Evidence map›Paper›PMID 28589857›Full record

ArticleBMC medical genomics2017

Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer.

Manu Shivakumar, Younghee Lee, Lisa Bang, Tullika Garg, Kyung-Ah Sohn, Dokyoon Kim

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 3 pooled it
3.0field-weighted citation impact, top 8% 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

41 citing papers in PubMed, 3 syntheses or guidelines pooled it, 65 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
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  6. Review
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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 4 institutions in 2 countries.

Manu ShivakumarBiomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA, USA.
Younghee LeeDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Lisa BangBiomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA, USA.
Tullika GargMowad Urology Department, Geisinger Health System, Danville, PA, USA.
Kyung-Ah SohnDepartment of Software and Computer Engineering, Ajou University, Suwon, South Korea. kasohn@ajoun.ac.kr.
Dokyoon KimBiomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA, USA. dkim@geisinger.edu.
Geisinger Health System · USAjou University · KRPennsylvania State University · USUniversity of Utah · US

Funding

Pharmacogenomics of Statin TherapyP50GM115318 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RISCH, NEIL J. · 2015 to 2019
$14.0M
NIGMS NIH HHS P50 GM115318
6 · The paper itself

Abstract

backgroundOne of the fundamental challenges in cancer is to detect the regulators of gene expression changes during cancer progression. Through transcriptional silencing of critical cancer-related genes, epigenetic change such as DNA methylation plays a crucial role in cancer. In addition, miRNA, another major component of epigenome, is also a regulator at the post-transcriptional levels that modulate transcriptome changes. However, a mechanistic role of synergistic interactions between DNA methylation and miRNA as epigenetic regulators on transcriptomic changes and its association with clinical outcomes such as survival have remained largely unexplored in cancer.

methodsIn this study, we propose an integrative framework to identify epigenetic interactions between methylation and miRNA associated with transcriptomic changes. To test the utility of the proposed framework, the bladder cancer data set, including DNA methylation, miRNA expression, and gene expression data, from The Cancer Genome Atlas (TCGA) was analyzed for this study.

resultsFirst, we found 120 genes associated with interactions between the two epigenomic components. Then, 11 significant epigenetic interactions between miRNA and methylation, which target E2F3, CCND1, UTP6, CDADC1, SLC35E3, METRNL, TPCN2, NACC2, VGLL4, and PTEN, were found to be associated with survival. To this end, exploration of TCGA bladder cancer data identified epigenetic interactions that are associated with survival as potential prognostic markers in bladder cancer.

conclusionsGiven the importance and prevalence of these interactions of epigenetic events in bladder cancer it is timely to understand further how different epigenetic components interact and influence each other.

Indexed as

DNA MethylationEpigenesis, GeneticGene Expression ProfilingAgedBiomarkers, TumorFemaleHumansMaleMicroRNAsPrognosisSurvival AnalysisUrinary Bladder NeoplasmsBiomarkers, TumorMicroRNAsBladder cancerIntegrative analysisInteraction between miRNA and methylationTCGA

Identifiers

PMID28589857
PMCPMC5461531
OpenAlexW2617359196

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.