PQD1: Clonal heterogeneity and targeted therapy resistance in melanoma. Molecular instability of cancer cells generates diversity that, in turn, enables tumor evolution. A strong selective pressure from targeted therapies can provide dramatic clinical responses but also drive such evolution to yield rapid drug resistant tumor growth. To effectively address this key challenge of modern day oncology, it is imperative to better understand the basic mechanisms underlying evolution of resistance in patients in vivo. We hypothesize that development of clinical resistance to targeted therapy in advanced cancers is a function of marked tumor heterogeneity and clonal selection rather than cellular adaptation to therapeutic pressure. Our proposal will test this hypothesis using targeted inhibition of oncogenic BRAF in melanoma as a model system. To achieve this we will employ a highly innovative approach that combines flow cytometry-based sorting of tumor nuclei directly from solid tumor archived paraffin-embedded clinical samples with next generation sequencing, providing a unique opportunity to exploit the extensive Mayo Clinic resources of archived clinically annotated melanoma tissues. Genomic sequence data obtained in these experiments from distinct clonal tumor populations sorted from a series of patient matched sensitive and resistant tissues will be used to define clonal tumor lineages and respective molecular events associated with resistance. We will also leverage the novel and robust informatics resources of our Stand Up To Cancer (SU2C) Melanoma Dream Team effort for clinically relevant interpretation of genomic data in this proposal. Finally, we will explore approaches to modulate development of resistance arising in patients in vivo in a unique, highly clinically relevant anima model system. Using tumorgrafts derived from patient's matched pre-treatment (sensitive) and relapsed (resistant) tissues, we will test the effects of altering drug dose and timing and explore rational combination treatments based on genomic data from paired tissues. The key issue addressed in this proposal holds relevance not only to melanoma but solid tumors in general. The outcomes of our proposed research have potential to significantly impact our understanding of drug resistance and the development of clinically relevant approaches to overcome it, which is of particular relevance as numerous targeted agents are reaching the clinic.