Because binding experiments often utilize displacement of a known ligand, they will not identify compounds binding at alternative sites of action. Gene expression measurements have additional attractive properties compared to other high-throughput technologies. Because microarray profiles represent an integrated output of multiple signaling pathways in the cell, they are potentially more sensitive than biochemical or cellular assays which are commonly designed to test one or a limited number of physiological parameters. Such expression profiles are also certainly more general in terms of measuring diverse signaling pathways and integrated biological events. Thus, SCH772984 assessment of hERG liability may be effectively evaluated in parallel with other endpoints of biological interest, such as inflammatory signaling, oxidative damage response, or metabolic perturbations. Additionally, the fact that our signature utilizes measurements in cancer cells derived from different tissues of origin suggests the attractive possibility of assaying the effects of hERG activity in these oncogenesis models, as previous research has linked hERG expression to tumor migration and cell volume. Admittedly, cells with cardiac lineage may be equally or more informative. Indeed, patient-derived induced pluripotent stem cell Perifosine models of cardiac disease have proven to be attractive disease models in electrophysiology studies, with additional evidence suggesting the potential for cardiac-specific transcriptional activity that may find utility in genomic drug-activity profiles. Combined with cost savings generated by custom arrays that measure only the subset of differentially expressed genes correlated with hERG risk, these aspects suggest the potential for a novel genetic platform to assess ion channel activity. More generally, our analysis contributes to growing evidence that systems-level measurements of drug effect reveal connections and similarities often invisible from the perspective of single molecular descriptors or activity measurements. These links suggest not only the possibility of mining such connections for predictive purposes, but also that the full pharmacological complexity of even long-standing medications may not yet be appreciated. Integrated analyses are thus poised to illuminate these patterns and suggest possibly novel indications or, as in our study, liabilities of existing drugs. Following pre-processing, we sought to remove correlations between arrays due to experimental batch rather than biological similarity by mean-centering probesets across all drugs in each batch, following a previously described pipeline. Since this correction assumes that on average a probeset should not be differentially expressed among an experimental batch of otherwise unrelated drugs, we retained only batches with sufficient numbers for this assumption to reasonably hold.