In this Special Series issue, Journal of Clinical Oncology presents a systematic assessment of cancer genomic information and its accelerating clinical impact. In the scientific literature and lay press, the relevant discipline is often called personalized, or precision, cancer medicine. The word personalized conveys the sense that cancer genomic data may facilitate rational treatment choices that are tailored to individual patients. The term precision refers to prospects for enhanced molecular resolution, mechanistic clarity, and therapeutic cogency that may accompany clinical implementation of genomics technologies. We have chosen the term genomics-driven cancer medicine in recognition of the fact that knowledge that emanates specifically from the cancer genome will likely continue to direct the opening act of precision oncology as it plays out in clinical and translational studies over the next several years. Although precision medicine will inevitably permeate many diseases (both cancer and noncancer), oncology arguably sits at its vanguard. One obvious reason is the fact that cancer is a genomic disease: most cancers harbor a cocktail of mutated (or otherwise altered) oncogenes and tumor suppressors that work in concert to specify the molecular pathways that lead to their genesis, maintenance, and progression. Toward this end, oncology research has benefitted immensely from the proliferation of worldwide efforts to characterize the genomes of thousands of cases spanning nearly all major cancer types. As described in the opening article of this Special Series issue, the same technologic and analytic advances that have enabled a comprehensive catalogue of cancer genes are becoming increasingly malleable for advanced clinical diagnostics. Together with the expanding compendium of targeted anticancer agents in clinical development or active use, oncology has served as a proving ground for the genomics-driven framework that is unique among medical specialties. Conceptually, the implementation of genomics-driven cancer medicine might seem straightforward (Fig 1): first, characterize the genomes of patients’ tumors using state-of-the-art technologies; second, filter the genomic data through a knowledge base of existing and emerging anticancer drugs; and third, present an annotated list to the treating oncologist that can be incorporated into clinical decision making. However, multiple challenges must be addressed to bring this ambitious goal to fruition. To begin with, high-quality genomic information must be obtained consistently in the diagnostic setting— often from sparse amounts of archival tumor tissue. The article by MacConaill reviews the remarkable technologic advances that make large-scale genomic data generation feasible in a clinical setting. Although questions persist regarding the extent of genomic data needed, the cost-effectiveness of various platforms, and how rapidly clinical genomic data can be delivered, it seems clear that available technologies for genome characterization are fast becoming equipped to meet the demands of precision oncology. The analytic challenges that accompany comprehensive genomic data have proven more problematic. The somatic and germline alterations that are relevant to each cancer must be identified with high
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