Abstract: Many lineage-specific transcription factors have well-defined oncogenic roles in the pathogenesis of distinct cancer types. However, with the exception of ligand binding nuclear transcription factors (i.e. AR, ER, RAR?), the majority of them are considered """"""""""""""""undruggable"""""""""""""""" because they lack the conventional """"""""""""""""druggable"""""""""""""""" pockets and model compounds for rational drug design. More importantly, transcription factors regulate large repertoire of transcriptional targets through poorly understood complex mechanisms often in a cell/tissue lineage-dependent manner, making it difficult to design sensitive and specific readouts amenable for high throughput screening. We propose to use an innovative approach that combines a high- throughput RNAi-based screening with high-complexity gene-signature based readouts to systematically discover """"""""""""""""druggable"""""""""""""""" targets that can specifically interfere with oncogenic ETS- family transcriptional program in distinct ETS-dependent cancer types, i.e., GIST and subsets of prostate cancer and melanoma. The ETS-dependent gene-signature is derived from integrative analyses of ETS-dependent transcriptomes, ETS genome-wide localization studies and the epigenetic landscapes in each distinct ETS-dependent cancer type. This approach, if proven successful, will undoubtedly generate novel therapeutic targets specific for oncogenic ETS- transcription factors and ETS-dependent-gene-signatures as biomarkers that can be directly translated into human clinical studies. Moreover, this integrative approach can be generalized to target other families of lineage-specific oncogenic transcription factors in their relevant malignancies. Public Health Relevance: Oncogenic transcription factors have well-established roles in driving oncogenesis especially in the relevant cancer types of specific tissue/cell lineages, and they represent the ideal therapeutic targets in the these malignancies. However, therapeutic development to specifically target oncogenic transcription factors has been hindered by their structural properties and lack of sensitive and specific high-complexity transcriptional readout amenable for high throughput screening. This proposal describes a novel integrative approach that combines a high throughput RNAi-based screen with high complexity gene-signature based readout to systematically discover druggable modifiers of oncogenic transcription factors.
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