Evidence map›Paper›PMID 34350240›Full record

ArticleAnnals of translational medicine2021

Identification of an IFN-β-associated gene signature for the prediction of overall survival among glioblastoma patients.

Lijing Cheng, Meiling Yuan, Shu Li, Zhiying Lian, Junjing Chen, Weibiao Lin, Jianbo Zhang, Shupeng Zhong

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Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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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

8 authors at 5 institutions in 1 country.

Lijing ChengDepartment of Neurology, The First Affiliated Hospital of Dali University, Dali University, Dali, China.
Meiling YuanDepartment of Neurology, The First Affiliated Hospital of Dali University, Dali University, Dali, China.
Shu LiDepartment of Neurology, Jinshan Hospital, Benxi Jinshan Affiliated Hospital of Dalian Medical University, Benxi, China.
Zhiying LianSecond Clinical Medical College, Southern Medical University, Guangzhou, China.
Junjing ChenDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, China.
Weibiao LinDepartment of Neurosurgery, Zhongshan City People's Hospital, Zhongshan, China.
Jianbo ZhangDepartment of Neurosurgery, Zhongshan City People's Hospital, Zhongshan, China.
Shupeng ZhongDepartment of Oncology, Zhongshan City People's Hospital, Zhongshan, China.
Zhongshan People's Hospital · CNDali University · CNDalian Medical University · CNNanchang University · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBrain glioblastoma multiforme (GBM) is the most common primary malignant intracranial tumor. The prognosis of this disease is extremely poor. While the introduction of β-interferon (IFN-β) regimen in the treatment of gliomas has significantly improved the outcome of patients; The mechanism by which IFN-β induces increased TMZ sensitivity has not been described. Therefore, the main objective of the study was to elucidate the molecular mechanisms responsible for the beneficial effect of IFNβ in GBM.

methodsMessenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) GBM and GSE83300 dataset from the Gene Expression Omnibus. Univariate Cox regression analysis and lasso Cox regression model established a novel 4-gene IFN-β signature (peroxiredoxin 1, Sec61 subunit beta, X-ray repair cross-complementing 5, and Bcl-2-like protein 2) for GBM prognosis prediction. Further, GBM samples (n=50) and normal brain tissues (n=50) were then used for real-time polymerase chain reaction experiments. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. Pearson correlation was applied to calculate the correlation between the long non-coding RNAs (lncRNAs) and IFN-β-associated genes. An lncRNA with a correlation coefficient |R

resultsPatients in the high-risk group had significantly poorer survival than patients in the low-risk group. The signature was found to be an independent prognostic factor for GBM survival. Furthermore, GSEA revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust 4-gene IFN-β signature for GBM prognosis prediction. The signature might contain potential biomarkers for metabolic therapy and treatment response prediction for GBM patients.

conclusionsIn the present study, we established a novel IFN-β-associated gene signature to predict the overall survival of GBM patients, which may help in clinical decision making for individual treatment.

Indexed as

Chinese Glioma Genome Atlas (CGGA)Gene Expression Omnibus (GEO)glioblastomaprognostic modelThe Cancer Genome Atlas (TCGA)β-interferon (IFN-β)

Identifiers

PMID34350240
PMCPMC8263857
OpenAlexW3168098587

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.