ArticleJournal of inflammation research2025
Development of Diagnostic and Predictive Models for COPD Based on Anoikis Resistance.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Smoker's Lungs: Quo Vadis? Exploring the Shared and Individual Smoking-Related Molecular Pathways of Emphysema, Carcinoma, and Fibrosis - An Illustrative Review.Thoracic cancer · 2026Review
- Proteomics-Based Study of Potential Emphysema Biomarkers Reveals Systemic Redox System and Extracellular Matrix Component Dysregulation.Diagnostics (Basel, Switzerland) · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic obstructive pulmonary disease (COPD) pathogenesis involves persistent airway inflammation and remodeling, yet the role of anoikis resistance remains poorly characterized. This study aimed to identify anoikis resistance-related hub genes and evaluate their clinical utility in COPD phenotyping and prognosis. Methods: Integrated bioinformatics analysis of the GSE11906 dataset identified anoikis resistance-related differentially expressed genes (DEGs). Functional enrichment, LASSO regression, and machine learning (RF, SVM, XGB, GLM) were employed to pinpoint core hub genes. Multi-level validation included external datasets (GSE19407), in vitro (CSE-stimulated 16HBE cells), in vivo (cigarette smoke-exposed mice), and clinical samples (PBMCs). Diagnostic and prognostic models were developed using logistic regression. Results: Five core hub genes (UCHL1, ME1, SLC2A1, BMP4, CRABP2) were identified, with ME1, SLC2A1, and BMP4 consistently upregulated in COPD across models and strongly correlated with emphysema index (negative, R = -0.41 to -0.45) and airway wall thickness (positive, R = 0.40-0.45). These genes exhibited significant associations with peribronchial immune cell infiltration. Diagnostic models for emphysema-predominant COPD (AUC = 0.860) and disease staging (AUC = 0.882), along with a prognostic model for hospitalization duration (AUC = 0.867), demonstrated robust clinical performance. Conclusion: ME1, SLC2A1, and BMP4 are pivotal anoikis resistance-related biomarkers in COPD, driving immune dysregulation and structural remodeling. The developed models enable precise phenotyping, severity stratification, and personalized prognosis prediction, advancing precision medicine strategies for COPD management.
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Registered trials
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