Evidence map›Paper›PMID 26949191›Full record

ArticleScientific reports2016

The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes.

Yihan Wang, Jingyu Zhang, Xingjun Xiao, Hongbo Liu, Fang Wang, Song Li, Yanhua Wen, Yanjun Wei, Jianzhong Su, Yunming Zhang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

16 citing papers in PubMed, 28 citations in OpenAlex.

  1. Association ofTranslational cancer research · 2026
    Article
  2. Article
  3. Article
  4. Methylated Septin9 (mCancer research communications · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. DNA Methylation Markers for Breast Cancer Detection in the Developing World.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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

11 authors at 2 institutions in 1 country.

Yihan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Jingyu ZhangDepartment of Gerontology, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
Xingjun XiaoDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Harbin 150086, China.
Hongbo LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Fang WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Song LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yanhua WenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yanjun WeiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Jianzhong SuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yunming ZhangDepartment of Gerontology, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
Yan ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Harbin Medical University · CNFirst Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As one of the most widely studied epigenetic modifications, DNA methylation has an important influence on human traits and cancers. Dynamic variations in DNA methylation have been reported in malignant neoplasm and aging; however, the mechanisms remain poorly understood. By constructing an age-associated and cancer-related weighted network (ACWN) based on the correlation of the methylation level and the protein-protein interaction, we found that DNA methylation changes associated with age were closely related to the occurrence of cancer. Additional analysis of 102 module genes mined from the ACWN revealed discrimination based on two main patterns. One pattern involved methylation levels that increased with aging and were higher in cancer patients compared with normal controls (HH pattern). The other pattern involved methylation levels that decreased with aging and were lower in cancer compared with normal (LL pattern). Upon incorporation with gene expression levels, 25 genes were filtered based on negative regulation by DNA methylation. These genes were regarded as potential cancer risk markers that were influenced by age in the process of carcinogenesis. Our results will facilitate further studies regarding the impact of the epigenetic effects of aging on diseases and will aid in the development of tailored cancer preventive strategies.

Indexed as

DNA MethylationEpigenesis, GeneticAdolescentAdultAgedAged, 80 and overAgingBiomarkers, TumorDNAFemaleHumansMaleMiddle AgedNeoplasmsYoung AdultBiomarkers, TumorDNA

Identifiers

PMID26949191
PMCPMC4779991
OpenAlexW2304569214

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.