Data from AACR Project GENIE: Powering Precision Medicine through an International Consortium Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.1158/2159-8290.c.6546577.v1
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.Significance: The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy. Cancer Discov; 7(8); 818–31. ©2017 AACR.See related commentary by Litchfield et al., p. 796.This article is highlighted in the In This Issue feature, p. 783
Related Topics
- Type
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- Language
- en
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- http://doi.org/10.1158/2159-8290.c.6546577.v1
- OA Status
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- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4392703241Canonical identifier for this work in OpenAlex
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https://doi.org/10.1158/2159-8290.c.6546577.v1Digital Object Identifier
- Title
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Data from AACR Project GENIE: Powering Precision Medicine through an International ConsortiumWork title
- Type
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preprintOpenAlex work type
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-04-03Full publication date if available
- Authors
-
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, F. García, 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 O. 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 ZhangList of authors in order
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https://doi.org/10.1158/2159-8290.c.6546577.v1Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1158/2159-8290.c.6546577.v1Direct OA link when available
- Concepts
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Precision medicine, Computer science, Medicine, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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