Abstract 2604: The Georgetown Database of Cancer (G-DOC): A web-based data sharing platform for precision medicine

Introduction An overarching goal of biomedical research is to improve the use and dissemination of rapidly growing biomedical datasets to support precision medicine. Individualized molecular profiling and the identification of predictive biomarkers can powerfully inform the choice of therapies for c...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2017-07, Vol.77 (13_Supplement), p.2604-2604
Hauptverfasser: Bhuvaneshwar, Krithika, Belouali, Anas, Rao, Shruti, Alaoui, Adil, Gusev, Yuriy, Clarke, Robert, Weiner, Louis M., Madhavan, Subha
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Sprache:eng
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Zusammenfassung:Introduction An overarching goal of biomedical research is to improve the use and dissemination of rapidly growing biomedical datasets to support precision medicine. Individualized molecular profiling and the identification of predictive biomarkers can powerfully inform the choice of therapies for cancer patients. However, both require integration of extensive molecular, clinical, and pharmacological data, often from disparate and diverse sources. The Georgetown Database of Cancer (G-DOC) was designed and engineered to be a unique multi-omics data analysis platform to enable translational research and precision medicine. Methods G-DOC is home to 61 datasets that contain data from over 10,000 patients across 14 diseases (10 cancers and 4 non-cancers). 1700+ researchers from over 48 different countries worldwide currently use the platform. The data and tools in the G-DOC system have enabled over 40 research publications. G-DOC has the largest public collection of brain cancer patients from NCI Rembrandt dataset (671 patients).G-DOC integrates clinical, transcriptomic, metabolomic, microRNA, next generation sequencing (NGS) data, and MRI medical images with systems-level analysis tools into a single, user-friendly platform. The “Variant Search” feature in G-DOC currently enables exploratory analysis of mutations based on genes, chromosomes, and functional location. A researcher can use this feature to 1) identify clinically actionable mutations in their dataset 2) identify pathways that may be affected by these mutations, and 3) identify novel mutations in their dataset and explore their potential impact on protein function. Results and Conclusion We are currently working on developing features to support the import, integration, search, and retrieval of CLIA/CAP-certified cancer molecular diagnostic (molDx) data. This will enhance G-DOC’s interoperability with clinical and patient molecular profiling data that may be already stored in other databases. Our vision is to continuously improve and expand G-DOC with the long-term vision of supporting integration of informatics techniques into everyday research and practice. Citation Format: Krithika Bhuvaneshwar, Anas Belouali, Shruti Rao, Adil Alaoui, Yuriy Gusev, Robert Clarke, Louis M. Weiner, Subha Madhavan. The Georgetown Database of Cancer (G-DOC): A web-based data sharing platform for precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr
ISSN:0008-5472
1538-7445
DOI:10.1158/1538-7445.AM2017-2604