Systems-Level Properties of EGFR-RAS-ERK Signaling Amplify Local Signals to Generate Dynamic Gene Expression Heterogeneity

Oncogenic EML4-ALK assemblies suppress growth factor perception and modulate drug tolerance

Drug resistance remains a challenge for targeted therapy of cancers driven by EML4-ALK and related fusion oncogenes. EML4-ALK forms cytoplasmic protein condensates, which result from networks of interactions between oncogene and adapter protein multimers. While these assemblies are associated with oncogenic signaling, their role in drug response is unclear. Here, we use optogenetics and live-cell imaging to find that EML4-ALK assemblies suppress transmembrane receptor tyrosine kinase (RTK) signaling by sequestering RTK adapter proteins including GRB2 and SOS1. Furthermore, ALK inhibition, while suppressing oncogenic signaling, simultaneously releases the sequestered adapters and thereby resensitizes RTK signaling. Resensitized RTKs promote rapid and pulsatile ERK reactivation that originates from paracrine ligands shed by dying cells. Reactivated ERK signaling promotes cell survival, which can be counteracted by combination therapies that block paracrine signaling. Our results identify a regulatory role for RTK fusion assemblies and uncover a mechanism of tolerance to targeted therapies.

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.

Featurizing Koopman mode decomposition for robust forecasting

This article introduces an advanced Koopman mode decomposition (KMD) technique-coined Featurized Koopman Mode Decomposition (FKMD)-that uses delay embedding and a learned Mahalanobis distance to enhance analysis and prediction of high-dimensional dynamical systems. The delay embedding expands the observation space to better capture underlying manifold structures, while the Mahalanobis distance adjusts observations based on the system's dynamics. This aids in featurizing KMD in cases where good features are not a priori known. We show that FKMD improves predictions for a high-dimensional linear oscillator, a high-dimensional Lorenz attractor that is partially observed, and a cell signaling problem from cancer research.

Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change

Extracellular signals induce changes to molecular programs that modulate multiple cellular phenotypes, including proliferation, motility, and differentiation status. The connection between dynamically adapting phenotypic states and the molecular programs that define them is not well understood. Here we develop data-driven models of single-cell phenotypic responses to extracellular stimuli by linking gene transcription levels to "morphodynamics" - changes in cell morphology and motility observable in time-lapse image data. We adopt a dynamics-first view of cell state by grouping single-cell trajectories into states with shared morphodynamic responses. The single-cell trajectories enable development of a first-of-its-kind computational approach to map live-cell dynamics to snapshot gene transcript levels, which we term MMIST, Molecular and Morphodynamics-Integrated Single-cell Trajectories. The key conceptual advance of MMIST is that cell behavior can be quantified based on dynamically defined states and that extracellular signals alter the overall distribution of cell states by altering rates of switching between states. We find a cell state landscape that is bound by epithelial and mesenchymal endpoints, with distinct sequences of epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET) intermediates. The analysis yields predictions for gene expression changes consistent with curated EMT gene sets and provides a prediction of thousands of RNA transcripts through extracellular signal-induced EMT and MET with near-continuous time resolution. The MMIST framework leverages true single-cell dynamical behavior to generate molecular-level omics inferences and is broadly applicable to other biological domains, time-lapse imaging approaches and molecular snapshot data.

Stimulus-response signaling dynamics characterize macrophage polarization states

The functional state of cells is dependent on their microenvironmental context. Prior studies described how polarizing cytokines alter macrophage transcriptomes and epigenomes. Here, we characterized the functional responses of 6 differentially polarized macrophage populations by measuring the dynamics of transcription factor nuclear factor κB (NF-κB) in response to 8 stimuli. The resulting dataset of single-cell NF-κB trajectories was analyzed by three approaches: (1) machine learning on time-series data revealed losses of stimulus distinguishability with polarization, reflecting canalized effector functions. (2) Informative trajectory features driving stimulus distinguishability ("signaling codons") were identified and used for mapping a cell state landscape that could then locate macrophages conditioned by an unrelated condition. (3) Kinetic parameters, inferred using a mechanistic NF-κB network model, provided an alternative mapping of cell states and correctly predicted biochemical findings. Together, this work demonstrates that a single analyte's dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this paper's transparent peer review process is included in the supplemental information.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Blockade of the ADAM8-Fra-1 complex attenuates neuroinflammation by suppressing the Map3k4/MAPKs axis after spinal cord injury

BACKGROUND

Mechanical spinal cord injury (SCI) is a deteriorative neurological disorder, causing secondary neuroinflammation and neuropathy. ADAM8 is thought to be an extracellular metalloproteinase, which regulates proteolysis and cell adherence, but whether its intracellular region is involved in regulating neuroinflammation in microglia after SCI is unclear.

METHODS

Using animal tissue RNA-Seq and clinical blood sample examinations, we found that a specific up-regulation of ADAM8 in microglia was associated with inflammation after SCI. In vitro, microglia stimulated by HMGB1, the tail region of ADAM8, promoted microglial inflammation, migration and proliferation by directly interacting with ERKs and Fra-1 to promote activation, then further activated Map3k4/JNKs/p38. Using SCI mice, we used BK-1361, a specific inhibitor of ADAM8, to treat these mice.

RESULTS

The results showed that administration of BK-1361 attenuated the level of neuroinflammation and reduced microglial activation and recruitment by inhibiting the ADAM8/Fra-1 axis. Furthermore, treatment with BK-1361 alleviated glial scar formation, and also preserved myelin and axonal structures. The locomotor recovery of SCI mice treated with BK-1361 was therefore better than those without treatment.

CONCLUSIONS

Taken together, the results showed that ADAM8 was a critical molecule, which positively regulated neuroinflammatory development and secondary pathogenesis by promoting microglial activation and migration. Mechanically, ADAM8 formed a complex with ERK and Fra-1 to further activate the Map3k4/JNK/p38 axis in microglia. Inhibition of ADAM8 by treatment with BK-1361 decreased the levels of neuroinflammation, glial formation, and neurohistological loss, leading to favorable improvement in locomotor functional recovery in SCI mice.

Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements

The Ras/ERK pathway drives cell proliferation and other oncogenic behaviors, and quantifying its activity in situ is of high interest in cancer diagnosis and therapy. Pathway activation is often assayed by measuring phosphorylated ERK. However, this form of measurement overlooks dynamic aspects of signaling that can only be observed over time. In this study, we combine a live, single-cell ERK biosensor approach with multiplexed immunofluorescence staining of downstream target proteins to ask how well immunostaining captures the dynamic history of ERK activity. Combining linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunostains, in which Fra-1 and pRb levels imply long term activation of ERK signaling, while Egr-1 and c-Myc indicate recent activation. We show that this framework can distinguish different classes of ERK dynamics within a heterogeneous population, providing a tool for annotating ERK dynamics within fixed tissues.

Host-derived growth factors drive ERK phosphorylation and MCL1 expression to promote osteosarcoma cell survival during metastatic lung colonization

PURPOSE

For patients with osteosarcoma, disease-related mortality most often results from lung metastasis-a phenomenon shared with many solid tumors. While established metastatic lesions behave aggressively, very few of the tumor cells that reach the lung will survive. By identifying mechanisms that facilitate survival of disseminated tumor cells, we can develop therapeutic strategies that prevent and treat metastasis.

METHODS

We analyzed single cell RNA-sequencing (scRNAseq) data from murine metastasis-bearing lungs to interrogate changes in both host and tumor cells during colonization. We used these data to elucidate pathways that become activated in cells that survive dissemination and identify candidate host-derived signals that drive activation. We validated these findings through live cell reporter systems, immunocytochemistry, and fluorescent immunohistochemistry. We then validated the functional relevance of key candidates using pharmacologic inhibition in models of metastatic osteosarcoma.

RESULTS

Expression patterns suggest that the MAPK pathway is significantly elevated in early and established metastases. MAPK activity correlates with expression of anti-apoptotic genes, especially MCL1. Niche cells produce growth factors that increase ERK phosphorylation and MCL1 expression in tumor cells. Both early and established metastases are vulnerable to MCL1 inhibition, but not MEK inhibition in vivo. Combining MCL1 inhibition with chemotherapy both prevented colonization and eliminated established metastases in murine models of osteosarcoma.

CONCLUSION

Niche-derived growth factors drive MAPK activity and MCL1 expression in osteosarcoma, promoting metastatic colonization. Although later metastases produce less MCL1, they remain dependent on it. MCL1 is a promising target for clinical trials in both human and canine patients.

A guide to ERK dynamics, part 2: downstream decoding

Signaling by the extracellular signal-regulated kinase (ERK) pathway controls many cellular processes, including cell division, death, and differentiation. In this second installment of a two-part review, we address the question of how the ERK pathway exerts distinct and context-specific effects on multiple processes. We discuss how the dynamics of ERK activity induce selective changes in gene expression programs, with insights from both experiments and computational models. With a focus on single-cell biosensor-based studies, we summarize four major functional modes for ERK signaling in tissues: adjusting the size of cell populations, gradient-based patterning, wave propagation of morphological changes, and diversification of cellular gene expression states. These modes of operation are disrupted in cancer and other related diseases and represent potential targets for therapeutic intervention. By understanding the dynamic mechanisms involved in ERK signaling, there is potential for pharmacological strategies that not only simply inhibit ERK, but also restore functional activity patterns and improve disease outcomes.

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.

Are physiological oscillations physiological?

Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to argue that oscillations play critical physiological roles, such as enabling systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic β-cells, glycolytic oscillations synchronize with calcium and mitochondrial oscillations to drive pulsatile insulin release, critical for liver regulation of glucose. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a re-thinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed in the clinic. A more dynamic approach will initiate a paradigm shift in our view of health and disease. A deeper look into the mechanisms that create, sustain and abolish oscillatory processes requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory. Nonlinear dynamics enables us to identify oscillatory ('pacemaking') mechanisms at the cellular, tissue and system levels.

Deciphering the roles of aryl hydrocarbon receptor (AHR) in regulating carcinogenesis

Aryl hydrocarbon receptor (AHR) is a ligand-dependent receptor that belongs to the superfamily of basic helix-loop-helix (bHLH) transcription factors. The activation of the canonical AHR signaling pathway is known to induce the expression of cytochrome P450 enzymes, facilitating the detoxification metabolism in the human body. Additionally, AHR could interact with various signaling pathways such as epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3), hypoxia-inducible factor-1α (HIF-1α), nuclear factor ekappa B (NF-κβ), estrogen receptor (ER), and androgen receptor (AR) signaling pathways. Over the past 30 years, several studies have reported that various chemical, physical, or biological agents, such as tobacco, hydrocarbon compounds, industrial and agricultural chemical wastes, drugs, UV, viruses, and other toxins, could affect AHR expression or activity, promoting cancer development. Thus, it is valuable to overview how these factors regulate AHR-mediated carcinogenesis. Current findings have reported that many compounds could act as AHR ligands to drive the expressions of AHR-target genes, such as CYP1A1, CYP1B1, MMPs, and AXL, and other targets that exert a pro-proliferation or anti-apoptotic effect, like XIAP. Furthermore, some other physical and chemical agents, such as UV and 3-methylcholanthrene, could promote AHR signaling activities, increasing the signaling activities of a few oncogenic pathways, such as the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways. Understanding how various factors regulate AHR-mediated carcinogenesis processes helps clinicians and scientists plan personalized therapeutic strategies to improve anti-cancer treatment efficacy. As many studies that have reported the roles of AHR in regulating carcinogenesis are preclinical or observational clinical studies that did not explore the detailed mechanisms of how different chemical, physical, or biological agents promote AHR-mediated carcinogenesis processes, future studies should focus on conducting large-scale and functional studies to unravel the underlying mechanism of how AHR interacts with different factors in regulating carcinogenesis processes.

Switching mechanism from AR to EGFR signaling via 3-O-sulfated heparan sulfate in castration-resistant prostate cancer

Androgen deprivation therapy is given to suppress prostate cancer growth; however, some cells continue to grow hormone-independently as castration-resistant prostate cancer (CRPC). Sulfated glycosaminoglycans promote ligand binding to receptors as co-receptors, but their role in CRPC remains unknown. Using the human prostate cancer cell line C4-2, which can proliferate in hormone-dependent and hormone-independent conditions, we found that epidermal growth factor (EGF)-activated EGFR-ERK1/2 signaling via 3-O-sulfated heparan sulfate (HS) produced by HS 3-O-sulfotransferase 1 (HS3ST1) is activated in C4-2 cells under hormone depletion. Knockdown of HS3ST1 in C4-2 cells suppressed hormone-independent growth, and inhibited both EGF binding to the cell surface and activation of EGFR-ERK1/2 signaling. Gefitinib, an EGFR inhibitor, significantly suppressed C4-2 cell proliferation and growth of a xenografted C4-2 tumor in castrated mouse. Collectively, our study has revealed a mechanism by which cancer cells switch to hormone-independent growth and identified the key regulator as 3-O-sulfated HS.

Autocrine activation of MAPK signaling mediates intrinsic tolerance to androgen deprivation in LY6D prostate cancer cells

The emergence of castration-resistant prostate cancer remains an area of unmet clinical need. We recently identified a subpopulation of normal prostate progenitor cells, characterized by an intrinsic resistance to androgen deprivation and expression of LY6D. We here demonstrate that conditional deletion of PTEN in the murine prostate epithelium causes an expansion of transformed LY6D+ progenitor cells without impairing stem cell properties. Transcriptomic analyses of LY6D+ luminal cells identified an autocrine positive feedback loop, based on the secretion of amphiregulin (AREG)-mediated activation of mitogen-activated protein kinase (MAPK) signaling, increasing cellular fitness and organoid formation. Pharmacological interference with this pathway overcomes the castration-resistant properties of LY6D+ cells with a suppression of organoid formation and loss of LY6D+ cells in vivo. Notably, LY6D+ tumor cells are enriched in high-grade and androgen-resistant prostate cancer, providing clinical evidence for their contribution to advanced disease. Our data indicate that early interference with MAPK inhibitors can prevent progression of castration-resistant prostate cancer.

Quantifying stimulus-response specificity to probe the functional state of macrophages

Immune sentinel macrophages initiate responses to pathogens via hundreds of immune response genes. Each immune threat demands a tailored response, suggesting that the capacity for stimulus-specific gene expression is a key functional hallmark of healthy macrophages. To quantify this property, termed "stimulus-response specificity" (SRS), we developed a single-cell experimental workflow and analytical approaches based on information theory and machine learning. We found that the response specificity of macrophages is driven by combinations of specific immune genes that show low cell-to-cell heterogeneity and are targets of separate signaling pathways. The "response specificity profile," a systematic comparison of multiple stimulus-response distributions, was distinctly altered by polarizing cytokines, and it enabled an assessment of the functional state of macrophages. Indeed, the response specificity profile of peritoneal macrophages from old and obese mice showed characteristic differences, suggesting that SRS may be a basis for measuring the functional state of innate immune cells. A record of this paper's transparent peer review process is included in the supplemental information.

Dynamic regulation of RAS and RAS signaling

RAS proteins regulate most aspects of cellular physiology. They are mutated in 30% of human cancers and 4% of developmental disorders termed Rasopathies. They cycle between active GTP-bound and inactive GDP-bound states. When active, they can interact with a wide range of effectors that control fundamental biochemical and biological processes. Emerging evidence suggests that RAS proteins are not simple on/off switches but sophisticated information processing devices that compute cell fate decisions by integrating external and internal cues. A critical component of this compute function is the dynamic regulation of RAS activation and downstream signaling that allows RAS to produce a rich and nuanced spectrum of biological outputs. We discuss recent findings how the dynamics of RAS and its downstream signaling is regulated. Starting from the structural and biochemical properties of wild-type and mutant RAS proteins and their activation cycle, we examine higher molecular assemblies, effector interactions and downstream signaling outputs, all under the aspect of dynamic regulation. We also consider how computational and mathematical modeling approaches contribute to analyze and understand the pleiotropic functions of RAS in health and disease.

Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response

Paracrine signaling is a fundamental process regulating tissue development, repair, and pathogenesis of diseases such as cancer. Herein we describe a method for quantitatively measuring paracrine signaling dynamics, and resultant gene expression changes, in living cells using genetically encoded signaling reporters and fluorescently tagged gene loci. We discuss considerations for selecting paracrine "sender-receiver" cell pairs, appropriate reporters, the use of this system to ask diverse experimental questions and screen drugs blocking intracellular communication, data collection, and the use of computational approaches to model and interpret these experiments.

Vitamin D and Systems Biology

The biological actions of the vitamin D receptor (VDR) have been investigated intensively for over 100 years and has led to the identification of significant insights into the repertoire of its biological actions. These were initially established to be centered on the regulation of calcium transport in the colon and deposition in bone. Beyond these well-known calcemic roles, other roles have emerged in the regulation of cell differentiation processes and have an impact on metabolism. The purpose of the current review is to consider where applying systems biology (SB) approaches may begin to generate a more precise understanding of where the VDR is, and is not, biologically impactful. Two SB approaches have been developed and begun to reveal insight into VDR biological functions. In a top-down SB approach genome-wide scale data are statistically analyzed, and from which a role for the VDR emerges in terms of being a hub in a biological network. Such approaches have confirmed significant roles, for example, in myeloid differentiation and the control of inflammation and innate immunity. In a bottom-up SB approach, current biological understanding is built into a kinetic model which is then applied to existing biological data to explain the function and identify unknown behavior. To date, this has not been applied to the VDR, but has to the related ERα and identified previously unknown mechanisms of control. One arena where applying top-down and bottom-up SB approaches may be informative is in the setting of prostate cancer health disparities.

ERK signaling dynamics: Lights, camera, transduction

Three-dimensional mammary epithelial acini are a model for understanding how microenvironment-driven signaling coordinates cell behavior and tissue morphogenesis. In this issue of Developmental Cell, Ender et al. use live-cell imaging to capture dynamic spatiotemporal patterns of ERK activity that instruct cell migration and survival fates in developing acini.

Cellular context alters EGF-induced ERK dynamics and reveals potential crosstalk with GDF-15

Cellular signaling dynamics are sensitive to differences in ligand identity, levels, and temporal patterns. These signaling patterns are also impacted by the larger context that the cell experiences (i.e., stimuli such as media formulation or substrate stiffness that are constant in an experiment exploring a particular variable but may differ between independent experiments which explore that variable) although the reason for different dynamics is not always obvious. Here, we compared extracellular-regulated kinase (ERK) signaling in response to epidermal growth factor treatment of human mammary epithelial cells cultures in either well culture or a microfluidic device. Using a single-cell ERK kinase translocation reporter, we observed extended ERK activation in well culture and only transient activity in microfluidic culture. The activity in microfluidic culture resembled that of the control condition, suggesting that shear stress led to the early activity and a loss of autocrine factors dampened extended signaling. Through experimental analysis we identified growth differentiation factor-15 as a candidate factor that led to extended ERK activation through a protein kinase C-α/β dependent pathway. Our results demonstrate that context impacts ERK dynamics and that comparison of distinct contexts can be used to elucidate new aspects of the cell signaling network.

AP-1 transcription factor network explains diverse patterns of cellular plasticity in melanoma cells

Cellular plasticity associated with fluctuations in transcriptional programs allows individual cells in a tumor to adopt heterogeneous differentiation states and switch phenotype during their adaptive responses to therapies. Despite increasing knowledge of such transcriptional programs, the molecular basis of cellular plasticity remains poorly understood. Here, we combine multiplexed transcriptional and protein measurements at population and single-cell levels with multivariate statistical modeling to show that the state of AP-1 transcription factor network plays a unifying role in explaining diverse patterns of plasticity in melanoma. We find that a regulated balance among AP-1 factors cJUN, JUND, FRA2, FRA1, and cFOS determines the intrinsic diversity of differentiation states and adaptive responses to MAPK inhibitors in melanoma cells. Perturbing this balance through genetic depletion of specific AP-1 proteins, or by MAPK inhibitors, shifts cellular heterogeneity in a predictable fashion. Thus, AP-1 may serve as a critical node for manipulating cellular plasticity with potential therapeutic implications.

Signalling dynamics, cell decisions, and homeostatic control in health and disease

Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.

MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY

A full understanding of cell signaling processes requires knowledge of protein structure/function relationships, protein-protein interactions, and the abilities of pathways to control phenotypes. Computational models offer a valuable framework for integrating that knowledge to predict the effects of system perturbations and interventions in health and disease. Whereas mechanistic models are well suited for understanding the biophysical basis for signal transduction and principles of therapeutic design, data-driven models are particularly suited to distill complex signaling relationships among samples and between multivariate signaling changes and phenotypes. Both approaches have limitations and provide incomplete representations of signaling biology, but their careful implementation and integration can provide new understanding for how manipulating system variables impacts cellular decisions.

Design and implementation of a microfluidic device capable of temporal growth factor delivery reveal filtering capabilities of the EGFR/ERK pathway

Utilizing microfluidics to mimic the dynamic temporal changes of growth factor and cytokine concentrations in vivo has greatly increased our understanding of how signal transduction pathways are structured to encode extracellular stimuli. To date, these devices have focused on delivering pulses of varying frequency, and there are limited cell culture models for delivering slowly increasing concentrations of stimuli that cells may experience in vivo. To examine this setting, we developed and validated a microfluidic device that can deliver increasing concentrations of growth factor over periods ranging from 6 to 24 h. Using this device and a fluorescent biosensor of extracellular-regulated kinase (ERK) activity, we delivered a slowly increasing concentration of epidermal growth factor (EGF) to human mammary epithelial cells and surprisingly observed minimal ERK activation, even at concentrations that stimulate robust activity in bolus delivery. The cells remained unresponsive to subsequent challenges with EGF, and immunocytochemistry suggested that the loss of an epidermal growth factor receptor was responsible. Cells were then challenged with faster rates of change of EGF, revealing an increased ERK activity as a function of rate of change. Specifically, both the fraction of cells that responded and the length of ERK activation time increased with the rate of change. This microfluidic device fills a gap in the current repertoire of in vitro microfluidic devices and demonstrates that slower, more physiological changes in growth factor presentation can reveal new regulatory mechanisms for how signal transduction pathways encode changes in the extracellular growth factor milieu.

NKX2-1 controls lung cancer progression by inducing DUSP6 to dampen ERK activity

The RAS→RAF→MEK→ERK pathway is hyperactivated in the majority of human lung adenocarcinoma (LUAD). However, the initial activating mutations induce homeostatic feedback mechanisms that limit ERK activity. How ERK activation reaches the tumor-promoting levels that overcome the feedback and drive malignant progression is unclear. We show here that the lung lineage transcription factor NKX2-1 suppresses ERK activity. In human tissue samples and cell lines, xenografts, and genetic mouse models, NKX2-1 induces the ERK phosphatase DUSP6, which inactivates ERK. In tumor cells from late-stage LUAD with silenced NKX2-1, re-introduction of NKX2-1 induces DUSP6 and inhibits tumor growth and metastasis. We show that DUSP6 is necessary for NKX2-1-mediated inhibition of tumor progression in vivo and that DUSP6 expression is sufficient to inhibit RAS-driven LUAD. Our results indicate that NKX2-1 silencing, and thereby DUSP6 downregulation, is a mechanism by which early LUAD can unleash ERK hyperactivation for tumor progression.

JARID1-targeted histone H3 demethylase inhibitors exhibit anti-proliferative activity and overcome cisplatin resistance in canine oral melanoma cell lines

Histone demethylases are overexpressed or display altered activity in numerous human cancers leading to alterations in cell cycle dynamics, DNA repair kinetics, and therapeutic resistance. Consequently, therapeutic targeting of histone demethylases has become an active and promising area of research in human oncology. However, the role of histone demethylases and the potential efficacy of demethylase inhibition in canine cancers remains largely unknown. In the present work, we addressed this knowledge gap by exploring the therapeutic potential of histone demethylase inhibitors (HDIs) in canine oral melanoma. Using canine melanoma cell lines, we determined that broad spectrum HDIs result in decreased cell survival and prolonged DNA damage repair kinetics. We then showed that JARID1B, a histone H3 demethylase implicated in proliferation-dormancy regulation and drug sensitivity in human cancers, is highly expressed in canine tumour tissues. HDIs targeting JARID1B, and related JARID1 family members, significantly reduced survival fractions in canine melanoma cell lines, but did not appear to modulate DNA damage repair kinetics like broad spectrum HDI treatments. Importantly, we found that the anti-proliferative effects of JARID1-targeted HDIs are preserved in cell lines resistant to platinum-based chemotherapeutics, suggesting that HDIs may serve as a viable therapeutic strategy when faced with oral melanomas that progress despite the use of conventional therapies.