Longitudinal Claudin Gene Expression Analyses in Canine Mammary Tissues and Thereof Derived Primary Cultures and Cell Lines.

Human and canine mammary tumours show partial claudin expression deregulations. Further, claudins have been used for directed therapeutic approaches. However, the development of claudin targeting approaches requires stable claudin expressing cell lines. This study reports the establishment and characterisation of canine mammary tissue derived cell lines, analysing longitudinally the claudin-1, -3, -4 and -7 expressions in original tissue samples, primary cultures and developed cell lines. Primary cultures were derived from 17 canine mammary tissues: healthy, lobular hyperplasia, simple adenoma, complex adenoma, simple tubular carcinoma, complex carcinoma, carcinoma arising in a benign mixed tumour and benign mixed tissue. Cultivation was performed, if possible, until passage 30. Claudin mRNA and protein expressions were analysed by PCR, QuantiGene Plex Assay, immunocytochemistry and immunofluorescence. Further, cytokeratin expression was analysed immunocytochemically. Cultivation resulted in 11 established cell lines, eight showing epithelial character. In five of the early passages the claudin expressions decreased compared to the original tissues. In general, claudin expressions were diminished during cultivation. Three cell lines kept longitudinally claudin, as well as epithelial marker expressions, representing valuable tools for the development of claudin targeted anti-tumour therapies.

Autocrine TGF-ß/ZEB/microRNA-200 signal transduction drives epithelial-mesenchymal transition: Kinetic models predict minimal drug dose to inhibit metastasis.

The epithelial-mesenchymal transition (EMT) is the crucial step that cancer cells must pass before they can undergo metastasis. The transition requires the activity of complex functional networks that downregulate properties of the epithelial phenotype and upregulate characteristics of the mesenchymal phenotype. The networks frequently include reciprocal repressions between transcription factors (TFs) driving the EMT and microRNAs (miRs) inducing the reverse process, termed mesenchymal-epithelial transition (MET). In this work we develop four kinetic models that are based on experimental data and hypotheses describing how autocrine transforming growth factor-ß (TGF-ß) signal transduction induces and maintains an EMT by upregulating the TFs ZEB1 and ZEB2 which repress the expression of the miR-200b/c family members. After successful model calibration we validate our models by predicting requirements for the maintenance of the mesenchymal steady state which agree with experimental data. Finally, we apply our validated kinetic models for the design of experiments in cancer therapy. We demonstrate how steady state properties of the kinetic models, combined with data from tumor-derived cell lines of individual patients, can predict the minimal amount of an inhibitor to induce a MET.

Anti-inflammatory effects of reactive oxygen species - a multi-valued logical model validated by formal concept analysis.

BACKGROUND: Recent findings suggest that in pancreatic acinar cells stimulated with bile acid, a pro-apoptotic effect of reactive oxygen species (ROS) dominates their effect on necrosis and spreading of inflammation. The first effect presumably occurs via cytochrome C release from the inner mitochondrial membrane. A pro-necrotic effect - similar to the one of Ca2+ - can be strong opening of mitochondrial pores leading to breakdown of the membrane potential, ATP depletion, sustained Ca2+ increase and premature activation of digestive enzymes. To explain published data and to understand ROS effects during the onset of acute pancreatitis, a model using multi-valued logic is constructed. Formal concept analysis (FCA) is used to validate the model against data as well as to analyze and visualize rules that capture the dynamics. RESULTS: Simulations for two different levels of bile stimulation and for inhibition or addition of antioxidants reproduce the qualitative behaviour shown in the experiments. Based on reported differences of ROS production and of ROS induced pore opening, the model predicts a more uniform apoptosis/necrosis ratio for higher and lower bile stimulation in liver cells than in pancreatic acinar cells. FCA confirms that essential dynamical features of the data are captured by the model. For instance, high necrosis always occurs together with at least a medium level of apoptosis. At the same time, FCA helps to reveal subtle differences between data and simulations. The FCA visualization underlines the protective role of ROS against necrosis. CONCLUSIONS: The analysis of the model demonstrates how ROS and decreased antioxidant levels contribute to apoptosis. Studying the induction of necrosis via a sustained Ca2+ increase, we implemented the commonly accepted hypothesis of ATP depletion after strong bile stimulation. Using an alternative model, we demonstrate that this process is not necessary to generate the dynamics of the measured variables. Opening of plasma membrane channels could also lead to a prolonged increase of Ca2+ and to necrosis. Finally, the analysis of the model suggests a direct experimental testing for the model-based hypothesis of a self-enhancing cycle of cytochrome C release and ROS production by interruption of the mitochondrial electron transport chain.

Analysing the impact of nucleo-cytoplasmic shuttling of ß-catenin and its antagonists APC, Axin and GSK3 on Wnt/ß-catenin signalling.

The canonical Wnt signalling pathway plays a critical role in development and disease. The key player of the pathway is ß-catenin. Its activity is mainly regulated by the destruction complex consisting of APC, Axin and GSK3. In the nucleus, the complex formation of ß-catenin and TCF initiates target gene expression. Our study provides a comprehensive analysis of the role of nucleo-cytoplasmic shuttling of APC, Axin, and GSK3 and the inactivation of ß-catenin by the destruction complex in Wnt/ß-catenin signalling. We address the following questions: Can nucleo-cytoplasmic shuttling of APC, Axin and GSK3 increase the [ß-catenin/TCF] concentration? And, how is the [ß-catenin/TCF] concentration influenced by phosphorylation and subsequent degradation of nuclear ß-catenin? Based on experimental findings, we develop a compartmental model and conduct several simulation experiments. Our analysis reveals the following key findings: 1) nucleo-cytoplasmic shuttling of ß-catenin and its antagonists can yield a spatial separation between the said proteins, which results in a breakdown of ß-catenin degradation, followed by an accumulation of ß-catenin and hence leads to an increase of the [ß-catenin/TCF] concentration. Our results strongly suggest that Wnt signalling can benefit from nucleo-cytoplasmic shuttling of APC, Axin and GSK3, although they are in general ß-catenin antagonising proteins. 2) The total robustness of the [ß-catenin/TCF] output is closely linked to its absolute concentration levels. We demonstrate that the compartmental separation of ß-catenin and the destruction complex does not only lead to a maximization, but additionally to an increased robustness of [ß-catenin/TCF] signalling against perturbations in the cellular environment. 3) A nuclear accumulation of the destruction complex renders the pathway robust against fluctuations in Wnt signalling and against changes in the compartmental distribution of ß-catenin. 4) Elucidating the impact of destruction complex inhibition, we show that the [ß-catenin/TCF] concentration is more effectively enhanced by inhibition of the kinase GSK3 rather than the binding of ß-catenin to the destruction complex.

Insights into erlotinib action in pancreatic cancer cells using a combined experimental and mathematical approach.

AIM: To gain insights into the molecular action of erlotinib in pancreatic cancer (PC) cells. METHODS: Two PC cell lines, BxPC-3 and Capan-1, were treated with various concentrations of erlotinib, the specific mitogen-activated protein kinase kinase (MEK) inhibitor U0126, and protein kinase B (AKT) inhibitor XIV. DNA synthesis was measured by 5-bromo-2'-deoxyuridine (BrdU) assays. Expression and phosphorylation of the epidermal growth factor receptor (EGFR) and downstream signaling molecules were quantified by Western blot analysis. The data were processed to calibrate a mathematical model, based on ordinary differential equations, describing the EGFR-mediated signal transduction. RESULTS: Erlotinib significantly inhibited BrdU incorporation in BxPC-3 cells at a concentration of 1 µmol/L, whereas Capan-1 cells were much more resistant. In both cell lines, MEK inhibitor U0126 and erlotinib attenuated DNA synthesis in a cumulative manner, whereas the AKT pathway-specific inhibitor did not enhance the effects of erlotinib. While basal phosphorylation of EGFR and extracellular signal-regulated kinase (ERK) did not differ much between the two cell lines, BxPC-3 cells displayed a more than five-times higher basal phospho-AKT level than Capan-1 cells. Epidermal growth factor (EGF) at 10 ng/mL induced the phosphorylation of EGFR, AKT and ERK in both cell lines with similar kinetics. In BxPC-3 cells, higher levels of phospho-AKT and phospho-ERK (normalized to the total protein levels) were observed. Independent of the cell line, erlotinib efficiently inhibited phosphorylation of EGFR, AKT and ERK. The mathematical model successfully simulated the experimental findings and provided predictions regarding phosphoprotein levels that could be verified experimentally. CONCLUSION: Our data suggest basal AKT phosphorylation and the degree of EGF-induced activation of AKT and ERK as molecular determinants of erlotinib efficiency in PC cells.

Quantitative modelling of amyloidogenic processing and its influence by SORLA in Alzheimer's disease.

The extent of proteolytic processing of the amyloid precursor protein (APP) into neurotoxic amyloid-ß (Aß) peptides is central to the pathology of Alzheimer's disease (AD). Accordingly, modifiers that increase Aß production rates are risk factors in the sporadic form of AD. In a novel systems biology approach, we combined quantitative biochemical studies with mathematical modelling to establish a kinetic model of amyloidogenic processing, and to evaluate the influence by SORLA/SORL1, an inhibitor of APP processing and important genetic risk factor. Contrary to previous hypotheses, our studies demonstrate that secretases represent allosteric enzymes that require cooperativity by APP oligomerization for efficient processing. Cooperativity enables swift adaptive changes in secretase activity with even small alterations in APP concentration. We also show that SORLA prevents APP oligomerization both in cultured cells and in the brain in vivo, eliminating the preferred form of the substrate and causing secretases to switch to a less efficient non-allosteric mode of action. These data represent the first mathematical description of the contribution of genetic risk factors to AD substantiating the relevance of subtle changes in SORLA levels for amyloidogenic processing as proposed for patients carrying SORL1 risk alleles.

Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells.

The present work exemplifies how parameter identifiability analysis can be used to gain insights into differences in experimental systems and how uncertainty in parameter estimates can be handled. The case study, presented here, investigates interferon-gamma (IFNγ) induced STAT1 signalling in two cell types that play a key role in pancreatic cancer development: pancreatic stellate and cancer cells. IFNγ inhibits the growth for both types of cells and may be prototypic of agents that simultaneously hit cancer and stroma cells. We combined time-course experiments with mathematical modelling to focus on the common situation in which variations between profiles of experimental time series, from different cell types, are observed. To understand how biochemical reactions are causing the observed variations, we performed a parameter identifiability analysis. We successfully identified reactions that differ in pancreatic stellate cells and cancer cells, by comparing confidence intervals of parameter value estimates and the variability of model trajectories. Our analysis shows that useful information can also be obtained from nonidentifiable parameters. For the prediction of potential therapeutic targets we studied the consequences of uncertainty in the values of identifiable and nonidentifiable parameters. Interestingly, the sensitivity of model variables is robust against parameter variations and against differences between IFNγ induced STAT1 signalling in pancreatic stellate and cancer cells. This provides the basis for a prediction of therapeutic targets that are valid for both cell types.

Cerebral amyloid-ß proteostasis is regulated by the membrane transport protein ABCC1 in mice.

In Alzheimer disease (AD), the intracerebral accumulation of amyloid-ß (Aß) peptides is a critical yet poorly understood process. Aß clearance via the blood-brain barrier is reduced by approximately 30% in AD patients, but the underlying mechanisms remain elusive. ABC transporters have been implicated in the regulation of Aß levels in the brain. Using a mouse model of AD in which the animals were further genetically modified to lack specific ABC transporters, here we have shown that the transporter ABCC1 has an important role in cerebral Aß clearance and accumulation. Deficiency of ABCC1 substantially increased cerebral Aß levels without altering the expression of most enzymes that would favor the production of Aß from the Aß precursor protein. In contrast, activation of ABCC1 using thiethylperazine (a drug approved by the FDA to relieve nausea and vomiting) markedly reduced Aß load in a mouse model of AD expressing ABCC1 but not in such mice lacking ABCC1. Thus, by altering the temporal aggregation profile of Aß, pharmacological activation of ABC transporters could impede the neurodegenerative cascade that culminates in the dementia of AD.

Systems biology of JAK-STAT signalling in human malignancies.

Originally implicated in the regulation of survival, proliferation and differentiation of haematopoietic cells, the JAK-STAT pathway has also been linked to developmental processes, growth control and maintenance of homeostasis in a variety of other cells and tissues. Although it remains a complex system, its relative simplicity and the availability of molecular data makes it particularly attractive for modelling approaches. In this review, we will focus on JAK-STAT signalling in the context of cancer and present efforts to investigate signalling dynamics with the help of mathematical models. We describe the modelling workflow that realises a systems biology approach and give an example for interferon-γ signalling in pancreatic stellate cells.

Nucleo-cytoplasmic shuttling of APC can maximize ß-catenin/TCF concentration.

ß-catenin is the key player of the canonical Wnt pathway. Its activity is mainly regulated via protein degradation. In the nucleus, its interaction with TCF initiates target gene expression. Although the functional relevance is unclear, it has been shown that ß-catenin antagonists are also capable of nucleo-cytoplasmic shuttling. The focus of our systems biology analysis lies on the ß-catenin subcellular distribution regulated by the antagonist and scaffolding protein APC. We address the following questions: Can the concentration of the transcription factor complex [ß-catenin/TCF], which is considered as the output of the pathway, be maximized by APC nucleo-cytoplasmic shuttling and how is retention of ß-catenin by APC influencing this output? We established a mathematical model based on experimental findings to examine the influence of nucleo-cytoplasmic shuttling of APC and retention of ß-catenin by APC on the output of the pathway. The model is based on ordinary differential equations and includes protein shuttling between the two compartments nucleus and cytoplasm as well as protein complex formation in each compartment. We discuss how the steady state concentration of [ß-catenin/TCF] is influenced by APC shuttling and retention. The analysis of the model shows that the breakdown of ß-catenin cytoplasmic retention induced by APC shuttling can enhance nuclear accumulation of ß-catenin and hence maximize the output of the pathway. Using mathematical modelling, we demonstrate that in certain parameter ranges, the steady state concentration of [ß-catenin/TCF] benefits from APC shuttling. The inhibitory effect of APC is alleviated due to shuttling of APC. Surprisingly, our study therefore indicates that the nucleo-cytoplasmic shuttling of APC can have a beneficial effect on the output of the pathway in steady state, although APC is in general a ß-catenin antagonizing protein. Furthermore, we show that saturated protein translocation can under certain conditions be modelled by pure diffusion. A difference in the shuttling rate constants of sufficient orders of magnitude leads to an accumulation in either compartment, which corresponds to saturation in translocation.

Studies on mechanisms of interferon-gamma action in pancreatic cancer using a data-driven and model-based approach.

BACKGROUND: Interferon-gamma (IFNγ) is a multifunctional cytokine with antifibrotic and antiproliferative efficiency. We previously found that pancreatic stellate cells (PSC), the main effector cells in cancer-associated fibrosis, are targets of IFNγ action in the pancreas. Applying a combined experimental and computational approach, we have demonstrated a pivotal role of STAT1 in IFNγ signaling in PSC. Using in vivo and in vitro models of pancreatic cancer, we have now studied IFNγ effects on the tumor cells themselves. We hypothesize that IFNγ inhibits tumor progression through two mechanisms, reduction of fibrogenesis and antiproliferative effects on the tumor cells. To elucidate the molecular action of IFNγ, we have established a mathematical model of STAT1 activation and combined experimental studies with computer simulations. RESULTS: In BALB/c-nu/nu mice, flank tumors composed of DSL-6A/C1 pancreatic cancer cells and PSC grew faster than pure DSL-6A/C1 cell tumors. IFNγ inhibited the growth of both types of tumors to a similar degree. Since the stroma reaction typically reduces the efficiency of therapeutic agents, these data suggested that IFNγ may retain its antitumor efficiency in PSC-containing tumors by targeting the stellate cells. Studies with cocultures of DSL-6A/C1 cells and PSC revealed a modest antiproliferative effect of IFNγ under serum-free conditions. Immunoblot analysis of STAT1 phosphorylation and confocal microscopy studies on the nuclear translocation of STAT1 in DSL-6A/C1 cells suggested that IFNγ-induced activation of the transcription factor was weaker than in PSC. The mathematical model not only reproduced the experimental data, but also underscored the conclusions drawn from the experiments by indicating that a maximum of 1/500 of total STAT1 is located as phosphorylated STAT1 in the nucleus upon IFNγ treatment of the tumor cells. CONCLUSIONS: IFNγ is equally effective in DSL-6A/C1 tumors with and without stellate cells. While its action in the presence of PSC may be explained by inhibition of fibrogenesis, its efficiency in PSC-free tumors is unlikely to be caused by direct effects on the tumor cells alone but may involve inhibitory effects on local stroma cells as well. To gain further insights, we also plan to apply computer simulations to the analysis of tumor growth in vivo.

Thresholds in transient dynamics of signal transduction pathways.

Transient dynamics of signal transduction pathways play an important role in many biological processes, including cell differentiation, apoptosis, metabolism and DNA damage response. Recent examples of quantitative methods to characterize transient signals include transient metabolic control coefficients and finite time Lyapunov exponents. In our work we compare these quantitative methods to characterize transient phenomena and specifically discuss their predictive power for three examples. We focus on the identification of thresholds that separate different transient dynamic behaviors. Our investigation leads to the following results: The spectrum of the finite-time Lyapunov exponents unambiguously and reliably identifies putative thresholds in transient dynamics. Metabolic control coefficients do not reliably detect all thresholds and suffer from false positives.

Mathematical modelling of interferon-gamma signalling in pancreatic stellate cells reflects and predicts the dynamics of STAT1 pathway activity.

Signal transducer and activator of transcription (STAT) 1 is essentially involved in the mediation of antifibrotic interferon-gamma (IFN gamma) effects in pancreatic stellate cells (PSC). Here, we have further analysed the activation of the STAT1 pathway in a PSC line by combining quantitative data generation with mathematical modelling. At saturating concentrations of IFN gamma, a triphasic pattern of STAT1 activation was observed. An initial, rapid induction of phospho-STAT1 was followed by a plateau phase and another, long-lasting phase of further increase. The late increase occurred despite enhanced expression of the feedback inhibitor (SOCS1), and corresponded to increased levels of total STAT1 protein. If IFN gamma was applied at non-saturating concentrations, phospho-STAT1 and SOCS1 levels peaked and declined again over a 12 hour period, while STAT1 protein levels remained high. The mathematical model, based on a system of ordinary differential equations, describes temporal changes of the network components as a function of interactions and transport processes. The model reproduced activation profiles of all components of the STAT1 pathway that were experimentally analysed. Furthermore, it successfully predicted the dynamics of network components in additional experimental studies. Based on experimental findings and the results obtained from modelling, we suggest exhaustion of applied IFN gamma and STAT1 dephosphorylation by tyrosine phosphatases as limiting factors of STAT1 activation in PSC. In contrast, we did not obtain compelling evidence that SOCS1 acts as an efficient feedback inhibitor in our experimental system. We believe that further investigations into mathematical modelling of the STAT1 pathway will improve the understanding of the antifibrotic interferon action.

Systems biologists seek fuller integration of systems biology approaches in new cancer research programs.

Systems biology takes an interdisciplinary approach to the systematic study of complex interactions in biological systems. This approach seeks to decipher the emergent behaviors of complex systems rather than focusing only on their constituent properties. As an increasing number of examples illustrate the value of systems biology approaches to understand the initiation, progression, and treatment of cancer, systems biologists from across Europe and the United States hope for changes in the way their field is currently perceived among cancer researchers. In a recent EU-US workshop, supported by the European Commission, the German Federal Ministry for Education and Research, and the National Cancer Institute of the NIH, the participants discussed the strengths, weaknesses, hurdles, and opportunities in cancer systems biology.

Intracellular delay limits cyclic changes in gene expression.

Based on previously published experimental observations and mathematical models for Hes1, p53 and NF-kappaB gene expression, we improve these models through a distributed delay formulation of the time lag between transcription factor binding and mRNA production. This description of natural variability for delays introduces a transition from a stable steady state to limit cycle oscillations and then a second transition back to a stable steady state which has not been observed in previously published models. We demonstrate our approach for two models. The first model describes Hes1 autorepression with equations for Hes1 mRNA production and Hes1 protein translation. The second model describes Hes1 repression by the protein complex Gro/TLE1/Hes1, where Gro/TLE1 is activated by Hes1 phosphorylation. Finally, we discuss our analytical and numerical results in relation to experimental data.

Wnt signal pathways and neural stem cell differentiation.

Self-renewal, migration and differentiation of neural progenitor cells are controlled by a variety of pleiotropic signal molecules. Members of the morphogen family of Wnt molecules play a crucial role for developmental and repair mechanisms in the embryonic and adult nervous system. A strategy of disclosure of the role of different canonical (glycogen synthase kinase-3beta/beta-catenin-dependent) and noncanonical (Ca2+- and JNK-dependent) signal pathways for progenitor cell expansion and differentiations is illustrated at the example of the rat striatal progenitor cell line ST14A that is immortalized by stable retroviral transfection with a temperature-sensitive mutant of the SV40 large T antigen. A shift from permissive 33 degrees C to nonpermissive 39 degrees C leads to proliferation stop and start of differentiation into glial and neuronal cells. Investigation of expression of Wnts, Wnt receptors and Wnt-dependent signal pathway assay point to a stage-dependent involvement of canonical and noncanonical signaling in proliferation and differentiation of ST14A cells, whereby a mutual suppression of pathway activities is likely. Canonical Wnt molecules are not detected in proliferating and differentiating ST14A cells except Wnt2. The noncanonical Wnt molecules Wnt4, Wnt5a and Wnt11 are expressed in proliferating cells and increase during differentiation, whereas cellular beta-catenin decreases in the early phase and is restored in the late phase of differentiation. Accumulation of beta-catenin at the membrane in undifferentiated proliferating cells and its nuclear localization in nondividing undifferentiated cells under differentiation conditions argues for a distinct spatially regulated role of the molecule in the proliferation and early differentiation phase. Ca2+-dependent and JNK-dependent noncanonical Wnt signaling is not detected during differentiation of ST14A cells. Complete exploration of the role of Wnt pathways, for differentiation of the neural progenitor cells ST14A will require Wnt overexpression and exposure of ST14A cells to exogenous Wnts either with purified Wnts or by co-cultures with Wnt producers.

Annotating significant pairs of transcription factor binding sites in regulatory DNA.

In the presented work we search for transcription factor binding sites (BS) by including additional information about typical BS patterns. The new proposed score combines the ordinary profile score based on TRANSFAC-matrices together with a score based on pairs of BS. The latter score positively weights pairs of BS that tend to occur together in many regulatory DNA-sequences, in contrast to a random background model. The empirical BS pair frequencies result from our evaluation of a large dataset of orthologous genes.

SIR-dependent repression of non-telomeric genes in Saccharomyces cerevisiae?

The proteins Sir2, Sir3 and Sir4 repress transcription of the silent mating-type loci HML and HMR and of reporter genes inserted at telomeres. Previous microarray analyses suggested that additional non-telomeric genes exist which are repressed by the Sir proteins. In this study, we tested the expression of 12 such genes by Northern analysis and RT-PCR. However, we were unable to verify their SIR-dependent regulation, which suggests that SIR-mediated repression may be restricted to the known repressed regions.

Annotating regulatory DNA based on man-mouse genomic comparison.

Non-coding DNA segments that are conserved between the human and mouse genomic sequence are good indicators of possible regulatory sequences. Here we report on a systematic approach to delineate such conserved elements from upstream regions of orthologous gene pairs from man and mouse. We focus on orthologous genes in order to maximize our chances to find functionally similar regulatory elements. The identification of conserved elements is effected using the Waterman-Eggert local suboptimal alignment algorithm. We have modified an implementation of this algorithm such that it integrates the determination of statistical significance for the local suboptimal alignments. This has the effect of outputting a dynamically determined number of suboptimal alignments that are deemed statistically significant. Comparison with experimentally determined annotation shows a striking enrichement of regulatory sites among the conserved regions. Furthermore, the conserved regions tend to cover the promotor region described in the EPD database.