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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

Citació

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, num. 2025. ISSN 2041-1723. [consulted: 19 of August of 2026]. Available at: https://hdl.handle.net/2445/178783

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