NEW YORK (GenomeWeb) – The American Association for Cancer Research launched an international genomic and clinical data sharing project called GENIE today that aims to bring together genomic and outcome data from different cancer centers.
The initial phase of GENIE, which stands for Genomics, Evidence, Neoplasia, Information, Exchange, involves seven founding members from the US, Canada, and Europe, as well as two informatics partners, which will aggregate their clinical-grade patient sequence data.
The founding members of the consortium are the Center for Personalized Cancer Treatment in Utrecht, the Netherlands; Dana-Farber Cancer Institute in Boston; Institut Gustave Roussy in Villejuif, France; Johns Hopkins University's Sidney Kimmel Comprehensive Cancer Center in Baltimore; Memorial Sloan Kettering Cancer Center in New York; Princess Margaret Cancer Centre in Toronto; and Vanderbilt-Ingram Cancer Center in Nashville, Tennessee. The two informatics partners are Seattle-based Sage Bionetworks and cBioPortal of New York.
AACR Project GENIE will pool CLIA- and ISO-certified sequencing data from the participating institutions into a single registry and link them with select longitudinal clinical outcomes. Access to the data will be opened after a defined period of exclusivity, and the first data set is being made publicly available today.
The registry already contains more than 17,000 genomic records, which are enriched in late-stage cancers and only contain clinical-grade sequencing data that has been used to inform clinical decisions. The number of records is expected to grow over time as member institutions add patients and as the consortium grows after the project's pilot phase.
"Data-sharing projects are crucial because they connect data producers, mainly doctors from hospitals, and data analysts who are bioinformaticians and biologists," said Fabrice André, a professor at Institut Gustave Roussy and a member of the AACR Project GENIE steering committee.
Project participants are hoping the registry will help with validating gene signatures of drug response or prognosis, identifying new patient populations for FDA-approved drugs, expanding patient populations that will benefit from existing drugs, and identifying new drug targets and biomarkers.