CHAIRPERSONS:
Lynda Chin, Harvard Medical School, Dana-Farber Cancer Institute, Boston, MA
Joe W. Gray, Lawrence Berkeley National Laboratory, Berkeley, CA
William R. Sellers, Novartis Institutes for BioMedical Research, Cambridge, MA
Richard L. Schilsky, University of Chicago Medical Center, Chicago, IL
In the era of the cancer genome projects, vast and complex epi/genomic and proteomic information annotated with clinical parameters will be generated. How does the cancer research field rapidly convert these data into meaningful functional/mechanistic insights that can advance our understanding of cancer pathogenesis and enable development of new diagnostic and therapeutic agents? Are significant statistical correlations sufficient to harness the full clinical potential of these complex data sets in a manner that will change the practice of cancer medicine? Who will be the “users” of these data? It is envisioned that translation of these data will require multi-disciplinary integrated systems biology approaches not typical of traditional basic and translational research. This meeting is intended to bring together these “users”, representing computational biologists, cancer biologists and clinicians who together hold the potential to convert these vast multidimensional genomic datasets into basic and translational hypotheses that can be tested and validated, and ultimately used to guide discovery of more effective diagnostic, drugs and associated biomarkers. Emphasis will be on “functionalizing” the genomic insights; developing in vitro and in vivo high-content biological systems that offer a more productive and better defined path to identify and distinguish key pathogenetic events from noise; assessing the diagnostic, prognostic or predictive significance of genomic changes; and designing effective experiments to retrospectively and prospectively validate genomic-based molecular biomarkers and therapeutic targets.
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