Evidence map›Paper›PMID 32410107›Full record

ArticleCellular and molecular neurobiology2021

An Immune-Related lncRNA Signature to Predict Survival In Glioma Patients.

Pengfei Xia, Qing Li, Guanlin Wu, Yimin Huang

Open access · greenAbstract read
In one paragraph

Article in Cellular and molecular neurobiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
3.8field-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

42 citing papers in PubMed, 65 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

4 authors at 2 institutions in 1 country.

Pengfei XiaCellular Neuroscience, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.ORCID http://orcid.org/0000-0001-5086-1755
Qing LiCharité-Universitätsmedizin Berlin, Berlin, Germany.
Guanlin WuCharité-Universitätsmedizin Berlin, Berlin, Germany.ORCID http://orcid.org/0000-0001-9711-452X
Yimin HuangCellular Neuroscience, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany. yimin.huang@mdc-berlin.de.ORCID http://orcid.org/0000-0001-9600-1195
Charité - Universitätsmedizin Berlin · DEMax Delbrück Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioma is the most common and fatal primary brain tumor in human. Long non-coding RNA (lncRNA), which are characterized by regulation of gene expression and chromatin recombination play an important role in glioma, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify Immune-related lncRNAs in glioma. In this study,we collected and evaluated the RNA-seq data of The Cancer Genome Atlas (TCGA, https://www.ncbi.nlm.nih.gov/ ) and Chinese Glioma Genome Atlas (CGGA, https://www.cgga.org.cn/ ) glioma patients and immune-related lncRNAs were screened. Cox regression and LASSO analysis were performed to construct a risk score formula to explor the different overall survival between high- and low-risk groups in TCGA and verified with CGGA. Gene ontology (GO) and pathway-enrichment analysis (KEGG) were performed to identify the function of screened genes. Co-expression network were performed of these genes for further analysis. Eleven immune-related lncRNAs were concerned to be involved in survival and adopted to construct the risk score formula. Patients with high-risk score held poor survival both in TCGA and CGGA. Compared with current clinical data, the Area Under Curve (AUC) of different years and Principal components analysis (PCA) suggested that the formula had better predictive power. Functional Annotation of immune-related lncRNAs showed that the differences overall survival of high and low RS group might be caused by the cell differentiation, microtubule polymerization, etc. We successfully constructed an immune-related lncRNAs formula with powerful predictive function, which provides certain guidance value to the analysis of glioma pathogenesis and clinical treatment, and potential therapeutic targets for glioma treatment.

Indexed as

Gene Expression ProfilingAlgorithmsBrain NeoplasmsCell Line, TumorGene Expression Regulation, NeoplasticGliomaHumansKaplan-Meier EstimateMolecular Sequence AnnotationPrincipal Component AnalysisPrognosisProportional Hazards ModelsReproducibility of ResultsRNA, Long NoncodingSurvival AnalysisRNA, Long NoncodingGliomaImmuneLncRNAPrognosis

Identifiers

PMID32410107
PMCPMC11448555
OpenAlexW3025745989

What OpenQuestion holds

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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.