Evidence map›Paper›PMID 28351398›Full record

ArticleBMC cancer2017

Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

Tyler McInnes, Donghui Zou, Dasari S Rao, Francesca M Munro, Vicky L Phillips, John L McCall, Michael A Black, Anthony E Reeve, Parry J Guilford

Abstract read
In one paragraph

Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. BRAFiScience · 2025
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  19. Article
  20. Methylation ofFrontiers in molecular biosciences · 2021
    Article
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

9 authors.

Tyler McInnesCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.
Donghui ZouCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.
Dasari S RaoCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.
Francesca M MunroDepartment of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand.
Vicky L PhillipsDepartment of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand.
John L McCallDepartment of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand.
Michael A BlackCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.
Anthony E ReeveCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.
Parry J GuilfordCancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand. parry.guilford@otago.ac.nz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer.

methodsDNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC.

resultsIn this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16).

conclusionsOur genome-wide characterization of DNA methylation in colorectal cancer has identified 132 genes hypermethylated in 100% of CIMP-H samples. Three genes, EYA4, TLX1 and TFPI2 are hypermethylated in >90% of all tumour samples, regardless of CIMP subtype.

Indexed as

CpG IslandsDNA MethylationGene Expression Regulation, NeoplasticGenome, HumanAdenocarcinoma, MucinousAgedBiomarkers, TumorColorectal NeoplasmsFemaleHumansMaleNeoplasm StagingPhenotypePrognosisBiomarkers, TumorCIMPColorectal cancerEpigenomeMethylation

Identifiers

PMID28351398
PMCPMC5371203

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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.