Evidence map›Paper›PMID 42523546›Full record

ArticleResearch square2026

Metastasis-associated DNA methylation alterations persist after accounting for immune and stromal cell heterogeneity in primary colorectal tumors.

Alos B Diallo, Sabin D Hart, John P Zavras, Scott M Palisoul, Fred W Kolling, Louis J Vaickus, Jiaoyuan E Sun, Lucas A Salas, Brock C Christensen, Joshua J Levy

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Alos B DialloDartmouth College.
Sabin D HartDartmouth College.
John P ZavrasDartmouth College.
Scott M PalisoulDartmouth-Hitchcock Medical Center.
Fred W KollingDartmouth Cancer Center.
Louis J VaickusDartmouth-Hitchcock Medical Center.
Jiaoyuan E SunDartmouth-Hitchcock Medical Center.
Lucas A SalasDartmouth College.
Brock C ChristensenDartmouth College.
Joshua J LevyCedars-Sinai Medical Center.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI MICHAEL L WHITFIELD · 2019 to 2026
$27.2M
Pilot Project ProgramP30GM149408 · NIGMS · DARTMOUTH COLLEGE · PI MARGARET Rita KARAGAS · 2023 to 2026
$6.3M
Acquisition of the NextSeq2000 Sequencing platform to Increase Next Generation Sequencing Throughput While Reducing Costs at DartmouthS10OD030242 · OD · DARTMOUTH COLLEGE · PI KOLLING IV, FRED W · 2021 to 2021
$321k
NCI NIH HHS P30 CA023108NIGMS NIH HHS P20 GM130454NIGMS NIH HHS P30 GM149408NIH HHS S10 OD030242
6 · The paper itself

Abstract

Background: Metastatic colorectal cancer (CRC) remains a major cause of cancer mortality, yet how epigenetic states within the tumor microenvironment (TME) relate to metastatic progression has not been fully characterized. Although aberrant DNA methylation has been implicated in cancer progression, many studies do not account for immune and stromal cell composition, which can confound bulk methylation analyses. We sought to define DNA methylation patterns in primary colorectal tumors associated with lymph node and distant metastasis, while accounting for tumor microenvironment cellular composition. Methods: We analyzed DNA methylation patterns from 57 patients with stage pT3 colorectal adenocarcinoma, comparing tumors with and without concurrent metastasis. Methylation cytometry deconvolution was performed to estimate immune, stromal, and tumor cell fractions. Differentially methylated positions associated with metastatic status were identified using covariate-adjusted epigenome-wide association analyses, with genomic context enrichment to assess regional methylation patterns. Genomic context enrichment and gene annotations were used to assess biological relevance. Methylation-expression correlations were assessed in an independent TCGA-COAD cohort to evaluate whether discovery loci correspond to differences in gene expression. Results: Metastatic status was not associated with large-scale differences in inferred cellular composition. Epigenome-wide analyses identified hypomethylated loci mapped to genes involved in Wnt/β-catenin and PI3K/Akt signaling, epithelial-mesenchymal transition, and immune modulation, whereas hypermethylated loci tracked to genes related to adhesion, Wnt signaling, cytoskeletal organization, and interferon signaling. Genomic context enrichment revealed CpG island enrichment among hypermethylated DMPs in the distant metastasis contrast. Among metastasis-associated CpGs, 23 showed significant negative correlations between methylation and gene expression in TCGA-COAD (FDR < 0.05), predominantly at promoter-proximal CpG islands, supporting a relationship between promoter methylation and reduced gene expression. Two candidate CpGs showed directional concordance with significance in matched TCGA contrasts. Conclusions: We identify distinct epigenetic alterations associated with metastatic progression in colorectal cancer that are largely independent of bulk immune and stromal composition. Integration of methylation-expression data supports a role for promoter hypermethylation in metastasis-associated gene silencing. These findings highlight potential methylation-based biomarkers of metastatic risk and may inform future precision oncology strategies in CRC.

Indexed as

colorectal cancerDNA Methylationepigeneticsepigenomewide association studytumor microenvironment

Identifiers

PMID42523546
PMCPMC13405491

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.