Lung cancer is a devastating disease that presents a challenge to basic research to provide new steps toward therapeutic advances. The cell-type-specific responses to oncogenic mutations that initiate and regulate lung cancer remain poorly defined. A better understanding of the relevant signaling pathways and mechanisms that control therapeutic outcome could also provide new insight. Improved conditional mouse models are now available as tools to improve the understanding of the cellular and molecular origins of adenocarcinoma. These models have already proven their utility in proof-of-principle experiments with new technologies including genomics and imaging. Integrated thinking to apply technological advances while using the appropriate mouse model is likely to facilitate discoveries that will significantly improve lung cancer detection and intervention.