Evidence map›Paper›PMID 34754221›Full record

ArticleInternational journal of general medicine2021

Identification and Validation of a Seizure-Free-Related Gene Signature for Predicting Poor Prognosis in Lower-Grade Gliomas.

Jinxing Li, Jing Huan, Fu Yang, Haixin Chen, Mingguang Wang, Xueyuan Heng

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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 3 institutions in 1 country.

Jinxing LiGuangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong, People's Republic of China.
Jing HuanGuangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong, People's Republic of China.
Fu YangGuangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong, People's Republic of China.
Haixin ChenDepartment of Neurosurgery, Linyi People's Hospital, Linyi, 276000, Shandong, People's Republic of China.
Mingguang WangDepartment of Neurosurgery, Linyi People's Hospital, Linyi, 276000, Shandong, People's Republic of China.
Xueyuan HengDepartment of Neurosurgery, Linyi People's Hospital, Linyi, 276000, Shandong, People's Republic of China.
Linyi People's Hospital · CNGuangzhou University of Chinese Medicine · CNWeifang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLower-grade gliomas (LGGs) patients presented seizure-free have a worse survival than those presented with seizures. However, the current knowledge on its potential value in LGGs remains scarce. PURPOSE: This study aimed to identify a novel gene signature associated with seizures-free for predicting poor prognosis for LGGs patients. MATERIALS AND

methodsThe RNA expression and clinical information of LGGs patients were downloaded from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were screened out between LGGs patients presented seizures-free and seizures. The novel gene signature was constructed by Lasso and multivariate regression analyses for predicting prognosis in LGGs. Its prognostic value was assessed and validated by Kaplan-Meier analyses and receiver operating characteristic (ROC) curves. Multivariate regression analysis was applied to identify the independent prognostic value of the gene signature. Furthermore, bioinformatics analysis was performed to elucidate the molecular mechanisms.

resultsA total of 253 DEGs were screened out between LGG patients presented with seizures and free of seizures. A 5-gene signature (HIST1H4F, HORMAD2, LILRA3, PRSS33, and TBX20 genes) was constructed from these 253 DEGs. Kaplan-Meier analyses and ROC curves assessed and validated the good performance of the 5-gene signature in differentiating and predicting prognosis of high- and low-risk patients. Multivariate regression analysis determined the independent prognostic value of the 5-gene signature. According to bioinformatics analysis, DEGs were mainly enriched in biological processes related to positive regulation of transcription from RNA polymerase II promoter, G-protein coupled receptor signaling pathway, and pathways of cytokine-cytokine receptor interaction, chemokine signaling pathway.

conclusionOur findings suggested that the 5-gene signature might serve as a potential prognostic biomarker and provide guidance for the personalized LGGs management.

Indexed as

gene signaturelower-grade gliomasseizures-free

Identifiers

PMID34754221
PMCPMC8570923
OpenAlexW3209768363

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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.