Lung cancer is one of the most common malignancies and the leading cause of cancer-related deaths worldwide. Although many oncogenes and tumor suppressors have been uncovered in the past decades, the pathogenesis and mechanisms of lung tumorigenesis and progression are unclear. The advancement of high-throughput sequencing technique and bioinformatics methods has led to the discovery of some unknown important protein-coding genes or noncoding RNAs in human cancers. In this study, we tried to identify and validate lung cancer driver genes to facilitate the diagnosis and individualized treatment of patients with this disease. To analyze distinct gene profile in lung cancer, the RNA sequencing data from TCGA and microarray data from Gene Expression Omnibus were used. Then, shRNA-pooled screen data and CRISPR-Cas9-based screen data in lung cancer cells were used to validate the functional roles of identified genes. We found that thousands of gene expression patterns are altered in lung cancer, and genomic alterations contribute to the dysregulation of these genes. Furthermore, we identified some potential lung cancer driver genes, such as TBX2, MCM4, SLC2A1, BIRC5, and CDC20, whose expression is significantly upregulated in lung cancer, and the copy number of these genes is amplified in the genome of patients with lung cancer. More importantly, overexpression of these genes is associated with poorer survival of patients with lung cancer, and knockdown or knockout of these genes results in decreased cell proliferation in lung cancer cells. Taken together, the genomewide comprehensive analysis combined with screen data analyses may provide a valuable help for identifying cancer driver genes for diagnosis and prevention of patients with lung cancer.