Information Transfer in Gonadotropin-releasing Hormone (GnRH) Signaling: EXTRACELLULAR SIGNAL-REGULATED KINASE (ERK)-MEDIATED FEEDBACK LOOPS CONTROL HORMONE SENSING

Effects and action mechanism of gonadotropins on ovarian follicular cells: A novel role of Sphingosine-1-Phosphate (S1P). A review

Follicle-stimulating hormone (FSH) and luteinizing hormone (LH) control antral follicular growth by regulating several processes, such as the synthesis of hormones and signaling molecules, proliferation, survival, apoptosis, luteinization, and ovulation. To exert these effects, gonadotropins bind to their respective Gs protein-coupled receptors, activating the protein kinase A (PKA) pathway or recruiting Gq proteins to activate protein kinase C (PKC) signaling. Although the action mechanism of FSH and LH is clear, recently, it has been shown that both gonadotropins promote the synthesis of sphingosine-1-phosphate (S1P) in granulosa and theca cells through the activation of sphingosine kinase 1. Moreover, the inhibition of SPHKs reduces S1P synthesis, cell viability, and the proliferation of follicular cells in response to gonadotropins, and the addition of S1P to the culture medium increases the proliferation of granulosa and theca cells without apparent effects on sexual steroid synthesis. Therefore, we consider that S1P is a crucial signaling molecule that complements the canonical gonadotropin pathway to promote the proliferation and viability of granulosa and theca cells.

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information-theoretic framework to quantify the distribution of sensing abilities from single-cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an 'average cell'. We verify these predictions using live-cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells' sensing abilities. This information-theoretic framework will significantly improve our understanding of how cells sense in their environment.

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information theoretic framework to quantify the distribution of sensing abilities from single cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an " average cell ". We verify these predictions using live cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells' sensing abilities. This information theoretic framework will significantly improve our understanding of how cells sense in their environment.

Mathematical models in GnRH research

Mathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article provides an overview of the impact that mathematical models had on GnRH research. Indeed, over the last 20 years mathematical modelling has been used to describe and explore the physiology of the GnRH neuron, the mechanisms underlying GnRH pulsatile secretion, and GnRH signalling to the pituitary. Importantly, these models have contributed to GnRH research via novel hypotheses and predictions regarding the bursting behaviour of the GnRH neuron, the role of kisspeptin neurons in the emergence of pulsatile GnRH dynamics, and the decoding of GnRH signals by biochemical signalling networks. We envisage that with the advent of novel experimental technologies, mathematical modelling will have an even greater role to play in our endeavour to understand the complex spatiotemporal dynamics underlying the reproductive neuroendocrine system.

Phenotypic variability, not noise, accounts for most of the cell-to-cell heterogeneity in IFN-γ and oncostatin M signaling responses

Cellular signaling responses show substantial cell-to-cell heterogeneity, which is often ascribed to the inherent randomness of biochemical reactions, termed molecular noise, wherein high noise implies low signaling fidelity. Alternatively, heterogeneity could arise from differences in molecular content between cells, termed molecular phenotypic variability, which does not necessarily imply imprecise signaling. The contribution of these two processes to signaling heterogeneity is unclear. Here, we fused fibroblasts to produce binuclear syncytia to distinguish noise from phenotypic variability in the analysis of cytokine signaling. We reasoned that the responses of the two nuclei within one syncytium could approximate the signaling outcomes of two cells with the same molecular content, thereby disclosing noise contribution, whereas comparison of different syncytia should reveal contribution of phenotypic variability. We found that ~90% of the variance in the primary response (which was the abundance of phosphorylated, nuclear STAT) to stimulation with the cytokines interferon-γ and oncostatin M resulted from differences in the molecular content of individual cells. Thus, our data reveal that cytokine signaling in the system used here operates in a reproducible, high-fidelity manner.

The tyrosine phosphatase SHP2 increases robustness and information transfer within IL-6-induced JAK/STAT signalling

Background

Cell-to-cell heterogeneity is an inherent feature of multicellular organisms and is central in all physiological and pathophysiological processes including cellular signal transduction. The cytokine IL-6 is an essential mediator of pro- and anti-inflammatory processes. Dysregulated IL-6-induced intracellular JAK/STAT signalling is associated with severe inflammatory and proliferative diseases. Under physiological conditions JAK/STAT signalling is rigorously controlled and timely orchestrated by regulatory mechanisms such as expression of the feedback-inhibitor SOCS3 and activation of the protein-tyrosine phosphatase SHP2 (PTPN11). Interestingly, the function of negative regulators seems not to be restricted to controlling the strength and timely orchestration of IL-6-induced STAT3 activation. Exemplarily, SOCS3 increases robustness of late IL-6-induced STAT3 activation against heterogenous STAT3 expression and reduces the amount of information transferred through JAK/STAT signalling.

Methods

Here we use multiplexed single-cell analyses and information theoretic approaches to clarify whether also SHP2 contributes to robustness of STAT3 activation and whether SHP2 affects the amount of information transferred through IL-6-induced JAK/STAT signalling.

Results

SHP2 increases robustness of both basal, cytokine-independent STAT3 activation and early IL-6-induced STAT3 activation against differential STAT3 expression. However, SHP2 does not affect robustness of late IL-6-induced STAT3 activation. In contrast to SOCS3, SHP2 increases the amount of information transferred through IL-6-induced JAK/STAT signalling, probably by reducing cytokine-independent STAT3 activation and thereby increasing sensitivity of the cells. These effects are independent of SHP2-dependent MAPK activation.

Conclusion

In summary, the results of this study extend our knowledge of the functions of SHP2 in IL-6-induced JAK/STAT signalling. SHP2 is not only a repressor of basal and cytokine-induced STAT3 activity, but also ensures robustness and transmission of information.

Plain English summary Cells within a multicellular organism communicate with each other to exchange information about the environment. Communication between cells is facilitated by soluble molecules that transmit information from one cell to the other. Cytokines such as interleukin-6 are important soluble mediators that are secreted when an organism is faced with infections or inflammation. Secreted cytokines bind to receptors within the membrane of their target cells. This binding induces activation of an intracellular cascade of reactions called signal transduction, which leads to cellular responses. An important example of intracellular signal transduction is JAK/STAT signalling. In healthy organisms signalling is controlled and timed by regulatory mechanisms, whose activation results in a controlled shutdown of signalling pathways. Interestingly, not all cells within an organism are identical. They differ in the amount of proteins involved in signal transduction, such as STAT3. These differences shape cellular communication and responses to intracellular signalling. Here, we show that an important negative regulatory protein called SHP2 (or PTPN11) is not only responsible for shutting down signalling, but also for steering signalling in heterogeneous cell populations. SHP2 increases robustness of STAT3 activation against variable STAT3 amounts in individual cells. Additionally, it increases the amount of information transferred through JAK/STAT signalling by increasing the dynamic range of pathway activation in heterogeneous cell populations. This is an amazing new function of negative regulatory proteins that contributes to communication in heterogeneous multicellular organisms in health and disease.

Computational methods for characterizing and learning from heterogeneous cell signaling data

Heterogeneity in cell signaling pathways is increasingly appreciated as a fundamental feature of cell biology and a driver of clinically relevant disease phenotypes. Understanding the causes of heterogeneity, the cellular mechanisms used to control heterogeneity, and the downstream effects of heterogeneity in single cells are all key obstacles for manipulating cellular populations and treating disease. Recent advances in genetic engineering, including multiplexed fluorescent reporters, have provided unprecedented measurements of signaling heterogeneity, but these vast data sets are often difficult to interpret, necessitating the use of computational techniques to extract meaning from the data. Here, we review recent advances in computational methods for extracting meaning from these novel data streams. In particular, we evaluate how machine learning methods related to dimensionality reduction and classification can identify structure in complex, dynamic datasets, simplifying interpretation. We also discuss how mechanistic models can be merged with heterogeneous data to understand the underlying differences between cells in a population. These methods are still being developed, but the work reviewed here offers useful applications of specific analysis techniques that could enable the translation of single-cell signaling data to actionable biological understanding.

Single-Cell Information Analysis Reveals That Skeletal Muscles Incorporate Cell-to-Cell Variability as Information Not Noise

Cell-to-cell variability in signal transduction in biological systems is often considered noise. However, intercellular variation (i.e., cell-to-cell variability) has the potential to enable individual cells to encode different information. Here, we show that intercellular variation increases information transmission of skeletal muscle. We analyze the responses of multiple cultured myotubes or isolated skeletal muscle fibers as a multiple-cell channel composed of single-cell channels. We find that the multiple-cell channel, which incorporates intercellular variation as information, not noise, transmitted more information in the presence of intercellular variation than in the absence according to the "response diversity effect," increasing in the gradualness of dose response by summing the cell-to-cell variable dose responses. We quantify the information transmission of human facial muscle contraction during intraoperative neurophysiological monitoring and find that information transmission of muscle contraction is comparable to that of a multiple-cell channel. Thus, our data indicate that intercellular variation can increase the information capacity of tissues.

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.

An information theoretic approach to insulin sensing by human kidney podocytes

Podocytes are key components of the glomerular filtration barrier (GFB). They are insulin-responsive but can become insulin-resistant, causing features of the leading global cause of kidney failure, diabetic nephropathy. Insulin acts via insulin receptors to control activities fundamental to GFB integrity, but the amount of information transferred is unknown. Here we measure this in human podocytes, using information theory-derived statistics that take into account cell-cell variability. High content imaging was used to measure insulin effects on Akt, FOXO and ERK. Mutual Information (MI) and Channel Capacity (CC) were calculated as measures of information transfer. We find that insulin acts via noisy communication channels with more information flow to Akt than to ERK. Information flow estimates were increased by consideration of joint sensing (ERK and Akt) and response trajectory (live cell imaging of FOXO1-clover translocation). Nevertheless, MI values were always <1Bit as most information was lost through signaling. Constitutive PI3K activity is a predominant feature of the system that restricts the proportion of CC engaged by insulin. Negative feedback from Akt supressed this activity and thereby improved insulin sensing, whereas sensing was robust to manipulation of feedforward signaling by inhibiting PI3K, PTEN or PTP1B. The decisions made by individual podocytes dictate GFB integrity, so we suggest that understanding the information on which the decisions are based will improve understanding of diabetic kidney disease and its treatment.

Plasma kisspeptin levels in boys with hypogonadotropic delayed puberty

BACKGROUND

In hypogonadotropic forms of delayed puberty (DP), hypophyseal follicle-stimulating (FSH) and luteinizing (LH) hormones, normally released with GnRH stimulation, are detected low. Since kisspeptin (KP) is a strong stimulant of GnRH neurons, it is considered to have a role in DP etiology. It may be hypothesized that abnormal plasma levels of KP are indicative of DP. The study aimed at evaluation and comparison of plasma KP levels in boys of pre-pubertal age, with normal puberty and diagnosed primary hypogonadotropic forms of DP.

METHODS

The study comprised 22 boys with verified hypogonadotropic DP (age 14-17 years), 25 boys with normal puberty (age 14-17 years), and 28 pre-pubertal boys (age 6-9 years). Triprorelin stimulation test was performed in DP patients. Plasma KP values were compared between three groups.

RESULTS

Statistically significant difference was found for the overall distribution of the plasma KP values across different groups (Kruskal-Wallis H=21.95, P<0.001). The highest values were found in the DP group (median: 45.0 pg/mL). Median values in the pre-pubertal boys and in the normal pubertal adolescents were equal to 13.8 pg/mL. No statistically significant difference was found for plasma KP levels in the DP boys who had either positive or negative response to Triptorelin stimulation test. Plasma KP level exceeding 16.9 pg/mL was a reliable predictor of hypoganadotropic DP (sensitivity 72.7%, specificity 92.0%).

CONCLUSIONS

Plasma KP levels are elevated in hypogonadotropic DP cases and may serve as a useful diagnostic tool in evaluating boys with DP.

1,4-Dioxane exposure induces kidney damage in mice by perturbing specific renal metabolic pathways: An integrated omics insight into the underlying mechanisms

1,4-Dioxane (dioxane), an industrial solvent widely detected in environmental and biological matrices, has potential nephrotoxicity. However, the underlying mechanism by which dioxane induces kidney damage remains unclear. In this study, we used an integrated approach, combining kidney transcriptomics and urine metabolomics, to explore the mechanism for the toxic effects of dioxane on the mouse kidney. Transcriptomics profiling showed that exposure to 0.5 mg/L dioxane induced perturbations of multiple signaling pathways in kidneys, such as MAPK and Wnt, although no changes in oxidative stress indicators or anatomical pathology were observed. Exposure to 500 mg/L dioxane significantly disrupted various metabolic pathways, concomitantly with observed renal tissue damage and stimulated oxidant defense system. Urine metabolomic analysis using NMR indicated that exposure to dioxane gradually altered the metabolic profile of urine. Within the full range of altered metabolites, the metabolic pathway containing glycine, serine and threonine was the most significantly altered pathway at the early stage of exposure (3 weeks) in both 0.5 and 500 mg/L dioxane-treated groups. However, with prolonged exposure (9 and 12 weeks), the level of taurine significantly decreased after treatment of 0.5 mg/L dioxane, while exposure to 500 mg/L dioxane significantly increased glutathione levels in urine and decreased arginine metabolism. Furthermore, integrated omics analysis showed that 500 mg/L dioxane exposure induced arginine deficiency by perturbing several genes involved in renal arginine metabolism. Shortage of arginine coupled with increased oxidative stress could lead to renal dysfunction. These findings offer novel insights into the toxicity of dioxane.

Robustness and Information Transfer within IL-6-induced JAK/STAT Signalling

Cellular communication via intracellular signalling pathways is crucial. Expression and activation of signalling proteins is heterogenous between isogenic cells of the same cell-type. However, mechanisms evolved to enable sufficient communication and to ensure cellular functions. We use information theory to clarify mechanisms facilitating IL-6-induced JAK/STAT signalling despite cell-to-cell variability. We show that different mechanisms enabling robustness against variability complement each other. Early STAT3 activation is robust as long as cytokine concentrations are low. Robustness at high cytokine concentrations is ensured by high STAT3 expression or serine phosphorylation. Later the feedback-inhibitor SOCS3 increases robustness. Channel Capacity of JAK/STAT signalling is limited by cell-to-cell variability in STAT3 expression and is affected by the same mechanisms governing robustness. Increasing STAT3 amount increases Channel Capacity and robustness, whereas increasing STAT3 tyrosine phosphorylation reduces robustness but increases Channel Capacity. In summary, we elucidate mechanisms preventing dysregulated signalling by enabling reliable JAK/STAT signalling despite cell-to-cell heterogeneity.

The role of mitogen-activated protein kinase-extracellular receptor kinase pathway in female fertility outcomes: a focus on pituitary gonadotropins regulation

Mammalian reproduction systems are largely regulated by the secretion of two gonadotropins, that is, luteinizing hormone (LH) and follicle-stimulating hormone (FSH). The main action of LH and FSH on the ovary is to stimulate secretion of estradiol and progesterone, which play an important role in the ovarian function and reproductive cycle control. FSH and LH secretions are strictly controlled by the gonadotropin-releasing hormone (GnRH), which is secreted from the hypothalamus into the pituitary vascular system. Maintaining normal secretion of LH and FSH is dependent on pulsatile secretion of GnRH. Extracellular signal-regulated kinase (ERK) proteins, as the main components of mitogen-activated protein kinase (MAPK) signaling pathways, are involved in the primary regulation of GnRH-stimulated transcription of the gonadotropins' α subunit in the pituitary cells. However, GnRH-stimulated expression of the β subunit has not yet been reported. Furthermore, GnRH-mediated stimulation of ERK1 and ERK2 leads to several important events such as cell proliferation and differentiation. In this review, we briefly introduce the relationship between ERK signaling and gonadotropin secretion, and its importance in female infertility.

Comparative aspects of GnRH-Stimulated signal transduction in the vertebrate pituitary - Contributions from teleost model systems

Gonadotropin-releasing hormone (GnRH) is a major regulator of reproduction through actions on pituitary gonadotropin release and synthesis. Although it is often thought that pituitary cells are exposed to only one GnRH, multiple GnRH forms are delivered to the pituitary of teleost fishes; interestingly this can include the cGnRH-II form usually thought to be non-hypophysiotropic. GnRHs can regulate other pituitary cell-types, both directly as well as indirectly, and multiple GnRH receptors (GnRHRs) may also be expressed in the pituitary, and even within a single pituitary cell-type. Literature on the differential actions of native GnRH isoforms in primary pituitary cells is largely derived from teleost fishes. This review will outline the diversity and complexity of GnRH-GnRHR signal transduction found within vertebrate gonadotropes as well as extra-gonadotropic sites with special emphasis on comparative studies from fish models. The implications that GnRHR transduction mechanisms are GnRH isoform-, function-, and cell-specific are also discussed.

Gonadotropin-releasing hormone signaling: An information theoretic approach

Gonadotropin-releasing hormone (GnRH) is a peptide hormone that mediates central control of reproduction, acting via G-protein coupled receptors that are primarily G_q coupled and mediate GnRH effects on the synthesis and secretion of luteinizing hormone and follicle-stimulating hormone. A great deal is known about the GnRH receptor signaling network but GnRH is secreted in short pulses and much less is known about how gonadotropes decode this pulsatile signal. Similarly, single cell measures reveal considerable cell-cell heterogeneity in responses to GnRH but the impact of this variability on signaling is largely unknown. Ordinary differential equation-based mathematical models have been used to explore the decoding of pulse dynamics and information theory-derived statistical measures are increasingly used to address the influence of cell-cell variability on the amount of information transferred by signaling pathways. Here, we describe both approaches for GnRH signaling, with emphasis on novel insights gained from the information theoretic approach and on the fundamental question of why GnRH is secreted in pulses.

Enhanced insulin receptor, but not PI3K, signalling protects podocytes from ER stress

Disruption of the insulin-PI3K-Akt signalling pathway in kidney podocytes causes endoplasmic reticulum (ER) stress, leading to podocyte apoptosis and proteinuria in diabetic nephropathy. We hypothesised that by improving insulin sensitivity we could protect podocytes from ER stress. Here we use established activating transcription factor 6 (ATF6)- and ER stress element (ERSE)-luciferase assays alongside a novel high throughput imaging-based C/EBP homologous protein (CHOP) assay to examine three models of improved insulin sensitivity. We find that by improving insulin sensitivity at the level of the insulin receptor (IR), either by IR over-expression or by knocking down the negative regulator of IR activity, protein tyrosine-phosphatase 1B (PTP1B), podocytes are protected from ER stress caused by fatty acids or diabetic media containing high glucose, high insulin and inflammatory cytokines TNFα and IL-6. However, contrary to this, knockdown of the negative regulator of PI3K-Akt signalling, phosphatase and tensin homolog deleted from chromosome 10 (PTEN), sensitizes podocytes to ER stress and apoptosis, despite increasing Akt phosphorylation. This indicates that protection from ER stress is conferred through not just the PI3K-Akt pathway, and indeed we find that inhibiting the MEK/ERK signalling pathway rescues PTEN knockdown podocytes from ER stress.

Induction of Stress Signaling In Vitro and Suppression of Gonadotropin Secretion by Free Fatty Acids in Female Mouse Gonadotropes

An emerging body of evidence supports the concept that the pituitary is a site for integration of multiple physiological and metabolic signals that inform and modulate endocrine pathways. Multiple endocrine mediators of energy balance and adiposity are known to impinge on the neuroendocrine axis regulating reproduction. Observations in humans show that obesity is correlated with decreased gonadotropin secretion, and studies have also suggested that pituitary sensitivity to stimulation by gonadotropin-releasing hormone (GnRH) is decreased in obese individuals. Free fatty acids are a potential mediator of adiposity and energy balance, but their impact as an endocrine modulator of pituitary function has not been closely examined. We evaluated the impact of free fatty acids on a pituitary gonadotrope cell line and in primary pituitary cultures of female mice. We show that increasing physiologically relevant doses of the monounsaturated ω-9 fatty acid oleate induces cellular stress and increases production of reactive oxygen species in a mouse gonadotrope cell line. In contrast, the unsaturated ω-3 α-linolenic and ω-6 linoleic fatty acids do not have this effect. Additionally, oleate can activate immediate-early gene expression independent of GnRH stimulation but has a negative impact on GnRH induction and expression of the gonadotropin subunit gene Lhb. Further, oleate suppresses gonadotropin secretion in response to pulsatile stimulation by GnRH. These results indicate that free fatty acids can directly alter gonadotropin gene expression and secretion in response to GnRH and may provide a link between energy sensing and reproduction.

Exploring Dynamics and Noise in Gonadotropin-Releasing Hormone (GnRH) Signaling

Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes. These are G_q-coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. FSH and LH control steroidogenesis and gametogenesis in the gonads so GnRH mediates control of reproduction by the central nervous system. GnRH is secreted in short pulses and the effects of GnRH on its target cells are dependent on the dynamics of these pulses. Here we provide a brief overview of the signaling network activated by GnRH with emphasis on the use of high content imaging for their examination. We also describe computational approaches that we have used to simulate GnRH signaling in order to explore dynamics, noise, and information transfer in this system.

Combined targeting of Raf and Mek synergistically inhibits tumorigenesis in triple negative breast cancer model systems

Aberrant Ras-MAPK signaling from receptor tyrosine kinases (RTKs), including epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor-2 (HER2), is a hallmark of triple negative breast cancer (TNBC); thus providing rationale for targeting the Ras-MAPK pathway. Components of this EGFR/HER2-Ras-Raf-Mek-Erk pathway were co-targeted in the MDA-MB-231 and MDA-MB-468 human TNBC cell lines, and in vitro effects on signaling and cytotoxicity, as well as in vivo effects on xenograft tumor growth and metastasis were assessed. The dual EGFR/HER2 inhibitor lapatinib (LPN) displayed greater cytotoxic potency and MAPK signaling inhibition than the EGFR inhibitor erlotinib, suggesting both EGFR and HER2 contribute to MAPK signaling in this TNBC model. The Raf inhibitor sorafenib (SFN) or the Mek inhibitor U0126 suppressed MAPK signaling to a greater extent than LPN; which correlated with greater cytotoxic potency of SFN, but not U0126. However, U0126 potentiated the cytotoxic efficacy of LPN and SFN in an additive and synergistic manner, respectively. This in-series Raf-Mek co-targeting synergy was recapitulated in orthotopic mouse xenografts, where SFN and the Mek inhibitor selumitinib (AZD6244) inhibited primary tumor growth and pulmonary metastasis. Raf and Mek co-inhibition exhibits synergy in TNBC models and represent a promising combination therapy for this aggressive breast cancer type.

Mathematical modeling of gonadotropin-releasing hormone signaling

Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control reproduction. These are G_q-coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field.

Information Transfer via Gonadotropin-Releasing Hormone Receptors to ERK and NFAT: Sensing GnRH and Sensing Dynamics

Information theoretic approaches can be used to quantify information transfer via cell signaling networks. In this study, we do so for gonadotropin-releasing hormone (GnRH) activation of extracellular signal-regulated kinase (ERK) and nuclear factor of activated T cells (NFAT) in large numbers of individual fixed LβT2 and HeLa cells. Information transfer, measured by mutual information between GnRH and ERK or NFAT, was <1 bit (despite 3-bit system inputs). It was increased by sensing both ERK and NFAT, but the increase was <50%. In live cells, information transfer via GnRH receptors to NFAT was also <1 bit and was increased by consideration of response trajectory, but the increase was <10%. GnRH secretion is pulsatile, so we explored information gained by sensing a second pulse, developing a model of GnRH signaling to NFAT with variability introduced by allowing effectors to fluctuate. Simulations revealed that when cell–cell variability reflects rapidly fluctuating effector levels, additional information is gained by sensing two GnRH pulses, but where it is due to slowly fluctuating effectors, responses in one pulse are predictive of those in another, so little information is gained from sensing both. Wet laboratory experiments revealed that the latter scenario holds true for GnRH signaling; within the timescale of our experiments (1 to 2 hours), cell–cell variability in the NFAT pathway remains relatively constant, so trajectories are reproducible from pulse to pulse. Accordingly, joint sensing, sensing of response trajectories, and sensing of repeated pulses can all increase information transfer via GnRH receptors, but in each case the increase is small.

Reactive Oxygen Species Link Gonadotropin-Releasing Hormone Receptor Signaling Cascades in the Gonadotrope

Biological rhythms lie at the center of regulatory schemes that control many aspects of living systems. At the cellular level, meaningful responses to external stimuli depend on propagation and quenching of a signal to maintain vigilance for subsequent stimulation or changes that serve to shape and modulate the response. The hypothalamus-pituitary-gonad endocrine axis that controls reproductive development and function relies on control through rhythmic stimulation. Central to this axis is the pulsatile stimulation of the gonadotropes by hypothalamic neurons through episodic release of the neuropeptide gonadotropin-releasing hormone. Alterations in pulsatile stimulation of the gonadotropes result in differential synthesis and secretion of the gonadotropins LH and FSH and changes in the expression of their respective hormone subunit genes. The requirement to amplify signals arising from activation of the gonadotropin-releasing hormone (GnRH) receptor and to rapidly quench the resultant signal to preserve an adaptive response suggests the need for rapid activation and feedback control operating at the level of intracellular signaling. Emerging data suggest that reactive oxygen species (ROS) can fulfill this role in the GnRH receptor signaling through activation of MAP kinase signaling cascades, control of negative feedback, and participation in the secretory process. Results obtained in gonadotrope cell lines or other cell models indicate that ROS can participate in each of these regulatory cascades. We discuss the potential advantage of reactive oxygen signaling for modulating the gonadotrope response to GnRH stimulation and the potential mechanisms for this action. These observations suggest further targets of study for regulation in the gonadotrope.

Exploring 3D structure of human gonadotropin hormone receptor at antagonist state using homology modeling, molecular dynamic simulation, and cross-docking studies

Human gonadotropin hormone receptor, a G-protein coupled receptor, is the target of many medications used in fertility disorders. Obtaining more structural information about the receptor could be useful in many studies related to drug design. In this study, the structure of human gonadotropin receptor was subjected to homology modeling studies and molecular dynamic simulation within a DPPC lipid bilayer for 100 ns. Several frames were thereafter extracted from simulation trajectories representing the receptor at different states. In order to find a proper model of the receptor at the antagonist state, all frames were subjected to cross-docking studies of some antagonists with known experimental values (Ki). Frame 194 revealed a reasonable correlation between docking calculated energy scores and experimental activity values (|r| = 0.91). The obtained correlation was validated by means of SSLR and showed the presence of no chance correlation for the obtained model. Different structural features reported for the receptor, such as two disulfide bridges and ionic lock between GLU90 and LYS 121 were also investigated in the final model.