Abstract
Background: Chronic obstructive pulmonary disease (COPD) was a risk factor for lung cancer tumorigenesis. This study aimed to discover novel diagnostic biomark-ers for COPD patients and determine their underlying pathogenetic mechanisms. Materials and methods: Dif-ferentially expressed genes (DEGs) in COPD samples and normal controls were analyzed and utilized to construct a network associated with a high risk for COPD occur-rence. Enrichment analysis was applied on the strength of Gene Ontology (GO) annotations and Kyoto Encyclo-pedia of Genes and Genomes (KEGG) pathway analysis. The RT-qPCR analysis was performed to determine 10 hub genes in COPD. ELISA assay was utilized to meas-ure IL-1β, IL-6, and IL-10 levels. Spearman’s correlation analysis was conducted to detect the correlation between inflammatory cytokines and AHNAK expression. Cell proliferation and apoptosis were evaluated by CCK-8 and flow cytometry assays. Results: AHNAK was significantly increased in COPD serum samples compared with non-COPD smokers and strongly correlated with inflammation. AHNAK level could also discriminate COPD from non-COPD with high accuracy. Conclusion: AHNAK may be a feasible biomarker playing crucial functions in the diagnosis and progression of COPD.
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Zhang, C., & Liu, Y. (2023). Identification of AHNAK expression associated with the pathogenesis of chronic obstructive pulmonary disease by bioinformatic analysis. Acta Biochimica Polonica, 70(4), 761–766. https://doi.org/10.18388/abp.2020_6041
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