Evidence map›Paper›PMID 32791689›Full record

ArticleMedicine2020

An autophagy-related model of 4 key genes for predicting prognosis of patients with laryngeal cancer.

Meng-Si Luo, Guan-Jiang Huang, Hong-Bing Liu

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. 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
0.7field-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

3 citing papers in PubMed, 9 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

3 authors at 2 institutions in 1 country.

Meng-Si LuoDepartment of Anesthesiology, Zhongshan Hospital of Traditional Chinese Medicine, Affiliated to Guangzhou University of Chinese Medicine, Zhongshan, Guangdong Province.
Guan-Jiang HuangDepartment of Otorhinolaryngology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province.
Hong-Bing LiuDepartment of Otolaryngology-head and neck Surgery, The Second Affiliated Hospital of Nanchang University. No 1, Nanchang, Jiangxi, People's Republic of China.
Second Affiliated Hospital of Zhejiang University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autophagy, a major cause of cancer-related death, is correlated with the pathogenesis of various diseases including cancers. Our study aimed to develop an autophagy-related model for predicting prognosis of patients with laryngeal cancer.We analyzed the correlation between expression profiles of autophagy-related genes (ARGs) and clinical outcomes in 111 laryngeal cancer patients from The Cancer Genome Atlas (TCGA). Afterward, gene functional enrichment analyses of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to find the major biological attributes. Univariate Cox regression analyses and multivariate Cox regression analyses were performed to screen ARGs whose expression profiles were significantly associated with laryngeal cancer patients overall survival (OS). Furthermore, to provide the doctors and patients with a quantitative method to perform an individualized survival prediction, we constructed a prognostic nomogram.Thirty eight differentially expressed ARGs were screened out in laryngeal cancer patients through the TCGA database. Related functional enrichments may act as tumor-suppressive roles in the tumorigenesis of laryngeal cancer. Subsequently, 4 key prognostic ARGs (IKBKB, ST13, TSC2, and MAP2K7) were identified from all ARGs by the Cox regression model, which significantly correlated with OS in laryngeal cancer. Furthermore, the risk score was constructed, which significantly divided laryngeal cancer patients into high- and low-risk groups. Integrated with clinical characteristics, gender, N and the risk score are very likely associated with patients OS. A prognostic nomogram of ARGs was constructed using the Cox regression model.Our study could provide a valuable prognostic model for predicting the prognosis of laryngeal cancer patients and a new understanding of autophagy in laryngeal cancer.

Indexed as

NomogramsAge FactorsAutophagyCarrier ProteinsFemaleGene Expression ProfilingHumansI-kappa B KinaseLaryngeal NeoplasmsMaleMAP Kinase Kinase 7Models, BiologicalMolecular ChaperonesNeoplasm StagingPrognosisProportional Hazards ModelsCarrier ProteinsI-kappa B KinaseIKBKB protein, humanMAP2K7 protein, humanMAP Kinase Kinase 7Molecular ChaperonesST13 protein, humanTSC2 protein, humanTuberous Sclerosis Complex 2 ProteinTumor Suppressor Proteins

Identifiers

PMID32791689
PMCPMC7386963
OpenAlexW3045020839

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.