Evidence map›Paper›PMID 39913623›Full record

ArticlePloS one2025

Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment.

Ting Yi

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

1 author.

Ting YiSouthern University of Science and Technology Hospital, Shenzhen, Guangdong, China.ORCID https://orcid.org/0009-0006-3239-3832

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile drug therapy and allergen immunotherapy are useful for alleviating symptoms of seasonal allergic rhinitis (AR), existing therapeutic options remain limited. Cuproptosis is a novel form of programmed cell death, and its role in allergic rhinitis has not yet been explored. Researching the interaction between cuproptosis and allergic rhinitis will likely pave the way for future treatment of this disease.

methodsA microarray dataset of AR patients and normal controls (GSE43523) were obtained from the Gene Expression Omnibus (GEO) database for differential gene analysis. Cuproptosis related genes were extracted from the differentially expressed genes (DEGs) to form the AR/cuprotosis-gene set and analyzed by the GO and KEGG databases. Intersection analysis further defined the AR signature genes (AR-sg). Consensus cluster analyses were used to define the AR/cuprotosis-genes into subsets. Finally, AR signature genes were used as targets for drug prediction and molecular docking to identify candidate drugs that may affect SAR.

resultsFour AR signature genes (MRPS30, CLPX, MRPL13, and MRPL53) were selected by the MCC, EPC, BottleNeck, and Closeness algorithms. Correlation analysis of the AR signature genes and immune genes showed strong interactions; xCell analysis identified multiple immune cell types and supported these cells' importance in the AR pathogenesis. Finally, drug target analysis suggests that 1,5-isoquinolinediol and gefitinib have the potential to become future AR treatments.

conclusionOur study analyzed allergic rhinitis and cuproptosis related genes by the bioinformatics approach and predicted 1,5-isoquinolinediol and gefitinib as potentially useful drugs for treating AR patients in the future.

Indexed as

Rhinitis, AllergicDatabases, GeneticGene Expression ProfilingHumansMolecular Docking Simulation

Identifiers

PMID39913623
PMCPMC11801562

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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.