Evidence map›Paper›PMID 31423235›Full record

ArticleOncology letters2019

DNA methylation profiling identifies potentially significant epigenetically-regulated genes in glioblastoma multiforme.

Shifeng Kan, Song Chai, Wenhua Chen, Bo Yu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Electrotherapies for Glioblastoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Review
  6. Review
  7. Article
  8. Review
  9. 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

4 authors.

Shifeng KanDepartment of Rehabilitation, Shanghai General Hospital, Shanghai Jiaotong University, Shanghai 200080, P.R. China.
Song ChaiDepartment of Rehabilitation, Shanghai General Hospital, Shanghai Jiaotong University, Shanghai 200080, P.R. China.
Wenhua ChenDepartment of Rehabilitation, Shanghai General Hospital, Shanghai Jiaotong University, Shanghai 200080, P.R. China.
Bo YuDepartment of Rehabilitation, Shanghai General Hospital, Shanghai Jiaotong University, Shanghai 200080, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is one of the most lethal and damaging types of human cancer. The current study was conducted to identify differentially methylated genes (DMGs) between GBM and normal controls, and to improve our understanding of GBM at the epigenetic level. The DNA methylation profile of GBM was downloaded from the Gene Expression Omnibus (GEO) database using the accession number GSE50923. The MethyAnalysis package was applied to identify DMGs between GBM and controls, which were then analyzed by functional enrichment analysis. Protein-protein interaction (PPI) networks were constructed using the hypermethylated and hypomethylated genes. Finally, transcription factors (TFs) that can regulate the hypermethylated and hypomethylated genes were predicted, followed by construction of transcriptional regulatory networks. Furthermore, another relevant dataset, GSE22867, was downloaded from the GEO database for data validation. A total of 476 hypermethylated and 850 hypomethylated genes were identified, which were mainly associated with the functions of 'G-protein-coupled receptors ligand binding', 'cytokine activity', 'cytokine-cytokine receptor interaction', and 'D-glutamine and D-glutamate metabolism'. The hypermethylated gene neuropeptide Y (

Indexed as

abnormal methylationfunctional enrichment analysisglioblastoma multiformeprotein-protein interaction networktranscription factors

Identifiers

PMID31423235
PMCPMC6614665

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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.