Evidence map›Paper›PMID 22235325›Full record

ArticlePloS one2012

Reproducibility and concordance of differential DNA methylation and gene expression in cancer.

Chen Yao, Hongdong Li, Xiaopei Shen, Zheng He, Lang He, Zheng Guo

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

15 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Methylation of theMolecules (Basel, Switzerland) · 2019
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. [Next-generation sequencing for lung cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2014
    Review
  12. MicroRNA and transcription factor mediated regulatory network for ovarian cancer: regulatory network of ovarian cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2013
    Article
  13. Article
  14. Article
  15. 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

6 authors at 1 institution in 1 country.

Chen YaoBioinformatics Centre and Key Laboratory for NeuroInfomation of the Education Ministry of China, School of Life Science, University of Electronic Science and Technology of China, Chengdu, China.
Hongdong Li
Xiaopei Shen
Zheng He
Lang He
Zheng Guo
University of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHundreds of genes with differential DNA methylation of promoters have been identified for various cancers. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed. METHODOLOGY/PRINCIPAL

findingsUsing array data for seven types of cancers, we first evaluated the effects of experimental batches on differential DNA methylation detection. Second, we compared the directions of DNA methylation changes detected from different datasets for the same cancer. Third, we evaluated the concordance between methylation and gene expression changes. Finally, we compared DNA methylation changes in different cancers. For a given cancer, the directions of methylation and expression changes detected from different datasets, excluding potential batch effects, were highly consistent. In different cancers, DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression, whereas hypomethylation was only weakly correlated with the up-regulation of genes. Finally, we found that genes commonly hypomethylated in different cancers primarily performed functions associated with chronic inflammation, such as 'keratinization', 'chemotaxis' and 'immune response'.

conclusionsBatch effects could greatly affect the discovery of DNA methylation biomarkers. For a particular cancer, both differential DNA methylation and gene expression can be reproducibly detected from different studies with no batch effects. While DNA hypermethylation is significantly linked to gene down-regulation, hypomethylation is only weakly correlated with gene up-regulation and is likely to be linked to chronic inflammation.

Indexed as

Computational BiologyDatabases, FactualDNA MethylationGenomicsHumansNeoplasmsOligonucleotide Array Sequence AnalysisPromoter Regions, GeneticReproducibility of ResultsTranscriptome

Identifiers

PMID22235325
PMCPMC3250460
OpenAlexW2031069500

What OpenQuestion holds

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LicenceCC BY
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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.