Strong negative feedback from Erk to Raf confers robustness to MAPK signalling

Systems Biology of the Cancer Cell

Questions in cancer have engaged systems biologists for decades. During that time, the quantity of molecular data has exploded, but the need for abstractions, formal models, and simplifying insights has remained the same. This review brings together classic breakthroughs and recent findings in the field of cancer systems biology, focusing on cancer cell pathways for tumorigenesis and therapeutic response. Cancer cells mutate and transduce information from their environment to alter gene expression, metabolism, and phenotypic states. Understanding the molecular architectures that make each of these steps possible is a long-term goal of cancer systems biology pursued by iterating between quantitative models and experiments. We argue that such iteration is the best path to deploying targeted therapies intelligently so that each patient receives the maximum benefit for their cancer.

Gossiping about death: Apoptosis-induced ERK waves as coordinators of multicellular fate decisions

Apoptosis is now recognized as a highly dynamic process that involves the release of a large set of signaling molecules that convey information to cells neighboring an apoptotic site. Recent studies in epithelial systems have discovered that apoptotic cells trigger waves of pulses of mitogen-activated protein kinase (MAPK) / extracellular signal-regulated kinase (ERK) pathway activity in their neighbors. At the single-cell level, the ERK pulses emerge from the MAPK pathway's excitable network properties, such as ultrasensitivity and adaptation. At the cell population level, apoptosis-induced ERK waves (AiEWs) emerge from propagation of ERK pulses across cells via a mechanism that involves mechanical inputs and paracrine signaling. AiEWs enable cell populations to dynamically coordinate fate decision signaling during tissue homeostasis and development. This spatio-temporal signaling mechanism can be hijacked by cancer cells to induce drug-tolerant persister states when apoptosis is triggered by cytotoxic or targeted therapies, undermining treatment efficacy. In this review, we summarize our current understanding of AiEWs, including their initiation, propagation, and coordination of fate decision signaling within a population. We discuss how the relatively simple properties of single cells, and their interactions within a collective coordinate these dynamic signaling patterns. We highlight their implication in resistance to cancer therapy and explore potential strategies to target these waves to re-sensitize cancer cells. Finally, we discuss emerging technologies and future directions to expand the study of this biological phenomenon.

Genetic assimilation, robustness and plasticity are key processes in the development and evolution of novel traits

This is a commentary on how C.H. Waddington's experiments in the 1950's, first published in 1953 in a provocatively titled paper "Genetic assimilation of an acquired character," laid the foundation for the field of phenotypic plasticity, and how the ideas he developed eventually led to new ways of understanding phenotypic robustness, plasticity, and how novel traits develop and evolve. The "acquired characters" that Waddington worked with were based on Goldschmidt's ideas of "phenocopies": new phenotypes that develop after an environmental stress that resemble the phenotypes of known mutations. The idea behind genetic assimilation, first outlined by Waddington in 1942, is that existing developmental pathways can be rearranged and redirected through selection to stabilize the phenocopy phenotype, without requiring new mutations. In the short term, Waddington's work led to the discovery of heat shock proteins and the role of Hsp90 in masking defective proteins and allowing the accumulation of cryptic genetic variation. Subsequent studies revealed a host of stabilizing systems that operate at all levels of biological organization that make phenotypes robust to genetic and environmental variation. Many of these resemble homeostatic mechanisms that don't require a stress shock but operate under normal physiological conditions and allow for the accumulation of large amounts of cryptic genetic variation. This cryptic genetic variation can be revealed by mutations or environmental factors that destabilize a homeostatic mechanism. Selection can then act on the phenotypic variants that are produced. This scenario corresponds to the modern phenotype-first hypothesis for the evolution of novel traits that was foreseen by Waddington as early as 1942.

Quantitative modeling of signaling in aggressive B cell lymphoma unveils conserved core network

B cell receptor (BCR) signaling is required for the survival and maturation of B cells and is deregulated in B cell lymphomas. While proximal BCR signaling is well studied, little is known about the crosstalk of downstream effector pathways, and a comprehensive quantitative network analysis of BCR signaling is missing. Here, we semi-quantitatively modelled BCR signaling in Burkitt lymphoma (BL) cells using systematically perturbed phosphorylation data of BL-2 and BL-41 cells. The models unveiled feedback and crosstalk structures in the BCR signaling network, including a negative crosstalk from p38 to MEK/ERK. The relevance of the crosstalk was verified for BCR and CD40 signaling in different BL cells and confirmed by global phosphoproteomics on ERK itself and known ERK target sites. Compared to the starting network, the trained network for BL-2 cells was better transferable to BL-41 cells. Moreover, the BL-2 network was also suited to model BCR signaling in Diffuse large B cell lymphoma cells lines with aberrant BCR signaling (HBL-1, OCI-LY3), indicating that BCR aberration does not cause a major downstream rewiring.

Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways

The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data.

Multistationarity questions in reduced versus extended biochemical networks

We address several questions in reduced versus extended networks via the elimination or addition of intermediate complexes in the framework of chemical reaction networks with mass-action kinetics. We clarify and extend advances in the literature concerning multistationarity in this context, mainly from Feliu and Wiuf (J R Soc Interface 10:20130484, 2013), Sadeghimanesh and Feliu (Bull Math Biol 81:2428-2462, 2019), Pérez Millán and Dickenstein (SIAM J Appl Dyn Syst 17(2):1650-1682, 2018), Dickenstein et al. (Bull Math Biol 81:1527-1581, 2019). We establish general results about MESSI systems, which we use to compute the circuits of multistationarity for significant biochemical networks.

Network switches and their role in circadian clocks

Circadian rhythms are generated by complex interactions among genes and proteins. Self-sustained ∼24 h oscillations require negative feedback loops and sufficiently strong nonlinearities that are the product of molecular and network switches. Here, we review common mechanisms to obtain switch-like behavior, including cooperativity, antagonistic enzymes, multisite phosphorylation, positive feedback, and sequestration. We discuss how network switches play a crucial role as essential components in cellular circadian clocks, serving as integral parts of transcription-translation feedback loops that form the basis of circadian rhythm generation. The design principles of network switches and circadian clocks are illustrated by representative mathematical models that include bistable systems and negative feedback loops combined with Hill functions. This work underscores the importance of negative feedback loops and network switches as essential design principles for biological oscillations, emphasizing how an understanding of theoretical concepts can provide insights into the mechanisms generating biological rhythms.

Coupling allows robust mammalian redox circadian rhythms despite heterogeneity and noise

Circadian clocks are endogenous oscillators present in almost all cells that drive daily rhythms in physiology and behavior. There are two mechanisms that have been proposed to explain how circadian rhythms are generated in mammalian cells: through a transcription-translation feedback loop (TTFL) and based on oxidation/reduction reactions, both of which are intrinsically stochastic and heterogeneous at the single cell level. In order to explore the emerging properties of stochastic and heterogeneous redox oscillators, we simplify a recently developed kinetic model of redox oscillations to an amplitude-phase oscillator with 'twist' (period-amplitude correlation) and subject to Gaussian noise. We show that noise and heterogeneity alone lead to fast desynchronization, and that coupling between noisy oscillators can establish robust and synchronized rhythms with amplitude expansions and tuning of the period due to twist. Coupling a network of redox oscillators to a simple model of the TTFL also contributes to synchronization, large amplitudes and fine-tuning of the period for appropriate interaction strengths. These results provide insights into how the circadian clock compensates randomness from intracellular sources and highlight the importance of noise, heterogeneity and coupling in the context of circadian oscillators.

A guide to ERK dynamics, part 1: mechanisms and models

Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.

Modeling unveils sex differences of signaling networks in mouse embryonic stem cells

For a short period during early development of mammalian embryos, both X chromosomes in females are active, before dosage compensation is ensured through X-chromosome inactivation. In female mouse embryonic stem cells (mESCs), which carry two active X chromosomes, increased X-dosage affects cell signaling and impairs differentiation. The underlying mechanisms, however, remain poorly understood. To dissect X-dosage effects on the signaling network in mESCs, we combine systematic perturbation experiments with mathematical modeling. We quantify the response to a variety of inhibitors and growth factors for cells with one (XO) or two X chromosomes (XX). We then build models of the signaling networks in XX and XO cells through a semi-quantitative modeling approach based on modular response analysis. We identify a novel negative feedback in the PI3K/AKT pathway through GSK3. Moreover, the presence of a single active X makes mESCs more sensitive to the differentiation-promoting Activin A signal and leads to a stronger RAF1-mediated negative feedback in the FGF-triggered MAPK pathway. The differential response to these differentiation-promoting pathways can explain the impaired differentiation propensity of female mESCs.

Automatic detection of spatio-temporal signaling patterns in cell collectives

Increasing experimental evidence points to the physiological importance of space-time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.

Monte Carlo samplers for efficient network inference

Accessing information on an underlying network driving a biological process often involves interrupting the process and collecting snapshot data. When snapshot data are stochastic, the data's structure necessitates a probabilistic description to infer underlying reaction networks. As an example, we may imagine wanting to learn gene state networks from the type of data collected in single molecule RNA fluorescence in situ hybridization (RNA-FISH). In the networks we consider, nodes represent network states, and edges represent biochemical reaction rates linking states. Simultaneously estimating the number of nodes and constituent parameters from snapshot data remains a challenging task in part on account of data uncertainty and timescale separations between kinetic parameters mediating the network. While parametric Bayesian methods learn parameters given a network structure (with known node numbers) with rigorously propagated measurement uncertainty, learning the number of nodes and parameters with potentially large timescale separations remain open questions. Here, we propose a Bayesian nonparametric framework and describe a hybrid Bayesian Markov Chain Monte Carlo (MCMC) sampler directly addressing these challenges. In particular, in our hybrid method, Hamiltonian Monte Carlo (HMC) leverages local posterior geometries in inference to explore the parameter space; Adaptive Metropolis Hastings (AMH) learns correlations between plausible parameter sets to efficiently propose probable models; and Parallel Tempering takes into account multiple models simultaneously with tempered information content to augment sampling efficiency. We apply our method to synthetic data mimicking single molecule RNA-FISH, a popular snapshot method in probing transcriptional networks to illustrate the identified challenges inherent to learning dynamical models from these snapshots and how our method addresses them.

Oncogenic signaling is coupled to colorectal cancer cell differentiation state

Colorectal cancer progression is intrinsically linked to stepwise deregulation of the intestinal differentiation trajectory. In this process, sequential mutations of APC, KRAS, TP53, and SMAD4 enable oncogenic signaling and establish the hallmarks of cancer. Here, we use mass cytometry of isogenic human colon organoids and patient-derived cancer organoids to capture oncogenic signaling, cell phenotypes, and differentiation states in a high-dimensional single-cell map. We define a differentiation axis in all tumor progression states from normal to cancer. Our data show that colorectal cancer driver mutations shape the distribution of cells along the differentiation axis. In this regard, subsequent mutations can have stem cell promoting or restricting effects. Individual nodes of the cancer cell signaling network remain coupled to the differentiation state, regardless of the presence of driver mutations. We use single-cell RNA sequencing to link the (phospho-)protein signaling network to transcriptomic states with biological and clinical relevance. Our work highlights how oncogenes gradually shape signaling and transcriptomes during tumor progression.

The ERK activator, BCI, inhibits ciliogenesis and causes defects in motor behavior, ciliary gating, and cytoskeletal rearrangement

MAPK pathways are well-known regulators of the cell cycle, but they have also been found to control ciliary length in a wide variety of organisms and cell types from Caenorhabditis elegans neurons to mammalian photoreceptors through unknown mechanisms. ERK1/2 is a MAP kinase in human cells that is predominantly phosphorylated by MEK1/2 and dephosphorylated by the phosphatase DUSP6. We have found that the ERK1/2 activator/DUSP6 inhibitor, (E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one (BCI), inhibits ciliary maintenance in Chlamydomonas and hTERT-RPE1 cells and assembly in Chlamydomonas These effects involve inhibition of total protein synthesis, microtubule organization, membrane trafficking, and KAP-GFP motor dynamics. Our data provide evidence for various avenues for BCI-induced ciliary shortening and impaired ciliogenesis that gives mechanistic insight into how MAP kinases can regulate ciliary length.

Memory of stochastic single-cell apoptotic signaling promotes chemoresistance in neuroblastoma

Gene expression noise is known to promote stochastic drug resistance through the elevated expression of individual genes in rare cancer cells. However, we now demonstrate that chemoresistant neuroblastoma cells emerge at a much higher frequency when the influence of noise is integrated across multiple components of an apoptotic signaling network. Using a JNK activity biosensor with longitudinal high-content and in vivo intravital imaging, we identify a population of stochastic, JNK-impaired, chemoresistant cells that exist because of noise within this signaling network. Furthermore, we reveal that the memory of this initially random state is retained following chemotherapy treatment across a series of in vitro, in vivo, and patient models. Using matched PDX models established at diagnosis and relapse from individual patients, we show that HDAC inhibitor priming cannot erase the memory of this resistant state within relapsed neuroblastomas but improves response in the first-line setting by restoring drug-induced JNK activity within the chemoresistant population of treatment-naïve tumors.

Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway

Nongenetic heterogeneity is key to cellular decisions, as even genetically identical cells respond in very different ways to the same external stimulus, e.g., during cell differentiation or therapeutic treatment of disease. Strong heterogeneity is typically already observed at the level of signaling pathways that are the first sensors of external inputs and transmit information to the nucleus where decisions are made. Since heterogeneity arises from random fluctuations of cellular components, mathematical models are required to fully describe the phenomenon and to understand the dynamics of heterogeneous cell populations. Here, we review the experimental and theoretical literature on cellular signaling heterogeneity, with special focus on the TGFβ/SMAD signaling pathway.

Design and selection of optimal ErbB-targeting bispecific antibodies in pancreatic cancer

The ErbB family of receptor tyrosine kinases is a primary target for small molecules and antibodies for pancreatic cancer treatment. Nonetheless, the current treatments for this tumor are not optimal due to lack of efficacy, resistance, or toxicity. Here, using the novel BiXAb™ tetravalent format platform, we generated bispecific antibodies against EGFR, HER2, or HER3 by considering rational epitope combinations. We then screened these bispecific antibodies and compared them with the parental single antibodies and antibody pair combinations. The screen readouts included measuring binding to the cognate receptors (mono and bispecificity), intracellular phosphorylation signaling, cell proliferation, apoptosis and receptor expression, and also immune system engagement assays (antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity). Among the 30 BiXAbs™ tested, we selected 3Patri-1Cetu-Fc, 3Patri-1Matu-Fc and 3Patri-2Trastu-Fc as lead candidates. The in vivo testing of these three highly efficient bispecific antibodies against EGFR and HER2 or HER3 in pre-clinical mouse models of pancreatic cancer showed deep antibody penetration in these dense tumors and robust tumor growth reduction. Application of such semi-rational/semi-empirical approach, which includes various immunological assays to compare pre-selected antibodies and their combinations with bispecific antibodies, represents the first attempt to identify potent bispecific antibodies against ErbB family members in pancreatic cancer.

The overview of Mitogen-activated extracellular signal-regulated kinase (MEK)-based dual inhibitor in the treatment of cancers

Mitogen-activated extracellular signal-regulated kinase 1 and 2 (MEK1/2) are the critical components of the mitogen-activated protein kinase/extracellular signal-regulated kinase 1 and 2 (MAPK/ERK1/2) signaling pathway which is one of the well-characterized kinase cascades regulating cell proliferation, differentiation, growth, metabolism, survival and mobility both in normal and cancer cells. The aberrant activation of MAPK/ERK1/2 pathway is a hallmark of numerous human cancers, therefore targeting the components of this pathway to inhibit its dysregulation is a promising strategy for cancer treatment. Enormous efforts have been done in the development of MEK1/2 inhibitors and encouraging advancements have been made, including four inhibitors approved for clinical use. However, due to the multifactorial property of cancer and rapidly arising drug resistance, the clinical efficacy of these MEK1/2 inhibitors as monotherapy are far from ideal. Several alternative strategies have been developed to improve the limited clinical efficacy, including the dual inhibitor which is a single drug molecule able to simultaneously inhibit two targets. In this review, we first introduced the activation and function of the MAPK/ERK1/2 components and discussed the advantages of MEK1/2-based dual inhibitors compared with the single inhibitors and combination therapy in the treatment of cancers. Then, we overviewed the MEK1/2-based dual inhibitors for the treatment of cancers and highlighted the theoretical basis of concurrent inhibition of MEK1/2 and other targets for development of these dual inhibitors. Besides, the status and results of these dual inhibitors in both preclinical and clinical studies were also the focus of this review.

Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

BACKGROUND

Development of resistance to targeted therapies has tempered initial optimism that precision oncology would improve poor outcomes for cancer patients. Resistance mechanisms, however, can also confer new resistance-specific vulnerabilities, termed collateral sensitivities. Here we investigated anaplastic lymphoma kinase (ALK) inhibitor resistance in neuroblastoma, a childhood cancer frequently affected by activating ALK alterations.

METHODS

Genome-wide forward genetic CRISPR-Cas9 based screens were performed to identify genes associated with ALK inhibitor resistance in neuroblastoma cell lines. Furthermore, the neuroblastoma cell line NBLW-R was rendered resistant by continuous exposure to ALK inhibitors. Genes identified to be associated with ALK inhibitor resistance were further investigated by generating suitable cell line models. In addition, tumor and liquid biopsy samples of four patients with ALK-mutated neuroblastomas before ALK inhibitor treatment and during tumor progression under treatment were genomically profiled.

RESULTS

Both genome-wide CRISPR-Cas9-based screens and preclinical spontaneous ALKi resistance models identified NF1 loss and activating NRASQ61K mutations to confer resistance to chemically diverse ALKi. Moreover, human neuroblastomas recurrently developed de novo loss of NF1 and activating RAS mutations after ALKi treatment, leading to therapy resistance. Pathway-specific perturbations confirmed that NF1 loss and activating RAS mutations lead to RAS-MAPK signaling even in the presence of ALKi. Intriguingly, NF1 loss rendered neuroblastoma cells hypersensitive to MEK inhibition.

CONCLUSIONS

Our results provide a clinically relevant mechanistic model of ALKi resistance in neuroblastoma and highlight new clinically actionable collateral sensitivities in resistant cells.

eEF2K Activity Determines Synergy to Cotreatment of Cancer Cells With PI3K and MEK Inhibitors

PI3K-mammalian target of rapamycin and MAPK/ERK kinase (MEK)/mitogen-activated protein kinase (MAPK) are the most frequently dysregulated signaling pathways in cancer. A problem that limits the success of therapies that target individual PI3K-MAPK members is that these pathways converge to regulate downstream functions and often compensate each other, leading to drug resistance and transient responses to therapy. In order to overcome resistance, therapies based on cotreatments with PI3K/AKT and MEK/MAPK inhibitors are now being investigated in clinical trials, but the mechanisms of sensitivity to cotreatment are not fully understood. Using LC-MS/MS-based phosphoproteomics, we found that eukaryotic elongation factor 2 kinase (eEF2K), a key convergence point downstream of MAPK and PI3K pathways, mediates synergism to cotreatment with trametinib plus pictilisib (which target MEK1/2 and PI3Kα/δ, respectively). Inhibition of eEF2K by siRNA or with a small molecule inhibitor reversed the antiproliferative effects of the cotreatment with PI3K plus MEK inhibitors in a cell model-specific manner. Systematic analysis in 12 acute myeloid leukemia cell lines revealed that eEF2K activity was increased in cells for which PI3K plus MEKi cotreatment is synergistic, while PKC potentially mediated resistance to such cotreatment. Together, our study uncovers eEF2K activity as a key mediator of responses to PI3Ki plus MEKi and as a potential biomarker to predict synergy to cotreatment in cancer cells.

Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics

Combining single-cell measurements of ERK activity dynamics with perturbations provides insights into the MAPK network topology. We built circuits consisting of an optogenetic actuator to activate MAPK signaling and an ERK biosensor to measure single-cell ERK dynamics. This allowed us to conduct RNAi screens to investigate the role of 50 MAPK proteins in ERK dynamics. We found that the MAPK network is robust against most node perturbations. We observed that the ERK-RAF and the ERK-RSK2-SOS negative feedback operate simultaneously to regulate ERK dynamics. Bypassing the RSK2-mediated feedback, either by direct optogenetic activation of RAS, or by RSK2 perturbation, sensitized ERK dynamics to further perturbations. Similarly, targeting this feedback in a human ErbB2-dependent oncogenic signaling model increased the efficiency of a MEK inhibitor. The RSK2-mediated feedback is thus important for the ability of the MAPK network to produce consistent ERK outputs, and its perturbation can enhance the efficiency of MAPK inhibitors.

Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles

Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells. First, we engineer a synthetic covalent modification cycle based on kinase and phosphatase proteins derived from the bifunctional histidine kinase EnvZ, enabling analog tuning of gene expression via its response regulator OmpR. By regulating phosphatase expression with endogenous miRNAs, we demonstrate cell-type specific signaling responses and a new strategy for accurate cell type classification. Finally, we implement a tunable negative feedback controller via a small molecule-stabilized phosphatase, reducing output expression variance and mitigating the context-dependent effects of off-target regulation and resource competition. Our work lays the foundation for establishing tunable, precise, and robust control over cell behavior with synthetic signaling networks.

Role of Furin in Colon Cancer Stem Cells Malignant Phenotype and Expression of LGR5 and NANOG in KRAS and BRAF-Mutated Colon Tumors

Proprotein convertases or PCs are known to regulate the malignant phenotype of colon cancer cells by different mechanisms, but their effects on cancer stem cells (CSCs) have been less widely investigated. Here, we report that PCs expression is altered in colon CSCs, and the inhibition of their activity reduced colon CSCs growth, survival, and invasion in three-dimensional spheroid cultures. In vivo, repression of PCs activity by the general PC inhibitors α1-PDX, Spn4A, or decanoyl-RVKR-chloromethylketone (CMK) significantly reduced tumor expression levels of the stem cell markers LGR5 and NANOG that are associated with reduced tumor xenografts. Further analysis revealed that reduced tumor growth mediated by specific silencing of the convertase Furin in KRAS or BRAF mutated-induced colon tumors was associated with reduced expression of LGR5 and NANOG compared to wild-type KRAS and BRAF tumors. Analysis of various calcium regulator molecules revealed that while the calcium-transporting ATPase 4 (ATP2B4) is downregulated in all the Furin-silenced colon cancer cells, the Ca2+-mobilizing P2Y receptors, was specifically repressed in BRAF mutated cells and ORAI1 and CACNA1H in KRAS mutated cells. Taken together, our findings indicate that PCs play an important role in the malignant phenotype of colon CSCs and stem cell markers' expression and highlight PCs repression, particularly of Furin, to target colon tumors with KRAS or BRAF mutation.

Live imaging approach of dynamic multicellular responses in ERK signaling during vertebrate tissue development

The chemical and mechanical responses of cells via the exchange of information during growth and development result in the formation of biological tissues. Information processing within the cells through the signaling pathways and networks inherent to the constituent cells has been well-studied. However, the cell signaling mechanisms responsible for generating dynamic multicellular responses in developing tissues remain unclear. Here, I review the dynamic multicellular response systems during the development and growth of vertebrate tissues based on the extracellular signal-regulated kinase (ERK) pathway. First, an overview of the function of the ERK signaling network in cells is provided, followed by descriptions of biosensors essential for live imaging of the quantification of ERK activity in tissues. Then adducing four examples, I highlight the contribution of live imaging techniques for studying the involvement of spatio-temporal patterns of ERK activity change in tissue development and growth. In addition, theoretical implications of ERK signaling are also discussed from the viewpoint of dynamic systems. This review might help in understanding ERK-mediated dynamic multicellular responses and tissue morphogenesis.

Systematic analysis of noise reduction properties of coupled and isolated feed-forward loops

Cells can maintain their homeostasis in a noisy environment since their signaling pathways can filter out noise somehow. Several network motifs have been proposed for biological noise filtering and, among these, feed-forward loops have received special attention. Specific feed-forward loops show noise reducing capabilities, but we notice that this feature comes together with a reduced signal transducing performance. In posttranslational signaling pathways feed-forward loops do not function in isolation, rather they are coupled with other motifs to serve a more complex function. Feed-forward loops are often coupled to other feed-forward loops, which could affect their noise-reducing capabilities. Here we systematically study all feed-forward loop motifs and all their pairwise coupled systems with activation-inactivation kinetics to identify which networks are capable of good noise reduction, while keeping their signal transducing performance. Our analysis shows that coupled feed-forward loops can provide better noise reduction and, at the same time, can increase the signal transduction of the system. The coupling of two coherent 1 or one coherent 1 and one incoherent 4 feed-forward loops can give the best performance in both of these measures.

Cellular behavior can be affected by noise in molecular interactions. Signaling pathways should process noisy input signals and support cellular decision making by properly transducing the signals, while removing noise from them. Three component networks of feed-forward loops (FFLs) have been proposed to serve as ideal noise reducers, while linear pathways were shown to be good signal transducers. These signaling units do not work in isolation, so there is a possibility that a combination of various feed-forward loops can provide good noise reduction, while maintaining good signal transduction. To test this hypothesis, we have systematically tested the noise reducing and signal transducing capabilities of all possible combinations of feed-forward loops and compared them with the performance of individual FFLs. We built mathematical models of all these systems and compared their capabilities at reducing noise in the input signal while maintaining responses to meaningful changes in the incoming signal. We found that a combination of two copies of a special type of fully positive signaling FFLs is the best noise reducer, while a combination of two incoherent (one positive, one negative signal) FFLs can provide the best signal transduction. The combination of these two FFLs could provide good signal processing where both noise reduction and signal transduction are achieved.

Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance

Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines. By generating quantitative perturbation data and mathematical modelling, we determined potential resistance mechanisms. We found that negative feedbacks within MAPK signalling and via the IGF receptor mediate re-activation of MAPK signalling upon treatment in resistant cell lines. By using cell-line specific models, we predict that combinations of MEK inhibitors with RAF or IGFR inhibitors can overcome resistance, and tested these predictions experimentally. In addition, phospho-proteomic profiling confirmed the cell-specific feedback effects and synergy of MEK and IGFR targeted treatment. Our study shows that a quantitative understanding of signalling and feedback mechanisms facilitated by models can help to develop and optimise therapeutic strategies. Our findings should be considered for the planning of future clinical trials introducing MEKi in the treatment of neuroblastoma.

Mitogen-activated protein kinase activity drives cell trajectories in colorectal cancer

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define transcriptional states of colorectal cancer cells and signals controlling their development by performing single-cell transcriptome analysis of tumors and matched non-cancerous tissues of twelve colorectal cancer patients. We defined patient-overarching colorectal cancer cell clusters characterized by differential activities of oncogenic signaling pathways such as mitogen-activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient-derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen-activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR-BRAF-MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories. Our results highlight directional cancer cell development as a driver of non-genetic cancer cell heterogeneity and re-routing of trajectories as a response to targeted therapy.

Oncogenic mutant RAS signaling activity is rescaled by the ERK/MAPK pathway

Activating mutations in RAS are present in ~ 30% of human tumors, and the resulting aberrations in ERK/MAPK signaling play a central role in oncogenesis. However, the form of these signaling changes is uncertain, with activating RAS mutants linked to both increased and decreased ERK activation in vivo. Rationally targeting the kinase activity of this pathway requires clarification of the quantitative effects of RAS mutations. Here, we use live‐cell imaging in cells expressing only one RAS isoform to quantify ERK activity with a new level of accuracy. We find that despite large differences in their biochemical activity, mutant KRAS isoforms within cells have similar ranges of ERK output. We identify roles for pathway‐level effects, including variation in feedback strength and feedforward modulation of phosphatase activity, that act to rescale pathway sensitivity, ultimately resisting changes in the dynamic range of ERK activity while preserving responsiveness to growth factor stimuli. Our results reconcile seemingly inconsistent reports within the literature and imply that the signaling changes induced by RAS mutations early in oncogenesis are subtle.

Cytokine combinations for human blood stem cell expansion induce cell type- and cytokine-specific signaling dynamics

How hematopoietic stem cells (HSCs) integrate signals from their environment to make fate decisions remains incompletely understood. Current knowledge is based on either averages of heterogeneous populations or snapshot analyses, both missing important information about the dynamics of intracellular signaling activity. By combining fluorescent biosensors with time-lapse imaging and microfluidics, we measured the activity of the extracellular signal-regulated kinase (ERK) pathway over time (i.e. dynamics) in live single human umbilical cord blood HSCs and multipotent progenitor cells (MPPs). In single cells, ERK signaling dynamics were highly heterogeneous and depended on the cytokines, their combinations, and cell types. ERK signaling was activated by SCF and FLT3L in HSCs, but by SCF, IL3 and GCSF in MPPs. Different cytokines and their combinations led to distinct ERK signaling dynamics frequencies, and ERK dynamics in HSCs were more transient than those in MPPs. A combination of 5 cytokines recently shown to maintain HSCs in long-term culture, had a more-than-additive effect in eliciting sustained ERK dynamics in HSCs. ERK signaling dynamics also predicted future cell fates. E.g. CD45RA expression increased more in HSC daughters with intermediate than with transient or sustained ERK signaling. We demonstrate heterogeneous, cytokine- and cell type- specific ERK signaling dynamics, illustrating their relevance in regulating HSPC fates.

Disentangling Pro-mitotic Signaling during Cell Cycle Progression using Time-Resolved Single-Cell Imaging

Cells rely on input from extracellular growth factors to control their proliferation during development and adult homeostasis. Such mitogenic inputs are transmitted through multiple signaling pathways that synergize to precisely regulate cell cycle entry and progression. Although the architecture of these signaling networks has been characterized in molecular detail, their relative contribution, especially at later cell cycle stages, remains largely unexplored. By combining quantitative time-resolved measurements of fluorescent reporters in untransformed human cells with targeted pharmacological inhibitors and statistical analysis, we quantify epidermal growth factor (EGF)-induced signal processing in individual cells over time and dissect the dynamic contribution of downstream pathways. We define signaling features that encode information about extracellular ligand concentrations and critical time windows for inducing cell cycle transitions. We show that both extracellular signal-regulated kinase (ERK) and phosphatidylinositol 3-kinase (PI3K) activity are necessary for initial cell cycle entry, whereas only PI3K affects the duration of S phase at later stages of mitogenic signaling.

Drosophila RASopathy models identify disease subtype differences and biomarkers of drug efficacy

RASopathies represent a family of mostly autosomal dominant diseases that are caused by missense variants in the rat sarcoma viral oncogene/mitogen activated protein kinase (RAS/MAPK) pathway including KRAS, NRAS, BRAF, RAF1, and SHP2. These variants are associated with overlapping but distinct phenotypes that affect the heart, craniofacial, skeletal, lymphatic, and nervous systems. Here, we report an analysis of 13 Drosophila transgenic lines, each expressing a different human RASopathy isoform. Similar to their human counterparts, each Drosophila line displayed common aspects but also important differences including distinct signaling pathways such as the Hippo and SAPK/JNK signaling networks. We identified multiple classes of clinically relevant drugs-including statins and histone deacetylase inhibitors-that improved viability across most RASopathy lines; in contrast, several canonical RAS pathway inhibitors proved less broadly effective. Overall, our study compares and contrasts a large number of RASopathy-associated variants including their therapeutic responses.

Identification of X-chromosomal genes that drive sex differences in embryonic stem cells through a hierarchical CRISPR screening approach

BACKGROUND

X-chromosomal genes contribute to sex differences, in particular during early development, when both X chromosomes are active in females. Double X-dosage shifts female pluripotent cells towards the naive stem cell state by increasing pluripotency factor expression, inhibiting the differentiation-promoting MAP kinase (MAPK) signaling pathway, and delaying differentiation.

RESULTS

To identify the genetic basis of these sex differences, we use a two-step CRISPR screening approach to comprehensively identify X-linked genes that cause the female pluripotency phenotype in murine embryonic stem cells. A primary chromosome-wide CRISPR knockout screen and three secondary screens assaying for different aspects of the female pluripotency phenotype allow us to uncover multiple genes that act in concert and to disentangle their relative roles. Among them, we identify Dusp9 and Klhl13 as two central players. While Dusp9 mainly affects MAPK pathway intermediates, Klhl13 promotes pluripotency factor expression and delays differentiation, with both factors jointly repressing MAPK target gene expression.

CONCLUSIONS

Here, we elucidate the mechanisms that drive sex-induced differences in pluripotent cells and our approach serves as a blueprint to discover the genetic basis of the phenotypic consequences of other chromosomal effects.

Model-based robustness and bistability analysis for methylation-based, epigenetic memory systems

In recent years, epigenetic memory systems have been developed based on DNA methylation and positive feedback systems. Achieving a robust design for these systems is generally a challenging and multifactorial task. We developed and validated a novel mathematical model to describe methylation-based epigenetic memory systems that capture switching dynamics of methylation levels and methyltransferase amounts induced by different inputs. A bifurcation analysis shows that the system operates in the bistable range, but in its current setup is not robust to changes in parameters. An expansion of the model captures heterogeneity of cell populations by accounting for distributed cell division rates. Simulations predict that the system is highly sensitive to variations in temperature, which affects cell division and the efficiency of the zinc finger repressor. A moderate decrease in temperature leads to a highly heterogeneous response to input signals and bistability on a single-cell level. The predictions of our model were confirmed by flow cytometry experiments conducted in this study. Overall, the results of our study give insights into the functional mechanisms of methylation-based memory systems and demonstrate that the switching dynamics can be highly sensitive to experimental conditions.

Research progress of MEK1/2 inhibitors and degraders in the treatment of cancer

Mitogen-activated protein kinase kinases 1 and 2 (MEK1/2) are the crucial part of the RAS-RAF-MEK-ERK pathway (or ERK pathway), which is involved in the regulation of various cellular processes including proliferation, survival, and differentiation et al. Targeting MEK has become an important strategy for cancer therapy, and 4 MEK inhibitors (MEKis) have been approved by FDA to date. However, the application of MEKis is limited due to acquired resistance under long-term treatment. Fortunately, an emerging technology, named proteolysis targeting chimera (PROTAC), could break through this limitation by inducing MEK1/2 degradation. Compared to MEKis, MEK1/2 PROTAC is rarely studied and only three MEK1/2 PROTAC molecules, have been reported until now. This paper will outline the ERK pathway and the mechanism and research progress of MEK1/2 inhibitors, but focus on the development of MEK degraders and their optimization strategies. PAC-1 strategy which can induce MEK degradation indirectly, other PROTACs on ERK pathway, the advantages and challenges of PROTAC technology will be subsequently discussed.

New advances in the clinical management of RAS and BRAF mutant colorectal cancer patients

INTRODUCTION

In colorectal carcinogenesis, genetic alterations in RAS and BRAF oncogenes play an important role for cancer initiation and/or progression and represent a key focus in the search for targeted therapies. Despite many years of research and a great amount of studies, until very recently this pathway was considered extremely hard to downregulate to obtain a significant clinical impact in colorectal cancer patients. But better times are coming with the advent of new promising drugs and combinations strategies.

AREAS COVERED

In this review, we go over the biological characteristics of the MAPK pathway in colorectal tumors, while illustrating the clinical correlation of RAS and BRAF mutations, particularly its prognostic and predictive value. We also present newly data about recent improvements in the treatment strategy for patients harboring these types of tumors.

EXPERT COMMENTARY

With great advances in the knowledge of molecular basis of RAS and BRAF mutant colorectal cancer in conjunction with biotechnology development and the constant effort for improvement, in the near future many new therapeutic options would be available for the management of this group of patient with dismal prognosis.

RET Receptor Tyrosine Kinase: Role in Neurodegeneration, Obesity, and Cancer

Rearranged during transfection (RET) is the tyrosine kinase receptor that under normal circumstances interacts with ligand at the cell surface and mediates various essential roles in a variety of cellular processes such as proliferation, differentiation, survival, migration, and metabolism. RET plays a pivotal role in the development of both peripheral and central nervous systems. RET is expressed from early stages of embryogenesis and remains expressed throughout all life stages. Mutations either activating or inhibiting RET result in several aggressive diseases, namely cancer and Hirschsprung disease. However, the physiological ligand-dependent activation of RET receptor is important for the survival and maintenance of several neuronal populations, appetite, and weight gain control, thus providing an opportunity for the development of disease-modifying therapeutics against neurodegeneration and obesity. In this review, we describe the structure of RET, its signaling, and its role in both normal conditions as well as in several disorders. We highlight the differences in the signaling and outcomes of constitutive and ligand-induced RET activation. Finally, we review the data on recently developed small molecular weight RET agonists and their potential for the treatment of various diseases.

Identifiability and experimental design in perturbation studies

MOTIVATION

A common strategy to infer and quantify interactions between components of a biological system is to deduce them from the network's response to targeted perturbations. Such perturbation experiments are often challenging and costly. Therefore, optimizing the experimental design is essential to achieve a meaningful characterization of biological networks. However, it remains difficult to predict which combination of perturbations allows to infer specific interaction strengths in a given network topology. Yet, such a description of identifiability is necessary to select perturbations that maximize the number of inferable parameters.

RESULTS

We show analytically that the identifiability of network parameters can be determined by an intuitive maximum-flow problem. Furthermore, we used the theory of matroids to describe identifiability relationships between sets of parameters in order to build identifiable effective network models. Collectively, these results allowed to device strategies for an optimal design of the perturbation experiments. We benchmarked these strategies on a database of human pathways. Remarkably, full network identifiability was achieved, on average, with less than a third of the perturbations that are needed in a random experimental design. Moreover, we determined perturbation combinations that additionally decreased experimental effort compared to single-target perturbations. In summary, we provide a framework that allows to infer a maximal number of interaction strengths with a minimal number of perturbation experiments.

AVAILABILITY AND IMPLEMENTATION

IdentiFlow is available at github.com/GrossTor/IdentiFlow.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Robust network inference using response logic

Motivation

A major challenge in molecular and cellular biology is to map out the regulatory networks of cells. As regulatory interactions can typically not be directly observed experimentally, various computational methods have been proposed to disentangling direct and indirect effects. Most of these rely on assumptions that are rarely met or cannot be adapted to a given context.

Results

We present a network inference method that is based on a simple response logic with minimal presumptions. It requires that we can experimentally observe whether or not some of the system’s components respond to perturbations of some other components, and then identifies the directed networks that most accurately account for the observed propagation of the signal. To cope with the intractable number of possible networks, we developed a logic programming approach that can infer networks of hundreds of nodes, while being robust to noisy, heterogeneous or missing data. This allows to directly integrate prior network knowledge and additional constraints such as sparsity. We systematically benchmark our method on KEGG pathways, and show that it outperforms existing approaches in DREAM3 and DREAM4 challenges. Applied to a novel perturbation dataset on PI3K and MAPK pathways in isogenic models of a colon cancer cell line, it generates plausible network hypotheses that explain distinct sensitivities toward various targeted inhibitors due to different PI3K mutants.

Availability and implementation

A Python/Answer Set Programming implementation can be accessed at github.com/GrossTor/response-logic. Data and analysis scripts are available at github.com/GrossTor/response-logic-projects.

Supplementary information

Supplementary data are available at Bioinformatics online.

RAF dimer inhibition enhances the antitumor activity of MEK inhibitors in K-RAS mutant tumors

The mutation of K‐RAS represents one of the most frequent genetic alterations in cancer. Targeting of downstream effectors of RAS, including of MEK and ERK, has limited clinical success in cancer patients with K‐RAS mutations. The reduced sensitivity of K‐RAS‐mutated cells to certain MEK inhibitors (MEKi) is associated with the feedback phosphorylation of MEK by C‐RAF and with the reactivation of mitogen‐activated protein kinase (MAPK) signaling. Here, we report that the RAF dimer inhibitors lifirafenib (BGB‐283) and compound C show a strong synergistic effect with MEKi, including mirdametinib (PD‐0325901) and selumetinib, in suppressing the proliferation of K‐RAS‐mutated non‐small‐cell lung cancer and colorectal cancer (CRC) cell lines. This synergistic effect was not observed with the B‐RAF^V600E selective inhibitor vemurafenib. Our mechanistic analysis revealed that RAF dimer inhibition suppresses RAF‐dependent MEK reactivation and leads to the sustained inhibition of MAPK signaling in K‐RAS‐mutated cells. This synergistic effect was also observed in several K‐RAS mutant mouse xenograft models. A pharmacodynamic analysis supported a role for the synergistic phospho‐ERK blockade in enhancing the antitumor activity observed in the K‐RAS mutant models. These findings support a vertical inhibition strategy in which RAF dimer and MEKi are combined to target K‐RAS‐mutated cancers, and have led to a Phase 1b/2 combination therapy study of lifirafenib and mirdametinib in solid tumor patients with K‐RAS mutations and other MAPK pathway aberrations.

Activation of Steroidogenesis, Anti-Apoptotic Activity, and Proliferation in Porcine Granulosa Cells by RUNX1 Is Negatively Regulated by H3K27me3 Transcriptional Repression

H3K27me3 is an epigenetic modification that results in the repression of gene transcription. The transcription factor RUNX1 (the runt-related transcription factor 1) influences granulosa cells' growth and ovulation. This research uses ELISA, flow cytometry, EDU, ChIP-PCR, WB and qPCR to investigate steroidogenesis, cell apoptosis, and the proliferation effect of RUNX1 in porcine granulosa cells (pGCs) as regulated by H3K27me3. Decreased H3K27me3 stimulates the expression of steroidogenesis-related genes, including CYP11A1, PTGS2, and STAR, as well as prostaglandin. H3K27me3 transcriptionally represses RUNX1 here, whereas RUNX1 acts as an activator of FSHR, CYP11A1, and CYP19A1, promoting the production of androgen, estrogen, and prostaglandin, as well as increasing anti-apoptotic and cell proliferation activity, but decreasing progesterone. Both the complementary recovery of the H3K27me3 antagonist with the siRUNX1 signal, and the H3K27me3 agonist with the RUNX1 signal to maintain RUNX1 lead to the activation of CYP19A1, ER1, HSD17β4, and STAR here. Androgen and prostaglandin are significantly repressed but progesterone is markedly increased with the antagonist and siRUNX1. Prostaglandin is significantly promoted with the agonist and RUNX1. Furthermore, H3K27me3-RUNX1 affects the anti-apoptotic activity and stimulation of proliferation in pGCs. The present work verifies the transcriptional suppression of RUNX1 by H3K27me3 during antral follicular development and maturation, which determines the levels of hormone synthesis and cell apoptosis and proliferation in the pGC microenvironment.

Mutations That Confer Drug-Resistance, Oncogenicity and Intrinsic Activity on the ERK MAP Kinases-Current State of the Art

Unique characteristics distinguish extracellular signal-regulated kinases (Erks) from other eukaryotic protein kinases (ePKs). Unlike most ePKs, Erks do not autoactivate and they manifest no basal activity; they become catalysts only when dually phosphorylated on neighboring Thr and Tyr residues and they possess unique structural motifs. Erks function as the sole targets of the receptor tyrosine kinases (RTKs)-Ras-Raf-MEK signaling cascade, which controls numerous physiological processes and is mutated in most cancers. Erks are therefore the executers of the pathway’s biology and pathology. As oncogenic mutations have not been identified in Erks themselves, combined with the tight regulation of their activity, Erks have been considered immune against mutations that would render them intrinsically active. Nevertheless, several such mutations have been generated on the basis of structure-function analysis, understanding of ePK evolution and, mostly, via genetic screens in lower eukaryotes. One of the mutations conferred oncogenic properties on Erk1. The number of interesting mutations in Erks has dramatically increased following the development of Erk-specific pharmacological inhibitors and identification of mutations that cause resistance to these compounds. Several mutations have been recently identified in cancer patients. Here we summarize the mutations identified in Erks so far, describe their properties and discuss their possible mechanism of action.

Design, Synthesis, and Biological Evaluation of MEK PROTACs

PROteolysis TArgeting Chimeras (PROTACs) targeting the degradation of MEK have been designed based on allosteric MEK inhibitors. Inhibition of the phosphorylation of ERK1/2 was less effective with the PROTACs than a small-molecule inhibitor; the best PROTACs, however, were more effective in inhibiting proliferation of A375 cells than an inhibitor.

How the diversity of the faces arises

BACKGROUND

The evolution of the face is crucial for each species to adapt to different diets, environments, and in some species, to promote social interaction. The diversity in the shapes of the face results from divergence in the process of facial development that begins during early embryonic development.

HIGHLIGHTS

Here we review the recent advancements in the understanding of the genetic, epigenetic, molecular, and cellular basis of facial diversity. We also review the robustness of facial development and how it relates to the evolution of the face. Finally, we discuss the current challenges in achieving a deeper understanding of facial diversity.

CONCLUSION

We have gained much knowledge with respect to cis-regulatory elements, gene expression, cellular behavior, and the physical forces in facial development in the past two decades. Significant interdisciplinary work is needed to integrate these varied pieces of information into a complete picture of how the diversity of faces arises.

Network Topologies That Can Achieve Dual Function of Adaptation and Noise Attenuation

Many signaling systems execute adaptation under circumstances that require noise attenuation. Here, we identify an intrinsic trade-off existing between sensitivity and noise attenuation in the three-node networks. We demonstrate that although fine-tuning timescales in three-node adaptive networks can partially mediate this trade-off in this context, it prolongs adaptation time and imposes unrealistic parameter constraints. By contrast, four-node networks can effectively decouple adaptation and noise attenuation to achieve dual function without a trade-off, provided that these functions are executed sequentially. We illustrate ideas in seven biological examples, including Dictyostelium discoideum chemotaxis and the p53 signaling network and find that adaptive networks are often associated with a noise attenuation module. Our approach may be applicable to finding network design principles for other dual and multiple functions.

When More Is Less: Dual Phosphorylation Protects Signaling Off State against Overexpression

Kinases in signaling pathways are commonly activated by multisite phosphorylation. For example, the mitogen-activated protein kinase Erk is activated by its kinase Mek by two consecutive phosphorylations within its activation loop. In this article, we use kinetic models to study how the activation of Erk is coupled to its abundance. Intuitively, Erk activity should rise with increasing amounts of Erk protein. However, a mathematical model shows that the signaling off state is robust to increasing amounts of Erk, and Erk activity may even decline with increasing amounts of Erk. This counterintuitive, bell-shaped response of Erk activity to increasing amounts of Erk arises from the competition of the unmodified and single phosphorylated form of Erk for access to its kinase Mek. This shows that phosphorylation cycles can contain an intrinsic robustness mechanism that protects signaling from aberrant activation e.g., by gene expression noise or kinase overexpression after gene duplication events in diseases like cancer.

Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.

Protein-Protein Interactions: Emerging Oncotargets in the RAS-ERK Pathway

Given the implication of aberrant RAS-extracellular signal-regulated kinase (ERK) signaling in the development of a large number of tumor types, this route is under intense scrutiny to identify new anticancer drugs. Most avenues in that direction have been primarily focused on the inhibition of the catalytic activity of the kinases that participate in this pathway. Although promising, the efficacy of these therapies is short lived due to undesired toxicity and/or drug resistance problems. As an alternative path, new efforts are now being devoted to the targeting of protein-protein interactions (PPIs) involved in the flow of RAS-ERK signals. Many of these efforts have shown promising results in preclinical models. In this review, we summarize recent progress made in this area.