Evidence map›Paper›PMID 28415743›Full record

ArticleOncotarget2017

Survival differences of CIMP subtypes integrated with CNA information in human breast cancer.

Huihan Wang, Weili Yan, Shumei Zhang, Yue Gu, Yihan Wang, Yanjun Wei, Hongbo Liu, Fang Wang, Qiong Wu, Yan Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

10 authors.

Huihan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Weili YanSchool of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, 150001, China.
Shumei ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yue GuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yihan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yanjun WeiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, 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.
Qiong WuSchool of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, 150001, China.
Yan ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CpG island methylator phenotype of breast cancer is associated with widespread aberrant methylation at specified CpG islands and distinct patient outcomes. However, the influence of copy number contributing to the prognosis of tumors with different CpG island methylator phenotypes is still unclear. We analyzed both genetic (copy number) and epigenetic alterations in 765 breast cancers from The Cancer Genome Atlas data portal and got a panel of 15 biomarkers for copy number and methylation status evaluation. The gene panel identified two groups corresponding to distinct copy number profiles. In status of mere-loss copy number, patients were faced with a greater risk if they presented a higher CpG islands methylation pattern in biomarker panels. But for samples presenting merely-gained copy number, higher methylation level of CpG islands was associated with improved viability. In all, the integration of copy number alteration and methylation information enhanced the classification power on prognosis. Moreover, we found the molecular subtypes of breast cancer presented different distributions in two CpG island methylation phenotypes. Generated by the same set of human methylation 450K data, additional copy number information could provide insights into survival prediction of cancers with less heterogeneity and might help to determine the biomarkers for diagnosis and treatment for breast cancer patients in a more personalized approach.

Indexed as

CpG IslandsDNA Copy Number VariationsDNA MethylationBiomarkers, TumorBreast NeoplasmsCase-Control StudiesComputational BiologyEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPhenotypePrognosisProportional Hazards ModelsSurvival AnalysisBiomarkers, Tumorbiomarkerbreast cancercopy number alteration (CNA)CpG island methylator phenotype (CIMP)prognosis

Identifiers

PMID28415743
PMCPMC5564726

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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.