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2020-04-24

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cc-by (c) Mattesen, Trine B. et al., 2020
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/178783

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

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Recurs relacionat

https://doi.org/10.1038/s41467-020-16000-6

Resum

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.

Matèries

Càncer colorectal, Genètica quantitativa, Pronòstic mèdic

Matèries (anglès)

Colorectal cancer, Quantitative genetics, Prognosis

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Col·leccions

Articles publicats en revistes (Ciències Fisiològiques)

Citació

MATTESEN, Trine B., et al. MethCORR Modelling of Methylomes From Formalin-Fixed Paraffin-Embedded Tissue Enables Characterization and Prognostication of Colorectal Cancer. Nature Communications. 2020. Vol. 11, núm. 2025. ISSN 2041-1723. [consulta: 10 de maig de 2026]. Disponible a: https://hdl.handle.net/2445/178783

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