Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/178783
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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.identifier.issn2041-1723-
dc.identifier.urihttp://hdl.handle.net/2445/178783-
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.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.urihttps://creativecommons.org/licenses/by/4.0/-
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-
dc.identifier.idgrec700369-
dc.date.updated2021-07-05T10:16:08Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid32332866-
Appears in Collections:Articles publicats en revistes (Ciències Fisiològiques)

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