First identified in the early 1980s as retroviral oncogenes, the Raf proteins have been the objects of intense research. The discoveries 10 years later that the Raf family members (Raf-1, B-Raf, and A-Raf) are bona fide Ras effectors and upstream activators of the ubiquitous ERK pathway increased the interest in these proteins primarily because of the central role that this cascade plays in cancer development. The important role of Raf in cancer was corroborated in 2002 with the discovery of B-Raf genetic mutations in a large number of tumors. This led to intensified drug development efforts to target Raf signaling in cancer. This work yielded not only recent clinical successes but also surprising insights into the regulation of Raf proteins by homodimerization and heterodimerization. Surprising insights also came from the hunt for new Raf targets. Although MEK remains the only widely accepted Raf substrate, new kinase-independent roles for Raf proteins have emerged. These include the regulation of apoptosis by suppressing the activity of the proapoptotic kinases, ASK1 and MST2, and the regulation of cell motility and differentiation by controlling the activity of Rok-α. In this review, we discuss the regulation of Raf proteins and their role in cancer, with special focus on the interacting proteins that modulate Raf signaling. We also describe the new pathways controlled by Raf proteins and summarize the successes and failures in the development of efficient anticancer therapies targeting Raf. Finally, we also argue for the necessity of more systemic approaches to obtain a better understanding of how the Ras-Raf signaling network generates biological specificity.

Summary Turnover and exchange of nucleosomal histones and their variants, a process long believed to be static in post-replicative cells, remains largely unexplored in brain. Here, we describe a novel mechanistic role for HIRA (histone cell cycle regulator) and proteasomal degradation associated histone dynamics in the regulation of activity-dependent transcription, synaptic connectivity and behavior. We uncover a dramatic developmental profile of nucleosome occupancy across the lifespan of both rodents and humans, with the histone variant H3.3 accumulating to near saturating levels throughout the neuronal genome by mid-adolescence. Despite such accumulation, H3.3 containing nucleosomes remain highly dynamic–in a modification independent manner–to control neuronal- and glial-specific gene expression patterns throughout life. Manipulating H3.3 dynamics in both embryonic and adult neurons confirmed its essential role in neuronal plasticity and cognition. Our findings establish histone turnover as a critical, and previously undocumented, regulator of cell-type specific transcription and plasticity in mammalian brain.

One-sentence summary: Analysis of the ERK circuitry suggests the most effective targets in the pathway for inhibition, which may aid in drug development Editor's Summary: Biological Circuits Inform Drug Development The mitogen-activated protein kinase (MAPK) pathway involves a three-tiered kinase module, which amplifies the signal. Many cells also have negative feedback loops from the last kinase in the module back to various points upstream in the pathway. Sturm et al. show that the MAPK module with negative feedback loops results in a system like that of a negative feedback amplifier (NFA), which is an engineering design that smoothens the output to changes in input and makes a system robust to change. These NFA-like properties may explain why some cells are sensitive to inhibition of the second kinase in the cascade (they lack the feedback loops); whereas other cells are resistant to inhibition at this point (their feedback loops are intact). These results also have implications for drug development, because inhibitors that target components that are outside the NFA are more effective at inhibiting the pathway. Abstract Three-tiered kinase modules, such as the Raf-MEK-ERK mitogen-activated protein kinase pathway, are widespread in biology suggesting that this structure conveys evolutionary advantageous properties. Here, we show that the three-tiered kinase amplifier module combined with negative feedback recapitulates the design principles of a negative feedback amplifier (NFA), which is used in electronic circuits to convey robustness, output stabilization, and linearization of nonlinear signal amplification. With mathematical modelling and experimental validation, we demonstrated that the ERK pathway has properties of a NFA that (i) converts intrinsic switch-like activation kinetics into graded linear responses; (ii) conveys robustness to changes in rates of reactions within the NFA module; and (iii) stabilizes outputs in response to drug-induced perturbations of the amplifier. These properties determine biological behavior, including activation kinetics and the response to drugs.

Summary Activation of ErbB receptors by epidermal growth factor (EGF) or heregulin (HRG) determines distinct cell fate decisions, although signals propagate through shared pathways. Using modeling and experiments, we unravel how EGF and HRG generate distinct, all-or-none responses of the phosphorylated transcription factor c-Fos. In the cytosol, EGF induces transient and HRG induces sustained ERK activation. In the nucleus, however, ERK activity and c-fos mRNA expression are transient for both ligands. Knockdown of dual-specificity phosphatases extends HRG-stimulated nuclear ERK activation, but not c-fos mRNA expression, implying the existence of a HRG-induced repressor of c-fos transcription. Further experiments confirmed that this repressor is mainly induced by HRG, but not EGF, and requires new protein synthesis. We show how a spatially distributed, signaling-transcription cascade robustly discriminates between transient and sustained ERK activities at the c-Fos system level. The proposed control mechanisms are general and operate in different cell types, stimulated by various ligands.

Deregulation of ErbB signaling plays a key role in the progression of multiple human cancers. To help understand ErbB signaling quantitatively, in this work we combine traditional experiments with computational modeling, building a model that describes how stimulation of all four ErbB receptors with epidermal growth factor (EGF) and heregulin (HRG) leads to activation of two critical downstream proteins, extracellular-signal-regulated kinase (ERK) and Akt. Model analysis and experimental validation show that (i) ErbB2 overexpression, which occurs in approximately 25% of all breast cancers, transforms transient EGF-induced signaling into sustained signaling, (ii) HRGinduced ERK activity is much more robust to the ERK cascade inhibitor U0126 than EGF-induced ERK activity, and (iii) phosphoinositol-3 kinase is a major regulator of post-peak but not pre-peak EGF-induced ERK activity. Sensitivity analysis leads to the hypothesis that ERK activation is robust to parameter perturbation at high ligand doses, while Akt activation is not.

Extracellular signal-regulated kinase (ERK) controls fundamental cellular functions, including cell fate decisions 1,2 . In PC12, cells shifting ERK activation from transient to sustained induces neuronal differentiation 3 . As ERK associates with both regulators and effectors 4 , we hypothesized that the mechanisms underlying the switch could be revealed by assessing the dynamic changes in ERK-interacting proteins that specifically occur under differentiation conditions. Using quantitative proteomics, we identified 284 ERK-interacting proteins. Upon induction of differentiation, 60 proteins changed their binding to ERK, including many proteins that were not known to participate in differentiation. We functionally characterized a subset, showing that they regulate the pathway at several levels and by different mechanisms, including signal duration, ERK localization, feedback, crosstalk with the Akt pathway and differential interaction and phosphorylation of transcription factors. Integrating these data with a mathematical model confirmed that ERK dynamics and differentiation are regulated by distributed control mechanisms rather than by a single master switch.

SummaryDynamic interactions between RhoA and Rac1, members of the Rho small GTPase family, play a vital role in the control of cell migration. Using predictive mathematical modeling, mass spectrometry-based quantitation of network components, and experimental validation in MDA-MB-231 mesenchymal breast cancer cells, we show that a network containing Rac1, RhoA, and PAK family kinases can produce bistable, switch-like responses to a graded PAK inhibition. Using a small chemical inhibitor of PAK, we demonstrate that cellular RhoA and Rac1 activation levels respond in a history-dependent, bistable manner to PAK inhibition. Consequently, we show that downstream signaling, actin dynamics, and cell migration also behave in a bistable fashion, displaying switches and hysteresis in response to PAK inhibition. Our results demonstrate that PAK is a critical component in the Rac1-RhoA inhibitory crosstalk that governs bistable GTPase activity, cell morphology, and cell migration switches.

Western blot data are widely used in quantitative applications such as statistical testing and mathematical modelling. To ensure accurate quantitation and comparability between experiments, Western blot replicates must be normalised, but it is unclear how the available methods affect statistical properties of the data. Here we evaluate three commonly used normalisation strategies: (i) by fixed normalisation point or control; (ii) by sum of all data points in a replicate; and (iii) by optimal alignment of the replicates. We consider how these different strategies affect the coefficient of variation (CV) and the results of hypothesis testing with the normalised data. Normalisation by fixed point tends to increase the mean CV of normalised data in a manner that naturally depends on the choice of the normalisation point. Thus, in the context of hypothesis testing, normalisation by fixed point reduces false positives and increases false negatives. Analysis of published experimental data shows that choosing normalisation points with low quantified intensities results in a high normalised data CV and should thus be avoided. Normalisation by sum or by optimal alignment redistributes the raw data uncertainty in a mean-dependent manner, reducing the CV of high intensity points and increasing the CV of low intensity points. This causes the effect of normalisations by sum or optimal alignment on hypothesis testing to depend on the mean of the data tested; for high intensity points, false positives are increased and false negatives are decreased, while for low intensity points, false positives are decreased and false negatives are increased. These results will aid users of Western blotting to choose a suitable normalisation strategy and also understand the implications of this normalisation for subsequent hypothesis testing.