Person:

Liao, R

Cancer is a set of complex genetic diseases driven by diverse genomic alterations. The genomic study of cancer has enabled the discovery of novel, targetable events in almost all cancer types and in turn, has led to the development of new, targeted cancer therapies benefiting patients; however, the recent explosion of genomic datasets has also resulted in huge lists of new oncogenic factors of unknown biological relevance, and uncertainty over how best to use the data appropriately to influence patient care. Some of the most pressing questions surround the use of statistical methods to identify actionable genomic alterations in cancer and the identification of driving oncogenes in the context of the genomic evolution of cancer cells, undergone before, during, and after prolonged treatment regimens.

Somatic mutations in Fibroblast Growth Factor Receptor 2 (FGFR2) are present in 4-5% of patients diagnosed with non-small cell lung cancer (NSCLC). Amplification and mutations in FGFR genes have been identified in patients with NSCLC and clinical trials are testing the efficacy of anti-FGFR therapies. FGFR2 and other FGFR kinase family gene alterations have been found in both lung squamous cell carcinoma and lung adenocarcinoma though mouse models of FGFR driven lung cancers have not been reported. Here, we generated a genetically engineered mouse model (GEMM) of NSCLC driven by a kinase domain mutation in FGFR2. Combined with p53 ablation, primary grade III/IV adenocarcinoma was induced in the lung epithelial compartment exhibiting locally invasive and pleiotropic tendencies largely made up of multinucleated cells. Tumors were acutely sensitive to pan-FGFR inhibition. This is the first FGFR2-driven lung cancer GEMM, which can be applied across different cancer indications in a preclinical setting.