Evidence map›Paper›PMID 33290989›Full record

ArticleTranslational oncology2021

Hub gene identification and prognostic model construction for isocitrate dehydrogenase mutation in glioma.

Yanfei Jia, Wenzhen Yang, Bo Tang, Qian Feng, Zhiqiang Dong

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2021. 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
0.2field-weighted citation impact, top 55% 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, 4 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Yanfei JiaDepartment of Neurosurgery, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu Province 730000, China.
Wenzhen YangDepartment of Neurosurgery, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu Province 730000, China.
Bo TangDepartment of Neurosurgery, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu Province 730000, China.
Qian FengDepartment of Neurosurgery, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu Province 730000, China.
Zhiqiang DongDepartment of Neurosurgery, Lanzhou University Second Hospital, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu Province 730000, China. Electronic address: dongzqiang443@aliyun.com.
Lanzhou University Second Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our study attempted to identify hub genes related to isocitrate dehydrogenase (IDH) mutation in glioma and develop a prognostic model for IDH-mutant glioma patients. In a first step, ten hub genes significantly associated with the IDH status were identified by weighted gene coexpression analysis (WGCNA). The functional enrichment analysis demonstrated that the most enriched terms of these hub genes were cadherin binding and glutathione metabolism. Three of these hub genes were significantly linked with the survival of glioma patients. 328 samples of IDH-mutant glioma were separated into two datasets: a training set (N = 228) and a test set (N = 100). Based on the training set, we identified two IDH-mutant subtypes with significantly different pathological features by using consensus clustering. A 31 gene-signature was identified by the least absolute shrinkage and selection operator (LASSO) algorithm and used for establishing a differential prognostic model for IDH-mutant patients. In addition, the test set was employed for validating the prognostic model, and the model was proven to be of high value in classifying prognostic information of samples. The functional annotation revealed that the genes related to the model were mainly enriched in nuclear division, DNA replication, and cell cycle. Collectively, this study provided novel insights into the molecular mechanism of IDH mutation in glioma, and constructed a prognostic model which can be effective for predicting prognosis of glioma patients with IDH-mutation, which might promote the development of IDH target agents in glioma therapies and contribute to accurate prognostication and management in IDH-mutant glioma patients.

Indexed as

GliomaIDH mutationMachine learningPrognosisWGCNA

Identifiers

PMID33290989
PMCPMC7720094
OpenAlexW3111635306

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.