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AACR Project GENIE:Powering PrecisionMedicine through anInternationalConsortium Fabrice AndréMónica ArnedosAlexander S. Baras2017 год

AACR Project GENIE: Powering Precision Medicine through an International Consortium
статья из журнала

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Аннотация: The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine.
Год издания: 2017
Авторы: Fabrice André, Mónica Arnedos, Alexander S. Baras, José Baselga, Philippe L. Bédard, Michael F. Berger, Mariska Bierkens, Fabien Calvo, Ethan Cerami, Debyani Chakravarty, Kristen K. Dang, Nancy E. Davidson, Catherine Del Vecchio Fitz, Semih Doğan, Raymond N. DuBois, Matthew D. Ducar, P. Andrew Futreal, Jianjiong Gao, Francisco Moacir Pinheiro Garcia, Stuart M. Gardos, Christopher D. Gocke, Benjamin Groß, Justin Guinney, Zachary Heins, Stephanie Hintzen, Hugo M. Horlings, Jan Hudeček, David M. Hyman, Suzanne Kamel‐Reid, Cyriac Kandoth, Walter Kinyua, Priti Kumari, Ritika Kundra, Marc Ladanyi, Céline Lefèbvre, Michele L. Lenoue-Newton, Eva M. Lepisto, Mia Levy, Neal I. Lindeman, James Lindsay, David Liu, Zhibin Lu, Laura E. MacConaill, Ian Maurer, David S. Maxwell, Gerrit A. Meijer, Funda Meric‐Bernstam, Christine Micheel, Clinton Miller, Gordon B. Mills, Nathanael D. Moore, Petra M. Nederlof, Larsson Omberg, John A. Orechia, Ben Ho Park, Trevor J. Pugh, Brendan Reardon, Barrett J. Rollins, Mark J. Routbort, Charles L. Sawyers, Deborah Schrag, Nikolaus Schultz, Kenna Shaw, Priyanka Shivdasani, Lillian L. Siu, David B. Solit, Gabe S. Sonke, Jean Charles Soria, Parin Sripakdeevong, Natalie Stickle, Thomas Stricker, Shawn M. Sweeney, Barry S. Taylor, Jelle J. ten Hoeve, Stacy B. Thomas, Eliezer M. Van Allen, Laura van ’t Veer, Tony van de Velde, Harm van Tinteren, Victor E. Velculescu, Carl Virtanen, Emile E. Voest, Lucy Lu Wang, Chetna Wathoo, Stuart Watt, Celeste Yu, Thomas Yu, Emily Yu, Ahmet Zehir, Hongxin Zhang
Издательство: American Association for Cancer Research
Источник: Cancer Discovery
Ключевые слова: Cancer Genomics and Diagnostics, Radiomics and Machine Learning in Medical Imaging, Ferroptosis and cancer prognosis
Другие ссылки: Cancer Discovery (HTML)
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