Evidence map›Paper›PMID 34222011›Full record

ArticleFrontiers in oncology2021

A Novel Classification of Glioma Subgroup, Which Is Highly Correlated With the Clinical Characteristics and Tumor Tissue Characteristics, Based on the Expression Levels of Gβ and Gγ Genes.

Zehao Cai, Chunna Yu, Shenglan Li, Can Wang, Yaqiong Fan, Qiang Ji, Feng Chen, Wenbin Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 10 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.

Zehao CaiDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Chunna YuDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Shenglan LiDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Can WangDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Yaqiong FanDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Qiang JiDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Feng ChenDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.
Wenbin LiDepartment of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical Unversity, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGlioma is a classical type of primary brain tumors that is most common seen in adults, and its high heterogeneity used to be a reference standard for subgroup classification. Glioma has been diagnosed based on histopathology, grade, and molecular markers including IDH mutation, chromosome 1p/19q loss, and H3K27M mutation. This subgroup classification cannot fully meet the current needs of clinicians and researchers. We, therefore, present a new subgroup classification for glioma based on the expression levels of Gβ and Gγ genes to complement studies on glioma and Gβγ subunits, and to support clinicians to assess a patient's tumor status.

methodsGlioma samples retrieved from the CGGA database and the TCGA database. We clustered the gliomas into different groups by using expression values of Gβ and Gγ genes extracted from RNA sequencing data. The Kaplan-Meier method with a two-sided log-rank test was adopted to compare the OS of the patients between GNB2 group and non-GNB2 group. Univariate Cox regression analysis was referred to in order to investigate the prognostic role of each Gβ and Gγ genes. KEGG and ssGSEA analysis were applied to identify highly activated pathways. The "estimate" package, "GSVA" package, and the online analytical tools CIBERSORTx were employed to evaluate immune cell infiltration in glioma samples.

resultsThree subgroups were identified. Each subgroup had its own specific pathway activation pattern and other biological characteristics. High M2 cell infiltration was observed in the GNB2 subgroup. Different subgroups displayed different sensitivities to chemotherapeutics. GNB2 subgroup predicted poor survival in patients with gliomas, especially in patients with LGG with mutation IDH and non-codeleted 1p19q.

conclusionThe subgroup classification we proposed has great application value. It can be used to select chemotherapeutic drugs and the prognosis of patients with target gliomas. The unique relationships between subgroups and tumor-related pathways are worthy of further investigation to identify therapeutic Gβγ heterodimer targets.

Indexed as

gliomaG protein subunitprognosisRNA sequencing datasubgroup classification

Identifiers

PMID34222011
PMCPMC8250418
OpenAlexW3173331043

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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.