ArticleInternational journal of chronic obstructive pulmonary disease2026
Identification and Validation of a Two-Gene NK Cell-Related Risk Model for COPD: Integration of Single-Cell and Bulk RNA-Seq Analysis.
Article in International journal of chronic obstructive pulmonary disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Chronic obstructive pulmonary disease (COPD) involves chronic inflammation with potential involvement of natural killer (NK) cells, but NK cell-related diagnostic markers remain limited. This study aimed to identify NK cell-related hub genes and construct a risk model for COPD. Methods: This work was mainly based on multiple transcriptomic datasets, including single-cell RNA-seq data (GSE173896, 5 COPD vs 2 control) and bulk data (GSE38974 (23 COPD vs 9 control), GSE8545 (18 COPD vs 18 control), GSE11784 (22 COPD vs 72 control)). NK cell-related differentially expressed genes (DEGs) were identified. GO, KEGG, and LASSO logistic regression were applied to screen hub genes and build a risk score model. ROC analysis evaluated model performance. Immune cell infiltration was assessed via CIBERSORT. Results: A total of 135 NK cell-related DEGs were identified. After cross-analysis, two hub genes, JUNB and TNFAIP3, were selected to construct the risk model, both significantly upregulated in COPD comparing with controls (p <0.05). The risk model showed relatively good performance, achieving AUCs of 0.928 (95% CI: 0.891-0.962) in training set and 0.754 (95% CI: 0.674-0.835) in validation set. High-risk patients showed increased infiltration of monocytes and macrophages M0, and all differential immune cells exhibited significant positive/negative correlation with the risk score. Conclusion: Our two-gene NK cell-related diagnostic risk model shows good discriminatory ability for distinguishing COPD patients, providing insights into inflammatory and immune associations. The model holds promise as a potential non-invasive diagnostic tool and may inform personalized therapeutic strategies for COPD patients.
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