This application addresses broad Challenge Area (08) Genomics and specific Challenge Topic, 08-CA-106: Development of methods for the validation of gene discoveries as they relate to cancer. Specific targeting of oncogenic signaling pathways with kinase inhibitors has vastly improved clinical outcomes for patients with a variety of cancer diagnoses, most notably patients with chronic myeloid leukemia. To expand this targeted-therapy approach to all forms of cancer, disease-causing genes must first be identified. Towards that end, we and others have applied a variety of techniques to detect oncogenic aberrations at the genomic level, including gene resequencing or gene expression profiling in cancer cells. We have also developed an RNAi-based screen to rapidly identify target genes in primary cancer cells obtained directly from leukemia patients. However, application of these analyses in piecemeal fashion has resulted in large numbers of unvalidated targets. Distinguishing between false-positives that have no disease-relevance and bona fide oncogenes that exhibit complex and elusive mechanisms of oncogenesis has been difficult. Integration of our RNAi-based functional screen with recently available techniques of Next Generation sequencing and exonbased expression arrays represents a perfect complement of technologies-knowledge of siRNA-sensitive genes will guide sequencing and array analysis, while high-throughput sequence and gene expression profiles will expedite the process of functional target validation. We propose that integration of techniques-functional profiling, Next Generation sequencing, and gene expression arrays-will significantly accelerate the pace of target identification and validation.
An effective paradigm for accelerating development of clinical cancer therapeutics must entail an integrated approach in which functional assay-based target identification is supported with genomic and gene expression-based validation techniques. By integrating functional siRNA profiling of leukemia patient samples with Next Generation sequencing and gene expression arrays, we hypothesize that we will significantly accelerate the pace of target identification and validation.
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| Tyner, Jeffrey W; Fletcher, Luke B; Wang, Ellen Q et al. (2010) MET receptor sequence variants R970C and T992I lack transforming capacity. Cancer Res 70:6233-7 |
