The emergence of multidimensional datasets characterizing genetic, epigenetic, and functional properties of large normal and tumor-related samples is creating unique opportunities for the systems-level dissection of mechanisms associated with malignant phenotypes. Coupled with novel high-throughput technologies and computational methodologies for the dissection, interrogation, and perturbation of genome-wide regulatory pathways, this will lead to highly efficient approaches for the rapid identification and validation of therapeutic targets, their small molecule inhibitors, and associated biomarkers. Columbia University investigators have pioneered systems-biology-based approaches for the dissection of regulatory networks in human malignancies and for their interrogation, using computational, RNAi, and small-molecule approaches, to identify molecular targets for therapeutic intervention. The goal of this project is the use and build upon a successful pipeline between the investigators labs for the discovery and validation of master regulator modules that implement functional bottlenecks that integrate aberrant signals from multiple genetic and epigenetic alterations, and thus, constitute natural dependencies (i.e., Achille's heel) for the tumor subtype. These will be characterized in terms of their synergistic behavior, driver genetic alterations, and druggable modulators. This pipeline will allow processing of a novel tumor phenotype every 18 to 24 months, yielding validated individual and synergistic targets that constitute either oncogene or non-oncogene dependencies of the tumor or that increase sensitivity to existing FDA approved or late-stage development compounds. Relevance: The identification of targets that abrogate tumorigenesis in the patient, are extensively biochemically characterized, chemically tractable, and highly penetrant constitutes one of the greatest challenges of cancer research. The goal of this proposal is to leverage an integrative computational and experimental pipeline for the systematic identification of novel potential targets that may inspire future development of therapeutic applications.
The identification of targets that abrogate tumorigenesis in the patient, are extensively biochemically characterized, chemically tractable, and highly penetrant constitutes one of the greatest challenges of cancer research. By interrogating multidimensional datasets characterizing genetic, epigenetic, and functional properties of large normal and tumor-related samples, it is the aim of this proposal to leverage an integrative computational and experimental pipeline for the systematic identification of novel targets that may inspire future development of therapeutic applications.
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