Evidence map›Paper›PMID 39696831›Full record

ArticleMolecular oncology2025

Unraveling epigenetic heterogeneity across gastrointestinal adenocarcinomas through a standardized analytical framework.

Rita Pinto, Hege Marie Vedeld, Guro Elisabeth Lind, Marine Jeanmougin

Abstract read
In one paragraph

Article in Molecular oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rita PintoDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0002-7213-3801
Hege Marie VedeldDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway.
Guro Elisabeth LindDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0003-4643-9345
Marine JeanmouginDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital - Norwegian Radium Hospital, Oslo, Norway.

Funding

Helse Sør-Øst RHF 2019030Kreftforeningen 368530-6260-333692
6 · The paper itself

Abstract

In this study, we propose an alternative approach for stratifying genome-scale DNA methylation profiles of gastrointestinal (GI) adenocarcinomas based on a robust analytical framework. A set of 978 GI adenocarcinomas and 120 adjacent normal tissues from public repositories was quality controlled and analyzed. Hierarchical consensus clustering of the tumors, based on differential epigenetic variability between malignant and normal samples, identified six distinct subtypes defined either by a pan-GI or a lower GI-specific phenotype. In addition to methylation levels, aberrant methylation frequencies and the degree of DNA methylation instability contributed to the characterization of each subtype. We found significant differences in the outcome of patients, with the poorest overall survival seen for those belonging to a pan-GI subtype with infrequent aberrant methylation. In conclusion, our standardized approach contributes to a refined characterization of the epigenetic heterogeneity in GI adenocarcinomas, offering insights into subtype-specific methylation with the potential to support prognostication.

Indexed as

AdenocarcinomaEpigenesis, GeneticGastrointestinal NeoplasmsGenetic HeterogeneityAgedCluster AnalysisDNA MethylationFemaleHumansMaleMiddle AgedPrognosisdifferential variabilityDNA methylationmolecular subtyping

Identifiers

PMID39696831
PMCPMC11977639

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.