This application proposes a systematic effort to collect and analyze multi-factorial """"""""Pharmaco-Response Signatures"""""""" (PRSs) for 15 therapeutic small molecules across a bank of 80 cancer cells lines for which genomic data is becoming available. The signatures will be used to elucidate response mechanisms, identify specific determinants of drug sensitivity or resistance at the cellular level, and create new response classifiers. PRSs will be based on high dimensionality measurements of phenotypes in single cells collected using high content microscopy supplemented by biochemical and plate-based assays, all performed at multiple times following exposure to drug at multiple doses (for a total of ca. 5 x105 unique measurements). The data will be analyzed using a variety of mathematical modeling methods that incorporate more or less prior knowledge and will, in all cases, be combined with gene sequence and transcriptional data on pre-treatment state. Regions of the drug/cell line/dose response landscape that are particularly rich will be subjected to in-depth biochemical analysis aimed at creation of detailed mechanistic models of response pathways. By providing a more effective means to prioritize lead compounds, PRSs should help to overcome substantial obstacles to the development of therapeutic small molecules. Looking forward, such signatures should also be useful in monitoring patients during the course of therapy. For example, applying PRSs to measurements made on circulating tumor cells would fundamentally advance the personalization of cancer therapy. The assembly and analysis of sophisticated new signatures of drug response will involve close collaboration between seven investigators with expertise in medicinal chemistry, systems biology, genomics and high content screening and could not be undertaken in the absence of RC2 funding. Pharmaco-response signatures are expected to find a wide audience in industry and academe and to meet a critical knowledge gap;their creation will require new informatics approaches, reduction to practice of diverse measurement technologies and application of innovative mathematical modeling- the essence of a """"""""grand opportunity.""""""""
Project Narrative The proposed development of pharmaco-response signatures is directly relevant to NIH goals of developing better anti-cancer drugs and identifying those patients most likely to benefit from specific therapies;it also meets the GO (RFA-OD-09-004) requirement that a unique information resource be developed through collaborative attack on a fundamental problem in translational drug development. The work can be initiated immediately and substantially completed within two years.
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