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Quantitative comparison of DNA methylation assays for biomarker development and clinical applications

by Lopez, Virginia , Hansen, Lise Lotte , Holcomb, Thomas , Dahmcke, Christina M , Strogantsev, Ruslan , Guldberg, Per , Haake, Andrea , Queirós, Ana C , Esteller, Manel , Assenov, Yassen , Fernández, Agustín F , Sauter, Guido , Tierling, Sascha , Kläver, Ruth , Sun, Xueguang , Clark, Susan J , Shames, David S , Walter, Jörn , Siebert, Reiner , Weichenhan, Dieter , Fraga, Mario F , Berdasco, María , Paul, Dirk S , Plongthongkum, Nongluk , Kulis, Marta , Statham, Aaron , Diep, Dinh , Halbritter, Florian , Bock, Christoph , Nair, Shalima S , Plass, Christoph , Nygren, Anders O H , Booher, Keith , Qu, Wenjia , Beck, Stephan , Stirzaker, Clare , Schlomm, Thorsten , Datlinger, Paul , Busato, Florence , Martín-Subero, José I , Hussmann, Dianna , Walter, Kimberly , Ito, Mitsuteru , Heilmann, Katharina , Urdinguio, Rocío G , Laird, Peter W , Gerhauser, Clarissa , Campan, Mihaela , Peist, Ralf , Ferguson-Smith, Anne C , Tost, Jörg , Carmona, Francisco J , Reinicke, Frank , Kreutz, Martin , Dahl, Christina , Zhang, Kun , Weisenberger, Daniel J , Bergmann, Anke K

in 631/154/53 / 631/1647/2210/2213 / 631/208/176/1988 / 631/61/32 / Agriculture / Algorithms / analysis / Bioinformatics / Biological assay / Biological markers / Biomarkers / Biomedical Engineering/Biotechnology / Biomedicine / Biotechnology / Comparative analysis / Computer Science / Deoxyribonucleic acid / DNA / DNA - genetics / DNA methylation / DNA Methylation - genetics / DNA Modification Methylases - genetics / Genetic aspects / Genetic Markers - genetics / Genetics / Genomes / Health aspects / High-Throughput Nucleotide Sequencing - methods / High-Throughput Screening Assays - methods / Laboratories / Life Sciences / Methylation / Promoter Regions, Genetic - genetics / Reproducibility of Results / Sensitivity and Specificity

2016

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2016

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2016

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Journal Article

Quantitative comparison of DNA methylation assays for biomarker development and clinical applications

Lopez, Virginia,

Hansen, Lise Lotte,

Holcomb, Thomas,

Dahmcke, Christina M,

Strogantsev, Ruslan,

Guldberg, Per,

Haake, Andrea,

Queirós, Ana C,

Esteller, Manel,

Assenov, Yassen,

Fernández, Agustín F,

Sauter, Guido,

Tierling, Sascha,

Kläver, Ruth,

Sun, Xueguang,

Clark, Susan J,

Shames, David S,

Walter, Jörn,

Siebert, Reiner,

Weichenhan, Dieter,

Fraga, Mario F,

Berdasco, María,

Paul, Dirk S,

Plongthongkum, Nongluk,

Kulis, Marta,

Statham, Aaron,

Diep, Dinh,

Halbritter, Florian,

Bock, Christoph,

Nair, Shalima S,

Plass, Christoph,

Nygren, Anders O H,

Booher, Keith,

Qu, Wenjia,

Beck, Stephan,

Stirzaker, Clare,

Schlomm, Thorsten,

Datlinger, Paul,

Busato, Florence,

Martín-Subero, José I,

Hussmann, Dianna,

Walter, Kimberly,

Ito, Mitsuteru,

Heilmann, Katharina,

Urdinguio, Rocío G,

Laird, Peter W,

Gerhauser, Clarissa,

Campan, Mihaela,

Peist, Ralf,

Ferguson-Smith, Anne C,

Tost, Jörg,

Carmona, Francisco J,

Reinicke, Frank,

Kreutz, Martin,

Dahl, Christina,

Zhang, Kun,

Weisenberger, Daniel J,

Bergmann, Anke K

2016

Overview

A multicenter comparison of DNA methylation assays identifies robust methods for translational research and clinical diagnostics. DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.

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Nature Publishing Group US,Nature Publishing Group

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