrence and might enable risk stratification for CRC. We systematically reviewed and summarized studies addressing the association of whole-blood DNA methylation markers and risk of developing CRC or its precursors. We searched PubMed and ISI Web of Knowledge to identify relevant studies published until 12th November 2018. Two reviewers independently extracted data on study population characteristics, candidate genes, methylation measurement methods, methylation levels of patients in comparison to healthy controls, p-values, and odds ratios of the markers. Overall, 19 studies reporting 102 methylation markers for risk assessment of colorectal neoplasms met our inclusion criteria. The studies mostly used Methylation Specific Polymerase Chain Reaction (MS-PCR) for assessing the methylation status of a defined set of genes. Only two studies applied array-based genome-wide assays to assess the methylation levels. Five studies incorporated panels consisting of 2-10 individual methylation markers to assess their potential for stratifying the risk of developing colorectal neoplasms. However, none of these associations was confirmed in an independent cohort. In conclusion, whole-blood DNA methylation markers may be useful as biomarkers for risk stratification in CRC screening, but reproducible risk prediction algorithms are yet to be established by large scale epigenome-wide studies with thorough validation of results in prospective study cohorts including large screening populations. The possibilities of enhancing predictive power by combining methylation data with polygenetic risk scores and environmental risk factors need to be explored.
000144260 536__ $$0G:(DE-HGF)POF3-313$$a313 - Cancer risk factors and prevention (POF3-313)$$cPOF3-313$$fPOF III$$x0
000144260 588__ $$aDataset connected to CrossRef, PubMed,
000144260 7001_ $$0P:(DE-He78)e2927c4f5c050e0ad98ebb65eebe0d56$$aGuan, Zhong$$b1$$udkfz
000144260 7001_ $$0P:(DE-He78)01ef71f71b01a3ec3b698653fd43fe86$$aSchrotz-King, Petra$$b2$$udkfz
000144260 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b3$$eLast author$$udkfz
000144260 773__ $$0PERI:(DE-600)2527080-1$$a10.3390/cancers11070912$$gVol. 11, no. 7, p. 912 -$$n7$$p912 $$tCancers$$v11$$x2072-6694$$y2019
000144260 909CO $$ooai:inrepo02.dkfz.de:144260$$pVDB
000144260 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000144260 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)e2927c4f5c050e0ad98ebb65eebe0d56$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000144260 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)01ef71f71b01a3ec3b698653fd43fe86$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000144260 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000144260 9131_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0
000144260 9141_ $$y2019
000144260 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bCANCERS : 2017
000144260 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000144260 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000144260 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000144260 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central
000144260 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000144260 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000144260 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Blind peer review
000144260 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ
000144260 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000144260 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000144260 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000144260 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000144260 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000144260 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000144260 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bCANCERS : 2017
000144260 9201_ $$0I:(DE-He78)C070-20160331$$kC070$$lKlinische Epidemiologie und Alternsforschung$$x0
000144260 9201_ $$0I:(DE-He78)C120-20160331$$kC120$$lPräventive Onkologie$$x1
000144260 9201_ $$0I:(DE-He78)L101-20160331$$kL101$$lDKTK Heidelberg$$x2
000144260 980__ $$ajournal
000144260 980__ $$aVDB
000144260 980__ $$aI:(DE-He78)C070-20160331
000144260 980__ $$aI:(DE-He78)C120-20160331
000144260 980__ $$aI:(DE-He78)L101-20160331
000144260 980__ $$aUNRESTRICTED