Sage Bionetworks was recently granted an award by the NCI to serve as the Coordinating Center for the new Cancer Systems Biology Consortium (CSBC). The interdisciplinary investigators of the CSBC will integrate experimental biology with mathematical and computational modeling to gain insight into processes relevant to cancer initiation, progression, and treatment options. The Coordinating Center lead by Sage Bionetworks will facilitate data and resource sharing, as well as collaborative scientific activities and systems biology-oriented outreach.
NCI Launches New Cancer Systems Biology Consortium – CSBC
National Cancer Institute Press Release August 29, 2016
The National Cancer Institute has awarded grants to four Institutions to serve as Research Centers in NCI’s new Cancer Systems Biology Consortium (CSBC). The Institutions receiving Center grants are: Columbia University, Memorial Sloan Kettering Institute for Cancer Research, Stanford University and Yale University.
The overall research themes of the CSBC Research Centers address important questions in basic cancer research, including the emergence of drug resistance, the mechanisms underlying cancer metastasis, and the role of the immune system in cancer progression and treatment. Research conducted at the Research Centers will focus on the analysis of cancer as a complex biological system. The interdisciplinary investigators of the CSBC will integrate experimental biology with mathematical and computational modeling to gain insight into processes relevant to cancer initiation, progression, and treatment options.
The CSBC brings together clinical and basic cancer researchers with physical scientists, engineers, mathematicians and computer scientists to tackle key questions in cancer biology from a novel point of view. “Cancer is a complex disease and it challenges our traditional approaches, making it hard to predict tumor growth and drug response,” said Daniel Gallahan, Ph.D., deputy director of NCI’s Division of Cancer Biology. “Cancer systems biologists embrace that complexity and use many different types of data to build mathematical models that allow us to make predictions about whether a tumor will metastasize or what drug combinations will be effective.”