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pmid:40826767

Deciphering molecular overlaps between COPD and NSCLC subtypes (LUAD and LUSC): An integrative bioinformatics study.

Sevinç Akçay

Medicine · 2025 doi:10.1097/MD.0000000000043906

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
Deciphering molecular overlaps between COPD and NSCLC subtypes (LUAD and LUSC): An integrative bioinformatics study.
doi
10.1097/MD.0000000000043906
pmid
40826767
authors array · 1 item
[0]
Sevinç Akçay
journal
Medicine
year
2025
abstract
Chronic obstructive pulmonary disease (COPD) and non-small-cell lung cancer (NSCLC) are major global health problems. Despite clinical differences, emerging evidence suggests common molecular underpinnings, particularly between COPD and the 2 primary NSCLC subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In this integrative bioinformatics case-control study, we analyzed gene expression datasets (GSE76925, GSE18842, and GSE10072) obtained from the Gene Expression Omnibus (GEO) database, each comprising case-control samples. Differentially expressed genes (DEGs) were identified in COPD, LUAD, and LUSC patients. We performed analyses of protein-protein interaction (PPI) networks, investigated regulatory networks involving transcription factors (TFs) and microRNAs (miRNAs), and conducted pathway enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Drug-gene interactions were assessed to explore therapeutic opportunities. We identified 15 shared DEGs between COPD, LUAD, and LUSC, with distinct gene expression patterns between COPD-LUAD and COPD-LUSC. Notably, LUAD exhibited stronger molecular similarities with COPD than with LUSC. PPI analysis revealed COL10A1, POSTN, SPP1, MMP11, and GREM1 as key hub genes in extracellular matrix (ECM) remodeling and tumor progression. Functional enrichment highlighted ECM organization, apoptosis regulation, and transcriptional control as crucial processes in COPD-associated NSCLC. COPD-LUAD was enriched in cancer-related pathways, while COPD-LUSCs showed stronger immune and lipid metabolism involvement. Regulatory network analysis identified SP1 as a key transcriptional regulator, particularly in COPD-LUAD cells. miRNA-DEG interactions highlighted "hsa-miR-335-5p," "hsa-miR-192-5p," and "hsa-miR-215-5p" as the central regulators of COPD and NSCLC. Drug-gene interaction analysis identified Marimastat, Bosentan, and Minocycline as potential therapeutic agents that target key molecular pathways shared across COPD, LUAD and LUSC. Finally, survival analysis revealed that SPP1 (in LUAD), POSTN, and GREM1 (in LUSC) were significantly associated with better overall survival, suggesting their dual utility as both biomarkers and prognostic indicators. Our research highlights the unique regulatory distinctions between LUAD and LUSC while offering fresh insights into the molecular pathways that COPD and NSCLC share. This study represents the initial effort to map TF-miRNA-DEG-drug networks across COPD and both the LUAD and LUSC subtypes. These results suggest potential biomarkers for early diagnosis and highlight opportunities for drug repurposing to mitigate COPD-associated lung cancer risk.
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DEGs were classified into 3 groups: Group 1: COPD, LUSC, and LUAD; Group 2: COPD and LUSC; and Group 3: COPD and LUAD by the GEO2R statistical tool.[16] P < .05, log2FC > 1 (upregulated DEGs), or P < .05, and log2FC < 1 (downregulated DEGs) were the criteria used to identify DEGs.
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sections[4] "2.2. Identification of common DEGs" paragraph 2
quote
DEGs were classified into 3 groups: Group 1: COPD, LUSC, and LUAD; Group 2: COPD and LUSC; and Group 3: COPD and LUAD by the GEO2R statistical tool.[16] P < .05, log2FC > 1 (upregulated DEGs), or P < .05, and log2FC < 1 (downregulated DEGs) were the criteria used to identify DEGs.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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The study identified 15 differentially expressed genes shared among COPD, LUSC, and LUAD.
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sections[11] "3.1. Identification of common DEGs" paragraph 2
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Fifteen common DEGs were identified in COPD, LUSC, and LUAD.
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The study identified 15 differentially expressed genes shared among COPD, LUSC, and LUAD.
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DEGs were classified into 3 groups: Group 1: COPD, LUSC, and LUAD; Group 2: COPD and LUSC; and Group 3: COPD and LUAD by the GEO2R statistical tool.[16] P < .05, log2FC > 1 (upregulated DEGs), or P < .05, and log2FC < 1 (downregulated DEGs) were the criteria used to identify DEGs.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40826767", "kind": "science-record", "revision": 3, "content_hash": "sha256:343fd8bb2bfd65bc81cc02a756fb1eb7599cd86faf48d56025f01af2e624413e", "created_at": "2026-11-01T20:30:55Z", "updated_at": "2026-11-01T22:14:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Deciphering molecular overlaps between COPD and NSCLC subtypes (LUAD and LUSC): An integrative bioinformatics study.", "doi": "10.1097/MD.0000000000043906", "pmid": "40826767", "authors": ["Sevinç Akçay"], "journal": "Medicine", "year": 2025, "abstract": "Chronic obstructive pulmonary disease (COPD) and non-small-cell lung cancer (NSCLC) are major global health problems. Despite clinical differences, emerging evidence suggests common molecular underpinnings, particularly between COPD and the 2 primary NSCLC subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In this integrative bioinformatics case-control study, we analyzed gene expression datasets (GSE76925, GSE18842, and GSE10072) obtained from the Gene Expression Omnibus (GEO) database, each comprising case-control samples. Differentially expressed genes (DEGs) were identified in COPD, LUAD, and LUSC patients. We performed analyses of protein-protein interaction (PPI) networks, investigated regulatory networks involving transcription factors (TFs) and microRNAs (miRNAs), and conducted pathway enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Drug-gene interactions were assessed to explore therapeutic opportunities. We identified 15 shared DEGs between COPD, LUAD, and LUSC, with distinct gene expression patterns between COPD-LUAD and COPD-LUSC. Notably, LUAD exhibited stronger molecular similarities with COPD than with LUSC. PPI analysis revealed COL10A1, POSTN, SPP1, MMP11, and GREM1 as key hub genes in extracellular matrix (ECM) remodeling and tumor progression. Functional enrichment highlighted ECM organization, apoptosis regulation, and transcriptional control as crucial processes in COPD-associated NSCLC. COPD-LUAD was enriched in cancer-related pathways, while COPD-LUSCs showed stronger immune and lipid metabolism involvement. Regulatory network analysis identified SP1 as a key transcriptional regulator, particularly in COPD-LUAD cells. miRNA-DEG interactions highlighted \"hsa-miR-335-5p,\" \"hsa-miR-192-5p,\" and \"hsa-miR-215-5p\" as the central regulators of COPD and NSCLC. Drug-gene interaction analysis identified Marimastat, Bosentan, and Minocycline as potential therapeutic agents that target key molecular pathways shared across COPD, LUAD and LUSC. Finally, survival analysis revealed that SPP1 (in LUAD), POSTN, and GREM1 (in LUSC) were significantly associated with better overall survival, suggesting their dual utility as both biomarkers and prognostic indicators. Our research highlights the unique regulatory distinctions between LUAD and LUSC while offering fresh insights into the molecular pathways that COPD and NSCLC share. This study represents the initial effort to map TF-miRNA-DEG-drug networks across COPD and both the LUAD and LUSC subtypes. 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