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

Abstract

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 LUAD tumorigenesis. 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. We identified the overlapping differentially expressed genes (DEGs) in five independent microarray data sets 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-DEGs. Protein-protein interaction network analysis indicated that caveolin 1 (CAV1) and decorin (DCN) levels were significantly reduced and that these genes were the most promising predictive biomarkers for the occurrence and prognosis of LUAD. A cell proliferation assay indicated that overexpressed CAV1 and DCN could significantly inhibit the proliferation rate of A549 and H157 cells. Additionally, these two downregulated candidate genes were further verified by immunohistochemistry conducted on a LUAD tissue array and comprehensive bioinformatics analyses, including those using the Oncomine platform and the Cancer Cell Line Encyclopedia. Our study demonstrates low levels of CAV1 and DCN in LUAD. An understanding of their functional roles in LUAD biology would give us important insights that would be useful in further investigations.