Evidence map›Paper›PMID 34267555›Full record

ArticleCancer management and research2021

Dissecting Prognosis Modules and Biomarkers in Glioblastoma Based on Weighted Gene Co-Expression Network Analysis.

Fang Cao, Yinchun Fan, Yunhu Yu, Guohua Yang, Hua Zhong

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 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

5 authors at 3 institutions in 1 country.

Fang Cao *Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, 563000, People's Republic of China.ORCID 0000-0002-4900-8957
Yinchun Fan *Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, 563000, People's Republic of China.ORCID 0000-0002-1034-9738
Yunhu YuClinical Research Center for Neurological Disease, the People's Hospital of Hong Hua Gang District of ZunYi, Zunyi, 563000, People's Republic of China.
Guohua YangDemonstration Center for Experimental Basic Medicine Education of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.
Hua ZhongCollege of Life Sciences, Wuhan University, Wuhan, Hubei, 430072, People's Republic of China.ORCID 0000-0002-9358-1582
Wuhan University · CNZunyi Medical University · CNFirst People’s Hospital of Zunyi · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAs one of the most prevalent and malignant brain cancers, glioblastoma multiforme (GBM) presents a poor prognosis and the molecular mechanisms remain poorly understood. Consequently, molecular research, including various biomarkers, is essential to exploit the occurrence and development of glioma.

methodsWeighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression modules and networks based on the Chinese Glioma Genome Atlas (CGGA) glioblastoma specimens. Then, protein-protein interaction (PPI) and gene ontology (GO) analyses were performed to mine hub genes. RT-PCR and immunohistochemistry were employed to examine the expression level of GRPR, CXCL5, and CXCL11 in glioma patients.

resultsWe confirmed two gene modules by protein-protein interaction networks. Functional enrichment analysis was performed to identify the significance of gene modules. Prognostic biomarkers

conclusionIn this study, we developed and confirmed three mRNA signatures (GRPR, CXCL5, and CXCL11) for evaluating overall survival in GBM patients. Our research assists in existing understanding of GBM diagnosis and prognosis.

Indexed as

biomarkersCGGAGBMTCGAWGCNA

Identifiers

PMID34267555
PMCPMC8276137
OpenAlexW3181874873

What OpenQuestion holds

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LicenceCC BY-NC
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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.