PT - JOURNAL ARTICLE AU - Steven M. Hill AU - Nicole K. Nesser AU - Katie Johnson-Camacho AU - Mara Jeffress AU - Aimee Johnson AU - Chris Boniface AU - Simon E.F. Spencer AU - Yiling Lu AU - Laura M. Heiser AU - Yancey Lawrence AU - Nupur T. Pande AU - James E. Korkola AU - Joe W. Gray AU - Gordon B. Mills AU - Sach Mukherjee AU - Paul T. Spellman TI - Context-specificity in causal signaling networks revealed by phosphoprotein profiling AID - 10.1101/039636 DP - 2016 Jan 01 TA - bioRxiv PG - 039636 4099 - http://biorxiv.org/content/early/2016/02/15/039636.short 4100 - http://biorxiv.org/content/early/2016/02/15/039636.full AB - Summary Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks. However, it remains unclear whether signaling networks depend on biological context. Signaling networks encode causal influences – and not just correlations – between network components. Here, using a causal framework and systematic time-course assays of signaling proteins, we investigate the context-specificity of signaling networks in a cell line system. We focus on a well-defined set of signaling proteins profiled in four breast cancer cell lines under eight stimulus conditions and inhibition of specific kinases. The data, spanning multiple pathways and comprising approximately 70,000 phosphoprotein and 260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we validate in independent experiments. Furthermore, the data provide a resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.