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. Ultimately, even the best responses to targeted therapeutics result in dramatic, but transient responses. A small population of cells remain refractory and survive, comprising what is known as minimal residual disease (MRD). MRD provides the molecular basis and roots that drive drug resistance - one of the most urgent clinical struggles in the war against cancer. In this proposal I set out to understand the role of WT EGFR or other ERBB family members in modulating oncogenic programs, the sensitivity to targeted therapies, and MRD in mouse and organoid models of lung cancer. The work described in this project will allow me to use elegant genetic systems to separate out the distinct role and contributions for WT EGFR from other ERBB family members in the context of some of the most common molecular subtypes of lung cancer. I will also be able to define the consequences of EGFR loss on MRD using state-of-the-art single cell RNA-sequencing technologies. Ultimately, the long-term goal of these analyses is to identify and understand the molecular mechanisms that drive MRD and the deployment of rational, targeted polytherapy strategies to eradicate MRD in malignant 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.
