MethCORR Modelling of Methylomes From Formalin-Fixed Paraffin-Embedded Tissue Enables Characterization and Prognostication of Colorectal Cancer

dc.contributor.authorMattesen, Trine B.
dc.contributor.authorRasmussen, Mads H.
dc.contributor.authorSandoval, Juan
dc.contributor.authorOngen, Halit
dc.contributor.authorÁrnadóttir, Sigrid S.
dc.contributor.authorGladov, Josephine
dc.contributor.authorMartínez Cardús, Anna
dc.contributor.authorCastro de Moura, Manuel
dc.contributor.authorMadsen, Anders H.
dc.contributor.authorLaurberg, Søren
dc.contributor.authorDermitzakis, Emmanouil T.
dc.contributor.authorEsteller, Manel
dc.contributor.authorAndersen, Claus L.
dc.contributor.authorBramsen, Jesper B.
dc.date.accessioned2021-07-05T10:16:07Z
dc.date.available2021-07-05T10:16:07Z
dc.date.issued2020-04-24
dc.date.updated2021-07-05T10:16:08Z
dc.description.abstractTranscriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types.
dc.format.extent15 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec700369
dc.identifier.issn2041-1723
dc.identifier.pmid32332866
dc.identifier.urihttps://hdl.handle.net/2445/178783
dc.language.isoeng
dc.publisherNature Publishing Group
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1038/s41467-020-16000-6
dc.relation.ispartofNature Communications, 2020, vol. 11, num. 2025
dc.relation.urihttps://doi.org/10.1038/s41467-020-16000-6
dc.rightscc-by (c) Mattesen, Trine B. et al., 2020
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Ciències Fisiològiques)
dc.subject.classificationCàncer colorectal
dc.subject.classificationGenètica quantitativa
dc.subject.classificationPronòstic mèdic
dc.subject.otherColorectal cancer
dc.subject.otherQuantitative genetics
dc.subject.otherPrognosis
dc.titleMethCORR Modelling of Methylomes From Formalin-Fixed Paraffin-Embedded Tissue Enables Characterization and Prognostication of Colorectal Cancer
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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