AACR Project GENIE: Powering Precision Medicine through an International Consortium.

AACR Project GENIE: Powering Precision Medicine through an International Consortium.
复制标题

AACR GENIE 项目:通过国际联盟推动精准医疗。

DOI:
10.1158/2159-8290.cd-17-0151
复制
发表时间:
2017-08
期刊:
影响因子:
28.2
通讯作者:
AACR Project GENIE Consortium
AACR Project GENIE Consortium
中科院分区:
医学1区
文献类型:
--
作者:
AACR Project GENIE Consortium

文献摘要

被引文献

相似文献

AACR GENIE 项目是一个国际数据共享联盟,致力于通过将临床级癌症基因组数据与全球多个机构治疗的数万名癌症患者的临床结果数据相结合,为精准癌症医学建立证据基础。结合来自约 19,000 个样本的首次公开数据发布,我们描述了该联盟的目标、结构和数据标准,并报告了对基因组数据初始阶段进行高级分析的结论。我们还提供了 GENIE 数据临床实用性的示例,例如对多种癌症类型 (>30%) 的临床可操作性的估计以及准确反映最近报告的实际匹配率的 NCI-MATCH 试验的应计率预测。 GENIE 数据库预计将在 5 年内增长到超过 100,000 个样本,并应成为精准癌症医学的强大工具。 AACR GENIE 项目旨在促进全球多个机构共享整合的基因组和临床数据集,从而实现精准癌症医学研究,包括识别新的治疗靶点、设计生物标志物驱动的临床试验以及识别治疗反应的基因组决定因素。
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. 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.