Drug sensitivity and resistance are conventionally quantified by IC50 or Emax values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC50 and Emax on division rate creates artefactual correlations between genotype and drug sensitivity while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative drug response metrics that are insensitive to division number. These are based on estimating the magnitude of drug-induced growth rate inhibition (GR) using endpoint or time-course assays. We show that GR50 and GRmax are superior to conventional metrics for assessing the effects of drugs in dividing cells. Moreover, adopting GR metrics requires only modest changes in experimental protocols. We expect GR metrics to improve the study of cell signaling and growth using drugs, discovery of drug response biomarkers, and identification of drugs effective on specific patient-derived tumor cells.

Although the nuclear pore complex (NPC) is best known for its primary function as the key regulator of molecular traffic between the cytoplasm and the nucleus, a growing body of experimental evidence suggests that this structure participates in a considerably broader range of cellular activities on both sides of the nuclear envelope. Indeed, the NPC is emerging as an important regulator of gene expression through its influence on the internal architectural organization of the nucleus and its apparently extensive involvement in coordinating the seamless delivery of genetic information to the cytoplasmic protein synthesis machinery.

The ErbB signaling pathways, which regulate diverse physiological responses such as cell survival, proliferation and motility, have been subjected to extensive molecular analysis. Nonetheless, it remains poorly understood how different ligands induce different responses and how this is affected by oncogenic mutations. To quantify signal flow through ErbB-activated pathways we have constructed, trained and analyzed a mass action model of immediate-early signaling involving ErbB1-4 receptors (EGFR, HER2/Neu2, ErbB3 and ErbB4), and the MAPK and PI3K/Akt cascades. We find that parameter sensitivity is strongly dependent on the feature (e.g. ERK or Akt activation) or condition (e.g. EGF or heregulin stimulation) under examination and that this context dependence is informative with respect to mechanisms of signal propagation. Modeling predicts log-linear amplification so that significant ERK and Akt activation is observed at ligand concentrations far below the K d for receptor binding. However, MAPK and Akt modules isolated from the ErbB model continue to exhibit switch-like responses. Thus, key system-wide features of ErbB signaling arise from nonlinear interaction among signaling elements, the properties of which appear quite different in context and in isolation.