Identification of ERN1 as a Potential Context-Dependent Biomarker in Chronic Obstructive Pulmonary Disease Based on Bioinformatics Analysis of GSE57148 Dataset.

Purpose: To identify an endoplasmic-reticulum-stress-related candidate gene in chronic obstructive pulmonary disease (COPD) lung tissue and assess its internal discriminative performance and cross-cohort reproducibility. Patients and Methods: This bioinformatics study used the GSE57148 lung tissue dataset (98 COPD and 91 subjects with normal-spirometry; all male smokers undergoing lung resection). Differential expression was analyzed using limma on log2 (fragments per kilobase of transcript per million mapped reads [FPKM] + 1), followed by enrichment and protein-protein interaction analyses. Endoplasmic reticulum to nucleus signaling 1 (ERN1) was prioritized using a literature-informed post hoc multi-criteria framework. Internal discrimination was evaluated by receiver operating characteristic (ROC) analysis with repeated stratified 10-fold cross-validation and bootstrap optimism correction. External sensitivity analyses were performed in independent cohorts. Results: A total of 308 differentially expressed genes were identified. ERN1 was significantly upregulated in COPD (log2FC = 0.75, adjusted P = 1.98 x 10^-15). In the discovery cohort, ERN1 showed internal discrimination (area under the ROC curve [AUC] = 0.853; cross-validated AUC = 0.848). However, external replication was heterogeneous; in the largest mixed-sex cohort (GSE47460), discrimination was limited (AUC = 0.477), and adjusted external models remained non-significant. Conclusion: ERN1 is upregulated in COPD lung tissue in GSE57148 and represents an endoplasmic-reticulum-stress-related, context-dependent candidate signal. Current evidence is preliminary and requires prospective validation in independent, sex-balanced cohorts and clinically accessible biospecimens.