Melanoma brain metastasis (B-Met) carries a dismal prognosis, with a median survival of less than 6 months. Unfortunately, approximately 75% of patients with metastatic melanoma develop B-Mets during the course of their disease. There is no effective treatment and thus far there is no molecular marker(s) that can predict which primary tumors are most likely to progress to B-Met. Our preliminary data strongly support that melanoma B-Mets are not merely the terminal stage of a generally aggressive phenotype and that a B-Met-specific miRNA signature can be detected at the time the primary melanoma. We hypothesize that some of these miRNAs play a critical role in governing the molecular mechanisms responsible for the propagation and establishment of melanoma B-Met, including chemotaxis, adhesion, migration, and proliferation. First, B- Met associated miRNAs will be tested in vivo for their ability to modulate B-Met potential of melanoma cell lines. For the positie hits in the screen we will investigate the biological process and mechanism(s) by which they might contribute to melanoma B-Met. The results from our study will greatly advance the understanding of how miRNA modulate the metastatic process in general and why melanoma cells have a particular penchant for penetrating the blood brain barrier and proliferating in the neural microenvironment. Moreover, the identification of miRNAs and miRNA targets that actively participate in melanoma B-Met has the potential to reveal new avenues for treatment in patients for whom no viable approaches are currently available. In this study we will also evaluate the predictive capacity of the B-Met miRNA signature at the time of diagnosis in a prospective patient cohort. As novel, effective therapies with ability to penetrate the blood brain barrier are becoming available and being tested in the adjuvant setting (i.e. vemurafenib), having a signature with ability to predict B-met may become particularly useful for patient selection. Success from our application would satisfy NCI's goals in that 'improved prediction of clinical risk could help clinicians in communicating risk/benefit profiles for treatment options. (..) Insight into the biological basis for this stratification would be an important advance, with likel relevance to analogous lesions of several tissues'.