Project Summary: This proposal seeks to establish an annual short course in Cancer Systems Biology. Systems Biology harnesses ideas and methodologies from mathematics, physics, engineering and computer science to tackle fundamental questions about the organization, design and performance of complex biological systems, questions not easily addressed through traditional molecular and cellular approaches. Such questions are particularly relevant to Cancer Biology, where perturbations at multiple levels of control systems lead to aberrant behaviors and cascading failures in homeostasis leading to disease. The development of high throughput data generation technologies and their application in cancer has led to a shift in focus from individual components of cancer cells (e.g., genes) to large-scale, nonlinearly interacting networks involving signaling and communication of cancer cells with themselves and with their microenvironment. This has naturally led to the introduction of Systems Biology approaches into Cancer Biology and resulted in advances in our fundamental understanding of cancer initiation, progression and response to treatment. Yet widespread integration of Systems and Cancer Biology is hampered by a lack of training. Biologists and clinicians typically do not receive sufficient training in mathematical, statistical and computational tools needed to apply Systems Biology methodologies. On the other hand, physicists, mathematicians and others from non-biomedical fields who have the theoretical and computational knowledge base needed for Systems Biology, typically lack sufficient training in cancer biology needed to apply these methodologies to cancer. The goal of our course is to provide a diverse group of about 20 graduate students, postdocs, and experienced researchers an intensive three-week program at the University of California, Irvine to bridge individual training deficits that pose an obstacle to entry into the Cancer Systems Biology field and to provide a high-level systems biology exploration of a subset of core issues in current cancer research. The proposed course begins with a one-week Preparatory Workshop in either i) Mathematical and Computational Methods, or ii) Fundamentals of Cancer Biology and Biomedicine, followed by a two-week Core Course in which both lectures and laboratory modules are used to expose participants to cutting-edge methodologies and research topics at the intersection between Systems and Cancer Biology. Lectures and laboratory modules will be given by 19 UCI faculty (both academic and clinical) with research and teaching expertise in mathematics, physics, computer science, engineering and cancer biology. The goals of the course include (1) conveying an understanding of what Systems Biology is; (2) providing a grounding in mathematical and computational fundamentals; (3) fostering a deep understanding of how mathematical, statistical and computational models are used in biology and biomedicine; (4) providing opportunities to apply cutting-edge Systems Biology methods to specific problems in the areas of cancer biology, with an emphasis on the study of cancer cell heterogeneity and spatiotemporal dynamics at the genomic, cellular and microenvironmental levels; and (5) fostering interdisciplinary interactions among participants and teaching faculty. Lecture materials (video recorded), training datasets, and software tools will be made freely available through on-line distribution to maximize outreach. Course administration and logistics will be handled by the UC Irvine Center for Complex Biological Systems (CCBS), one of thirteen NIH National Centers for Systems Biology, in conjunction with the Chao Family Comprehensive Cancer Center, a NCI-designated comprehensive cancer center.

Project Narrative Funding from this grant will establish an annual three-week course at the University of California Irvine for training biomedical researchers with interests in applying System Biology approaches to the study of cancer. Systems Biology blends biology with concepts and methodologies derived from mathematics, computer science, engineering and physics, enabling researchers to approach and apply new tools to the complex and dynamic problems encountered in cancer.