Evidence map›Paper›PMID 29502292›Full record

ArticleJournal of molecular neuroscience : MN2018

Whole-Genome Expression Microarray Combined with Machine Learning to Identify Prognostic Biomarkers for High-Grade Glioma.

Chang Shu, Qiong Wang, Xiaoling Yan, Jinhuan Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of molecular neuroscience : MN, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Review
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  10. Prognosis Analysis and Validation of mFrontiers in oncology · 2020
    Article
  11. 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

4 authors at 2 institutions in 1 country.

Chang ShuSchool of Medicine, Nankai University, 94 Weijin Road, Tianjin, 300071, China.
Qiong WangTianjin Cerebral Vascular and Neural Degenerative Disease Key Laboratory, Tianjin Neurosurgery Institute, Tianjin Huan Hu Hospital, Tianjin, 300100, China.
Xiaoling YanTianjin Cerebral Vascular and Neural Degenerative Disease Key Laboratory, Tianjin Neurosurgery Institute, Tianjin Huan Hu Hospital, Tianjin, 300100, China.
Jinhuan WangSchool of Medicine, Nankai University, 94 Weijin Road, Tianjin, 300071, China. huanhuwangjinhuan@126.com.ORCID http://orcid.org/0000-0003-3816-1291
Nankai University · CNTianjin Huanhu Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of our study is to build a framework for a better understanding of high-grade glioma (HGG) prognostic-related biomarkers. Whole-genome gene expression microarray was performed to identify differently expressed genes between HGGs and low-grade diffuse gliomas. Several machine learning algorithms were used to filter prognostic-related genes. One hundred ninety-three HGG patients after surgical resection were selected for survival analysis. Immunohistochemistry were performed on these tumor samples to analyze IDH1 mutation status and protein expression of WEE1. qRT-PCR, western blotting, transwell assays, and scratch wound healing assays were performed to evaluate the effect of WEE1 knockdown or overexpression in HGG cells. Three prognostic-related genes (WEE1, IGF2PB3, and EMP3) were demonstrated to separate HGG patients into two different survival subgroups. The area under receiver operating characteristic curve of WEE1 was higher than that of IGF2BP3, EMP3, age, IDH status, 1p/19q status, and MGMT promoter status. WEE1 was an independent covariate compared with IDH status, age, and WHO grade. Knockdown or overexpression of WEE1 can inhibit or promote migration and invasion in U251 and U87 cell lines. WEE1, EMP3, and IGF2BP3 are reliable prognostic-related genes at the mRNA level. WEE1 is an independent prognostic biomarker in survival analysis and has potential diagnostic value for HGG patients. WEE1 can induce HGG cell migration and invasion in vitro.

Indexed as

Biomarkers, TumorBrain NeoplasmsCell Cycle ProteinsCell Line, TumorCell MovementDNA Modification MethylasesDNA Repair EnzymesFemaleGene Expression ProfilingGliomaHumansInsulin-Like Growth Factor IIMachine LearningMaleMembrane GlycoproteinsMutationBiomarkers, TumorCell Cycle ProteinsDNA Modification MethylasesDNA Repair EnzymesEMP3 protein, humanIGF2 protein, humanInsulin-Like Growth Factor IIMembrane GlycoproteinsMGMT protein, humanNuclear ProteinsProtein-Tyrosine KinasesTumor Suppressor ProteinsWEE1 protein, humanEMP3High-grade gliomaIGF2BP3MicroarrayWEE1

Identifiers

PMID29502292
OpenAlexW2793617808

What OpenQuestion holds

Textmetadata
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.