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A new approach is described for revealing the signal-transduction networks based on the clustering of network topologies, multiple genomic expression profiles, and cell signaling pathways. Its utility is illustrated by applying it to the analysis of prostate cancer metastasis. The resulting signal-transduction networks composed of those protein paths not only achieve high differential expression signatures in multiple microarray data sets but also function as the signal-transduction bridges linking the prostate cancer signaling pathway and other cell signaling pathways. The identified networks assemble both network topology and expression signatures for prostate metastasis into a meaningful biological context through signaling pathways and have the potential to be the key signal transductions for prostate cancer metastasis.