Large-Scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines.

Perturbation biology is a powerful approach to modeling quantitative cellular behaviors and understanding detailed disease mechanisms. However, large-scale protein response resources of cancer cell lines to perturbations are not available, resulting in a critical knowledge gap. Here we generated and compiled perturbed expression profiles of ∼210 clinically relevant proteins in >12,000 cancer cell line samples in response to ∼170 drug compounds using reverse-phase protein arrays. We show that integrating perturbed protein response signals provides mechanistic insights into drug resistance, increases the predictive power for drug sensitivity, and helps identify effective drug combinations. We build a systematic map of "protein-drug" connectivity and develop a user-friendly data portal for community use. Our study provides a rich resource to investigate the behaviors of cancer cells and the dependencies of treatment responses, thereby enabling a broad range of biomedical applications.

Enhancement of Ih, but not inhibition of IM, is a key mechanism underlying the PACAP-induced increase in excitability of guinea pig intrinsic cardiac neurons.

Pituitary adenylate cyclase-activating polypeptide (PACAP) increases excitability of guinea pig cardiac neurons, an effect mediated by PACAP-selective PAC(1) receptors. In dissociated guinea pig cardiac neurons, PACAP causes a positive shift of the voltage dependence of activation of the hyperpolarization-activated nonselective cation current (I(h)). This observation suggested that an enhancement of I(h) contributed to the increase in excitability in neurons within whole-mount cardiac ganglia preparations. To evaluate the role of I(h) in the PACAP-induced increase in excitability, we compared the increase in action potentials generated by 10 nM PACAP in control neurons and in neurons treated with ZD7288 (10 or 100 muM) or CsCl (2 or 2.5 mM), drugs known to inhibit I(h). In control cells exposed to PACAP, 1-s depolarizing current pulses elicited multiple action potential firing in 79% of the neurons. In ZD7288- or CsCl-containing solutions, the 10 nM PACAP-induced increase in excitability was markedly suppressed, with 7% and 21% of the neurons generating multiple action potentials, respectively. Prior results indicated that PACAP initiates depolarization by activating an inward current, which is separate from its enhancement of I(h). Here, we show that a PACAP-induced depolarization was comparable in control neurons and neurons bathed in a CsCl-containing solution, an observation indicating that CsCl did not interfere with activation of the PAC(1) receptor by PACAP. Additional experiments indicated that pretreatment with the putative M current (I(M)) inhibitor 1 mM BaCl(2), but not 10 microM XE991, initiated multiple firing in a majority of neurons, with resting potentials maintained at approximately -60 mV. Furthermore, in Ba(2+)-treated cells, 10 nM PACAP increased the number of action potentials generated. Our results indicate that PACAP enhancement of I(h), rather than inhibition of I(M) and other 1 mM Ba(2+)-sensitive K(+) currents, is a key ionic mechanism contributing to the peptide-induced increase in excitability for neurons within whole-mount cardiac ganglia preparations.

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.