Cancer is a complex and heterogeneous disease, demonstrating variations with respect to tumor types and between individual tumors. This heterogeneity has complicated the search for 'magic bullets'-individual genes or pathways that could be targeted and have beneficial effects for large numbers of patients. Instead, recent studies suggest that cancer can be more effectively analyzed through the use of systems biology techniques that examine multiple pathways and account for interactions between these pathways. In this review, we outline the various ways in which systems biology can be utilized to translate high-throughput data into a signaling network and then computationally analyze how cells make decisions based on the information flow through this network. We then discuss recent studies utilizing network-level analysis to reveal therapeutic targets, predict which tumors will be sensitive to existing drugs, and develop combinatorial therapies that target multiple pathways, demonstrating the potential for systems biology to revolutionize cancer therapy.
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