Multidimensional Single-Cell Analysis of BCR Signaling Reveals Proximal Activation Defect As a Hallmark of Chronic Lymphocytic Leukemia B Cells

Purpose

Chronic Lymphocytic Leukemia (CLL) is defined by a perturbed B-cell receptor-mediated signaling machinery. We aimed to model differential signaling behavior between B cells from CLL and healthy individuals to pinpoint modes of dysregulation.

Experimental Design

We developed an experimental methodology combining immunophenotyping, multiplexed phosphospecific flow cytometry, and multifactorial statistical modeling. Utilizing patterns of signaling network covariance, we modeled BCR signaling in 67 CLL patients using Partial Least Squares Regression (PLSR). Results from multidimensional modeling were validated using an independent test cohort of 38 patients.

Results

We identified a dynamic and variable imbalance between proximal (pSYK, pBTK) and distal (pPLCγ2, pBLNK, ppERK) phosphoresponses. PLSR identified the relationship between upstream tyrosine kinase SYK and its target, PLCγ2, as maximally predictive and sufficient to distinguish CLL from healthy samples, pointing to this juncture in the signaling pathway as a hallmark of CLL B cells. Specific BCR pathway signaling signatures that correlate with the disease and its degree of aggressiveness were identified. Heterogeneity in the PLSR response variable within the B cell population is both a characteristic mark of healthy samples and predictive of disease aggressiveness.

Conclusion

Single-cell multidimensional analysis of BCR signaling permitted focused analysis of the variability and heterogeneity of signaling behavior from patient-to-patient, and from cell-to-cell. Disruption of the pSYK/pPLCγ2 relationship is uncovered as a robust hallmark of CLL B cell signaling behavior. Together, these observations implicate novel elements of the BCR signal transduction as potential therapeutic targets.     

“Topological Significance” Analysis of Gene Expression and Proteomic Profiles from Prostate Cancer Cells Reveals Key Mechanisms of Androgen Response

Background

The problem of prostate cancer progression to androgen independence has been extensively studied. Several studies systematically analyzed gene expression profiles in the context of biological networks and pathways, uncovering novel aspects of prostate cancer. Despite significant research efforts, the mechanisms underlying tumor progression are poorly understood. We applied a novel approach to reconstruct system-wide molecular events following stimulation of LNCaP prostate cancer cells with synthetic androgen and to identify potential mechanisms of androgen-independent progression of prostate cancer.

Methodology/Principal Findings

We have performed concurrent measurements of gene expression and protein levels following the treatment using microarrays and iTRAQ proteomics. Sets of up-regulated genes and proteins were analyzed using our novel concept of “topological significance”. This method combines high-throughput molecular data with the global network of protein interactions to identify nodes which occupy significant network positions with respect to differentially expressed genes or proteins. Our analysis identified the network of growth factor regulation of cell cycle as the main response module for androgen treatment in LNCap cells. We show that the majority of signaling nodes in this network occupy significant positions with respect to the observed gene expression and proteomic profiles elicited by androgen stimulus. Our results further indicate that growth factor signaling probably represents a “second phase” response, not directly dependent on the initial androgen stimulus.

Conclusions/Significance

We conclude that in prostate cancer cells the proliferative signals are likely to be transmitted from multiple growth factor receptors by a multitude of signaling pathways converging on several key regulators of cell proliferation such as c-Myc, Cyclin D and CREB1. Moreover, these pathways are not isolated but constitute an interconnected network module containing many alternative routes from inputs to outputs. If the whole network is involved, a precisely formulated combination therapy may be required to fight the tumor growth effectively.     

Integrated Analysis of Gene Expression Profiles Associated with Response of Platinum/Paclitaxel-Based Treatment in Epithelial Ovarian Cancer

Purpose

This study aims to explore gene expression signatures and serum biomarkers to predict intrinsic chemoresistance in epithelial ovarian cancer (EOC).

Patients and Methods

Gene expression profiling data of 322 high-grade EOC cases between 2009 and 2010 in The Cancer Genome Atlas project (TCGA) were used to develop and validate gene expression signatures that could discriminate different responses to first-line platinum/paclitaxel-based treatments. A gene regulation network was then built to further identify hub genes responsible for differential gene expression between the complete response (CR) group and the progressive disease (PD) group. Further, to find more robust serum biomarkers for clinical application, we integrated our gene signatures and gene signatures reported previously to identify secretory protein-encoding genes by searching the DAVID database. In the end, gene-drug interaction network was constructed by searching Comparative Toxicogenomics Database (CTD) and literature.

Results

A 349-gene predictive model and an 18-gene model independent of key clinical features with high accuracy were developed for prediction of chemoresistance in EOC. Among them, ten important hub genes and six critical signaling pathways were identified to have important implications in chemotherapeutic response. Further, ten potential serum biomarkers were identified for predicting chemoresistance in EOC. Finally, we suggested some drugs for individualized treatment.

Conclusion

We have developed the predictive models and serum biomarkers for platinum/paclitaxel response and established the new approach to discover potential serum biomarkers from gene expression profiles. The potential drugs that target hub genes are also suggested.     

Coupled Stochastic Spatial and Non-Spatial Simulations of ErbB1 Signaling Pathways Demonstrate the Importance of Spatial Organization in Signal Transduction

Background

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation.

Methodology/Principal Findings

Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners.

Conclusions/Significance

Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.     

Skeletal muscle apoptotic signaling predicts thigh muscle volume and gait speed in community-dwelling older persons: an exploratory study

Background

Preclinical studies strongly suggest that accelerated apoptosis in skeletal myocytes may be involved in the pathogenesis of sarcopenia. However, evidence in humans is sparse. In the present study, we investigated whether apoptotic signaling in the skeletal muscle was associated with indices of muscle mass and function in older persons.

Methodology/Principal Findings

Community-dwelling older adults were categorized into high-functioning (HF) or low-functioning (LF) groups according to their short physical performance battery (SPPB) summary score. Participants underwent an isokinetic knee extensor strength test and 3-dimensional magnetic resonance imaging of the thigh. Vastus lateralis muscle samples were obtained by percutaneous needle biopsy and assayed for the expression of a set of apoptotic signaling proteins. Age, sex, number of comorbid conditions and medications as well as knee extensor strength were not different between groups. HF participants displayed greater thigh muscle volume compared with LF persons. Multivariate partial least squares (PLS) regressions showed significant correlations between caspase-dependent apoptotic signaling proteins and the muscular percentage of thigh volume (R² = 0.78; Q² = 0.61) as well as gait speed (R² = 0.81; Q² = 0.56). Significant variables in the PLS model of percent muscle volume were active caspase-8, cleaved caspase-3, cytosolic cytochrome c and mitochondrial Bak. The regression model of gait speed was mainly described by cleaved caspase-3 and mitochondrial Bax and Bak. PLS predictive apoptotic variables did not differ between functional groups. No correlation was determined between apoptotic signaling proteins and muscle strength or quality (strength per unit volume).

Conclusions/Significance

Data from this exploratory study show for the first time that apoptotic signaling is correlated with indices of muscle mass and function in a cohort of community-dwelling older persons. Future larger-scale studies are needed to corroborate these preliminary findings and determine if down-regulation of apoptotic signaling in skeletal myocytes will provide improvements in the muscle mass and functional status of older persons.     

Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data

Background

Network inference deals with the reconstruction of molecular networks from experimental data. Given N molecular species, the challenge is to find the underlying network. Due to data limitations, this typically is an ill-posed problem, and requires the integration of prior biological knowledge or strong regularization. We here focus on the situation when time-resolved measurements of a system’s response after systematic perturbations are available.

Results

We present a novel method to infer signaling networks from time-course perturbation data. We utilize dynamic Bayesian networks with probabilistic Boolean threshold functions to describe protein activation. The model posterior distribution is analyzed using evolutionary MCMC sampling and subsequent clustering, resulting in probability distributions over alternative networks. We evaluate our method on simulated data, and study its performance with respect to data set size and levels of noise. We then use our method to study EGF-mediated signaling in the ERBB pathway.

Conclusions

Dynamic Probabilistic Threshold Networks is a new method to infer signaling networks from time-series perturbation data. It exploits the dynamic response of a system after external perturbation for network reconstruction. On simulated data, we show that the approach outperforms current state of the art methods. On the ERBB data, our approach recovers a significant fraction of the known interactions, and predicts novel mechanisms in the ERBB pathway.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-250) contains supplementary material, which is available to authorized users.     

Nonadaptive Fluctuation in an Adaptive Sensory System: Bacterial Chemoreceptor

Background

Sensory systems often exhibit an adaptation or desensitization after a transient response, making the system ready to receive a new signal over a wide range of backgrounds. Because of the strong influence of thermal stochastic fluctuations on the biomolecules responsible for the adaptation, such as many membrane receptors and channels, their response is inherently noisy, and the adaptive property is achieved as a statistical average.

Methodology/Principal Findings

Here, we study a simple kinetic model characterizing the essential aspects of these adaptive molecular systems and show theoretically that, while such an adaptive sensory system exhibits a perfect adaptation property on average, its temporal stochastic fluctuations are able to be sensitive to the environmental conditions. Among the adaptive sensory systems, an extensively studied model system is the bacterial receptor responsible for chemotaxis. The model exhibits a nonadaptive fluctuation sensitive to the environmental ligand concentration, while perfect adaptation is achieved on average. Furthermore, we found that such nonadaptive fluctuation makes the bacterial behavior dependent on the environmental chemoattractant concentrations, which enhances the chemotactic performance.

Conclusions/Significance

This result indicates that adaptive sensory systems can make use of such stochastic fluctuation to carry environmental information, which is not possible by means of the average, while keeping responsive to the changing stimulus.     

Association of reactive oxygen species-mediated signal transduction with in vitro apoptosis sensitivity in chronic lymphocytic leukemia B cells

Background

Chronic lymphocytic leukemia (CLL) is a B cell malignancy with a variable clinical course and unpredictable response to therapeutic agents. Single cell network profiling (SCNP) utilizing flow cytometry measures alterations in signaling biology in the context of molecular changes occurring in malignancies. In this study SCNP was used to identify proteomic profiles associated with in vitro apoptotic responsiveness of CLL B cells to fludarabine, as a basis for ultimately linking these with clinical outcome.

Methodology/Principal Finding

SCNP was used to quantify modulated-signaling of B cell receptor (BCR) network proteins and in vitro F-ara-A mediated apoptosis in 23 CLL samples. Of the modulators studied the reactive oxygen species, hydrogen peroxide (H₂O₂), a known intracellular second messenger and a general tyrosine phosphatase inhibitor stratified CLL samples into two sub-groups based on the percentage of B cells in a CLL sample with increased phosphorylation of BCR network proteins. Separately, in the same patient samples, in vitro exposure to F-ara-A also identified two sub-groups with B cells showing competence or refractoriness to apoptotic induction. Statistical analysis showed that in vitro F-ara-A apoptotic proficiency was highly associated with the proficiency of CLL B cells to undergo H₂O₂-augmented signaling.

Conclusions/Significance

This linkage in CLL B cells among the mechanisms governing chemotherapy-induced apoptosis increased signaling of BCR network proteins and a likely role of phosphatase activity suggests a means of stratifying patients for their response to F-ara-A based regimens. Future studies will examine the clinical applicability of these findings and also the utility of this approach in relating mechanism to function of therapeutic agents.     

A population dynamics analysis of the interaction between adaptive regulatory T cells and antigen presenting cells

Background

Regulatory T cells are central actors in the maintenance of tolerance of self-antigens or allergens and in the regulation of the intensity of the immune response during infections by pathogens. An understanding of the network of the interaction between regulatory T cells, antigen presenting cells and effector T cells is starting to emerge. Dynamical systems analysis can help to understand the dynamical properties of an interaction network and can shed light on the different tasks that can be accomplished by a network.

Methodology and Principal Findings

We used a mathematical model to describe a interaction network of adaptive regulatory T cells, in which mature precursor T cells may differentiate into either adaptive regulatory T cells or effector T cells, depending on the activation state of the cell by which the antigen was presented. Using an equilibrium analysis of the mathematical model we show that, for some parameters, the network has two stable equilibrium states: one in which effector T cells are strongly regulated by regulatory T cells and another in which effector T cells are not regulated because the regulatory T cell population is vanishingly small. We then simulate different types of perturbations, such as the introduction of an antigen into a virgin system, and look at the state into which the system falls. We find that whether or not the interaction network switches from the regulated (tolerant) state to the unregulated state depends on the strength of the antigenic stimulus and the state from which the network has been perturbed.

Conclusion/Significance

Our findings suggest that the interaction network studied in this paper plays an essential part in generating and maintaining tolerance against allergens and self-antigens.     

Arbuscular mycorrhizal symbiosis increases relative apoplastic water flow in roots of the host plant under both well-watered and drought stress conditions

Background and Aims

The movement of water through mycorrhizal fungal tissues and between the fungus and roots is little understood. It has been demonstrated that arbuscular mycorrhizal (AM) symbiosis regulates root hydraulic properties, including root hydraulic conductivity. However, it is not clear whether this effect is due to a regulation of root aquaporins (cell-to-cell pathway) or to enhanced apoplastic water flow. Here we measured the relative contributions of the apoplastic versus the cell-to-cell pathway for water movement in roots of AM and non-AM plants.

Methods

We used a combination of two experiments using the apoplastic tracer dye light green SF yellowish and sodium azide as an inhibitor of aquaporin activity. Plant water and physiological status, root hydraulic conductivity and apoplastic water flow were measured.

Key Results

Roots of AM plants enhanced significantly relative apoplastic water flow as compared with non-AM plants and this increase was evident under both well-watered and drought stress conditions. The presence of the AM fungus in the roots of the host plants was able to modulate the switching between apoplastic and cell-to-cell water transport pathways.

Conclusions

The ability of AM plants to switch between water transport pathways could allow a higher flexibility in the response of these plants to water shortage according to the demand from the shoot.     

Poractant alfa (Curosurf?) increases phagocytosis of apoptotic neutrophils by alveolar macrophages in vivo

Background

Clearance of apoptotic neutrophils in the lung is an essential process to limit inflammation, since they could become a pro-inflammatory stimulus themselves. The clearance is partially mediated by alveolar macrophages, which phagocytose these apoptotic cells. The phagocytosis of apoptotic immune cells by monocytes in vitro has been shown to be augmented by several constituents of pulmonary surfactant, e.g. phospholipids and hydrophobic surfactant proteins. In this study, we assessed the influence of exogenous poractant alfa (Curosurf^®) instillation on the in vivo phagocytosis of apoptotic neutrophils by alveolar macrophages.

Methods

Poractant alfa (200 mg/kg) was instilled intratracheally in the lungs of three months old adult male C57/Black 6 mice, followed by apoptotic neutrophil instillation. Bronchoalveloar lavage was performed and alveolar macrophages and neutrophils were counted. Phagocytosis of apoptotic neutrophils was quantified by determining the number of apoptotic neutrophils per alveolar macrophages.

Results

Exogenous surfactant increased the number of alveolar macrophages engulfing apoptotic neutrophils 2.6 fold. The phagocytosis of apoptotic neutrophils was increased in the presence of exogenous surfactant by a 4.7 fold increase in phagocytosed apoptotic neutrophils per alveolar macrophage.

Conclusions

We conclude that the anti-inflammatory properties of surfactant therapy may be mediated in part by increased numbers of alveolar macrophages and increased phagocytosis of apoptotic neutrophils by alveolar macrophages.     

Optimization of Immunoglobulin Substitution Therapy by a Stochastic Immune Response Model

Background

The immune system is a complex adaptive system of cells and molecules that are interwoven in a highly organized communication network. Primary immune deficiencies are disorders in which essential parts of the immune system are absent or do not function according to plan. X-linked agammaglobulinemia is a B-lymphocyte maturation disorder in which the production of immunoglobulin is prohibited by a genetic defect. Patients have to be put on life-long immunoglobulin substitution therapy in order to prevent recurrent and persistent opportunistic infections.

Methodology

We formulate an immune response model in terms of stochastic differential equations and perform a systematic analysis of empirical therapy protocols that differ in the treatment frequency. The model accounts for the immunoglobulin reduction by natural degradation and by antigenic consumption, as well as for the periodic immunoglobulin replenishment that gives rise to an inhomogeneous distribution of immunoglobulin specificities in the shape space. Results are obtained from computer simulations and from analytical calculations within the framework of the Fokker-Planck formalism, which enables us to derive closed expressions for undetermined model parameters such as the infection clearance rate.

Conclusions

We find that the critical value of the clearance rate, below which a chronic infection develops, is strongly dependent on the strength of fluctuations in the administered immunoglobulin dose per treatment and is an increasing function of the treatment frequency. The comparative analysis of therapy protocols with regard to the treatment frequency yields quantitative predictions of therapeutic relevance, where the choice of the optimal treatment frequency reveals a conflict of competing interests: In order to diminish immunomodulatory effects and to make good economic sense, therapeutic immunoglobulin levels should be kept close to physiological levels, implying high treatment frequencies. However, clearing infections without additional medication is more reliably achieved by substitution therapies with low treatment frequencies. Our immune response model predicts that the compromise solution of immunoglobulin substitution therapy has a treatment frequency in the range from one infusion per week to one infusion per two weeks.     

Are There Neurophenotypes for Asthma? Functional Brain Imaging of the Interaction between Emotion and Inflammation in Asthma

Background

Asthma is a chronic inflammatory disease noteworthy for its vulnerability to stress and emotion-induced symptom intensification. The fact that psychological stress and mood and anxiety disorders appear to increase expression of asthma symptoms suggests that neural signaling between the brain and lung at least partially modulates the inflammatory response and lung function. However, the precise nature of the neural pathways implicated in modulating asthma symptoms is unknown. Moreover, the extent to which variations in neural signaling predict different phenotypes of disease expression has not been studied.

Methods and Results

We used functional magnetic resonance imaging to measure neural signals in response to asthma-specific emotional cues, following allergen exposure, in asthmatics with a dual response to allergen challenge (significant inflammation), asthmatics with only an immediate response (minimal inflammation), and healthy controls. The anterior insular cortex was differentially activated by asthma-relevant cues, compared to general negative cues, during the development of the late phase of the dual response in asthmatics. Moreover, the degree of this differential activation predicted changes in airway inflammation.

Conclusions

These findings indicate that neurophenotypes for asthma may be identifiable by neural reactivity of brain circuits known to be involved in processing emotional information. Those with greater activation in the anterior insula, in response to asthma-relevant psychological stimuli, exhibit greater inflammatory signals in the lung and increased severity of disease and may reflect a subset of asthmatics most vulnerable to the development of psychopathology. This approach offers an entirely new target for potential therapeutic intervention in asthma.     

Cpd-1 Null Mice Display a Subtle Neurological Phenotype

Background

CPD1 (also known as ANP32-E) belongs to a family of evolutionarily conserved acidic proteins with leucine rich repeats implicated in a variety of cellular processes regulating gene expression, vesicular trafficking, intracellular signaling and apoptosis. Because of its spatiotemporal expression pattern, CPD1 has been proposed to play an important role in brain morphogenesis and synaptic development.

Methodology/Principal Findings

We have generated CPD1 knock-out mice that we have subsequently characterized. These mice are viable and fertile. However, they display a subtle neurological clasping phenotype and mild motor deficits.

Conclusions/Significance

CPD1 is not essential for normal development; however, it appears to play a role in the regulation of fine motor functions. The minimal phenotype suggests compensatory biological mechanisms.     

Natural Spike Trains Trigger Short- and Long-Lasting Dynamics at Hippocampal Mossy Fiber Synapses in Rodents

Background

Synapses exhibit strikingly different forms of plasticity over a wide range of time scales, from milliseconds to hours. Studies on synaptic plasticity typically use constant-frequency stimulation to activate synapses, whereas in vivo activity of neurons is irregular.

Methodology/Principal Findings

Using extracellular and whole-cell electrophysiological recordings, we have here studied the synaptic responses at hippocampal mossy fiber synapses in vitro to stimulus patterns obtained from in vivo recordings of place cell firing of dentate gyrus granule cells in behaving rodents. We find that synaptic strength is strongly modulated on short- and long-lasting time scales during the presentation of the natural stimulus trains.

Conclusions/Significance

We conclude that dynamic short- and long-term synaptic plasticity at the hippocampal mossy fiber synapse plays a prominent role in normal synaptic function.