Evidence map›Paper›PMID 35757472›Full record

ArticleBioMed research international2022

A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma.

Zhikang Wu, Meimei Liu, Jinlong Fu, Jinwei Li, Lingyao Qin, Liuying Wu, Hongmou Chen, Xianlei Yan, Quan Liu, Jiemin Zheng

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2022. 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
0.7field-weighted citation impact, top 36% 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, 8 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

10 authors at 2 institutions in 1 country.

Zhikang WuDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.ORCID https://orcid.org/0000-0001-9358-4970
Meimei LiuDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Jinlong FuDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Jinwei LiDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Lingyao QinDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Liuying WuFaculty of Life Science, Hubei University, Wuhan, China.
Hongmou ChenDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Xianlei YanDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.ORCID https://orcid.org/0000-0002-7490-530X
Quan LiuDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.ORCID https://orcid.org/0000-0002-7477-4987
Jiemin ZhengDepartment of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.ORCID https://orcid.org/0000-0002-4184-2664
Fourth Affiliated Hospital of Guangxi Medical University · CNHubei University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioma is one of the most common intracranial malignancies that plagues people around the world. Despite current improvements in treatment, the prognosis of glioma is often unsatisfactory. Necroptosis is a form of programmed cell death. As research progresses, the role of necroptosis in tumors has gradually attracted the attention of researchers. And lncRNA is regarded as a critical role in the development of cancer. Therefore, this study is aimed at establishing a prognostic model based on necroptosis-associated lncRNAs to accurately assess the prognosis and immune response of patients with glioma. The RNA sequences of glioma patients and normal brain samples were downloaded from The Cancer Genome Atlas (TCGA) and GTEx databases, respectively. The coexpression analysis was performed to identify the necroptosis-related lncRNAs. Then, we utilized LASSO analysis following univariate Cox analysis to construct a prognostic model. Subsequently, we applied the Kaplan-Meier curve, time-dependent receiver operating characteristics (ROC), and univariate and multivariate Cox regression analyses to assess the effectiveness of this model. And the functional enrichment analyses and immune-related analyses were employed to investigate the potential biological functions. A validation set was obtained from the Chinese Glioma Genome Atlas (CGGA) database. And qRT-PCR was employed to further validate the expression levels of selected necroptosis-associated lncRNAs. Seven necroptosis-related lncRNAs (FAM13A-AS1, JMJD1C-AS1, LBX2-AS1, ZBTB20-AS4, HAR1A, SNHG14, and LINC00900) were determined to construct a prognostic model. The area under the ROC curve (AUC) was 0.871, 0.901, and 0.911 at 1, 2, and 3 years, respectively. The risk score was shown to be an important independent predictor in both univariate and multivariate Cox regression analyses. Through functional enrichment analyses, we found that the differentially expressed genes (DEGs) were mainly enriched in protein binding and signaling-related biological functions and immune-associated pathways. In conclusion, we established and validated a novel necroptosis-related lncRNA signature, which could accurately predict the overall survival of glioma patients and serve as potential therapeutic targets.

Indexed as

GliomaRNA, Long NoncodingBiomarkers, TumorGene Expression Regulation, NeoplasticGTPase-Activating ProteinsHumansImmunityJumonji Domain-Containing Histone DemethylasesKaplan-Meier EstimateNecroptosisOxidoreductases, N-DemethylatingPrognosisBiomarkers, TumorFAM13A protein, humanGTPase-Activating ProteinsJMJD1C protein, humanJumonji Domain-Containing Histone DemethylasesOxidoreductases, N-DemethylatingRNA, Long Noncoding

Identifiers

PMID35757472
PMCPMC9226973
OpenAlexW4283010480

What OpenQuestion holds

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LicenceCC BY
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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.