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pmid:36820598

Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer.

Weichang Yang · Zhouhua Li · Wenjun Wang · Juan Wu · Xiaoqun Ye

Medicine · 2023 doi:10.1097/MD.0000000000032861

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:36820598
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title
Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer.
doi
10.1097/MD.0000000000032861
pmid
36820598
authors array · 5 items
[0]
Weichang Yang
[1]
Zhouhua Li
[2]
Wenjun Wang
[3]
Juan Wu
[4]
Xiaoqun Ye
journal
Medicine
year
2023
abstract
Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.
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The GEO online analysis tool, GEO2R, was used to analyze the DEGs between asthma data GSE143303 (GPL10558) and NSCLC data GSE18842 (GPL570).
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The datasets generated during and/or analyzed during the current study are publicly available.
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The analysis identified 114 common differentially expressed genes between asthma and NSCLC.
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sections[13] "3.1. Identification of DEGs and common genes" paragraph 2
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The DEGs of GSE143303 and GSE18842 were analyzed by constructing a Venn diagram, and 114 common genes were obtained.
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The analysis identified 114 common differentially expressed genes between asthma and NSCLC.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36820598", "kind": "science-record", "revision": 3, "content_hash": "sha256:2f00c51be4a06a1ae829fe60aa5a91e32c7de83e9455ad5cecf929445735be61", "created_at": "2026-11-01T19:01:25Z", "updated_at": "2026-11-01T22:08:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer.", "doi": "10.1097/MD.0000000000032861", "pmid": "36820598", "authors": ["Weichang Yang", "Zhouhua Li", "Wenjun Wang", "Juan Wu", "Xiaoqun Ye"], "journal": "Medicine", "year": 2023, "abstract": "Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.", "claims": [{"id": "claim-method", "statement": "The GEO online analysis tool, GEO2R, was used to analyze the DEGs between asthma data GSE143303 (GPL10558) and NSCLC data GSE18842 (GPL570).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36820598", "locator": "sections[4] \"2.2. 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