Lung cancer is the most common cancer in men and women. In 2000 it caused an estimated 156,000 deaths, accounting for 28% of all cancer-related deaths. We have screened for differentially expressed genes in lung cancer using complementary DNA database mining and suppression subtractive hybridization based on the polymerase chain reaction. These genomics methods have been used to identify lung cancer genes that are tissue-specific, lung cancer–specific or both. We generated eight subtracted libraries using different subtraction combinations and sequenced 10,000 clones from each library. To confirm the differential expression of the candidate genes obtained, we used the real-time polymerase chain reaction with Taqman fluorescent probe assays. We generated gene expression profiles for some of these genes on different anatomical sites and in different disease states. We used this validation strategy to analyze 46 potential candidates. The RNA expression for 7 of these 46 genes was tested in more than 120 tissue samples. All genes showed high tissue-specific expression and overexpression in 45–67% of the lung cancer samples compared with the expression in normal adjacent tissues from the same individual. Full-length cloning, gene expression in bacteria and antibody production for these genes are under way. Once all the reagents are obtained, we will develop immunoassays to evaluate their utility as biomarkers for lung cancer. These genes, either individually or grouped in panels, could be of potential use as new tumor markers for early detection, differential diagnosis, prognosis, disease monitoring or cancer surveillance. They could also be useful as new therapeutic targets.