Evidence map›Paper›PMID 31729991›Full record

ArticleBMC medical genomics2019

Classification of glioma based on prognostic alternative splicing.

Yaomin Li, Zhonglu Ren, Yuping Peng, Kaishu Li, Xiran Wang, Guanglong Huang, Songtao Qi, Yawei Liu

Abstract read
In one paragraph

Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
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

25 citing papers in PubMed.

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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.

Yaomin LiDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China.
Zhonglu RenCollege of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, 510515, Guangdong, China.
Yuping PengDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China.
Kaishu LiDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China.
Xiran WangDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China.
Guanglong HuangDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China.
Songtao QiDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China. qisongtaonfyy@126.com.
Yawei LiuDepartment of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Dadao Bei Street 1838#, Guangzhou, People's Republic of China. liuyawei@smu.edu.cn.ORCID 0000-0003-4535-5019

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreviously developed classifications of glioma have provided enormous advantages for the diagnosis and treatment of glioma. Although the role of alternative splicing (AS) in cancer, especially in glioma, has been validated, a comprehensive analysis of AS in glioma has not yet been conducted. In this study, we aimed at classifying glioma based on prognostic AS.

methodsUsing the TCGA glioblastoma (GBM) and low-grade glioma (LGG) datasets, we analyzed prognostic splicing events. Consensus clustering analysis was conducted to classified glioma samples and correlation analysis was conducted to characterize regulatory network of splicing factors and splicing events.

resultsWe analyzed prognostic splicing events and proposed novel splicing classifications across pan-glioma samples (labeled pST1-7) and across GBM samples (labeled ST1-3). Distinct splicing profiles between GBM and LGG were observed, and the primary discriminator for the pan-glioma splicing classification was tumor grade. Subtype-specific splicing events were identified; one example is AS of zinc finger proteins, which is involved in glioma prognosis. Furthermore, correlation analysis of splicing factors and splicing events identified SNRPB and CELF2 as hub splicing factors that upregulated and downregulated oncogenic AS, respectively.

conclusionA comprehensive analysis of AS in glioma was conducted in this study, shedding new light on glioma heterogeneity and providing new insights into glioma diagnosis and treatment.

Indexed as

Alternative SplicingAdultBrain NeoplasmsCELF ProteinsCluster AnalysisDisease-Free SurvivalDNA MethylationFemaleGene Regulatory NetworksGlioblastomaGliomaHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm GradingCELF2 protein, humanCELF ProteinsNerve Tissue ProteinssnRNP Core ProteinsSNRPB protein, humanAlternative splicingClassificationGlioblastomaGliomaPrognosis

Identifiers

PMID31729991
PMCPMC6858651

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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.