RET inhibition in novel patient-derived models of RET-fusion positive lung adenocarcinoma reveals a role for MYC upregulation.

Overview

abstract

Multi-kinase RET inhibitors, such as cabozantinib and RXDX-105, are active in lung cancer patients with RET fusions; however, the overall response rates to these two drugs are unsatisfactory compared to other targeted therapy paradigms. Moreover, these inhibitors may have different efficacies against RET rearrangements depending on the upstream fusion partner. A comprehensive preclinical analysis of the efficacy of RET inhibitors is lacking due to a paucity of disease models harboring RET rearrangements. Here we generated two new patient-derived xenograft (PDX) models, one new patient-derived cell line, one PDX-derived cell line, and several isogenic cell lines with RET fusions. Using these models, we re-examined the efficacy and mechanism of action of cabozantinib and found that this RET inhibitor was effective at blocking growth of cell lines, activating caspase 3/7 and inhibiting activation of ERK and AKT. Cabozantinib treatment of mice bearing RET-fusion-positive cell line xenografts and two PDXs significantly reduced tumor proliferation without adverse toxicity. Moreover, cabozantinib was effective at reducing growth of a lung cancer PDX that was not responsive to RXDX-105. Transcriptomic analysis of lung tumors and cell lines with RET alterations showed activation of a MYC signature and this was suppressed by treatment of cell lines with cabozantinib. MYC protein levels were rapidly depleted following cabozantinib treatment. Taken together, our results demonstrate that cabozantinib is an effective agent in preclinical models harboring RET rearrangements with three different 5' fusion partners (CCDC6, KIF5B and TRIM33). Notably, we identify MYC as a protein that is upregulated by RET expression and down-regulated by cabozantinib treatment, opening up potentially new therapeutic avenues for combinatorial targeting RET-fusion driven lung cancers. The novel RET fusion-dependent preclinical models described herein represent valuable tools for further refinement of current therapies and the evaluation of novel therapeutic strategies.