Novel structure-based and combinatorial approaches for RET-fusion NSCLC

RET fusions occur in 2-3% cases of lung cancer and there are currently two FDA-approved RET-specific inhibitors, selpercatinib and pralsetinib, for the treatment of patients with RET fusion positive lung or thyroid cancers. Therapeutic resistance eventually emerges, however, and studies have shown that RET-dependent mechanisms of resistance include acquired resistance mutations that alter drug binding. Further, RET fusions and mutations are heterogeneous and the impact of specific fusion partners and RET variants on drug sensitivity is poorly understood. In a recent publication in Nature, our group reported that for a related driver oncogene, EGFR, both primary and acquired resistance mutations can be classified into distinct structural groups that correlate with drug sensitivity and resistance. This structure-function based classification has important advantages 1) structure-based groups predicted drug response significantly better than standard exon-based approaches, 2) this classification enabled us to match drugs for more than ~99% of atypical mutations where currently less than 50% of mutations have an FDA approved drug. In addition, preliminary preclinical and clinical data suggests that two RET-independent mechanisms of resistance- signal bypass and lineage shift-may also drive resistance even in the presence of effective RET inhibition. Applying methodologies we established for elucidating EGFR inhibitor resistance, we will develop a structure-function based classification which can immediately impact clinical decisions for selecting therapies; comprehensively characterize RET-dependent and -independent mechanisms of resistance and biomarkers to assess them; and develop rational therapeutic strategies to overcome resistance which can guide patient selection for future clinical studies.