Identification of CAV1 and DCN as potential predictive biomarkers for lung adenocarcinoma

Background Lung adenocarcinoma (LUAD) is the most common histological form of lung cancer that is clinically diagnosed. The aim of this study is to explore the novel genes associated with the LUAD tumorigenesis. Methods Comprehensive bioinformatics analyses of the data were obtained from several publicly available databases, such as the Gene Expression Omnibus, the Human Protein Atlas project and the Cancer Cell Line Encyclopedia. The clinical relevance of these novel genes in LUAD was further examined by immunohistochemistry. Results We identified the overlapping differentially expressed genes (DEGs) in five independent microarray datasets from the Gene Expression Omnibus database (GSE75037, GSE85716, GSE85841, GSE63459 and GSE32867). Using the criteria of |log(fold change)| ≥ 1 and p value < 0.05, 167 genes were preliminarily validated as co-differentially expressed genes (co-DEGs). Protein-protein interaction network analysis indicated that CAV1 and DCN levels were significantly reduced and that these ...