Evidence map›Paper›PMID 33365061›Full record

ArticleExperimental and therapeutic medicine2021

Interaction network of immune-associated genes affecting the prognosis of patients with glioblastoma.

Xiaohong Hou, Jialin Chen, Qiang Zhang, Yinchun Fan, Chengming Xiang, Guiyin Zhou, Fang Cao, Shengtao Yao

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 4 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 2 institutions in 1 country.

Xiaohong HouDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Jialin ChenDepartment of Neonatology, The First People's Hospital of Zunyi Affiliated to Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Qiang ZhangDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Yinchun FanDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Chengming XiangDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Guiyin ZhouDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Fang CaoDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Shengtao YaoDepartment of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Zunyi Medical University · CNFirst People’s Hospital of Zunyi · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is a common malignant tumor type of the nervous system. The purpose of the present study was to establish a regulatory network of immune-associated genes affecting the prognosis of patients with GBM. The GSE4290, GSE50161 and GSE2223 datasets from the Gene Expression Omnibus database were screened to identify common differentially expressed genes (co-DEGs). A functional enrichment analysis indicated that the co-DEGs were mainly enriched in cell communication, regulation of enzyme activity, immune response, nervous system, cytokine signaling in immune system and the AKT signaling pathway. The co-DEGs accumulated in immune response were then further investigated. For this, the intersection of those co-DEGs and currently known immune-regulatory genes was obtained and a differential expression analysis of these overlapping immune-associated genes was performed. A risk model was established using immune-regulatory genes that affect the prognosis of patients with GBM. The risk score was significantly associated with the prognosis of patients with GBM and had a significant independent predictive value. The risk model had high accuracy in predicting the prognosis of patients with GBM [area under the receiver operating characteristic curve (AUC)=0.764], which was higher than that of a previously reported model of prognosis-associated biomarkers (AUC=0.667). Furthermore, an interaction network was constructed by using immune-regulatory genes and transcription factors affecting the prognosis of patients with GBM and the University of California Santa Cruz database was used to perform a preliminary analysis of the transcription factors and immune genes of interest. The interaction network of immune-regulatory genes constructed in the present study enhances the current understanding of mechanisms associated with poor prognosis of patients with GBM. The risk score model established in the present study may be used to evaluate the prognosis of patients with GBM.

Indexed as

Gene Expression Omnibusglioblastomaimmune genepoor prognosisThe Cancer Genome Atlas

Identifiers

PMID33365061
PMCPMC7716634
OpenAlexW3101246503

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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.