Defining the Role of ERG in Modulating the AR Cistrome and Antiandrogen Sensitivity

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 DESCRIPTION (provided by applicant): Overexpression of ETS family transcription factors (ERG, ETV1, ETV4, ETV5, FLI1) through genomic fusion is the most common molecular aberration in prostate cancer, occurring in half of all cases. The TMPRSS2-ERG fusion that places ERG under the androgen-regulated TMRPSS2 gene is the predominant fusion, found in 80- 90% of all ETS-positive cancers. The molecular mechanisms underlying ETS-mediated oncogenesis in prostate cancer remain elusive. In genetically engineered mouse models (GEMM), ERG expression alone is not sufficient to drive prostate tumorigenesis. However, it causes dramatic reprogramming of the androgen receptor genomic binding profile (AR cistrome). In conjunction with Pten loss, ERG promotes tumorigenesis as well as significant transcriptome changes and confers resistance to combined PI3K/AR pathway inhibition, a therapy that is highly effective in prostate tumors initiated by Pten loss alone. These findings underscore the important biology that underlies interactions between AR, ERG and PTEN not only in mouse and human prostate cancer models, but also in human prostate cancer clinical specimens where aberrations in these pathways are also highly linked. This R01 project will examine the molecular details underlying these interactions by: (i) determining the mechanisms by which ERG reprograms the AR cistrome, creating a state where the prostate is primed to respond to upstream signals (e.g., Pten loss), (ii) elucidating the signaling events downstream of Pten loss that activate ERG-mediated transcription modules in mouse and human prostate tissue and (iii) determining the impact of ERG on response to AR pathway inhibition. To achieve these Aims, we will make extensive use of new mouse and human prostate organoid technology, generated by our group that enables precise mechanistic analysis of defined populations of luminal and basal prostate epithelial cells in ways not previously possible. We will leverage innovation approached in computational systems biology (Andrea Califano, Columbia) to predict candidate signaling pathways and transcription factors modulated by Pten loss that cooperate with ERG.