Systematically integrative analysis identifies diagnostic and prognostic candidates and small-molecule drugs for lung adenocarcinoma

Abstract

BackgroundLung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer (LC). However, the early-stage diagnostic rate is still low, and the 5-year overall survival (OS) rate remains poor. The present study aimed to identify critical genes as diagnostic and prognostic markers and small-molecule drugs for combating LUAD using a systematic bioinformatics analysis.MethodsFive gene expression profiling datasets were systematically integrated and analyzed. First, gene coexpression modules were identified, and differentially expressed genes (DEGs) were screened. Second, the functional changes of these DEGs were systematically investigated. Third, the protein-protein interaction network, high correlation module and key genes were identified. Fourth, prognosis and diagnostic analyses were performed. Fifth, small-molecule drugs were predicted for guiding LUAD therapy.ResultsFinally, 12-gene and 2-gene signatures were identified as diagnostic and prognostic markers. The areas under the curves (AUCs) of two signatures associated with 3-year survival were 0.686 and 0.603, respectively. The AUCs of two signatures were over 95% and 94% in diagnostic model, separately. Eleven small-molecule drugs were found and irinotecan was simultaneously predicted in three drug databases.ConclusionsThe present study identified some key dysregulated genes involved in LUAD and potential drugs by a comprehensive analysis, which provides novel insights into the pathological mechanism involved in LUAD and may shed light on the diagnosis, prognosis and treatment of LUAD patients.