Project 2: The single agent efficacy of selective mutant BRAF inhibitors in patients with advanced melanoma is uniformly short-lived, illustrating that therapeutic resistance is a paramount question in the field. Recognizing that micro-environmental context influences the biological behavior of a tumor, including response to therapy, a systematic and comprehensive effort to identify mechanisms of resistance. Thus, Project 2 brings to this P01 the uses of refined germline and non-germline genetically engineered models of BRAF-driven melanomas for discovery and validation of novel resistant genes as well as for preclinical therapeutic testing of combinations that can overcome resistance to selective BRAF inhibitor (BRAFi) in melanoma. The following 3 aims will be pursued:
Aim 1 : Identify genetic events conferring resistance to BRAFi in vivo. Here, using our refined BRAF^(R)??^-driven genetically engineered mouse model (GEMM) ("iBIP"), we will generate a longitudinal cohort of sensitive and resistant melanomas upon long-term administration of BRAFi. These tumors will be subjected to deep genomic characterization to identify candidate lesions mediating resistance. Candidates will be prioritized and validated for/n wVo functional genetic screening based on statistical significance as well as evolutionary conservation through compahson with human genomic data from Project 1.
Aim 2 : Identify co-extinction targets for combination therapeutics against BRAF* melanoma. Complementing Aim 1, this aim will take a global and unbiased approach to the discovery of co-extinction targets. We will define the BRAF* regulated network in melanoma maintenance through kinetic transcriptome profiling of regressing melanomas upon genetic inactivation of mutant BF^F* in IBIP mice.
Aim 3 : Develop rational combination strategies for overcoming resistance to BRAFi in vivo. The goal of this aim is to generate sufficient preclinical efficacy data to motivate a novel Phase 18/11 clinical trial on a combination regimen that inhibits a co-extinction target along with BRAFi. Here, we will use mouse models to systematically screen potential combinations for efficacy;the best combination will then be tested in preclinical therapeutic trials in the IBIP GEMM.
Resistance to selective BRAF inhibitors in melanoma is a paramount challenge in the clinics today. Thus, elucidating the mechanisms modulating response and conferring resistance is timely and relevant. Bringing to bear on this challenge cutting-edged genomics and computational science as well as refined genetically engineered mouse models enable a discovery effort that is unbiased and comprehensive.
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