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

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 d...

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Autores principales: Yang, Weichang, Li, Zhouhua, Wang, Wenjun, Wu, Juan, Ye, Xiaoqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907931/
https://www.ncbi.nlm.nih.gov/pubmed/36820598
http://dx.doi.org/10.1097/MD.0000000000032861
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author Yang, Weichang
Li, Zhouhua
Wang, Wenjun
Wu, Juan
Ye, Xiaoqun
author_facet Yang, Weichang
Li, Zhouhua
Wang, Wenjun
Wu, Juan
Ye, Xiaoqun
author_sort Yang, Weichang
collection PubMed
description 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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spelling pubmed-99079312023-02-10 Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer Yang, Weichang Li, Zhouhua Wang, Wenjun Wu, Juan Ye, Xiaoqun Medicine (Baltimore) 5700 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. Lippincott Williams & Wilkins 2023-02-10 /pmc/articles/PMC9907931/ /pubmed/36820598 http://dx.doi.org/10.1097/MD.0000000000032861 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 5700
Yang, Weichang
Li, Zhouhua
Wang, Wenjun
Wu, Juan
Ye, Xiaoqun
Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title_full Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title_fullStr Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title_full_unstemmed Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title_short Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
title_sort five-hub genes identify potential mechanisms for the progression of asthma to lung cancer
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907931/
https://www.ncbi.nlm.nih.gov/pubmed/36820598
http://dx.doi.org/10.1097/MD.0000000000032861
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