ArticleNature communications2020
MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
- Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers.Frontiers in nutrition · 2022Pooled it
- A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer.PloS one · 2025Article
- Clinical significance and immune landscape analyses of the coagulation-related gene signatures in gastric cancer.Journal of Cancer · 2025Article
- MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles.iScience · 2023Article
- MicroRNAs (miRNAs): Novel potential therapeutic targets in colorectal cancer.Frontiers in oncology · 2022Review
- MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples.Clinical epigenetics · 2021Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors at 7 institutions in 3 countries.
Funding
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.
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Registered trials
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