References of "Lucarelli, Philippe 50008855"
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See detailSystemic network analysis identifies XIAP and IkappaBalpha as potential drug targets in TRAIL resistant BRAF mutated melanoma.
Del Mistro, Greta; Lucarelli, Philippe UL; Muller, Ines et al

in NPJ systems biology and applications (2018), 4

Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent ... [more ▼]

Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent TRAIL receptor-targeted agonist IZI1551 to induce pronounced apoptotic cell death in mutBRAF melanoma cells. Aiming to identify molecular changes that may confer IZI1551 resistance we combined Dynamic Bayesian Network modelling with a sophisticated regularization strategy resulting in sparse and context-sensitive networks and show the performance of this strategy in the detection of cell line-specific deregulations of a signalling network. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells the model accurately and correctly predicted activation of NFkappaB in concert with upregulation of the anti-apoptotic protein XIAP as the key mediator of IZI1551 resistance. Thus, the incorporation of multiple regularization functions in logical network optimization may provide a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies. [less ▲]

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See detail"Stroma-induced phenotypic plasticity offers phenotype-specific targeting to improve melanoma treatment".
Seip, Kotryna; Jorgensen, Kjetil; Haselager, Marco Vincent et al

in Cancer letters (2018)

Cancer cells' phenotypic plasticity, promoted by stromal cells, contributes to intra-tumoral heterogeneity and affects response to therapy. We have disclosed an association between fibroblast-stimulated ... [more ▼]

Cancer cells' phenotypic plasticity, promoted by stromal cells, contributes to intra-tumoral heterogeneity and affects response to therapy. We have disclosed an association between fibroblast-stimulated phenotype switching and resistance to the clinically used BRAF inhibitor (BRAFi) vemurafenib in malignant melanoma, revealing a challenge in targeting the fibroblast-induced phenotype. Here we compared molecular features and drug sensitivity in melanoma cells grown as co-cultures with fibroblasts versus mono-cultures. In the presence of fibroblasts, melanoma cells switched to the dedifferentiated, mesenchymal-like, inflammatory phenotype that showed reduced sensitivity to the most of 275 tested cancer drugs. Fibroblasts, however, sensitized melanoma cells to PI3K inhibitors (PI3Ki) and particularly the inhibitor of GSK3, AR-A014418 (GSK3i), that showed superior efficacy in co-cultures. The proteome changes induced by the BRAFi+GSK3i combination mimicked changes induced by BRAFi in mono-cultures, and GSK3i in co-cultures. This suggests that the single drug drives the response to the combination treatment, depending on fibroblast presence or absence, consequently, phenotype. We propose that the BRAFi and GSK3i (or PI3Ki) combination exemplifies phenotype-specific combinatorial treatment that should be beneficial in phenotypically heterogeneous tumors rich in stromal interactions. [less ▲]

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See detailAnnexin A1 regulates EGFR activity and alters EGFR-containing tumour-derived exosomes in head and neck cancers.
Raulf, N.; Lucarelli, Philippe UL; Thavaraj, S. et al

in European journal of cancer (Oxford, England : 1990) (2018), 102

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the 6th most common cancer with approximately half a million cases diagnosed each year worldwide. HNSCC has a poor survival rate which has not ... [more ▼]

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the 6th most common cancer with approximately half a million cases diagnosed each year worldwide. HNSCC has a poor survival rate which has not improved for over 30 years. The molecular pathogenesis of HNSCCs remains largely unresolved; there is high prevalence of p53 mutations and EGFR overexpression; however, the contribution of these molecular changes to disease development and/or progression remains unknown. We have recently identified microRNA miR-196a to be highly overexpressed in HNSCC with poor prognosis. Oncogenic miR-196a directly targets Annexin A1 (ANXA1). Although increased ANXA1 expression levels have been associated with breast cancer development, its role in HNSCC is debatable and its functional contribution to HNSCC development remains unclear. METHODS: ANXA1 mRNA and protein expression levels were determined by RNA Seq analysis and immunohistochemistry, respectively. Gain- and loss-of-function studies were performed to analyse the effects of ANXA1 modulation on cell proliferation, mechanism of activation of EGFR signalling as well as on exosome production and exosomal phospho-EGFR. RESULTS: ANXA1 was found to be downregulated in head and neck cancer tissues, both at mRNA and protein level. Its anti-proliferative effects were mediated through the intracellular form of the protein. Importantly, ANXA1 downregulation resulted in increased phosphorylation and activity of EGFR and its downstream PI3K-AKT signalling. Additionally, ANXA1 modulation affected exosome production and influenced the release of exosomal phospho-EGFR. CONCLUSIONS: ANXA1 acts as a tumour suppressor in HNSCC. It is involved in the regulation of EGFR activity and exosomal phospho-EGFR release and could be an important prognostic biomarker. [less ▲]

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See detailUsing Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.
De Landtsheer, Sébastien; Lucarelli, Philippe UL; Sauter, Thomas UL

in Frontiers in physiology (2018), 9

Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down ... [more ▼]

Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information. [less ▲]

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See detailResolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression.
Lucarelli, Philippe UL; Schilling, Marcel; Kreutz, Clemens et al

in Cell Systems (2017)

Upon stimulation of cells with transforming growth factor beta (TGF-beta), Smad proteins form trimeric complexes and activate a broad spectrum of target genes. It remains unresolved which of the possible ... [more ▼]

Upon stimulation of cells with transforming growth factor beta (TGF-beta), Smad proteins form trimeric complexes and activate a broad spectrum of target genes. It remains unresolved which of the possible Smad complexes are formed in cellular contexts and how these contribute to gene expression. By combining quantitative mass spectrometry with a computational selection strategy, we predict and provide experimental evidence for the three most relevant Smad complexes in the mouse hepatoma cell line Hepa1-6. Utilizing dynamic pathway modeling, we specify the contribution of each Smad complex to the expression of representative Smad target genes, and show that these contributions are conserved in human hepatoma cell lines and primary hepatocytes. We predict, based on gene expression data of patient samples, increased amounts of Smad2/3/4 proteins and Smad2 phosphorylation as hallmarks of hepatocellular carcinoma and experimentally verify this prediction. Our findings demonstrate that modeling approaches can disentangle the complexity of transcription factor complex formation and its impact on gene expression. [less ▲]

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See detailFALCON: A Toolbox for the Fast Contextualisation of Logical Networks.
De Landtsheer, Sébastien UL; Trairatphisan, Panuwat UL; Lucarelli, Philippe UL et al

in Bioinformatics (Oxford, England) (2017)

Motivation: Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer ... [more ▼]

Motivation: Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. Results: We have developed a computational approach to contextualise logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualise networks, which includes a pipeline for conducting parameter analysis, knockouts, and easy and fast model investigation. The contextualised models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. Availability and implementation: FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON . FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. Contact: thomas.sauter@uni.lu. Supplementary information: Supplementary data are available at Bioinformatics online. [less ▲]

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See detailModel Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.
Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun et al

in Frontiers in physiology (2017), 8

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple ... [more ▼]

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines. [less ▲]

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See detailThermodynamically constrained averaging theory for cancer growth modelling
Albrecht, Marco UL; Sciumè, Giuseppe; Lucarelli, Philippe UL et al

in IFAC-PapersOnLine (2016), 49(26), 289-294

In Systems Biology, network models are often used to describe intracellular mechanisms at the cellular level. The obtained results are difficult to translate into three-dimensional biological systems of ... [more ▼]

In Systems Biology, network models are often used to describe intracellular mechanisms at the cellular level. The obtained results are difficult to translate into three-dimensional biological systems of higher order. The multiplicity and time dependency of cellular system boundaries, mechanical phenomena and spatial concentration gradients affect the intercellular relations and communication of biochemical networks. These environmental effects can be integrated with our promising cancer modelling environment, that is based on thermodynamically constrained averaging theory (TCAT). Especially, the TCAT parameter viscosity can be used as critical player in tumour evolution. Strong cell-cell contacts and a high degree of differentiation make cancer cells viscous and support compact tumour growth with high tumour cell density and accompanied displacement of the extracellular material. In contrast, dedifferentiation and losing of cell-cell contacts make cancer cells more fluid and lead to an infiltrating tumour growth behaviour without resistance due to the ECM. The fast expanding tumour front of the invasive type consumes oxygen and the limited oxygen availability behind the invasive front results automatically in a much smaller average tumour cell density in the tumour core. The proposed modelling technique is most suitable for tumour growth phenomena in stiff tissues like skin or bone with high content of extracellular matrix. [less ▲]

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See detailDownregulation of the TGF-beta pseudoreceptor BAMBI in non-small cell lung cancer enhances TGF-beta signaling and invasion.
Marwitz, Sebastian; Depner, Sofia; Dvornikov, Dmytro et al

in Cancer research (2016)

Non-small cell lung cancer (NSCLC) is characterized by early metastasis and has the highest mortality rate among all solid tumors, with the majority of patients diagnosed at an advanced stage where ... [more ▼]

Non-small cell lung cancer (NSCLC) is characterized by early metastasis and has the highest mortality rate among all solid tumors, with the majority of patients diagnosed at an advanced stage where curative therapeutic options are lacking. In this study, we identify a targetable mechanism involving TGF-beta elevation that orchestrates tumor progression in this disease. Substantial activation of this pathway was detected in human lung cancer tissues with concomitant downregulation of BAMBI, a negative regulator of the TGF-beta signaling pathway. Alterations of epithelial-to-mesenchymal transition (EMT) marker expression were observed in lung cancer samples compared to tumor-free tissues. Distinct alterations in the DNA methylation of the gene regions encoding TGF-beta pathway components were detected in NSCLC samples compared to tumor-free lung tissues. In particular, epigenetic silencing of BAMBI was identified as a hallmark of NSCLC. Reconstitution of BAMBI expression in NSCLC cells resulted in a marked reduction of TGF-beta-induced EMT, migration and invasion in vitro, along with reduced tumor burden and tumor growth in vivo. In conclusion, our results demonstrate how BAMBI downregulation drives the invasiveness of NSCLC, highlighting TGF-beta signaling as a candidate therapeutic target in this setting. [less ▲]

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See detailContext-specific flow through the MEK/ERK module produces cell- and ligand-specific patterns of ERK single and double phosphorylation.
Iwamoto, Nao; D'Alessandro, Lorenza A.; Depner, Sofia et al

in Science signaling (2016), 9(413), 13

The same pathway, such as the mitogen-activated protein kinase (MAPK) pathway, can produce different cellular responses, depending on stimulus or cell type. We examined the phosphorylation dynamics of the ... [more ▼]

The same pathway, such as the mitogen-activated protein kinase (MAPK) pathway, can produce different cellular responses, depending on stimulus or cell type. We examined the phosphorylation dynamics of the MAPK kinase MEK and its targets extracellular signal-regulated kinase 1 and 2 (ERK1/2) in primary hepatocytes and the transformed keratinocyte cell line HaCaT A5 exposed to either hepatocyte growth factor or interleukin-6. By combining quantitative mass spectrometry with dynamic modeling, we elucidated network structures for the reversible threonine and tyrosine phosphorylation of ERK in both cell types. In addition to differences in the phosphorylation and dephosphorylation reactions, the HaCaT network model required two feedback mechanisms, which, as the experimental data suggested, involved the induction of the dual-specificity phosphatase DUSP6 and the scaffold paxillin. We assayed and modeled the accumulation of the double-phosphorylated and active form of ERK1/2, as well as the dynamics of the changes in the monophosphorylated forms of ERK1/2. Modeling the differences in the dynamics of the changes in the distributions of the phosphorylated forms of ERK1/2 suggested that different amounts of MEK activity triggered context-specific responses, with primary hepatocytes favoring the formation of double-phosphorylated ERK1/2 and HaCaT A5 cells that produce both the threonine-phosphorylated and the double-phosphorylated form. These differences in phosphorylation distributions explained the threshold, sensitivity, and saturation of the ERK response. We extended the findings of differential ERK phosphorylation profiles to five additional cultured cell systems and matched liver tumor and normal tissue, which revealed context-specific patterns of the various forms of phosphorylated ERK. [less ▲]

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See detailExcemplify: a flexible template based solution, parsing and managing data in spreadsheets for experimentalists.
Shi, Lei; Jong, Lenneke; Wittig, Ulrike et al

in Journal of integrative bioinformatics (2013), 10(2), 220

In systems biology, quantitative experimental data is the basis of building mathematical models. In most of the cases, they are stored in Excel files and hosted locally. To have a public database for ... [more ▼]

In systems biology, quantitative experimental data is the basis of building mathematical models. In most of the cases, they are stored in Excel files and hosted locally. To have a public database for collecting, retrieving and citing experimental raw data as well as experimental conditions is important for both experimentalists and modelers. However, the great effort needed in the data handling procedure and in the data submission procedure becomes the crucial limitation for experimentalists to contribute to a database, thereby impeding the database to deliver its benefit. Moreover, manual copy and paste operations which are commonly used in those procedures increase the chance of making mistakes. Excemplify, a web-based application, proposes a flexible and adaptable template-based solution to solve these problems. Comparing to the normal template based uploading approach, which is supported by some public databases, rather than predefining a format that is potentiall impractical, Excemplify allows users to create their own experiment-specific content templates in different experiment stages and to build corresponding knowledge bases for parsing. Utilizing the embedded knowledge of used templates, Excemplify is able to parse experimental data from the initial setup stage and generate following stages spreadsheets automatically. The proposed solution standardizes the flows of data traveling according to the standard procedures of applying the experiment, cuts down the amount of manual effort and reduces the chance of mistakes caused by manual data handling. In addition, it maintains the context of meta-data from the initial preparation manuscript and improves the data consistency. It interoperates and complements RightField and SEEK as well. [less ▲]

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See detailDynamics and feedback loops in the transforming growth factor beta signaling pathway.
Wegner, Katja; Bachmann, Anastasia; Schad, Jan-Ulrich et al

in Biophysical chemistry (2012), 162

Transforming growth factor beta (TGF-beta) ligands activate a signaling cascade with multiple cell context dependent outcomes. Disruption or disturbance leads to variant clinical disorders. To develop ... [more ▼]

Transforming growth factor beta (TGF-beta) ligands activate a signaling cascade with multiple cell context dependent outcomes. Disruption or disturbance leads to variant clinical disorders. To develop strategies for disease intervention, delineation of the pathway in further detail is required. Current theoretical models of this pathway describe production and degradation of signal mediating proteins and signal transduction from the cell surface into the nucleus, whereas feedback loops have not exhaustively been included. In this study we present a mathematical model to determine the relevance of feedback regulators (Arkadia, Smad7, Smurf1, Smurf2, SnoN and Ski) on TGF-beta target gene expression and the potential to initiate stable oscillations within a realistic parameter space. We employed massive sampling of the parameters space to pinpoint crucial players for potential oscillations as well as transcriptional product levels. We identified Smad7 and Smurf2 with the highest impact on the dynamics. Based on these findings, we conducted preliminary time course experiments. [less ▲]

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