Identifying pyroptosis-related prognostic genes in the co-occurrence of lung adenocarcinoma and COPD via bioinformatics analysis.

Studies have indicated a complex association between chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma (LUAD). However, the underlying mechanisms of their coexistence are still not fully understood. Thus, this study evaluated the possible mechanisms and biomarkers of COPD and LUAD by analyzing public RNA sequencing databases via bioinformatics analysis. This study obtained the LUAD datasets (TCGA-LUAD, GSE118370, and GSE30219) and the COPD dataset (GSE11784 and GSE39874) from TCGA and GEO databases, respectively. The differentially expressed genes (DEGs) were analyzed using the DESeq2 and limma packages. These DEGs were then intersected with pyroptosis-related genes (PRGs) to produce PRDEGs, which were examined via GO analysis and KEGG enrichment analyses. Simultaneously, a prognostic model was developed using PRDEGs by the TCGA-LUAD dataset to generate diagnostic PRDEGs (DPRDEGs). The STING database was employed to develop a protein-protein interaction (PPI) network for DPRDEGs. Transcription factors-associated with DPRDEGs were also identified in the ChIPBase and hTFtarget databases. The comparative toxicogenomics database (CTD) was employed to detect possible drugs or small molecules that interacted with DPRDEGs, and results were illustrated using Cytoscape. Moreover, this study developed a prognostic model using multivariate analysis and simultaneously conducted a prognostic analysis. The results were further validated by immunohistochemistry (IHC), western blotting (WB), and qPCR of clinical specimens. A total of 273 DEGs were identified, and 12 PRDEGs were detected after intersecting with PRGs. Inflammation and infectious diseases were the primary enriched regions for these PRDEGs, as indicated by GO and KEGG enrichment analyses. The study identified six DPRDEGs (BNIP3, FTO, NEK7, POLR2H, S100A12, and TLR4) via prognosis modeling of PRDEGs. The expression of these DPRDEGs in COPD and LUAD was verified through IHC, WB, and qPCR examinations. Based on multifactorial prognosis modeling, among six, FTO, POLR2H, S100A12, and TLR4 revealed enhanced prognostic predictive effects. This study demonstrated that COPD and LUAD have common pathogenic mechanisms. The identified DPRDEGs and predictive models offer new perspectives for understanding and addressing COPD and LUAD.