There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
A confluence of biological, physical, engineering, computer, and health sciences is
setting the stage for a transformative leap toward data-driven, mechanism-based health
and health care for each individual.
Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, it is likely that successful interpretation of cancer genomes will require comprehensive knowledge of the molecular networks under selective pressure in oncogenesis. Here we announce the creation of a new effort, The Cancer Cell Map Initiative (CCMI), aimed at systematically detailing these complex interactions among cancer genes and how they differ between diseased and healthy states. We discuss recent progress that enables creation of these cancer cell maps across a range of tumor types and how they can be used to target networks disrupted in individual patients, significantly accelerating the development of precision medicine.
[1
]
School of Medicine, University of California, San Francisco, San Francisco, CA 94143,
USA.
[2
]
School of Medicine, University of California, San Francisco, San Francisco, CA 94143,
USA. Department of Cellular and Molecular Pharmacology, University of California,
San Francisco, San Francisco, CA 94158, USA. yamamoto@ucsf.edu.