Evidence map›Paper›PMID 40102503›Full record

ArticleScientific reports2025

Identification of hub genes between moderate to severe asthma and early lung adenocarcinoma through bioinformatics analysis.

Jiaqian Xue, Qingwei Zhou

Abstract read
In one paragraph

Article in Scientific reports, 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

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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Jiaqian XueRespiratory Department, The First Affiliated Hospital of Henan University of Chinese Medicine, No. 19 Renmin Road, Zhengzhou, 450000, Henan, China.
Qingwei ZhouRespiratory Department, The First Affiliated Hospital of Henan University of Chinese Medicine, No. 19 Renmin Road, Zhengzhou, 450000, Henan, China. hxktt001@126.com.

Funding

the Special Research Project of the National Clinical Research Base of Traditional Chinese Medicine 2022JDZX126
6 · The paper itself

Abstract

The objective of this study was to explore the genetic link between moderate to severe asthma and early-stage lung adenocarcinoma (LUAD) using bioinformatic methods. The Cancer Genome Atlas gene-expression profiles for early-stage LUAD and GSE76225 data set for moderate to severe asthma were selected for weighted gene co-expression network analysis, and intersected with the relevant module genes and selected hub genes; the relevant network of hub genes was then determined through a protein-protein interaction network. In addition, gene-set enrichment analysis and gene-set variation analysis (GSVA) were conducted on differentially expressed genes between normal and tumor groups. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses were applied to detect hub gene-related biological functions. Receiver operating characteristic (ROC) curves were employed to confirm the diagnostic value of hub genes. We identified four key genes, of which SFTPC exhibited relatively high value for areas under the ROC curves, indicating high diagnostic value for moderate to severe asthma. The clinical efficacy of SFTPC was thus consistent with GSVA results, indicating that moderate to severe asthma can inhibit the occurrence of early LUAD.

Indexed as

Adenocarcinoma of LungAsthmaComputational BiologyLung NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansProtein Interaction MapsROC CurveDiagnostic valueEarly-stage lung adenocarcinomaEnrichment analysisModerate to severe asthmaProtein–protein interaction networkWeighted gene co-expression network analysis

Identifiers

PMID40102503
PMCPMC11920247

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Registered trials

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