Drug-induced gene expression patterns that invert disease profiles have recently been illustrated to be a new strategy for drug-repositioning. In the present study, we validated this approach and focused on prediction of novel drugs for lung adenocarcinoma (AC), for which there is a pressing need to find novel therapeutic compounds. Firstly, connectivity map (CMap) analysis computationally predicted bezafibrate as a putative compound against lung AC. Then this hypothesis was verified by in vitro assays of anti-proliferation and cell cycle arrest. In silico docking evidence indicated that bezafibrate could target cyclin dependent kinase 2(CDK2), which regulates progression through the cell cycle. Furthermore, we found that bezafibrate can significantly down-regulate the expression of CDK2 mRNA and p-CDK2. Using a nude mice xenograft model, we also found that bezafibrate could inhibit tumor growth of lung AC in vivo. In conclusion, this study proposed bezafibrate as a potential therapeutic option for lung AC patients, illustrating the potential of in silico drug screening.