Evidence map›Paper›PMID 29152649›Full record

ArticleMolecular medicine reports2017

Identification of key genes in glioma CpG island methylator phenotype via network analysis of gene expression data.

Lijuan Bo, Bo Wei, Zhanfeng Wang, Daliang Kong, Zheng Gao, Zhuang Miao

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 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
0.1field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  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

6 authors at 2 institutions in 1 country.

Lijuan BoDepartment of Infections, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Bo WeiDepartment of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Zhanfeng WangDepartment of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Daliang KongDepartment of Orthopaedics, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Zheng GaoDepartment of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Zhuang MiaoDepartment of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Union Hospital · CNJilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression data were analysed using bioinformatic tools to demonstrate molecular mechanisms underlying the glioma CpG island methylator phenotype (CIMP). A gene expression data set (accession no. GSE30336) was downloaded from Gene Expression Omnibus, including 36 CIMP+ and 16 CIMP- glioma samples. Differential analysis was performed for CIMP+ vs. CIMP‑ samples using the limma package in R. Functional enrichment analysis was subsequently conducted for differentially expressed genes (DEGs) using Database for Annotation, Visualization and Integration Discovery. Protein‑protein interaction (PPI) networks were constructed for upregulated and downregulated genes with information from STRING. MicroRNAs (miRNAs) targeting DEGs were also predicted using WebGestalt. A total of 439 DEGs were identified, including 214 upregulated and 198 downregulated genes. The upregulated genes were involved in extracellular matrix organisation, defence and immune response, collagen fibril organisation and regulation of cell motion and the downregulated genes in cell adhesion, sensory organ development, regulation of system process, neuron differentiation and membrane organisation. A PPI network containing 134 nodes and 314 edges was constructed from the upregulated genes, whereas a PPI network consisting of 85 nodes and 80 edges was obtained from the downregulated genes. miRNAs regulating upregulated and downregulated genes were predicted, including miRNA‑124a and miRNA‑34a. Numerous key genes associated with glioma CIMP were identified in the present study. These findings may advance the understanding of glioma and facilitate the development of appropriate therapies.

Indexed as

CpG IslandsDNA MethylationGene Expression Regulation, NeoplasticGene Regulatory NetworksGliomaHumansMicroRNAsMolecular Sequence AnnotationProtein Interaction MappingProtein Interaction MapsMicroRNAs

Identifiers

PMID29152649
PMCPMC5780009
OpenAlexW2765726906

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.