DREAM Challenges, Precision Medicine Algorithms, and Perspectives on Cancer Genomics Research: December OCG e-Newsletter
, by OCG Staff
The latest edition of the Office of Cancer Genomics (OCG) e-Newsletter features DREAM challenges in collaboration with the CTD2 Network, algorithms to identify effective cancer treatments in precision oncology, databases and other community resources from OCG initiatives, a scientist interview on translating genomics for precision medicine for cancer, and accessing data associated with HCMI’s next-generation cancer models. OCG is a member office of the Center for Cancer Genomics.
CTD2 DREAM Challenges: Developing Predictive Algorithms to Identify Effective Cancer Treatment Strategies
Justin Guinney, Ph.D. from Sage Bionetworks
The Cancer Target Discovery and Development (CTD2) Network, in partnership with Sage Bionetworks, invites the community to participate in DREAM Challenges to develop predictive bioinformatics methods. The article provides the goals and questions addressed in the CTD2 Pancancer Drug Activity and CTD2 BeatAML DREAM Challenges.
Translating Genomics in Cancer: Interview with Dr. Andy Mungall
Cindy Kyi, PhD.
Dr. Andy Mungall is a genome scientist from the British Columbia Cancer Genome Sciences Centre who is involved with molecular characterization of tumors for Cancer Genome Characterization Initiative (CGCI) projects. In this interview, Dr. Mungall provides his background and perspectives on cancer genomics research.
Cracking the Cancer Code with Computational Approaches
Aaron T. Griffin, M.D. Ph.D. program, Prabhjot S. Mundi, M.D., and Andrea Califano, Ph.D. from the Columbia University CTD² Center
The Califano Lab at Columbia University developed the OncoMatch, OncoTarget, and OncoTreat algorithms to identify effective cancer treatment therapies. The researchers use an analogy of an orchestra with 20,000 musicians and damaged instruments to help explain their work uncovering the complexities of cancer.
OCG-Supported Initiatives Provide Valuable Resources to Advance and Accelerate Precision Oncology
Subhashini Jagu, Ph.D. and Cindy Kyi, Ph.D.
OCG-supported initiatives aim to accelerate the translational research efforts towards precision oncology. The article describes the databases and other resources available for the community.
HCMI Model-Associated Data Available at NCI’s Genomic Data Commons
Lauren Hurd, Ph.D. and Eva Tonsing Carter, Ph.D.
Next-generation cancer models from the Human Cancer Models Initiative (HCMI) have clinical and molecular data which are stored at NCI’s Genomic Data Commons (GDC). This article explains the types of HCMI data, generated from Cancer Model Development Centers, available at the GDC and how to access the data.