The CSBC initiative supports research that investigates the challenges of complexity in basic and translational cancer research through the explicit combination of experimental biology and computational modeling, multi-dimensional data analysis, and systems engineering.
Tackling Complex Questions
The Cancer Systems Biology Consortium (CSBC) is a program of the National Cancer Institute, one of the 27 Institutes and Centers that comprise the National Institutes of Health. The CSBC supports a community of interdisciplinary systems biologists who aim to integrate experimental biology and computational models to address important questions in basic cancer research. Cancer is a complex disease involving multiple molecular, genetic, and cellular events. Considering these events as a system of relationships or interactions, versus in isolation, can lead to a better understanding of how cancer develops and progresses. To make the most of this approach, cancer systems biology utilizes a wide variety of computational tools to build models that can help simplify the complex relationships in cancer. With the explosion in the quantity and quality of available experimental data, cancer systems biology is essential to translate data into insights and predictive models. As part of the cancer systems biology community, CSBC scientists provide intellectual leadership, participate in collaborative projects, and share resources and educational opportunities across the Consortium.
The CSBC Network
The CSBC brings together interdisciplinary teams of clinical and basic cancer researchers combined with physical scientists, engineers, mathematicians and computer scientists who collaborate to tackle key questions in cancer biology from a novel point of view. Our network is organized around a coordinating center (U24) that supports both research centers (U54) and research projects (U01).
Areas of Exploration
Cancer is a complex disease system involving multiple molecular, genetic, and cellular events. From its early initiation through progression and metastasis, cancer can adapt and evolve as a result of both internal and external cues. These properties make cancer difficult to predict, prevent, and/or treat. The CSBC focuses on the analysis of cancer as a complex biological system. Our researchers 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. Our programs look at the following areas of research:
Heterogeneity / Evolution
Drug Resistance / Sensitivity
Impact of CSBC Work
High throughput screening and other technologies have produced an explosion in the quantity of available experimental data. Systems analyses and predictive modeling are necessary to integrate across these datasets that span different length and time scales to understand the cancer process and convert data into knowledge. Predictions from systems biology models need to be experimentally tested or validated so they may be extended to translational and clinical applications.