Cancer cells acquire genetic and epigenetic alterations that often lead to dysregulation of oncogenic signal transduction pathways, which in turn alters downstream transcriptional programs.  We present a statistical method called affinity regression to link upstream signaling to downstream transcriptional response by exploiting reverse phase protein array (RPPA) and mRNA expression data in The Cancer Genome Atlas (TCGA) breast cancer project.  We show how to use the trained model to identify dysregulated signaling pathways associated with transcriptomic subtypes, drug response, and survival in breast cancer.