Lung cancer is the global leader in cancer related deaths, and responsible for an estimated 1.4 million deaths worldwide and ~160,000 deaths in the United States annually. Treatment outcomes have improved in recent years with our recent understanding that patients can be divided into subsets based on the presence of specific genetic mutations that occur in their tumors. These oncogenic mutations can serve as predictive biomarkers that these tumors can be targeted with certain specific therapeutics. This approach has improved therapeutic options for patient with certain oncogenic mutations, but not the majority of patients. One of the most common signaling pathways deregulated in lung cancer is the mitogen activated protein kinase pathway (MAPK). Common oncogenic mutations in this pathway include RAS and BRAF, but patients that harbor these mutations have no targeted therapies currently approved for their condition. Interestingly, both of these common driver mutations on their own result in benign adenomas, and require additional genetic alterations to drive fully malignant and lethal lung cancer. In this proposal, we set out to study genes that promote lung cancer progression for MAPK-driven lung cancers. This proposal utilizes the innovative sleeping beauty transposon system to identify genes that accelerate lung cancer progression in genetic mouse models of lung cancer.
In aims 1 and 2 these genes will be validated in mouse models of BRAF and KRAS oncogenic alterations, as well as human lung cancer patient-derived xenograft mouse models in aim 3. Genes that are validated to promote lung cancer progression will be further tested for molecular mechanisms of cooperation with BRAF and KRAS oncogenes. This analysis may result in information that will help with therapeutic development for malignant lung cancers that are positive for MAPK-driven lung cancers.
Lung cancer is the global leader in cancer related deaths, and responsible for an estimated 1.4 million deaths worldwide and ~160,000 deaths in the United States annually. Treatment outcomes have improved in recent years with our recent understanding that patients can be divided into subsets based on the presence of specific genetic mutations occurring in their tumors that can be targeted with certain specific therapeutics. This application proposes the analysis of mechanisms that drive lethal lung cancer progression, using genetic mouse experimental models of lung cancer.
