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André, Fabrice; Arnedos, Monica; Baras, Alexander S.; Baselga, José; Bedard, Philippe L.; Berger, Michael F.; Bierkens, Mariska; Calvo, Fabien; Cerami, Ethan; Chakravarty, Debyani; Dang, Kristen K.; Davidson, Nancy E.; Del Vecchio Fitz, Catherine; Dogan, Semih; DuBois, Raymond N.; Ducar, Matthew D.; Futreal, P. Andrew; Gao, Jianjiong; Garcia, Francisco; Gardos, Stu; Gocke, Christopher D.; Gross, Benjamin E.; Guinney, Justin; Heins, Zachary J.; [...]

AACR Project GENIE: Powering Precision Medicine through an International Consortium

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  • Media type: E-Article
  • Title: AACR Project GENIE: Powering Precision Medicine through an International Consortium
  • Contributor: André, Fabrice; Arnedos, Monica; Baras, Alexander S.; Baselga, José; Bedard, Philippe L.; Berger, Michael F.; Bierkens, Mariska; Calvo, Fabien; Cerami, Ethan; Chakravarty, Debyani; Dang, Kristen K.; Davidson, Nancy E.; Del Vecchio Fitz, Catherine; Dogan, Semih; DuBois, Raymond N.; Ducar, Matthew D.; Futreal, P. Andrew; Gao, Jianjiong; Garcia, Francisco; Gardos, Stu; Gocke, Christopher D.; Gross, Benjamin E.; Guinney, Justin; Heins, Zachary J.; [...]
  • Published: American Association for Cancer Research (AACR), 2017
  • Published in: Cancer Discovery, 7 (2017) 8, Seite 818-831
  • Language: English
  • DOI: 10.1158/2159-8290.cd-17-0151
  • ISSN: 2159-8274; 2159-8290
  • Origination:
  • Footnote:
  • Description: Abstract 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
  • Access State: Open Access