Evidence map›Paper›PMID 34773716›Full record

ArticleJournal of clinical laboratory analysis2021

Drug metabolism-related eight-gene signature can predict the prognosis of gastric adenocarcinoma.

Hong-Mei Yin, Qiong He, Jia Chen, Zhen Li, Wanli Yang, Xiaobo Hu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 13 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

6 authors at 2 institutions in 1 country.

Hong-Mei YinDepartment of Clinical Laboratory, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Qiong HePathology Department, Fudan University Shanghai Cancer Center, Shanghai, China.
Jia ChenDepartment of Clinical Laboratory, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Zhen LiDepartment of Clinical Laboratory, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Wanli YangDepartment of Clinical Laboratory, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiaobo HuDepartment of Clinical Laboratory, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID https://orcid.org/0000-0001-5467-9512
Shanghai University of Traditional Chinese Medicine · CNFudan University Shanghai Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic abnormalities in patients with gastric adenocarcinoma lead to drug resistance and poor prognosis. Therefore, this study aimed to explore biomarkers that can predict the prognostic risk of gastric adenocarcinoma by analyzing drug metabolism-related genes.

methodsThe RNA-seq and clinical information on gastric adenocarcinoma were downloaded from the UCSC and gene expression omnibus databases. Univariate and least absolute shrinkage and selection operator regression analyses were used to identify the prognostic gene signature of gastric adenocarcinoma. The relationships between gastric adenocarcinoma prognostic risk and tumor microenvironment were assessed using CIBERSORT, EPIC, QUANTISEQ, MCPCounter, xCell, and TIMER algorithms. The potential drugs that could target the gene signatures were predicted in WebGestalt, and molecular docking analysis verified their binding stabilities.

resultsCombined with clinical information, an eight-gene signature, including GPX3, ABCA1, NNMT, NOS3, SLCO4A1, ADH4, DHRS7, and TAP1, was identified from the drug metabolism-related gene set. Based on their expressions, risk scores were calculated, and patients were divided into high- and low-risk groups, which had significant differences in survival status and immune infiltrations. Risk group was also identified as an independent prognostic factor of gastric adenocarcinoma, and the established prognostic and nomogram models exhibited excellent capacities for predicting prognosis. Finally, miconazole and niacin were predicted as potential therapeutic drugs for gastric adenocarcinoma that bond stably with NOS3 and NNMT through hydrogen interactions.

conclusionsThis study proposed a drug metabolism-related eight-gene signature as a potential biomarker to predict the gastric adenocarcinoma prognosis risks.

Indexed as

AdenocarcinomaAdultAgedBiomarkers, TumorGlyburideHumansInactivation, MetabolicMiconazoleMiddle AgedMolecular Docking SimulationNomogramsPrognosisProtein Interaction MapsProteinsReproducibility of ResultsRisk FactorsBiomarkers, TumorGlyburideMiconazoleProteinsdrug metabolismgastric adenocarcinomaimmune microenvironmentmolecular dockingprognostic model

Identifiers

PMID34773716
PMCPMC8649372
OpenAlexW3212897405

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LicenceCC BY-NC-ND
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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.