Large NCI clinical trials and research projects have been generating data on cancer genomes at an unprecedented rate, elucidating the mechanisms of cancer initiation and evolution, as well as resistance to therapy. To fully utilize this comprehensive data resource, which has exceeded a petabyte (1015 bytes) of data, the scientific community needs deep, user-friendly interactive computer visualizations of the data. These will empower investigators to discover the molecular processes driving each patient's cancer, and to identify potential translations of this knowledge into new therapies, ultimately advancing both our knowledge of cancer mechanisms and patient outcomes. We propose to develop a web-based Data Hub and Viz Hub platform to allow researchers to visualize the richness of the NCI's cancer genomics data from a single web interface. Visualizations will be composed of a set of ?bio-centric? views developed by the bioinformatics community and made available in BioJS, an open- source repository of tools to represent biological data. This will establish a new paradigm of web-based biological data visualization development by way of sharable and reusable modular open source components. To initiate the Viz Hub platform, we will integrate seven popular 3rd-party bioinformatics visualizations into the existing UCSC Xena Browser utilizing a plug-and-play framework. We will then work closely with several clinical labs to develop two new translational visualizations for the next generation of genomic medicine. One will be a Longitudinal Omics Integrator, giving researchers a highlighted overview of a patient while drilling down into genomic and functional data collected throughout treatment. Another will help researchers investigate responses to various new types of immunotherapy, which promise to revolutionize cancer treatment. This Immuno-Tracker and Immunoediting Viewer will show how immunogenic neoantigens, T-cell receptors, and B-cell receptors change over disease progression and in response to treatment. The visualization needs of the scientific community, NCI's Genomic Data Analysis Network, and Disease Working groups will be fully supported through our system of public and restricted Data Hubs. Our high- performance Data Hubs will be easy to install on a diverse range of computing environments. Users will be able to integrate public and restricted data, from large consortia and individual researchers (including their own labs), seamlessly on our web-based Viz Hub. Our commitment to bioinformatics community standards, such as GA4GH and BioJS, ensures that our contributions will be interoperable. Our designs will be vetted by users through testing in tumor boards and at designated booths at international cancer meetings. This will ensure that our platform will effectively serve researchers, biologists and clinicians now and into the future of precision medicine.
We propose to create a web-based system called Xena for user-friendly interactive computer visualization and exploration of cancer genomes and other big data from large NCI clinical trials and projects. With a strong focus on usability and application in personalized medicine, Xena will integrate visual representations of cancer data into a single easy-to-use interface, helping cancer researchers identify potential clinical treatments for each cancer patient, in part by rapidly comparing them to thousands of other patients. By making big data accessible and interpretable, our project will accelerate research into the mechanisms and treatment of cancer, the second-leading cause of death in the U.S.
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