Genetic Determinants of Tumor Growth and Drug Sensitivity in EGFR Mutant Lung Cancer

PROJECT SUMMARY The discovery of mutations in EGFR that drive lung cancer growth and confer sensitivity to tyrosine kinase inhibitors (TKIs) has transformed the treatment of lung cancer. However, responses to TKIs are variable and resistance ultimately develops. Thus, EGFR-driven lung cancers still cause ~20,000 deaths annually in the US. These tumors have frequent alterations in diverse tumor suppressor genes (TSGs), however which of these alterations co-operate to drive tumor growth, how they impact cancer cell state, and whether they are key determinants of responses to therapy remains largely unknown. Current methods to uncover relationships between EGFR and TSGs largely rely on correlative human genomic studies and cell line-based models. However, genomic studies are often statistically underpowered to uncover genetic interactions and do not provide information on TSG function. Conversely, cell line studies do not recapitulate the in vivo environment and the limited cell lines that exist represent only a subset of EGFR mutant tumors. To overcome these limitations and better understand the genomic drivers of lung cancer growth and drug responses in vivo, we recently integrated a novel autochthonous mouse model of oncogenic EGFR-driven lung cancer with CRISPR/Cas9- mediated somatic genome editing and high-throughput tumor barcode sequencing. Using this multiplexed in vivo model, we uncovered the splicing factor RBM10 as a poorly characterized suppressor of tumor growth and unexpectedly found that inactivation of the “tumor suppressor” Lkb1 is synthetic lethal with oncogenic EGFR. Here, we will investigate how genotype controls the biology of oncogenic EGFR-driven lung cancer. Specifically, we will establish the cellular and molecular consequences of Rbm10 inactivation and elucidate the mechanism that underlies the synthetic lethality between EGFR and Lkb1. Moreover, understanding how tumor genotype influences treatment responses could reveal genotype-specific therapeutic vulnerabilities. Thus, we will leverage our multiplexed in vivo gene editing platform to determine the impact of additional TSGs on EGFR mutant lung cancer growth and uncover genomic drivers of responses to therapy. This work will increase our fundamental understanding of the genomic determinants of EGFR mutant lung cancer growth and reveal novel and therapeutically targetable pro-tumorigenic pathways. These findings could ultimately inform precision treatments for patients with oncogenic EGFR-driven lung cancer.