The goal of personalized cancer medicine is to effectively match the right treatment strategy with the patient. This includes an improvement of prognosis to identify which patients should be treated as well as the ability to predict which therapy will be most effective for the individual patient. Recent advances in the use of genomic technologies, primarily gene expression profiling with DNA microarrays, has provided mechanisms to address each of these questions. The prognosis of early-stage lung cancer patients (stage IA) is clearly imprecise because nearly 30% of these patients will develop disease recurrence (determined according to the TNM staging system). Gene expression profiles have been developed that can accurately predict recurrence and, when applied to the population of patients with stage IA disease, demonstrate a capacity to potentially identify those individuals likely to have been misclassified as low risk. In addition, gene expression information has also demonstrated an ability to predict who will respond to a particular chemotherapy regimen, providing a further opportunity to more effectively guide the selection of available therapies that best match the individual patient. Finally, other strategies offer the hope of better using the newly developed, experimental therapies that target specific components of the oncogenic process. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual lung cancer patient.