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Insights & Innovations Blog

Find the latest updates, spotlights, and news from CCG.

  • CTD^2: Bridging Genomics to Therapeutics
    October 19, 2017, by Subhashini Jagu, Ph.D. & Freddie L. Pruitt, Ph.D.

    The Cancer Target Discovery and Development (CTD^2) initiative was established by the National Cancer Institute (NCI) to bridge the gap between cancer genomics and precision oncology and has developed many approaches for identifying therapeutic targets, perturbagens, and biomarkers. CTD^2 is currently exploring cancer heterogeneities and developing strategies to overcome treatment resistance.

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  • A Brief Tour of DAVE: The Genomic Data Commons Analysis Toolkit
    September 12, 2017, by Zhining Wang, Ph.D.

    The Genomic Data Commons (GDC) gives a brief tour of DAVE: Data Analysis, Visualization, and Exploration Tools. GDC welcomes user questions and feedback to help build an accessible and valuable genomic data resource.

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  • TRACERx: Trailblazing Longitudinal Cancer Genomics
    June 1, 2017, by Jean C. Zenklusen, M.S., Ph.D.

    The Cancer Genome Atlas (TCGA) has been analyzed in more than one thousand scientific publications and enabled countless discoveries, but mostly using cross-sectional studies. To study in depth how cancer evolves and progresses, NCI's Center for Cancer Genomics (CCG) is supporting the innovative, longitudinal study Tracking Non-Small-Cell Lung Cancer Evolution through Therapy (TRACERx).

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  • ROS1+ Cancer Patients Partner to Increase Research
    May 23, 2017, by Janet Freeman-Daily, MS, Eng

    ROS1ders, a group of lung cancer patients who share a rare genetic abnormality involving the ROS1 gene, united to support each other and promote research. They formed the Global ROS1 Initiative, a collaboration between foundations, academic researchers, and industry that aims to improve outcomes for future patients.

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  • Researchers Design a Precise Library for CRISPR-Mediated Genetic Screens
    April 6, 2017, by Amy E. Blum, M.A.

    Researchers in the Cancer Target Discovery and Development Network used machine learning to create improved CRISPR libraries for genomic studies. Their new libraries of single guide RNAs can be used to alter gene expression with greater sensitivity and specificity.

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