Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/178783
Title: MethCORR Modelling of Methylomes From Formalin-Fixed Paraffin-Embedded Tissue Enables Characterization and Prognostication of Colorectal Cancer
Author: Mattesen, Trine B.
Rasmussen, Mads H.
Sandoval, Juan
Ongen, Halit
Árnadóttir, Sigrid S.
Gladov, Josephine
Martínez Cardús, Anna
Castro de Moura, Manuel
Madsen, Anders H.
Laurberg, Søren
Dermitzakis, Emmanouil T.
Esteller, Manel
Andersen, Claus L.
Bramsen, Jesper B.
Keywords: Càncer colorectal
Genètica quantitativa
Pronòstic mèdic
Colorectal cancer
Quantitative genetics
Prognosis
Issue Date: 24-Apr-2020
Publisher: Nature Publishing Group
Abstract: Transcriptional 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.
Note: Reproducció del document publicat a: https://doi.org/10.1038/s41467-020-16000-6
It is part of: Nature Communications, 2020, vol. 11, num. 2025
URI: http://hdl.handle.net/2445/178783
Related resource: https://doi.org/10.1038/s41467-020-16000-6
ISSN: 2041-1723
Appears in Collections:Articles publicats en revistes (Ciències Fisiològiques)

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