Discrete dynamic modeling of T cell survival signaling networks

Science.gov (United States)

Zhang, Ranran

2009-03-01

Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

Hsp70-Bag3 interactions regulate cancer-related signaling networks.

Science.gov (United States)

Colvin, Teresa A; Gabai, Vladimir L; Gong, Jianlin; Calderwood, Stuart K; Li, Hu; Gummuluru, Suryaram; Matchuk, Olga N; Smirnova, Svetlana G; Orlova, Nina V; Zamulaeva, Irina A; Garcia-Marcos, Mikel; Li, Xiaokai; Young, Z T; Rauch, Jennifer N; Gestwicki, Jason E; Takayama, Shinichi; Sherman, Michael Y

2014-09-01

Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here, we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling by modulating the activity of the transcription factors NF-κB, FoxM1, Hif1α, the translation regulator HuR, and the cell-cycle regulators p21 and survivin. We also identified a small-molecule inhibitor, YM-1, that disrupts the Hsp70-Bag3 interaction. YM-1 mirrored the effects of Hsp70 depletion on these signaling pathways, and in vivo administration of this drug was sufficient to suppress tumor growth in mice. Overall, our results defined Bag3 as a critical factor in Hsp70-modulated signaling and offered a preclinical proof-of-concept that the Hsp70-Bag3 complex may offer an appealing anticancer target. ©2014 American Association for Cancer Research.

Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

Science.gov (United States)

Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

2014-08-01

The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

Wnt signaling in cancer

Science.gov (United States)

Zhan, T; Rindtorff, N; Boutros, M

2017-01-01

Wnt signaling is one of the key cascades regulating development and stemness, and has also been tightly associated with cancer. The role of Wnt signaling in carcinogenesis has most prominently been described for colorectal cancer, but aberrant Wnt signaling is observed in many more cancer entities. Here, we review current insights into novel components of Wnt pathways and describe their impact on cancer development. Furthermore, we highlight expanding functions of Wnt signaling for both solid and liquid tumors. We also describe current findings how Wnt signaling affects maintenance of cancer stem cells, metastasis and immune control. Finally, we provide an overview of current strategies to antagonize Wnt signaling in cancer and challenges that are associated with such approaches. PMID:27617575

Construction and Deciphering of Human Phosphorylation-Mediated Signaling Transduction Networks.

Science.gov (United States)

Zhang, Menghuan; Li, Hong; He, Ying; Sun, Han; Xia, Li; Wang, Lishun; Sun, Bo; Ma, Liangxiao; Zhang, Guoqing; Li, Jing; Li, Yixue; Xie, Lu

2015-07-02

Protein phosphorylation is the most abundant reversible covalent modification. Human protein kinases participate in almost all biological pathways, and approximately half of the kinases are associated with disease. PhoSigNet was designed to store and display human phosphorylation-mediated signal transduction networks, with additional information related to cancer. It contains 11 976 experimentally validated directed edges and 216 871 phosphorylation sites. Moreover, 3491 differentially expressed proteins in human cancer from dbDEPC, 18 907 human cancer variation sites from CanProVar, and 388 hyperphosphorylation sites from PhosphoSitePlus were collected as annotation information. Compared with other phosphorylation-related databases, PhoSigNet not only takes the kinase-substrate regulatory relationship pairs into account, but also extends regulatory relationships up- and downstream (e.g., from ligand to receptor, from G protein to kinase, and from transcription factor to targets). Furthermore, PhoSigNet allows the user to investigate the impact of phosphorylation modifications on cancer. By using one set of in-house time series phosphoproteomics data, the reconstruction of a conditional and dynamic phosphorylation-mediated signaling network was exemplified. We expect PhoSigNet to be a useful database and analysis platform benefiting both proteomics and cancer studies.

MicroRNA functional network in pancreatic cancer: From biology to ...

Indian Academy of Sciences (India)

[Wang J and Sen S 2011 MicroRNA functional network in pancreatic cancer: From biology to biomarkers of disease. ... growth factor type I receptor; INSR, insulin receptor; IPA, Ingenuity Pathway Analysis; IPMN, ..... Prostate cancer signalling.

Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

Science.gov (United States)

Ghanat Bari, Mehrab; Ung, Choong Yong; Zhang, Cheng; Zhu, Shizhen; Li, Hu

2017-08-01

Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 10 8 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.

Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

Directory of Open Access Journals (Sweden)

Herman F Fumiã

Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.

Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

International Nuclear Information System (INIS)

Stueckle, Todd A.; Lu, Yongju; Davis, Mary E.; Wang, Liying; Jiang, Bing-Hua; Holaskova, Ida; Schafer, Rosana; Barnett, John B.; Rojanasakul, Yon

2012-01-01

Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a 6 month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A ‘pro-cancer’ gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment. Highlights: ► Chronic As 2 O 3

Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

Energy Technology Data Exchange (ETDEWEB)

Stueckle, Todd A., E-mail: tstueckle@hsc.wvu.edu [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States); Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Lu, Yongju, E-mail: yongju6@hotmail.com [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States); Davis, Mary E., E-mail: mdavis@wvu.edu [Department of Physiology, West Virginia University, Morgantown, WV 26506 (United States); Wang, Liying, E-mail: lmw6@cdc.gov [Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Jiang, Bing-Hua, E-mail: bhjiang@jefferson.edu [Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, PA 19107 (United States); Holaskova, Ida, E-mail: iholaskova@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Schafer, Rosana, E-mail: rschafer@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Barnett, John B., E-mail: jbarnett@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Rojanasakul, Yon, E-mail: yrojan@hsc.wvu.edu [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States)

2012-06-01

Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a 6 month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A ‘pro-cancer’ gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment. Highlights: ► Chronic As{sub 2}O

Signal interaction of Hedgehog/GLI and epidermal growth factor receptor signaling in cancer development

International Nuclear Information System (INIS)

Eberl, M.

2012-01-01

The subject of this PhD thesis is based on the cooperation of Hedgehog (HH)/GLI with epidermal growth factor receptor (EGFR) signaling synergistically promoting oncogenic transformation and cancer growth. In previous studies we have demonstrated that the HH/GLI and EGFR signaling pathways interact synergistically resulting not only in selective induction of HH/GLI-EGFR target genes, but also in the onset of oncogenic transformation and tumor formation (Kasper, Schnidar et al. 2006; Schnidar, Eberl et al. 2009). However, the molecular key mediators acting downstream of HH/GLI and EGFR signal cooperation were largely unknown and the in vivo evidence for the therapeutic relevance of HH/GLI and EGFR signal cooperation in HH-associated cancers was lacking. During my PhD thesis I could demonstrate that the integration of EGFR and HH/GLI signaling involves activation of RAS/MEK/ERK and JUN/AP1 signaling in response to EGFR activation. Furthermore I succeeded in identifying genes, including stem cell- (SOX2, SOX9), tumor growth- (JUN, TGFA, FGF19) and metastasis-associated genes (SPP1/osteopontin, CXCR4) that showed synergistic transcriptional activation by HH/GLI-EGFR signal integration. Importantly, I could demonstrate that these genes arrange themselves within a stable interdependent signaling network, which is required for in vivo growth of basal cell carcinoma (BCC) and tumor-initiating pancreatic cancer cells. These data validate EGFR signaling as additional drug target in HH/GLI driven cancers and provide new therapeutic strategies based on combined targeting of cooperative HH/GLI-EGFR signaling and selected downstream target genes (Eberl, Klingler et al. 2012). (author) [de

Non-coding RNA networks in cancer.

Science.gov (United States)

Anastasiadou, Eleni; Jacob, Leni S; Slack, Frank J

2018-01-01

Thousands of unique non-coding RNA (ncRNA) sequences exist within cells. Work from the past decade has altered our perception of ncRNAs from 'junk' transcriptional products to functional regulatory molecules that mediate cellular processes including chromatin remodelling, transcription, post-transcriptional modifications and signal transduction. The networks in which ncRNAs engage can influence numerous molecular targets to drive specific cell biological responses and fates. Consequently, ncRNAs act as key regulators of physiological programmes in developmental and disease contexts. Particularly relevant in cancer, ncRNAs have been identified as oncogenic drivers and tumour suppressors in every major cancer type. Thus, a deeper understanding of the complex networks of interactions that ncRNAs coordinate would provide a unique opportunity to design better therapeutic interventions.

Signal Processing and Neural Network Simulator

Science.gov (United States)

Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

1995-04-01

The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

An approach for optimally extending mathematical models of signaling networks using omics data.

Science.gov (United States)

Bianconi, Fortunato; Patiti, Federico; Baldelli, Elisa; Crino, Lucio; Valigi, Paolo

2015-01-01

Mathematical modeling is a key process in Systems Biology and the use of computational tools such as Cytoscape for omics data processing, need to be integrated in the modeling activity. In this paper we propose a new methodology for modeling signaling networks by combining ordinary differential equation models and a gene recommender system, GeneMANIA. We started from existing models, that are stored in the BioModels database, and we generated a query to use as input for the GeneMANIA algorithm. The output of the recommender system was then led back to the kinetic reactions that were finally added to the starting model. We applied the proposed methodology to EGFR-IGF1R signal transduction network, which plays an important role in translational oncology and cancer therapy of non small cell lung cancer.

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

Science.gov (United States)

Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2013-01-01

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

Molecular signaling involving intrinsically disordered proteins in prostate cancer

Directory of Open Access Journals (Sweden)

Anna Russo

2016-01-01

Full Text Available Investigations on cellular protein interaction networks (PINs reveal that proteins that constitute hubs in a PIN are notably enriched in Intrinsically Disordered Proteins (IDPs compared to proteins that constitute edges, highlighting the role of IDPs in signaling pathways. Most IDPs rapidly undergo disorder-to-order transitions upon binding to their biological targets to perform their function. Conformational dynamics enables IDPs to be versatile and to interact with a broad range of interactors under normal physiological conditions where their expression is tightly modulated. IDPs are involved in many cellular processes such as cellular signaling, transcriptional regulation, and splicing; thus, their high-specificity/low-affinity interactions play crucial roles in many human diseases including cancer. Prostate cancer (PCa is one of the leading causes of cancer-related mortality in men worldwide. Therefore, identifying molecular mechanisms of the oncogenic signaling pathways that are involved in prostate carcinogenesis is crucial. In this review, we focus on the aspects of cellular pathways leading to PCa in which IDPs exert a primary role.

Bladder Cancer Advocacy Network

Science.gov (United States)

... Grants Bladder Cancer Think Tank Bladder Cancer Research Network Bladder Cancer Genomics Consortium Get Involved Ways to ... us? Who we are The Bladder Cancer Advocacy Network (BCAN) is a community of patients, caregivers, survivors, ...

Adipocyte activation of cancer stem cell signaling in breast cancer

Institute of Scientific and Technical Information of China (English)

Benjamin; Wolfson; Gabriel; Eades; Qun; Zhou

2015-01-01

Signaling within the tumor microenvironment has a critical role in cancer initiation and progression. Adipocytes, one of the major components of the breast microenvironment,have been shown to provide pro-tumorigenic signals that promote cancer cell proliferation and invasiveness in vitro and tumorigenicity in vivo. Adipocyte secreted factors such as leptin and interleukin-6(IL-6) have a paracrine effect on breast cancer cells. In adipocyte-adjacent breast cancer cells, the leptin and IL-6 signaling pathways activate janus kinase 2/signal transducer and activatorof transcription 5, promoting the epithelial-mesenchymal transition, and upregulating stemness regulators such as Notch, Wnt and the Sex determining region Y-box 2/octamer binding transcription factor 4/Nanog signaling axis. In this review we will summarize the major signaling pathways that regulate cancer stem cells in breast cancer and describe the effects that adipocyte secreted IL-6 and leptin have on breast cancer stem cell signaling. Finally we will introduce a new potential treatment paradigm of inhibiting the adipocyte-breast cancer cell signaling via targeting the IL-6 or leptin pathways.

Signal-regulated systems and networks

CSIR Research Space (South Africa)

Van Zyl, TL

2010-07-01

Full Text Available The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article...

The redox biology network in cancer pathophysiology and therapeutics

Directory of Open Access Journals (Sweden)

Gina Manda

2015-08-01

Full Text Available The review pinpoints operational concepts related to the redox biology network applied to the pathophysiology and therapeutics of solid tumors. A sophisticated network of intrinsic and extrinsic cues, integrated in the tumor niche, drives tumorigenesis and tumor progression. Critical mutations and distorted redox signaling pathways orchestrate pathologic events inside cancer cells, resulting in resistance to stress and death signals, aberrant proliferation and efficient repair mechanisms. Additionally, the complex inter-cellular crosstalk within the tumor niche, mediated by cytokines, redox-sensitive danger signals (HMGB1 and exosomes, under the pressure of multiple stresses (oxidative, inflammatory, metabolic, greatly contributes to the malignant phenotype. The tumor-associated inflammatory stress and its suppressive action on the anti-tumor immune response are highlighted. We further emphasize that ROS may act either as supporter or enemy of cancer cells, depending on the context. Oxidative stress-based therapies, such as radiotherapy and photodynamic therapy, take advantage of the cytotoxic face of ROS for killing tumor cells by a non-physiologically sudden, localized and intense oxidative burst. The type of tumor cell death elicited by these therapies is discussed. Therapy outcome depends on the differential sensitivity to oxidative stress of particular tumor cells, such as cancer stem cells, and therefore co-therapies that transiently down-regulate their intrinsic antioxidant system hold great promise. We draw attention on the consequences of the damage signals delivered by oxidative stress-injured cells to neighboring and distant cells, and emphasize the benefits of therapeutically triggered immunologic cell death in metastatic cancer. An integrative approach should be applied when designing therapeutic strategies in cancer, taking into consideration the mutational, metabolic, inflammatory and oxidative status of tumor cells, cellular

NSP-CAS Protein Complexes: Emerging Signaling Modules in Cancer.

Science.gov (United States)

Wallez, Yann; Mace, Peter D; Pasquale, Elena B; Riedl, Stefan J

2012-05-01

The CAS (CRK-associated substrate) family of adaptor proteins comprises 4 members, which share a conserved modular domain structure that enables multiple protein-protein interactions, leading to the assembly of intracellular signaling platforms. Besides their physiological role in signal transduction downstream of a variety of cell surface receptors, CAS proteins are also critical for oncogenic transformation and cancer cell malignancy through associations with a variety of regulatory proteins and downstream effectors. Among the regulatory partners, the 3 recently identified adaptor proteins constituting the NSP (novel SH2-containing protein) family avidly bind to the conserved carboxy-terminal focal adhesion-targeting (FAT) domain of CAS proteins. NSP proteins use an anomalous nucleotide exchange factor domain that lacks catalytic activity to form NSP-CAS signaling modules. Additionally, the NSP SH2 domain can link NSP-CAS signaling assemblies to tyrosine-phosphorylated cell surface receptors. NSP proteins can potentiate CAS function by affecting key CAS attributes such as expression levels, phosphorylation state, and subcellular localization, leading to effects on cell adhesion, migration, and invasion as well as cell growth. The consequences of these activities are well exemplified by the role that members of both families play in promoting breast cancer cell invasiveness and resistance to antiestrogens. In this review, we discuss the intriguing interplay between the NSP and CAS families, with a particular focus on cancer signaling networks.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

Directory of Open Access Journals (Sweden)

Kumari Sonal Choudhary

2016-06-01

Full Text Available Epithelial to mesenchymal transition (EMT is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR, are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E and mesenchymal (EGFR_M networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

Science.gov (United States)

Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-06-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

Global characterization of signalling networks associated with tamoxifen resistance in breast cancer

DEFF Research Database (Denmark)

Browne, Brigid C.; Hochgräfe, Falko; Wu, Jianmin

2013-01-01

R cells. Phosphorylation of the tyrosine kinase Yes and expression of the actin‐binding protein myristoylated alanine‐rich C‐kinase substrate (MARCKS) were increased two‐ and eightfold in TamR cells respectively, and these proteins were selected for further analysis. Knockdown of either protein in Tam......Acquired resistance to the anti‐estrogen tamoxifen remains a significant challenge in breast cancer management. In this study, we used an integrative approach to characterize global protein expression and tyrosine phosphorylation events in tamoxifen‐resistant MCF7 breast cancer cells (Tam...... was perturbed in TamR cells, together with pathways enriched for proteins associated with growth factor, cell–cell and cell matrix‐initiated signalling. Consistent with known roles for Ras/MAPK and PI3‐kinase signalling in tamoxifen resistance, tyrosine‐phosphorylated MAPK1, SHC1 and PIK3R2 were elevated in Tam...

Prostate Cancer Biorepository Network

Science.gov (United States)

2017-10-01

AWARD NUMBER: W81XWH-14-2-0185 TITLE: Prostate Cancer Biorepository Network PRINCIPAL INVESTIGATOR: Jonathan Melamed, MD CONTRACTING ORGANIZATION...AND SUBTITLE 5a. CONTRACT NUMBER Prostate Cancer Biorepository Network 5b. GRANT NUMBER W81XWH-14-2-0185 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...infrastructure and operations of the Prostate Cancer Biorepository Network (PCBN). The aim of the PCBN is to provide prostate researchers with high-quality

Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

Science.gov (United States)

Knapp, Bettina; Kaderali, Lars

2013-01-01

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

Science.gov (United States)

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

Integrative modelling of the influence of MAPK network on cancer cell fate decision.

Directory of Open Access Journals (Sweden)

Luca Grieco

2013-10-01

Full Text Available The Mitogen-Activated Protein Kinase (MAPK network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3 activating mutations.

NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals.

Science.gov (United States)

Ruan, Peifeng; Shen, Jing; Santella, Regina M; Zhou, Shuigeng; Wang, Shuang

2016-09-19

DNA methylation plays an important role in many biological processes. Existing epigenome-wide association studies (EWAS) have successfully identified aberrantly methylated genes in many diseases and disorders with most studies focusing on analysing methylation sites one at a time. Incorporating prior biological information such as biological networks has been proven to be powerful in identifying disease-associated genes in both gene expression studies and genome-wide association studies (GWAS) but has been under studied in EWAS. Although recent studies have noticed that there are differences in methylation variation in different groups, only a few existing methods consider variance signals in DNA methylation studies. Here, we present a network-assisted algorithm, NEpiC, that combines both mean and variance signals in searching for differentially methylated sub-networks using the protein-protein interaction (PPI) network. In simulation studies, we demonstrate the power gain from using both the prior biological information and variance signals compared to using either of the two or neither information. Applications to several DNA methylation datasets from the Cancer Genome Atlas (TCGA) project and DNA methylation data on hepatocellular carcinoma (HCC) from the Columbia University Medical Center (CUMC) suggest that the proposed NEpiC algorithm identifies more cancer-related genes and generates better replication results. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Organization of signal flow in directed networks

International Nuclear Information System (INIS)

Bányai, M; Bazsó, F; Négyessy, L

2011-01-01

Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps

Mathematical Modelling Plant Signalling Networks

KAUST Repository

Muraro, D.

2013-01-01

During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

Pan-cancer analysis of TCGA data reveals notable signaling pathways

International Nuclear Information System (INIS)

Neapolitan, Richard; Horvath, Curt M.; Jiang, Xia

2015-01-01

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be

Tyrosine kinase signalling in breast cancer: Modulation of tyrosine kinase signalling in human breast cancer through altered expression of signalling intermediates

International Nuclear Information System (INIS)

Kairouz, Rania; Daly, Roger J

2000-01-01

The past decade has seen the definition of key signalling pathways downstream of receptor tyrosine kinases (RTKs) in terms of their components and the protein-protein interactions that facilitate signal transduction. Given the strong evidence that links signalling by certain families of RTKs to the progression of breast cancer, it is not surprising that the expression profile of key downstream signalling intermediates in this disease has also come under scrutiny, particularly because some exhibit transforming potential or amplify mitogenic signalling pathways when they are overexpressed. Reflecting the diverse cellular processes regulated by RTKs, it is now clear that altered expression of such signalling proteins in breast cancer may influence not only cellular proliferation (eg Grb2) but also the invasive properties of the cancer cells (eg EMS1/cortactin)

Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

Directory of Open Access Journals (Sweden)

Kirouac Daniel C

2012-05-01

Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

Science.gov (United States)

Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

2015-01-01

Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors.

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

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Masanao Sato

Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

Wnt5a Signaling in Cancer

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Marwa S. Asem

2016-08-01

Full Text Available Wnt5a is involved in activating several non-canonical WNT signaling pathways, through binding to different members of the Frizzled- and Ror-family receptors. Wnt5a signaling is critical for regulating normal developmental processes, including proliferation, differentiation, migration, adhesion and polarity. However, the aberrant activation or inhibition of Wnt5a signaling is emerging as an important event in cancer progression, exerting both oncogenic and tumor suppressive effects. Recent studies show the involvement of Wnt5a in regulating cancer cell invasion, metastasis, metabolism and inflammation. In this article, we review findings regarding the molecular mechanisms and roles of Wnt5a signaling in various cancer types, and highlight Wnt5a in ovarian cancer.

Social multimedia signals a signal processing approach to social network phenomena

CERN Document Server

Roy, Suman Deb

2014-01-01

This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

Discrete dynamic modeling of cellular signaling networks.

Science.gov (United States)

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Global Optimization for Transport Network Expansion and Signal Setting

OpenAIRE

Liu, Haoxiang; Wang, David Z. W.; Yue, Hao

2015-01-01

This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two pr...

Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

Science.gov (United States)

Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter

2014-06-01

Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Construction and analysis of circular RNA molecular regulatory networks in liver cancer.

Science.gov (United States)

Ren, Shuangchun; Xin, Zhuoyuan; Xu, Yinyan; Xu, Jianting; Wang, Guoqing

2017-01-01

Liver cancer is the sixth most prevalent cancer, and the third most frequent cause of cancer-related deaths. Circular RNAs (circRNAs), a kind of special endogenous ncRNAs, have been coming back to the forefront of cancer genomics research. In this study, we used a systems biology approach to construct and analyze the circRNA molecular regulatory networks in the context of liver cancer. We detected a total of 127 differentially expressed circRNAs and 3,235 differentially expressed mRNAs. We selected the top-5 upregulated circRNAs to construct a circRNA-miRNA-mRNA network. We enriched the pathways and gene ontology items and determined their participation in cancer-related pathways such as p53 signaling pathway and pathways involved in angiogenesis and cell cycle. Quantitative real-time PCR was performed to verify the top-five circRNAs. ROC analysis showed circZFR, circFUT8, circIPO11 could significantly distinguish the cancer samples, with an AUC of 0.7069, 0.7575, and 0.7103, respectively. Our results suggest the circRNA-miRNA-mRNA network may help us further understand the molecular mechanisms of tumor progression in liver cancer, and reveal novel biomarkers and therapeutic targets.

Neural networks in signal processing

International Nuclear Information System (INIS)

Govil, R.

2000-01-01

Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

Signaling in large-scale neural networks

DEFF Research Database (Denmark)

Berg, Rune W; Hounsgaard, Jørn

2009-01-01

We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this m......We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages...... of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons....

The Genome-Wide Analysis of Carcinoembryonic Antigen Signaling by Colorectal Cancer Cells Using RNA Sequencing.

Directory of Open Access Journals (Sweden)

Olga Bajenova

Full Text Available Сarcinoembryonic antigen (CEA, CEACAM5, CD66 is a promoter of metastasis in epithelial cancers that is widely used as a prognostic clinical marker of metastasis. The aim of this study is to identify the network of genes that are associated with CEA-induced colorectal cancer liver metastasis. We compared the genome-wide transcriptomic profiles of CEA positive (MIP101 clone 8 and CEA negative (MIP 101 colorectal cancer cell lines with different metastatic potential in vivo. The CEA-producing cells displayed quantitative changes in the level of expression for 100 genes (over-expressed or down-regulated. They were confirmed by quantitative RT-PCR. The KEGG pathway analysis identified 4 significantly enriched pathways: cytokine-cytokine receptor interaction, MAPK signaling pathway, TGF-beta signaling pathway and pyrimidine metabolism. Our results suggest that CEA production by colorectal cancer cells triggers colorectal cancer progression by inducing the epithelial- mesenchymal transition, increasing tumor cell invasiveness into the surrounding tissues and suppressing stress and apoptotic signaling. The novel gene expression distinctions establish the relationships between the existing cancer markers and implicate new potential biomarkers for colorectal cancer hepatic metastasis.

Muscarinic Receptor Signaling in Colon Cancer

Energy Technology Data Exchange (ETDEWEB)

Rosenvinge, Erik C. von, E-mail: evonrose@medicine.umaryland.edu; Raufman, Jean-Pierre [University of Maryland School of Medicine, Division of Gastroenterology & Hepatology, 22 S. Greene Street, N3W62, Baltimore, MD 21201 (United States); Department of Veterans Affairs, VA Maryland Health Care System, 10 North Greene Street, Baltimore, MD 21201 (United States)

2011-03-02

According to the adenoma-carcinoma sequence, colon cancer results from accumulating somatic gene mutations; environmental growth factors accelerate and augment this process. For example, diets rich in meat and fat increase fecal bile acids and colon cancer risk. In rodent cancer models, increased fecal bile acids promote colon dysplasia. Conversely, in rodents and in persons with inflammatory bowel disease, low-dose ursodeoxycholic acid treatment alters fecal bile acid composition and attenuates colon neoplasia. In the course of elucidating the mechanism underlying these actions, we discovered that bile acids interact functionally with intestinal muscarinic receptors. The present communication reviews muscarinic receptor expression in normal and neoplastic colon epithelium, the role of autocrine signaling following synthesis and release of acetylcholine from colon cancer cells, post-muscarinic receptor signaling including the role of transactivation of epidermal growth factor receptors and activation of the ERK and PI3K/AKT signaling pathways, the structural biology and metabolism of bile acids and evidence for functional interaction of bile acids with muscarinic receptors on human colon cancer cells. In murine colon cancer models, deficiency of subtype 3 muscarinic receptors attenuates intestinal neoplasia; a proof-of-concept supporting muscarinic receptor signaling as a therapeutic target for colon cancer.

Muscarinic Receptor Signaling in Colon Cancer

International Nuclear Information System (INIS)

Rosenvinge, Erik C. von; Raufman, Jean-Pierre

2011-01-01

According to the adenoma-carcinoma sequence, colon cancer results from accumulating somatic gene mutations; environmental growth factors accelerate and augment this process. For example, diets rich in meat and fat increase fecal bile acids and colon cancer risk. In rodent cancer models, increased fecal bile acids promote colon dysplasia. Conversely, in rodents and in persons with inflammatory bowel disease, low-dose ursodeoxycholic acid treatment alters fecal bile acid composition and attenuates colon neoplasia. In the course of elucidating the mechanism underlying these actions, we discovered that bile acids interact functionally with intestinal muscarinic receptors. The present communication reviews muscarinic receptor expression in normal and neoplastic colon epithelium, the role of autocrine signaling following synthesis and release of acetylcholine from colon cancer cells, post-muscarinic receptor signaling including the role of transactivation of epidermal growth factor receptors and activation of the ERK and PI3K/AKT signaling pathways, the structural biology and metabolism of bile acids and evidence for functional interaction of bile acids with muscarinic receptors on human colon cancer cells. In murine colon cancer models, deficiency of subtype 3 muscarinic receptors attenuates intestinal neoplasia; a proof-of-concept supporting muscarinic receptor signaling as a therapeutic target for colon cancer

Muscarinic Receptor Signaling in Colon Cancer

Directory of Open Access Journals (Sweden)

Jean-Pierre Raufman

2011-03-01

Full Text Available According to the adenoma-carcinoma sequence, colon cancer results from accumulating somatic gene mutations; environmental growth factors accelerate and augment this process. For example, diets rich in meat and fat increase fecal bile acids and colon cancer risk. In rodent cancer models, increased fecal bile acids promote colon dysplasia. Conversely, in rodents and in persons with inflammatory bowel disease, low-dose ursodeoxycholic acid treatment alters fecal bile acid composition and attenuates colon neoplasia. In the course of elucidating the mechanism underlying these actions, we discovered that bile acids interact functionally with intestinal muscarinic receptors. The present communication reviews muscarinic receptor expression in normal and neoplastic colon epithelium, the role of autocrine signaling following synthesis and release of acetylcholine from colon cancer cells, post-muscarinic receptor signaling including the role of transactivation of epidermal growth factor receptors and activation of the ERK and PI3K/AKT signaling pathways, the structural biology and metabolism of bile acids and evidence for functional interaction of bile acids with muscarinic receptors on human colon cancer cells. In murine colon cancer models, deficiency of subtype 3 muscarinic receptors attenuates intestinal neoplasia; a proof-of-concept supporting muscarinic receptor signaling as a therapeutic target for colon cancer.

Wnt signaling in triple-negative breast cancer

Science.gov (United States)

Pohl, SÖ-G; Brook, N; Agostino, M; Arfuso, F; Kumar, A P; Dharmarajan, A

2017-01-01

Wnt signaling regulates a variety of cellular processes, including cell fate, differentiation, proliferation and stem cell pluripotency. Aberrant Wnt signaling is a hallmark of many cancers. An aggressive subtype of breast cancer, known as triple-negative breast cancer (TNBC), demonstrates dysregulation in canonical and non-canonical Wnt signaling. In this review, we summarize regulators of canonical and non-canonical Wnt signaling, as well as Wnt signaling dysfunction that mediates the progression of TNBC. We review the complex molecular nature of TNBC and the emerging therapies that are currently under investigation for the treatment of this disease. PMID:28368389

MicroRNA-gene signaling pathways in pancreatic cancer

Directory of Open Access Journals (Sweden)

Alexandra Drakaki

2013-10-01

Full Text Available Pancreatic cancer is the fourth most frequent cause of cancer-related deaths and is characterized by early metastasis and pronounced resistance to chemotherapy and radiation therapy. Despite extensive esearch efforts, there is not any substantial progress regarding the identification of novel drugs against pancreatic cancer. Although the introduction of the chemotherapeutic agent gemcitabine improved clinical response, the prognosis of these patients remained extremely poor with a 5-year survival rate of 3-5%. Thus, the identification of the novel molecular pathways involved in pancreatic oncogenesis and the development of new and potent therapeutic options are highly desirable. Here, we describe how microRNAs control signaling pathways that are frequently deregulated during pancreatic oncogenesis. In addition, we provide evidence that microRNAs could be potentially used as novel pancreatic cancer therapeutics through reversal of chemotherapy and radiotherapy resistance or regulation of essential molecular pathways. Further studies should integrate the deregulated genes and microRNAs into molecular networks in order to identify the central regulators of pancreatic oncogenesis. Targeting these central regulators could lead to the development of novel targeted therapeutic approaches for pancreatic cancer patients.

Reconstruction of periodic signals using neural networks

Directory of Open Access Journals (Sweden)

José Danilo Rairán Antolines

2014-01-01

Full Text Available In this paper, we reconstruct a periodic signal by using two neural networks. The first network is trained to approximate the period of a signal, and the second network estimates the corresponding coefficients of the signal's Fourier expansion. The reconstruction strategy consists in minimizing the mean-square error via backpro-pagation algorithms over a single neuron with a sine transfer function. Additionally, this paper presents mathematical proof about the quality of the approximation as well as a first modification of the algorithm, which requires less data to reach the same estimation; thus making the algorithm suitable for real-time implementations.

Hedgehog signaling and therapeutics in pancreatic cancer.

LENUS (Irish Health Repository)

Kelleher, Fergal C

2012-02-01

OBJECTIVE: To conduct a systematic review of the role that the hedgehog signaling pathway has in pancreatic cancer tumorigenesis. METHOD: PubMed search (2000-2010) and literature based references. RESULTS: Firstly, in 2009 a genetic analysis of pancreatic cancers found that a core set of 12 cellular signaling pathways including hedgehog were genetically altered in 67-100% of cases. Secondly, in vitro and in vivo studies of treatment with cyclopamine (a naturally occurring antagonist of the hedgehog signaling pathway component; Smoothened) has shown that inhibition of hedgehog can abrogate pancreatic cancer metastasis. Thirdly, experimental evidence has demonstrated that sonic hedgehog (Shh) is correlated with desmoplasia in pancreatic cancer. This is important because targeting the Shh pathway potentially may facilitate chemotherapeutic drug delivery as pancreatic cancers tend to have a dense fibrotic stroma that extrinsically compresses the tumor vasculature leading to a hypoperfusing intratumoral circulation. It is probable that patients with locally advanced pancreatic cancer will derive the greatest benefit from treatment with Smoothened antagonists. Fourthly, it has been found that ligand dependent activation by hedgehog occurs in the tumor stromal microenvironment in pancreatic cancer, a paracrine effect on tumorigenesis. Finally, in pancreatic cancer, cells with the CD44+CD24+ESA+ immunophenotype select a population enriched for cancer initiating stem cells. Shh is increased 46-fold in CD44+CD24+ESA+ cells compared with normal pancreatic epithelial cells. Medications that destruct pancreatic cancer initiating stem cells are a potentially novel strategy in cancer treatment. CONCLUSIONS: Aberrant hedgehog signaling occurs in pancreatic cancer tumorigenesis and therapeutics that target the transmembrane receptor Smoothened abrogate hedgehog signaling and may improve the outcomes of patients with pancreatic cancer.

A fuzzy neural network for sensor signal estimation

International Nuclear Information System (INIS)

Na, Man Gyun

2000-01-01

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique. Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors

Network analysis of an in vitro model of androgen-resistance in prostate cancer

International Nuclear Information System (INIS)

Detchokul, Sujitra; Elangovan, Aparna; Crampin, Edmund J.; Davis, Melissa J.; Frauman, Albert G.

2015-01-01

The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer. We have developed an in vitro model of androgen-resistance to characterise molecular changes occurring as androgen resistance evolves over time. Our aim is to understand biological network profiles of transcriptomic changes occurring during the transition to androgen-resistance and to validate these changes between our in vitro model and clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced prostate cancer). We established an androgen-independent subline from LNCaP cells by prolonged exposure to androgen-deprivation. We examined phenotypic profiles and performed RNA-sequencing. The reads generated were compared to human clinical samples and were analysed using differential expression, pathway analysis and protein-protein interaction networks. After 24 weeks of androgen-deprivation, LNCaP cells had increased proliferative and invasive behaviour compared to parental LNCaP, and its growth was no longer responsive to androgen. We identified key genes and pathways that overlap between our cell line and clinical RNA sequencing datasets and analysed the overlapping protein-protein interaction network that shared the same pattern of behaviour in both datasets. Mechanisms bypassing androgen receptor signalling pathways are significantly enriched. Several steroid hormone receptors are differentially expressed in both datasets. In particular, the progesterone receptor is significantly differentially expressed and is part of the interaction network disrupted in both datasets. Other signalling pathways commonly altered in prostate cancer, MAPK and PI3K-Akt pathways, are significantly enriched in both datasets. The overlap between the human and cell-line differential expression profiles and protein networks was statistically significant showing that the cell-line model reproduces molecular patterns observed in

Targeting Apoptosis Signaling in Pancreatic Cancer

International Nuclear Information System (INIS)

Fulda, Simone

2011-01-01

The ability to escape apoptosis or programmed cell death is a hallmark of human cancers, for example pancreatic cancer. This can promote tumorigenesis, since too little cell death by apoptosis disturbs tissue homeostasis. Additionally, defective apoptosis signaling is the underlying cause of failure to respond to current treatment approaches, since therapy-mediated antitumor activity requires the intactness of apoptosis signaling pathways in cancer cells. Thus, the elucidation of defects in the regulation of apoptosis in pancreatic carcinoma can result in the identification of novel targets for therapeutic interference and for exploitation for cancer drug discovery

Targeting Apoptosis Signaling in Pancreatic Cancer

Energy Technology Data Exchange (ETDEWEB)

Fulda, Simone [Institute for Experimental Cancer Research in Pediatrics, Goethe-University Frankfurt, Komturstr. 3a, 60528 Frankfurt (Germany)

2011-01-11

The ability to escape apoptosis or programmed cell death is a hallmark of human cancers, for example pancreatic cancer. This can promote tumorigenesis, since too little cell death by apoptosis disturbs tissue homeostasis. Additionally, defective apoptosis signaling is the underlying cause of failure to respond to current treatment approaches, since therapy-mediated antitumor activity requires the intactness of apoptosis signaling pathways in cancer cells. Thus, the elucidation of defects in the regulation of apoptosis in pancreatic carcinoma can result in the identification of novel targets for therapeutic interference and for exploitation for cancer drug discovery.

Processing of seismic signals from a seismometer network

International Nuclear Information System (INIS)

Key, F.A.; Warburton, P.J.

1983-08-01

A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

ALDH1A1 maintains ovarian cancer stem cell-like properties by altered regulation of cell cycle checkpoint and DNA repair network signaling.

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Erhong Meng

Full Text Available OBJECTIVE: Aldehyde dehydrogenase (ALDH expressing cells have been characterized as possessing stem cell-like properties. We evaluated ALDH+ ovarian cancer stem cell-like properties and their role in platinum resistance. METHODS: Isogenic ovarian cancer cell lines for platinum sensitivity (A2780 and platinum resistant (A2780/CP70 as well as ascites from ovarian cancer patients were analyzed for ALDH+ by flow cytometry to determine its association to platinum resistance, recurrence and survival. A stable shRNA knockdown model for ALDH1A1 was utilized to determine its effect on cancer stem cell-like properties, cell cycle checkpoints, and DNA repair mediators. RESULTS: ALDH status directly correlated to platinum resistance in primary ovarian cancer samples obtained from ascites. Patients with ALDHHIGH displayed significantly lower progression free survival than the patients with ALDHLOW cells (9 vs. 3 months, respectively p<0.01. ALDH1A1-knockdown significantly attenuated clonogenic potential, PARP-1 protein levels, and reversed inherent platinum resistance. ALDH1A1-knockdown resulted in dramatic decrease of KLF4 and p21 protein levels thereby leading to S and G2 phase accumulation of cells. Increases in S and G2 cells demonstrated increased expression of replication stress associated Fanconi Anemia DNA repair proteins (FANCD2, FANCJ and replication checkpoint (pS317 Chk1 were affected. ALDH1A1-knockdown induced DNA damage, evidenced by robust induction of γ-H2AX and BAX mediated apoptosis, with significant increases in BRCA1 expression, suggesting ALDH1A1-dependent regulation of cell cycle checkpoints and DNA repair networks in ovarian cancer stem-like cells. CONCLUSION: This data suggests that ovarian cancer cells expressing ALDH1A1 may maintain platinum resistance by altered regulation of cell cycle checkpoint and DNA repair network signaling.

Role of Estrogen Receptor Signaling in Breast Cancer Metastasis

International Nuclear Information System (INIS)

Roy, S.S.; Vadlamudi, R.K.

2012-01-01

Metastatic breast cancer is a life-threatening stage of cancer and is the leading cause of death in advanced breast cancer patients. Estrogen signaling and the estrogen receptor (ER) are implicated in breast cancer progression, and the majority of the human breast cancers start out as estrogen dependent. Accumulating evidence suggests that ER signaling is complex, involving coregulatory proteins and extranuclear actions. ER-coregualtory proteins are tightly regulated under normal conditions with miss expression primarily reported in cancer. Deregulation of ER coregualtors or ER extranuclear signaling has potential to promote metastasis in ER-positive breast cancer cells. This review summarizes the emerging role of ER signaling in promoting metastasis of breast cancer cells, discusses the molecular mechanisms by which ER signaling contributes to metastasis, and explores possible therapeutic targets to block ER-driven metastasis

AR Signaling in Human Malignancies: Prostate Cancer and Beyond.

Science.gov (United States)

Antonarakis, Emmanuel S

2018-01-18

The notion that androgens and androgen receptor (AR) signaling are the hallmarks of prostate cancer oncogenesis and disease progression is generally well accepted. What is more poorly understood is the role of AR signaling in other human malignancies. This special issue of Cancers initially reviews the role of AR in advanced prostate cancer, and then explores the potential importance of AR signaling in other epithelial malignancies. The first few articles focus on the use of novel AR-targeting therapies in castration-resistant prostate cancer and the mechanisms of resistance to novel antiandrogens, and they also outline the interaction between AR and other cellular pathways, including PI3 kinase signaling, transcriptional regulation, angiogenesis, stromal factors, Wnt signaling, and epigenetic regulation in prostate cancer. The next several articles review the possible role of androgens and AR signaling in breast cancer, bladder cancer, salivary gland cancer, and hepatocellular carcinoma, as well as the potential treatment implications of using antiandrogen therapies in these non-prostatic malignancies.

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

Science.gov (United States)

Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

International Cancer Screening Network

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The International Cancer Screening Network promotes evidence-based cancer screening implementation and evaluation with cooperation from multilateral organizations around the globe. Learn more about how ICSN aims to reduce the global burden of cancer by supporting research and international collaboration.

RMOD: a tool for regulatory motif detection in signaling network.

Directory of Open Access Journals (Sweden)

Jinki Kim

Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

Identification and analysis of signaling networks potentially involved in breast carcinoma metastasis to the brain.

Directory of Open Access Journals (Sweden)

Feng Li

Full Text Available Brain is a common site of breast cancer metastasis associated with significant neurologic morbidity, decreased quality of life, and greatly shortened survival. However, the molecular and cellular mechanisms underpinning brain colonization by breast carcinoma cells are poorly understood. Here, we used 2D-DIGE (Difference in Gel Electrophoresis proteomic analysis followed by LC-tandem mass spectrometry to identify the proteins differentially expressed in brain-targeting breast carcinoma cells (MB231-Br compared with parental MDA-MB-231 cell line. Between the two cell lines, we identified 12 proteins consistently exhibiting greater than 2-fold (p<0.05 difference in expression, which were associated by the Ingenuity Pathway Analysis (IPA with two major signaling networks involving TNFα/TGFβ-, NFκB-, HSP-70-, TP53-, and IFNγ-associated pathways. Remarkably, highly related networks were revealed by the IPA analysis of a list of 19 brain-metastasis-associated proteins identified recently by the group of Dr. A. Sierra using MDA-MB-435-based experimental system (Martin et al., J Proteome Res 2008 7:908-20, or a 17-gene classifier associated with breast cancer brain relapse reported by the group of Dr. J. Massague based on a microarray analysis of clinically annotated breast tumors from 368 patients (Bos et al., Nature 2009 459: 1005-9. These findings, showing that different experimental systems and approaches (2D-DIGE proteomics used on brain targeting cell lines or gene expression analysis of patient samples with documented brain relapse yield highly related signaling networks, suggest strongly that these signaling networks could be essential for a successful colonization of the brain by metastatic breast carcinoma cells.

Cancer association study of aminoacyl-tRNA synthetase signaling network in glioblastoma.

Directory of Open Access Journals (Sweden)

Yong-Wan Kim

Full Text Available Aminoacyl-tRNA synthetases (ARSs and ARS-interacting multifunctional proteins (AIMPs exhibit remarkable functional versatility beyond their catalytic activities in protein synthesis. Their non-canonical functions have been pathologically linked to cancers. Here we described our integrative genome-wide analysis of ARSs to show cancer-associated activities in glioblastoma multiforme (GBM, the most aggressive malignant primary brain tumor. We first selected 23 ARS/AIMPs (together referred to as ARSN, 124 cancer-associated druggable target genes (DTGs and 404 protein-protein interactors (PPIs of ARSs using NCI's cancer gene index. 254 GBM affymetrix microarray data in The Cancer Genome Atlas (TCGA were used to identify the probe sets whose expression were most strongly correlated with survival (Kaplan-Meier plots versus survival times, log-rank t-test <0.05. The analysis identified 122 probe sets as survival signatures, including 5 of ARSN (VARS, QARS, CARS, NARS, FARS, and 115 of DTGs and PPIs (PARD3, RXRB, ATP5C1, HSP90AA1, CD44, THRA, TRAF2, KRT10, MED12, etc. Of note, 61 survival-related probes were differentially expressed in three different prognosis subgroups in GBM patients and showed correlation with established prognosis markers such as age and phenotypic molecular signatures. CARS and FARS also showed significantly higher association with different molecular networks in GBM patients. Taken together, our findings demonstrate evidence for an ARSN biology-dominant contribution in the biology of GBM.

Genome network medicine: innovation to overcome huge challenges in cancer therapy.

Science.gov (United States)

Roukos, Dimitrios H

2014-01-01

The post-ENCODE era shapes now a new biomedical research direction for understanding transcriptional and signaling networks driving gene expression and core cellular processes such as cell fate, survival, and apoptosis. Over the past half century, the Francis Crick 'central dogma' of single n gene/protein-phenotype (trait/disease) has defined biology, human physiology, disease, diagnostics, and drugs discovery. However, the ENCODE project and several other genomic studies using high-throughput sequencing technologies, computational strategies, and imaging techniques to visualize regulatory networks, provide evidence that transcriptional process and gene expression are regulated by highly complex dynamic molecular and signaling networks. This Focus article describes the linear experimentation-based limitations of diagnostics and therapeutics to cure advanced cancer and the need to move on from reductionist to network-based approaches. With evident a wide genomic heterogeneity, the power and challenges of next-generation sequencing (NGS) technologies to identify a patient's personal mutational landscape for tailoring the best target drugs in the individual patient are discussed. However, the available drugs are not capable of targeting aberrant signaling networks and research on functional transcriptional heterogeneity and functional genome organization is poorly understood. Therefore, the future clinical genome network medicine aiming at overcoming multiple problems in the new fields of regulatory DNA mapping, noncoding RNA, enhancer RNAs, and dynamic complexity of transcriptional circuitry are also discussed expecting in new innovation technology and strong appreciation of clinical data and evidence-based medicine. The problematic and potential solutions in the discovery of next-generation, molecular, and signaling circuitry-based biomarkers and drugs are explored. © 2013 Wiley Periodicals, Inc.

Information flow in a network of dispersed signalers-receivers

Science.gov (United States)

Halupka, Konrad

2017-11-01

I consider a stochastic model of multi-agent communication in regular network. The model describes how dispersed animals exchange information. Each agent can initiate and transfer the signal to its nearest neighbors, who may pass it farther. For an external observer of busy networks, signaling activity may appear random, even though information flow actually thrives. Only when signal initiation and transfer are at low levels do spatiotemporal autocorrelations emerge as clumping signaling activity in space and pink noise time series. Under such conditions, the costs of signaling are moderate, but the signaler can reach a large audience. I propose that real-world networks of dispersed signalers-receivers may self-organize into this state and the flow of information maintains their integrity.

Targeting Stromal-Cancer Cell Crosstalk Networks in Ovarian Cancer Treatment

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Tsz-Lun Yeung

2016-01-01

Full Text Available Ovarian cancer is a histologically, clinically, and molecularly diverse disease with a five-year survival rate of less than 30%. It has been estimated that approximately 21,980 new cases of epithelial ovarian cancer will be diagnosed and 14,270 deaths will occur in the United States in 2015, making it the most lethal gynecologic malignancy. Ovarian tumor tissue is composed of cancer cells and a collection of different stromal cells. There is increasing evidence that demonstrates that stromal involvement is important in ovarian cancer pathogenesis. Therefore, stroma-specific signaling pathways, stroma-derived factors, and genetic changes in the tumor stroma present unique opportunities for improving the diagnosis and treatment of ovarian cancer. Cancer-associated fibroblasts (CAFs are one of the major components of the tumor stroma that have demonstrated supportive roles in tumor progression. In this review, we highlight various types of signaling crosstalk between ovarian cancer cells and stromal cells, particularly with CAFs. In addition to evaluating the importance of signaling crosstalk in ovarian cancer progression, we discuss approaches that can be used to target tumor-promoting signaling crosstalk and how these approaches can be translated into potential ovarian cancer treatment.

[Intracellular signaling mechanisms in thyroid cancer].

Science.gov (United States)

Mondragón-Terán, Paul; López-Hernández, Luz Berenice; Gutiérrez-Salinas, José; Suárez-Cuenca, Juan Antonio; Luna-Ceballos, Rosa Isela; Erazo Valle-Solís, Aura

2016-01-01

Thyroid cancer is the most common malignancy of the endocrine system, the papillary variant accounts for 80-90% of all diagnosed cases. In the development of papillary thyroid cancer, BRAF and RAS genes are mainly affected, resulting in a modification of the system of intracellular signaling proteins known as «protein kinase mitogen-activated» (MAPK) which consist of «modules» of internal signaling proteins (Receptor/Ras/Raf/MEK/ERK) from the cell membrane to the nucleus. In thyroid cancer, these signanling proteins regulate diverse cellular processes such as differentiation, growth, development and apoptosis. MAPK play an important role in the pathogenesis of thyroid cancer as they are used as molecular biomarkers for diagnostic, prognostic and as possible therapeutic molecular targets. Mutations in BRAF gene have been correlated with poor response to treatment with traditional chemotherapy and as an indicator of poor prognosis. To review the molecular mechanisms involved in intracellular signaling of BRAF and RAS genes in thyroid cancer. Molecular therapy research is in progress for this type of cancer as new molecules have been developed in order to inhibit any of the components of the signaling pathway (RET/PTC)/Ras/Raf/MEK/ERK; with special emphasis on the (RET/PTC)/Ras/Raf section, which is a major effector of ERK pathway. Copyright © 2016 Academia Mexicana de Cirugía A.C. Publicado por Masson Doyma México S.A. All rights reserved.

Pharmacodynamic Assay Panel for Monitoring Phospho-Signaling Networks | Office of Cancer Clinical Proteomics Research

Science.gov (United States)

The DNA damage response (DDR) is a highly regulated signal transduction network that orchestrates the temporal and spatial organization of protein complexes required to repair (or tolerate) DNA damage (e.g., nucleotide excision repair, base excision repair, homologous recombination, non-homologous end joining, post-replication repair).

Synchronization transmission of laser pattern signal within uncertain switched network

Science.gov (United States)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

Quantitative phosphoproteomics to characterize signaling networks

DEFF Research Database (Denmark)

Rigbolt, Kristoffer T G; Blagoev, Blagoy

2012-01-01

for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify......Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform...... and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments...

Analysis and logical modeling of biological signaling transduction networks

Science.gov (United States)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

Directory of Open Access Journals (Sweden)

Ram Prahlad T

2008-08-01

Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models

Cancer Genetics and Signaling | Center for Cancer Research

Science.gov (United States)

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows participate in a structured mentoring program designed for scientific and career development and transition to independent positions.

Androgen Receptor Signaling in Bladder Cancer

OpenAIRE

Li, Peng; Chen, Jinbo; Miyamoto, Hiroshi

2017-01-01

Emerging preclinical findings have indicated that steroid hormone receptor signaling plays an important role in bladder cancer outgrowth. In particular, androgen-mediated androgen receptor signals have been shown to correlate with the promotion of tumor development and progression, which may clearly explain some sex-specific differences in bladder cancer. This review summarizes and discusses the available data, suggesting the involvement of androgens and/or the androgen receptor pathways in u...

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

Science.gov (United States)

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

Science.gov (United States)

Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

2012-01-01

High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

The ErbB family and androgen receptor signaling are targets of Celecoxib in prostate cancer.

Science.gov (United States)

Brizzolara, Antonella; Benelli, Roberto; Venè, Roberta; Barboro, Paola; Poggi, Alessandro; Tosetti, Francesca; Ferrari, Nicoletta

2017-08-01

Inflammation plays a central role in prostate cancer (PCa) development through significant crosstalk between the COX-2-ErbB family receptor network and androgen receptor (AR)-EGFR signaling pathways. The purpose of this work was to determine the ability of the COX-2 inhibitor Celecoxib to modulate the EGFR-AR signaling pathway in androgen-dependent PCa cells and to provide a rationale for its beneficial use in chemopreventive strategies. Functional studies of Celecoxib activity were performed on LNCaP prostate cancer cells. Western blotting, gene expression analysis, dual-luciferase reporter assay and ELISA were applied to assess the Celecoxib mechanisms of action. We found that Celecoxib, through EGF and amphiregulin (AREG) induction, caused EGFR and ErbB2 activation and consequent degradation associated with the inhibition of androgenic signaling. By upregulating the E3 ubiquitin ligase Nrdp1, Celecoxib also efficiently downregulated ErbB3, which is strongly implicated in castration-resistant prostate cancer. Lastly, Celecoxib directly regulated AR transcription and translation independent of ErbB activation by downregulating the RNA binding protein heterogeneous nuclear ribonucleoprotein K (hnRNP K). The simultaneous suppression of ErbB kinases and androgen signaling by Celecoxib represents a novel strategy to interrupt the vicious cycle of AR/ErbB cross-talk with the primary purpose of undermining their resilient signaling in prostate cancer progression. Our data provide important premises for the chemopreventive use of Celecoxib in the clinical management of prostate cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Pleiotrophin Signaling Through PTNR in Breast Cancer

National Research Council Canada - National Science Library

Powers, Ciaron

2001-01-01

... of intracellular signaling cascades. The pleiotrophin signaling pathway is known to be important in angiogenesis and breast cancer growth, but the exact mechanisms of pleiotrophin signaling remain undefined...

Network information improves cancer outcome prediction.

Science.gov (United States)

Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

2014-07-01

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Detection test of wireless network signal strength and GPS positioning signal in underground pipeline

Science.gov (United States)

Li, Li; Zhang, Yunwei; Chen, Ling

2018-03-01

In order to solve the problem of selecting positioning technology for inspection robot in underground pipeline environment, the wireless network signal strength and GPS positioning signal testing are carried out in the actual underground pipeline environment. Firstly, the strength variation of the 3G wireless network signal and Wi-Fi wireless signal provided by China Telecom and China Unicom ground base stations are tested, and the attenuation law of these wireless signals along the pipeline is analyzed quantitatively and described. Then, the receiving data of the GPS satellite signal in the pipeline are tested, and the attenuation of GPS satellite signal under underground pipeline is analyzed. The testing results may be reference for other related research which need to consider positioning in pipeline.

Decoding signalling networks by mass spectrometry-based proteomics

DEFF Research Database (Denmark)

Choudhary, Chuna Ram; Mann, Matthias

2010-01-01

Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system......-wide characterization of signalling events at the levels of post-translational modifications, protein-protein interactions and changes in protein expression. This technology delivers accurate and unbiased information about the quantitative changes of thousands of proteins and their modifications in response to any...... perturbation. Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation. Large-scale proteomics-based signalling research will fundamentally change our understanding of signalling networks....

Prioritizing Signaling Information Transmission in Next Generation Networks

Directory of Open Access Journals (Sweden)

Jasmina Baraković

2011-01-01

Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.

Retinoid Signaling in Pancreatic Cancer, Injury and Regeneration

Science.gov (United States)

Colvin, Emily K.; Susanto, Johana M.; Kench, James G.; Ong, Vivienna N.; Mawson, Amanda; Pinese, Mark; Chang, David K.; Rooman, Ilse; O'Toole, Sandra A.; Segara, Davendra; Musgrove, Elizabeth A.; Sutherland, Robert L.; Apte, Minoti V.; Scarlett, Christopher J.; Biankin, Andrew V.

2011-01-01

Background Activation of embryonic signaling pathways quiescent in the adult pancreas is a feature of pancreatic cancer (PC). These discoveries have led to the development of novel inhibitors of pathways such as Notch and Hedgehog signaling that are currently in early phase clinical trials in the treatment of several cancer types. Retinoid signaling is also essential for pancreatic development, and retinoid therapy is used successfully in other malignancies such as leukemia, but little is known concerning retinoid signaling in PC. Methodology/Principal Findings We investigated the role of retinoid signaling in vitro and in vivo in normal pancreas, pancreatic injury, regeneration and cancer. Retinoid signaling is active in occasional cells in the adult pancreas but is markedly augmented throughout the parenchyma during injury and regeneration. Both chemically induced and genetically engineered mouse models of PC exhibit a lack of retinoid signaling activity compared to normal pancreas. As a consequence, we investigated Cellular Retinoid Binding Protein 1 (CRBP1), a key regulator of retinoid signaling known to play a role in breast cancer development, as a potential therapeutic target. Loss, or significant downregulation of CRBP1 was present in 70% of human PC, and was evident in the very earliest precursor lesions (PanIN-1A). However, in vitro gain and loss of function studies and CRBP1 knockout mice suggested that loss of CRBP1 expression alone was not sufficient to induce carcinogenesis or to alter PC sensitivity to retinoid based therapies. Conclusions/Significance In conclusion, retinoid signalling appears to play a role in pancreatic regeneration and carcinogenesis, but unlike breast cancer, it is not mediated directly by CRBP1. PMID:22220202

Retinoid signaling in pancreatic cancer, injury and regeneration.

Directory of Open Access Journals (Sweden)

Emily K Colvin

Full Text Available BACKGROUND: Activation of embryonic signaling pathways quiescent in the adult pancreas is a feature of pancreatic cancer (PC. These discoveries have led to the development of novel inhibitors of pathways such as Notch and Hedgehog signaling that are currently in early phase clinical trials in the treatment of several cancer types. Retinoid signaling is also essential for pancreatic development, and retinoid therapy is used successfully in other malignancies such as leukemia, but little is known concerning retinoid signaling in PC. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the role of retinoid signaling in vitro and in vivo in normal pancreas, pancreatic injury, regeneration and cancer. Retinoid signaling is active in occasional cells in the adult pancreas but is markedly augmented throughout the parenchyma during injury and regeneration. Both chemically induced and genetically engineered mouse models of PC exhibit a lack of retinoid signaling activity compared to normal pancreas. As a consequence, we investigated Cellular Retinoid Binding Protein 1 (CRBP1, a key regulator of retinoid signaling known to play a role in breast cancer development, as a potential therapeutic target. Loss, or significant downregulation of CRBP1 was present in 70% of human PC, and was evident in the very earliest precursor lesions (PanIN-1A. However, in vitro gain and loss of function studies and CRBP1 knockout mice suggested that loss of CRBP1 expression alone was not sufficient to induce carcinogenesis or to alter PC sensitivity to retinoid based therapies. CONCLUSIONS/SIGNIFICANCE: In conclusion, retinoid signalling appears to play a role in pancreatic regeneration and carcinogenesis, but unlike breast cancer, it is not mediated directly by CRBP1.

All-optical network coding for DPSK signals

DEFF Research Database (Denmark)

An, Yi; Da Ros, Francesco; Peucheret, Christophe

2013-01-01

All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB.......All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB....

The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

Directory of Open Access Journals (Sweden)

Frank eEmmert-Streib

2014-02-01

Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

Androgen Receptor Signaling in Bladder Cancer

Science.gov (United States)

Li, Peng; Chen, Jinbo; Miyamoto, Hiroshi

2017-01-01

Emerging preclinical findings have indicated that steroid hormone receptor signaling plays an important role in bladder cancer outgrowth. In particular, androgen-mediated androgen receptor signals have been shown to correlate with the promotion of tumor development and progression, which may clearly explain some sex-specific differences in bladder cancer. This review summarizes and discusses the available data, suggesting the involvement of androgens and/or the androgen receptor pathways in urothelial carcinogenesis as well as tumor growth. While the precise mechanisms of the functions of the androgen receptor in urothelial cells remain far from being fully understood, current evidence may offer chemopreventive or therapeutic options, using androgen deprivation therapy, in patients with bladder cancer. PMID:28241422

Androgen Receptor Signaling in Bladder Cancer

Directory of Open Access Journals (Sweden)

Peng Li

2017-02-01

Full Text Available Emerging preclinical findings have indicated that steroid hormone receptor signaling plays an important role in bladder cancer outgrowth. In particular, androgen-mediated androgen receptor signals have been shown to correlate with the promotion of tumor development and progression, which may clearly explain some sex-specific differences in bladder cancer. This review summarizes and discusses the available data, suggesting the involvement of androgens and/or the androgen receptor pathways in urothelial carcinogenesis as well as tumor growth. While the precise mechanisms of the functions of the androgen receptor in urothelial cells remain far from being fully understood, current evidence may offer chemopreventive or therapeutic options, using androgen deprivation therapy, in patients with bladder cancer.

Tyrosine kinase signalling in breast cancer

International Nuclear Information System (INIS)

Hynes, Nancy E

2000-01-01

Cells are continuously exposed to diverse stimuli ranging from soluble endocrine and paracrine factors to signalling molecules on neighbouring cells. Receptors of the tyrosine kinase family play an important role in the integration and interpretation of these external stimuli, allowing a cell to respond appropriately to its environment. The activation of receptor tyrosine kinases (RTKs) is tightly controlled, allowing a normal cell to correctly integrate its external environment with internal signal transduction pathways. In contrast, due to numerous molecular alterations arising during the course of malignancy, a tumour is characterized by an abnormal response to its environment, which allows cancer cells to evade the normal mechanisms controlling cellular proliferation. Alterations in the expression of various RTKs, in their activation, and in the signalling molecules lying downstream of the receptors play important roles in the development of cancer. This topic is the major focus of the thematic review section of this issue of Breast Cancer Research

Modeling evolution of crosstalk in noisy signal transduction networks

Science.gov (United States)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

Mathematical Modelling Plant Signalling Networks

KAUST Repository

Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

2013-01-01

methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

Fiber fault location utilizing traffic signal in optical network.

Science.gov (United States)

Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

2013-10-07

We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

Dopamine D1 signaling organizes network dynamics underlying working memory.

Science.gov (United States)

Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

2016-06-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

Application of neural networks to signal prediction in nuclear power plant

International Nuclear Information System (INIS)

Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

1993-01-01

This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

Mapping the follicle-stimulating hormone-induced signalling networks

Directory of Open Access Journals (Sweden)

Pauline eGloaguen

2011-10-01

Full Text Available Follicle-stimulating hormone (FSH is a central regulator of male and female reproductive function. Over the last decade, there has been a growing perception of the complexity associated with FSH-induced cellular signalling. It is now clear that the canonical Gs/cAMP/PKA pathway is not the sole mechanism that must be considered in FSH biological actions. In parallel, consistent with the emerging concept of biased agonism, several examples of ligand-mediated selective signalling pathway activation by gonadotropin receptors have been reported. In this context, it is important to gain an integrative view of the signalling pathways induced by FSH and how they interconnect to form a network. In this review, we propose a first attempt at building topological maps of various pathways known to be involved in the FSH-induced signalling network. We discuss the multiple facets of FSH-induced signalling and how they converge to the hormone integrated biological response. Despite of their incompleteness, these maps of the FSH-induced signalling network represent a first step towards gaining a system-level comprehension of this hormone’s actions, which may ultimately facilitate the discovery of novel regulatory processes and therapeutic strategies for infertilities and non-steroidal contraception.

[Development of Holistic Cancer Treatment Centering Cancer Patients - From the Standpoint of Hypoxia and Hedgehog Signaling].

Science.gov (United States)

Onishi, Hideya; Ogino, Toshitatsu; Morisaki, Takashi; Katano, Mitsuo

2017-11-01

Recently, hypoxia that is one of cancer microenvironments, takes much attention. Because circumstance that we usually perform experiment is 20% O2 condition, it is likely that different signaling pathways may be activated in vivo cancer. We focused Hedgehog(Hh)signaling as one of activated pathways under hypoxia. It has been shown that Hh signaling is activated under hypoxia, followed by inducing malignant phenotypes in pancreatic cancer. Therefore, Hh signaling inhibitor should elicit anti-tumor effect. However, if we consider "whole-person therapy" we should confirm how Hh signaling affects the function of immune cells. In the present study, we describe hypoxia/Hh signaling/functions of cancer cells and immune cells focusing our previous results.

Evolution of SH2 domains and phosphotyrosine signalling networks

Science.gov (United States)

Liu, Bernard A.; Nash, Piers D.

2012-01-01

Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

Online Social Networks - Opportunities for Empowering Cancer Patients.

Science.gov (United States)

Mohammadzadeh, Zeinab; Davoodi, Somayeh; Ghazisaeidi, Marjan

2016-01-01

Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Directory of Open Access Journals (Sweden)

Yang X

2018-03-01

Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the

Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes.

Science.gov (United States)

Chen, Juan; Xu, Juan; Li, Yongsheng; Zhang, Jinwen; Chen, Hong; Lu, Jianping; Wang, Zishan; Zhao, Xueying; Xu, Kang; Li, Yixue; Li, Xia; Zhang, Yan

2017-02-07

Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

Assuring SS7 dependability: A robustness characterization of signaling network elements

Science.gov (United States)

Karmarkar, Vikram V.

1994-04-01

Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

The cancer cell map initiative: defining the hallmark networks of cancer.

Science.gov (United States)

Krogan, Nevan J; Lippman, Scott; Agard, David A; Ashworth, Alan; Ideker, Trey

2015-05-21

Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, it is likely that successful interpretation of cancer genomes will require comprehensive knowledge of the molecular networks under selective pressure in oncogenesis. Here we announce the creation of a new effort, The Cancer Cell Map Initiative (CCMI), aimed at systematically detailing these complex interactions among cancer genes and how they differ between diseased and healthy states. We discuss recent progress that enables creation of these cancer cell maps across a range of tumor types and how they can be used to target networks disrupted in individual patients, significantly accelerating the development of precision medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

Weak signal transmission in complex networks and its application in detecting connectivity.

Science.gov (United States)

Liang, Xiaoming; Liu, Zonghua; Li, Baowen

2009-10-01

We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

Subsurface event detection and classification using Wireless Signal Networks.

Science.gov (United States)

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Human cancer protein-protein interaction network: a structural perspective.

Directory of Open Access Journals (Sweden)

Gozde Kar

2009-12-01

Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

Expansion of Sphingosine Kinase and Sphingosine-1-Phosphate Receptor Function in Normal and Cancer Cells: From Membrane Restructuring to Mediation of Estrogen Signaling and Stem Cell Programming

Science.gov (United States)

2018-01-01

Sphingolipids, sphingolipid metabolizing enzymes, and their receptors network are being recognized as part of the signaling mechanisms, which govern breast cancer cell growth, migration, and survival during chemotherapy treatment. Approximately 70% of breast cancers are estrogen receptor (ER) positive and, thus, rely on estrogen signaling. Estrogen activates an intracellular network composed of many cytoplasmic and nuclear mediators. Some estrogen effects can be mediated by sphingolipids. Estrogen activates sphingosine kinase 1 (SphK1) and amplifies the intracellular concentration of sphingosine-1-phosphate (S1P) in breast cancer cells during stimulation of proliferation and survival. Specifically, Estrogen activates S1P receptors (S1PR) and induces growth factor receptor transactivation. SphK, S1P, and S1PR expression are causally associated with endocrine resistance and progression to advanced tumor stages in ER-positive breast cancers in vivo. Recently, the network of SphK/S1PR was shown to promote the development of ER-negative cancers and breast cancer stem cells, as well as stimulating angiogenesis. Novel findings confirm and broaden our knowledge about the cross-talk between sphingolipids and estrogen network in normal and malignant cells. Current S1PRs therapeutic inhibition was indicated as a promising chemotherapy approach in non-responsive and advanced malignancies. Considering that sphingolipid signaling has a prominent role in terminally differentiated cells, the impact should be considered when designing specific SphK/S1PR inhibitors. This study analyzes the dynamic of the transformation of sphingolipid axis during a transition from normal to pathological condition on the level of the whole organism. The sphingolipid-based mediation and facilitation of global effects of estrogen were critically accented as a bridging mechanism that should be explored in cancer prevention. PMID:29385066

Expansion of Sphingosine Kinase and Sphingosine-1-Phosphate Receptor Function in Normal and Cancer Cells: From Membrane Restructuring to Mediation of Estrogen Signaling and Stem Cell Programming

Directory of Open Access Journals (Sweden)

Olga A. Sukocheva

2018-01-01

Full Text Available Sphingolipids, sphingolipid metabolizing enzymes, and their receptors network are being recognized as part of the signaling mechanisms, which govern breast cancer cell growth, migration, and survival during chemotherapy treatment. Approximately 70% of breast cancers are estrogen receptor (ER positive and, thus, rely on estrogen signaling. Estrogen activates an intracellular network composed of many cytoplasmic and nuclear mediators. Some estrogen effects can be mediated by sphingolipids. Estrogen activates sphingosine kinase 1 (SphK1 and amplifies the intracellular concentration of sphingosine-1-phosphate (S1P in breast cancer cells during stimulation of proliferation and survival. Specifically, Estrogen activates S1P receptors (S1PR and induces growth factor receptor transactivation. SphK, S1P, and S1PR expression are causally associated with endocrine resistance and progression to advanced tumor stages in ER-positive breast cancers in vivo. Recently, the network of SphK/S1PR was shown to promote the development of ER-negative cancers and breast cancer stem cells, as well as stimulating angiogenesis. Novel findings confirm and broaden our knowledge about the cross-talk between sphingolipids and estrogen network in normal and malignant cells. Current S1PRs therapeutic inhibition was indicated as a promising chemotherapy approach in non-responsive and advanced malignancies. Considering that sphingolipid signaling has a prominent role in terminally differentiated cells, the impact should be considered when designing specific SphK/S1PR inhibitors. This study analyzes the dynamic of the transformation of sphingolipid axis during a transition from normal to pathological condition on the level of the whole organism. The sphingolipid-based mediation and facilitation of global effects of estrogen were critically accented as a bridging mechanism that should be explored in cancer prevention.

Signalling network construction for modelling plant defence response.

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Dragana Miljkovic

Full Text Available Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2 triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be

Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

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Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

2017-03-01

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

Calcium and Nuclear Signaling in Prostate Cancer

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Ivan V. Maly

2018-04-01

Full Text Available Recently, there have been a number of developments in the fields of calcium and nuclear signaling that point to new avenues for a more effective diagnosis and treatment of prostate cancer. An example is the discovery of new classes of molecules involved in calcium-regulated nuclear import and nuclear calcium signaling, from the G protein-coupled receptor (GPCR and myosin families. This review surveys the new state of the calcium and nuclear signaling fields with the aim of identifying the unifying themes that hold out promise in the context of the problems presented by prostate cancer. Genomic perturbations, kinase cascades, developmental pathways, and channels and transporters are covered, with an emphasis on nuclear transport and functions. Special attention is paid to the molecular mechanisms behind prostate cancer progression to the malignant forms and the unfavorable response to anti-androgen treatment. The survey leads to some new hypotheses that connect heretofore disparate results and may present a translational interest.

Chemical Modulation of WNT Signaling in Cancer.

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Zhang, Li-Shu; Lum, Lawrence

2018-01-01

Genetically based observations stemming from defects in development and in regeneration form the foundation of our understanding regarding how the secreted WNT proteins control coordinated cell fate decision-making in adult tissues. At the same time, our anticipation of potential benefits and unwanted toxicities associated with candidate anticancer agents targeting WNT signal transduction are also reliant upon this blueprint of WNT-associated physiology. Despite the long established role of WNT signaling in cancer, the emergence of WNT signaling as a suppressor of immunological attack in melanoma reveals an unanticipated anticancer potential in targeting WNT signaling. Here we review the literature associated with WNT signaling in cancer and discuss potential challenges that may be associated with the chemical attack of this important cellular process in achieving therapeutic goals. Although a number of small molecules targeting WNT signaling are introduced here, we center our discussion on antagonists of the WNT acyltransferase porcupine (PORCN) given the recent entry of two candidate molecules in clinical testing. Copyright © 2018 Elsevier Inc. All rights reserved.

Subsurface Event Detection and Classification Using Wireless Signal Networks

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Muhannad T. Suleiman

2012-11-01

Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

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White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Protein Phosphatase 2A in the Regulation of Wnt Signaling, Stem Cells, and Cancer.

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Thompson, Joshua J; Williams, Christopher S

2018-02-26

Protein phosphorylation is a ubiquitous cellular process that allows for the nuanced and reversible regulation of protein activity. Protein phosphatase 2A (PP2A) is a heterotrimeric serine-threonine phosphatase-composed of a structural, regulatory, and catalytic subunit-that controls a variety of cellular events via protein dephosphorylation. While much is known about PP2A and its basic biochemistry, the diversity of its components-especially the multitude of regulatory subunits-has impeded the determination of PP2A function. As a consequence of this complexity, PP2A has been shown to both positively and negatively regulate signaling networks such as the Wnt pathway. Wnt signaling modulates major developmental processes, and is a dominant mediator of stem cell self-renewal, cell fate, and cancer stem cells. Because PP2A affects Wnt signaling both positively and negatively and at multiple levels, further understanding of this complex dynamic may ultimately provide insight into stem cell biology and how to better treat cancers that result from alterations in Wnt signaling. This review will summarize literature that implicates PP2A as a tumor suppressor, explore PP2A mutations identified in human malignancy, and focus on PP2A in the regulation of Wnt signaling and stem cells so as to better understand how aberrancy in this pathway can contribute to tumorigenesis.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

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Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

Navigating cancer network attractors for tumor-specific therapy

DEFF Research Database (Denmark)

Creixell, Pau; Schoof, Erwin; Erler, Janine Terra

2012-01-01

understanding of the processes by which genetic lesions perturb these networks and lead to disease phenotypes. Network biology will help circumvent fundamental obstacles in cancer treatment, such as drug resistance and metastasis, empowering personalized and tumor-specific cancer therapies....

Hierarchical feedback modules and reaction hubs in cell signaling networks.

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Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

Hierarchical feedback modules and reaction hubs in cell signaling networks.

Directory of Open Access Journals (Sweden)

Jianfeng Xu

Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

Science.gov (United States)

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

mTOR Signaling Confers Resistance to Targeted Cancer Drugs.

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Guri, Yakir; Hall, Michael N

2016-11-01

Cancer is a complex disease and a leading cause of death worldwide. Extensive research over decades has led to the development of therapies that target cancer-specific signaling pathways. However, the clinical benefits of such drugs are at best transient due to tumors displaying intrinsic or adaptive resistance. The underlying compensatory pathways that allow cancer cells to circumvent a drug blockade are poorly understood. We review here recent studies suggesting that mammalian TOR (mTOR) signaling is a major compensatory pathway conferring resistance to many cancer drugs. mTOR-mediated resistance can be cell-autonomous or non-cell-autonomous. These findings suggest that mTOR signaling should be monitored routinely in tumors and that an mTOR inhibitor should be considered as a co-therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Load-induced modulation of signal transduction networks.

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Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

2011-10-11

Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

Signaling mechanisms underlying the robustness and tunability of the plant immune network

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Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

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F. Bagheri

2013-02-01

Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer

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Samra Khalid

2016-10-01

Full Text Available Background Breast cancer (BC is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s. It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α associated Biological Regulatory Network (BRN for a small part of complex events that leads to BC metastasis. Methods A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN to analyze the logical parameters of the involved entities. Results In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. Conclusion The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR for wet lab experiments as well as provided valuable insights in the treatment of cancers

AR-Signaling in Human Malignancies: Prostate Cancer and Beyond

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Michael T. Schweizer

2017-01-01

Full Text Available In the 1940s Charles Huggins reported remarkable palliative benefits following surgical castration in men with advanced prostate cancer, and since then the androgen receptor (AR has remained the main therapeutic target in this disease. Over the past couple of decades, our understanding of AR-signaling biology has dramatically improved, and it has become apparent that the AR can modulate a number of other well-described oncogenic signaling pathways. Not surprisingly, mounting preclinical and epidemiologic data now supports a role for AR-signaling in promoting the growth and progression of several cancers other than prostate, and early phase clinical trials have documented preliminary signs of efficacy when AR-signaling inhibitors are used in several of these malignancies. In this article, we provide an overview of the evidence supporting the use of AR-directed therapies in prostate as well as other cancers, with an emphasis on the rationale for targeting AR-signaling across tumor types.

Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

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Andre Terzic

2009-04-01

Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

Using Social Network Analysis to Evaluate Community Capacity Building of a Regional Community Cancer Network

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Luque, John; Tyson, Dinorah Martinez; Lee, Ji-Hyun; Gwede, Clement; Vadaparampil, Susan; Noel-Thomas, Shalewa; Meade, Cathy

2010-01-01

The Tampa Bay Community Cancer Network (TBCCN) is one of 25 Community Network Programs funded by the National Cancer Institute's (NCI's) Center to Reduce Cancer Health Disparities with the objectives to create a collaborative infrastructure of academic and community based organizations and to develop effective and sustainable interventions to…

The impact of phosphatases on proliferative and survival signaling in cancer.

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Narla, Goutham; Sangodkar, Jaya; Ryder, Christopher B

2018-05-03

The dynamic and stringent coordination of kinase and phosphatase activity controls a myriad of physiologic processes. Aberrations that disrupt the balance of this interplay represent the basis of numerous diseases. For a variety of reasons, early work in this area portrayed kinases as the dominant actors in these signaling events with phosphatases playing a secondary role. In oncology, these efforts led to breakthroughs that have dramatically altered the course of certain diseases and directed vast resources toward the development of additional kinase-targeted therapies. Yet, more recent scientific efforts have demonstrated a prominent and sometimes driving role for phosphatases across numerous malignancies. This maturation of the phosphatase field has brought with it the promise of further therapeutic advances in the field of oncology. In this review, we discuss the role of phosphatases in the regulation of cellular proliferation and survival signaling using the examples of the MAPK and PI3K/AKT pathways, c-Myc and the apoptosis machinery. Emphasis is placed on instances where these signaling networks are perturbed by dysregulation of specific phosphatases to favor growth and persistence of human cancer.

Targeting multiple pro-apoptotic signaling pathways with curcumin in prostate cancer cells.

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Mariela Rivera

Full Text Available Curcumin, an extract from the turmeric rhizome (Curcuma longa, is known to exhibit anti-inflammatory, antioxidant, chemopreventive and antitumoral activities against aggressive and recurrent cancers. Accumulative data indicate that curcumin may induce cancer cell death. However, the detailed mechanism underlying its pro-apoptotic and anti-cancer effects remains to be elucidated. In the present study, we examined the signaling pathways triggered by curcumin, specifically, the exact molecular mechanisms of curcumin-induced apoptosis in highly metastatic human prostate cancer cells. The effect of curcumin was evaluated using for the first time in prostate cancer, a gel-free shotgun quantitative proteomic analysis coupled with Tandem Mass Tag isobaric labeling-based-signaling networks. Results were confirmed at the gene expression level by qRT-PCR and at the protein expression level by western blot and flow cytometry. Our findings revealed that curcumin induced an Endoplasmic Reticulum stress-mediated apoptosis in PC3. The mechanisms by which curcumin promoted cell death in these cells were associated with cell cycle arrest, increased reactive oxygen species, autophagy and the Unfolded Protein Response. Furthermore, the upregulation of ER stress was measured using key indicators of ER stress: Glucose-Regulated Protein 78, Inositol-Requiring Enzyme 1 alpha, Protein Disulfide isomerase and Calreticulin. Chronic ER stress induction was concomitant with the upregulation of pro-apoptotic markers (caspases 3,9,12 and Poly (ADP-ribose polymerase. The downregulated proteins include anti-apoptotic and anti-tumor markers, supporting their curcumin-induced pro-apoptotic role in prostate cancer cells. Taken together, these data suggest that curcumin may serve as a promising anticancer agent by inducing a chronic ER stress mediated cell death and activation of cell cycle arrest, UPR, autophagy and oxidative stress responses.

Targeting multiple pro-apoptotic signaling pathways with curcumin in prostate cancer cells

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Rivera, Mariela; Ramos, Yanilda; Rodríguez-Valentín, Madeline; López-Acevedo, Sheila; Cubano, Luis A.; Zou, Jin; Zhang, Qiang; Wang, Guangdi

2017-01-01

Curcumin, an extract from the turmeric rhizome (Curcuma longa), is known to exhibit anti-inflammatory, antioxidant, chemopreventive and antitumoral activities against aggressive and recurrent cancers. Accumulative data indicate that curcumin may induce cancer cell death. However, the detailed mechanism underlying its pro-apoptotic and anti-cancer effects remains to be elucidated. In the present study, we examined the signaling pathways triggered by curcumin, specifically, the exact molecular mechanisms of curcumin-induced apoptosis in highly metastatic human prostate cancer cells. The effect of curcumin was evaluated using for the first time in prostate cancer, a gel-free shotgun quantitative proteomic analysis coupled with Tandem Mass Tag isobaric labeling-based-signaling networks. Results were confirmed at the gene expression level by qRT-PCR and at the protein expression level by western blot and flow cytometry. Our findings revealed that curcumin induced an Endoplasmic Reticulum stress-mediated apoptosis in PC3. The mechanisms by which curcumin promoted cell death in these cells were associated with cell cycle arrest, increased reactive oxygen species, autophagy and the Unfolded Protein Response. Furthermore, the upregulation of ER stress was measured using key indicators of ER stress: Glucose-Regulated Protein 78, Inositol-Requiring Enzyme 1 alpha, Protein Disulfide isomerase and Calreticulin. Chronic ER stress induction was concomitant with the upregulation of pro-apoptotic markers (caspases 3,9,12) and Poly (ADP-ribose) polymerase. The downregulated proteins include anti-apoptotic and anti-tumor markers, supporting their curcumin-induced pro-apoptotic role in prostate cancer cells. Taken together, these data suggest that curcumin may serve as a promising anticancer agent by inducing a chronic ER stress mediated cell death and activation of cell cycle arrest, UPR, autophagy and oxidative stress responses. PMID:28628644

Altered small-world properties of gray matter networks in breast cancer

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Hosseini S M

2012-05-01

Full Text Available Abstract Background Breast cancer survivors, particularly those treated with chemotherapy, are at significantly increased risk for long-term cognitive and neurobiologic impairments. These deficits tend to involve skills that are subserved by distributed brain networks. Additionally, neuroimaging studies have shown a diffuse pattern of brain structure changes in chemotherapy-treated breast cancer survivors that might impact large-scale brain networks. Methods We therefore applied graph theoretical analysis to compare the gray matter structural networks of female breast cancer survivors with a history of chemotherapy treatment and healthy age and education matched female controls. Results Results revealed reduced clustering coefficient and small-world index in the brain network of the breast cancer patients across a range of network densities. In addition, the network of the breast cancer group had less highly interactive nodes and reduced degree/centrality in the frontotemporal regions compared to controls, which may help explain the common impairments of memory and executive functioning among these patients. Conclusions These results suggest that breast cancer and chemotherapy may decrease regional connectivity as well as global network organization and integration, reducing efficiency of the network. To our knowledge, this is the first report of altered large-scale brain networks associated with breast cancer and chemotherapy.

Stochastic effects as a force to increase the complexity of signaling networks

KAUST Repository

Kuwahara, Hiroyuki

2013-07-29

Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.

Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

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Zhi Zheng

2012-01-01

Full Text Available A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells.

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

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Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

2018-04-01

The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

Network perturbation by recurrent regulatory variants in cancer.

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Kiwon Jang

2017-03-01

Full Text Available Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.

Optical Performance Monitoring and Signal Optimization in Optical Networks

DEFF Research Database (Denmark)

Petersen, Martin Nordal

2006-01-01

The thesis studies performance monitoring for the next generation optical networks. The focus is on all-optical networks with bit-rates of 10 Gb/s or above. Next generation all-optical networks offer large challenges as the optical transmitted distance increases and the occurrence of electrical-optical......-electrical regeneration points decreases. This thesis evaluates the impact of signal degrading effects that are becoming of increasing concern in all-optical high-speed networks due to all-optical switching and higher bit-rates. Especially group-velocity-dispersion (GVD) and a number of nonlinear effects will require...... enhanced attention to avoid signal degradations. The requirements for optical performance monitoring features are discussed, and the thesis evaluates the advantages and necessity of increasing the level of performance monitoring parameters in the physical layer. In particular, methods for optical...

OPNET simulation Signaling System No.7 (SS7) network interfaces

OpenAIRE

Ow, Kong Chung.

2000-01-01

This thesis presents an OPNET model and simulation of the Signaling System No.7 (SS7) network, which is dubbed the world's largest data communications network. The main focus of the study is to model one of its levels, the Message Transfer Part Level 3, in accordance with the ITU.T recommendation Q.704. An overview of SS7 that includes the evolution and basics of SS7 architecture is provided to familarize the reader with the topic. This includes the protocol stack, signaling points, signaling...

Hedgehog Signals Mediate Anti-Cancer Drug Resistance in Three-Dimensional Primary Colorectal Cancer Organoid Culture

Directory of Open Access Journals (Sweden)

Tatsuya Usui

2018-04-01

Full Text Available Colorectal cancer is one of the most common causes of cancer death worldwide. In patients with metastatic colorectal cancer, combination treatment with several anti-cancer drugs is employed and improves overall survival in some patients. Nevertheless, most patients with metastatic disease are not cured owing to the drug resistance. Cancer stem cells are known to regulate resistance to chemotherapy. In the previous study, we established a novel three-dimensional organoid culture model from tumor colorectal tissues of human patients using an air–liquid interface (ALI method, which contained numerous cancer stem cells and showed resistance to 5-fluorouracil (5-FU and Irinotecan. Here, we investigate which inhibitor for stem cell-related signal improves the sensitivity for anti-cancer drug treatment in tumor ALI organoids. Treatment with Hedgehog signal inhibitors (AY9944, GANT61 decreases the cell viability of organoids compared with Notch (YO-01027, DAPT and Wnt (WAV939, Wnt-C59 signal inhibitors. Combination treatment of AY9944 or GANT61 with 5-FU, Irinotecan or Oxaliplatin decreases the cell viability of tumor organoids compared with each anti-cancer drug alone treatment. Treatment with AY9944 or GANT61 inhibits expression of stem cell markers c-Myc, CD44 and Nanog, likely through the decrease of their transcription factor, GLI-1 expression. Combination treatment of AY9944 or GANT61 with 5-FU or Irinotecan also prevents colony formation of colorectal cancer cell lines HCT116 and SW480. These findings suggest that Hedgehog signals mediate anti-cancer drug resistance in colorectal tumor patient-derived ALI organoids and that the inhibitors are useful as a combinational therapeutic strategy against colorectal cancer.

Reverse engineering GTPase programming languages with reconstituted signaling networks.

Science.gov (United States)

Coyle, Scott M

2016-07-02

The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

Systems Perturbation Analysis of a Large-Scale Signal Transduction Model Reveals Potentially Influential Candidates for Cancer Therapeutics

Science.gov (United States)

Puniya, Bhanwar Lal; Allen, Laura; Hochfelder, Colleen; Majumder, Mahbubul; Helikar, Tomáš

2016-01-01

Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. Computational approaches such as network analysis are important tools to understand system dynamics as well as to identify critical components that could be further explored as therapeutic targets. Here, we performed perturbation analysis of a large-scale signal transduction model in extracellular environments that stimulate cell death, growth, motility, and quiescence. Each of the model’s components was perturbed under both loss-of-function and gain-of-function mutations. Using 1,300 simulations under both types of perturbations across various extracellular conditions, we identified the most and least influential components based on the magnitude of their influence on the rest of the system. Based on the premise that the most influential components might serve as better drug targets, we characterized them for biological functions, housekeeping genes, essential genes, and druggable proteins. The most influential components under all environmental conditions were enriched with several biological processes. The inositol pathway was found as most influential under inactivating perturbations, whereas the kinase and small lung cancer pathways were identified as the most influential under activating perturbations. The most influential components were enriched with essential genes and druggable proteins. Moreover, known cancer drug targets were also classified in influential components based on the affected components in the network. Additionally, the systemic perturbation analysis of the model revealed a network motif of most influential components which affect each other. Furthermore, our analysis predicted novel combinations of cancer drug targets with various effects on other most influential components. We found that the combinatorial perturbation consisting of PI3K inactivation and overactivation of IP3R1 can lead to increased activity levels of apoptosis

Proteomic approaches for quantitative cancer cell signaling

DEFF Research Database (Denmark)

Voellmy, Franziska

studies in an effort to contribute to the study of signaling dynamics in cancer systems. This thesis is divided into two parts. Part I begins with a brief introduction in the use of omics in systems cancer research with a focus on mass spectrometry as a means to quantitatively measure protein...

Lessons Learned from the Young Breast Cancer Survivorship Network.

Science.gov (United States)

Gisiger-Camata, Silvia; Nolan, Timiya S; Vo, Jacqueline B; Bail, Jennifer R; Lewis, Kayla A; Meneses, Karen

2017-11-30

The Young Breast Cancer Survivors Network (Network) is an academic and community-based partnership dedicated to education, support, and networking. The Network used a multi-pronged approach via monthly support and networking, annual education seminars, website networking, and individual survivor consultation. Formative and summative evaluations were conducted using group survey and individual survivor interviews for monthly gatherings, annual education meetings, and individual consultation. Google Analytics was applied to evaluate website use. The Network began with 4 initial partnerships and grew to 38 in the period from 2011 to 2017. During this 5-year period, 5 annual meetings (598 attendees), 23 support and networking meetings (373), and 115 individual survivor consultations were conducted. The Network website had nearly 12,000 individual users and more than 25,000 page views. Lessons learned include active community engagement, survivor empowerment, capacity building, social media outreach, and network sustainability. The 5-year experiences with the Network demonstrated that a regional program dedicated to the education, support, networking, and needs of young breast cancer survivors and their families can become a vital part of cancer survivorship services in a community. Strong community support, engagement, and encouragement were vital components to sustain the program.

Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

Science.gov (United States)

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

Signal Transduction Pathways of TNAP: Molecular Network Analyses.

Science.gov (United States)

Négyessy, László; Györffy, Balázs; Hanics, János; Bányai, Mihály; Fonta, Caroline; Bazsó, Fülöp

2015-01-01

Despite the growing body of evidence pointing on the involvement of tissue non-specific alkaline phosphatase (TNAP) in brain function and diseases like epilepsy and Alzheimer's disease, our understanding about the role of TNAP in the regulation of neurotransmission is severely limited. The aim of our study was to integrate the fragmented knowledge into a comprehensive view regarding neuronal functions of TNAP using objective tools. As a model we used the signal transduction molecular network of a pyramidal neuron after complementing with TNAP related data and performed the analysis using graph theoretic tools. The analyses show that TNAP is in the crossroad of numerous pathways and therefore is one of the key players of the neuronal signal transduction network. Through many of its connections, most notably with molecules of the purinergic system, TNAP serves as a controller by funnelling signal flow towards a subset of molecules. TNAP also appears as the source of signal to be spread via interactions with molecules involved among others in neurodegeneration. Cluster analyses identified TNAP as part of the second messenger signalling cascade. However, TNAP also forms connections with other functional groups involved in neuronal signal transduction. The results indicate the distinct ways of involvement of TNAP in multiple neuronal functions and diseases.

Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

International Nuclear Information System (INIS)

Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

2006-01-01

The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

Hybrid digital signal processing and neural networks applications in PWRs

International Nuclear Information System (INIS)

Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

1991-01-01

Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

Ganoderma lucidum targeting lung cancer signaling: A review.

Science.gov (United States)

Gill, Balraj Singh; Navgeet; Kumar, Sanjeev

2017-06-01

Lung cancer causes huge mortality to population, and pharmaceutical companies require new drugs as an alternative either synthetic or natural targeting lung cancer. The conventional therapies cause side effects, and therefore, natural products are used as a therapeutic candidate in lung cancer. Chemical diversity among natural products highlights the impact of evolution and survival of fittest. One such neglected natural product is Ganoderma lucidum used for promoting health and longevity for a longer time. The major bioconstituents of G. lucidum are mainly terpenes, polysaccharides, and proteins, which were explored for various activities ranging from apoptosis to autophagy. The bioconstituents of G. lucidum activate plasma membrane receptors and initiate various downstream signaling leading to nuclear factor-κB, phosphoinositide 3-kinase, Akt, and mammalian target of rapamycin in cancer. The bioconstituents regulate the expression of various genes involved in cell cycle, immune response, apoptosis, and autophagy in lung cancer. This review highlights the inextricable role of G. lucidum and its bioconstituents in lung cancer signaling for the first time.

A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

Directory of Open Access Journals (Sweden)

Xinkui Liu

2018-01-01

Full Text Available Background. As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered. Objective. The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC. Methods. This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis. Results. The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility. Conclusions. This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

Applying Statistical and Complex Network Methods to Explore the Key Signaling Molecules of Acupuncture Regulating Neuroendocrine-Immune Network

Directory of Open Access Journals (Sweden)

Kuo Zhang

2018-01-01

Full Text Available The mechanisms of acupuncture are still unclear. In order to reveal the regulatory effect of manual acupuncture (MA on the neuroendocrine-immune (NEI network and identify the key signaling molecules during MA modulating NEI network, we used a rat complete Freund’s adjuvant (CFA model to observe the analgesic and anti-inflammatory effect of MA, and, what is more, we used statistical and complex network methods to analyze the data about the expression of 55 common signaling molecules of NEI network in ST36 (Zusanli acupoint, and serum and hind foot pad tissue. The results indicate that MA had significant analgesic, anti-inflammatory effects on CFA rats; the key signaling molecules may play a key role during MA regulating NEI network, but further research is needed.

Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

DEFF Research Database (Denmark)

Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

2015-01-01

Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used...... also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

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Matthew Ruffalo

2015-12-01

Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

Science.gov (United States)

Banerji, Christopher R. S.; Severini, Simone; Caldas, Carlos; Teschendorff, Andrew E.

2015-01-01

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers. PMID:25793737

Intra-tumour signalling entropy determines clinical outcome in breast and lung cancer.

Directory of Open Access Journals (Sweden)

Christopher R S Banerji

2015-03-01

Full Text Available The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample's genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.

Digital Signal Processing and Control for the Study of Gene Networks

Science.gov (United States)

Shin, Yong-Jun

2016-04-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Unraveling the Complexities of Androgen Receptor Signaling in Prostate Cancer Cells

OpenAIRE

Heemers, Hannelore V.; Tindall, Donald J.

2009-01-01

Androgen signaling is critical for proliferation of prostate cancer cells but cannot be fully inhibited by current androgen deprivation therapies. A study by Xu et al. in this issue of Cancer Cell provides insights into the complexities of androgen signaling in prostate cancer and suggests avenues to target a subset of androgen-sensitive genes.

Overload Control in a SIP Signaling Network

OpenAIRE

Masataka Ohta

2007-01-01

The Internet telephony employs a new type of Internet communication on which a mutual communication is realized by establishing sessions. Session Initiation Protocol (SIP) is used to establish sessions between end-users. For unreliable transmission (UDP), SIP message should be retransmitted when it is lost. The retransmissions increase a load of the SIP signaling network, and sometimes lead to performance degradation when a network is overloaded. The paper proposes an overload control for a S...

Overlapping activities of TGF-β and Hedgehog signaling in cancer: therapeutic targets for cancer treatment.

Science.gov (United States)

Perrot, Carole Y; Javelaud, Delphine; Mauviel, Alain

2013-02-01

Recent advances in the field of cancer therapeutics come from the development of drugs that specifically recognize validated oncogenic or pro-metastatic targets. The latter may be mutated proteins with altered function, such as kinases that become constitutively active, or critical components of growth factor signaling pathways, whose deregulation leads to aberrant malignant cell proliferation and dissemination to metastatic sites. We herein focus on the description of the overlapping activities of two important developmental pathways often exacerbated in cancer, namely Transforming Growth Factor-β (TGF-β) and Hedgehog (HH) signaling, with a special emphasis on the unifying oncogenic role played by GLI1/2 transcription factors. The latter are the main effectors of the canonical HH pathway, yet are direct target genes of TGF-β/SMAD signal transduction. While tumor-suppressor in healthy and pre-malignant tissues, TGF-β is often expressed at high levels in tumors and contributes to tumor growth, escape from immune surveillance, invasion and metastasis. HH signaling regulates cell proliferation, differentiation and apoptosis, and aberrant HH signaling is found in a variety of cancers. We discuss the current knowledge on HH and TGF-β implication in cancer including cancer stem cell biology, as well as the current state, both successes and failures, of targeted therapeutics aimed at blocking either of these pathways in the pre-clinical and clinical settings. Copyright © 2012 Elsevier Inc. All rights reserved.

Wnt/β-catenin signaling regulates cancer stem cells in lung cancer A549 cells

International Nuclear Information System (INIS)

Teng, Ying; Wang, Xiuwen; Wang, Yawei; Ma, Daoxin

2010-01-01

Wnt/β-catenin signaling plays an important role not only in cancer, but also in cancer stem cells. In this study, we found that β-catenin and OCT-4 was highly expressed in cisplatin (DDP) selected A549 cells. Stimulating A549 cells with lithium chloride (LiCl) resulted in accumulation of β-catenin and up-regulation of a typical Wnt target gene cyclin D1. This stimulation also significantly enhanced proliferation, clone formation, migration and drug resistance abilities in A549 cells. Moreover, the up-regulation of OCT-4, a stem cell marker, was observed through real-time PCR and Western blotting. In a reverse approach, we inhibited Wnt signaling by knocking down the expression of β-catenin using RNA interference technology. This inhibition resulted in down-regulation of the Wnt target gene cyclin D1 as well as the proliferation, clone formation, migration and drug resistance abilities. Meanwhile, the expression of OCT-4 was reduced after the inhibition of Wnt/β-catenin signaling. Taken together, our study provides strong evidence that canonical Wnt signaling plays an important role in lung cancer stem cell properties, and it also regulates OCT-4, a lung cancer stem cell marker.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

Science.gov (United States)

Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Sensor signal analysis by neural networks for surveillance in nuclear reactors

International Nuclear Information System (INIS)

Keyvan, S.; Rabelo, L.C.

1992-01-01

The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

Science.gov (United States)

Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

2015-01-01

Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

Directory of Open Access Journals (Sweden)

Ananthi Jebaseeli Samuelraj

2015-01-01

Full Text Available Proxy Mobile IPV6 (PMIPV6 is a network based mobility management protocol which supports node’s mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node’s mobility should be modified to support group nodes’ mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

Applications of autoassociative neural networks for signal validation in accident management

International Nuclear Information System (INIS)

Fantoni, P.; Mazzola, A.

1994-01-01

The OECD Halden Reactor Project has been working for several years with computer based systems for determination on plant status including early fault detection and signal validation. The method here presented explores the possibility to use a neural network approach to validate important process signals during normal and abnormal plant conditions. In BWR plants, signal validation has two important applications: reliable thermal limits calculation and reliable inputs to other computerized systems that support the operator during accident scenarious. This work shows how a properly trained autoassociative neural network can promptly detect faulty process signal measurements and produce a best estimate of the actual process value. Noise has been artificially added to the input to evaluate the network ability to respond in a very low signal to noise ratio environment. Training and test datasets have been simulated by the real time transient simulator code APROS. Future development addresses the validation of the model through the use of real data from the plant. (author). 5 refs, 17 figs

Multiple-failure signal validation in nuclear power plants using artificial neural networks

International Nuclear Information System (INIS)

Fantoni, P.F.; Mazzola, A.

1996-01-01

The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

Introduction: Cancer Gene Networks.

Science.gov (United States)

Clarke, Robert

2017-01-01

Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary

Notch signaling in embryology and cancer

National Research Council Canada - National Science Library

Reichrath, J; Reichrath, Sandra

2012-01-01

"The goal of this volume is to comprehensively cover a highly readable overview on our present knowledge of the role of Notch signalling for embryology and cancer, with a focus on new findings in molecular biology...

Cluster synchronization transmission of different external signals in discrete uncertain network

Science.gov (United States)

Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

2018-07-01

We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

Towards the systematic discovery of signal transduction networks using phosphorylation dynamics data

Directory of Open Access Journals (Sweden)

Yachie Nozomu

2010-05-01

Full Text Available Abstract Background Phosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and their phosphosites is rapidly increasing as a result of recent mass spectrometry-based approaches. Results We analyzed time-course phosphoproteome data obtained previously by liquid chromatography mass spectrometry with the stable isotope labeling using amino acids in cell culture (SILAC method. This provides the relative phosphorylation activities of digested peptides at each of five time points after stimulating HeLa cells with epidermal growth factor (EGF. We initially calculated the correlations between the phosphorylation dynamics patterns of every pair of peptides and connected the strongly correlated pairs to construct a network. We found that peptides extracted from the same intracellular fraction (nucleus vs. cytoplasm tended to be close together within this phosphorylation dynamics-based network. The network was then analyzed using graph theory and compared with five known signal-transduction pathways. The dynamics-based network was correlated with known signaling pathways in the NetPath and Phospho.ELM databases, and especially with the EGF receptor (EGFR signaling pathway. Although the phosphorylation patterns of many proteins were drastically changed by the EGF stimulation, our results suggest that only EGFR signaling transduction was both strongly activated and precisely controlled. Conclusions The construction of a phosphorylation dynamics-based network provides a useful overview of condition-specific intracellular signal transduction using quantitative time-course phosphoproteome data under specific experimental conditions. Detailed prediction of signal transduction based on phosphoproteome dynamics remains challenging. However, since the phosphorylation profiles of kinase-substrate pairs on the specific pathway were localized in the dynamics

The self-renewal signaling pathways utilized by gastric cancer stem cells.

Science.gov (United States)

Fu, Ying; Li, Hui; Hao, Xishan

2017-04-01

Gastric cancer is a leading cause of cancer-related mortality worldwide. Cancer stem cells are the source of tumor recurrence and metastasis. Self-renewal is a marker of cancer stem cells and also the basis of long-lasting survival and tumor progression. Although the mechanism of gastric cancer stem cell self-renewal is not clear, there are several signaling pathways and environmental factors known to be involved. This mini review describes recent developments in the self-renewal signaling pathway of gastric cancer stem cell research. Advancements made in this field of research will likely support the development of novel therapeutic strategies for gastric cancer.

Personalized Network-Based Treatments in Oncology

DEFF Research Database (Denmark)

Robin, Xavier; Creixell, Pau; Radetskaya, Oxana

2013-01-01

Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technol...

Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

Science.gov (United States)

Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

2015-08-01

Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Targeting fibroblast growth factor receptor signaling inhibits prostate cancer progression.

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Feng, Shu; Shao, Longjiang; Yu, Wendong; Gavine, Paul; Ittmann, Michael

2012-07-15

Extensive correlative studies in human prostate cancer as well as studies in vitro and in mouse models indicate that fibroblast growth factor receptor (FGFR) signaling plays an important role in prostate cancer progression. In this study, we used a probe compound for an FGFR inhibitor, which potently inhibits FGFR-1-3 and significantly inhibits FGFR-4. The purpose of this study is to determine whether targeting FGFR signaling from all four FGFRs will have in vitro activities consistent with inhibition of tumor progression and will inhibit tumor progression in vivo. Effects of AZ8010 on FGFR signaling and invasion were analyzed using immortalized normal prostate epithelial (PNT1a) cells and PNT1a overexpressing FGFR-1 or FGFR-4. The effect of AZ8010 on invasion and proliferation in vitro was also evaluated in prostate cancer cell lines. Finally, the impact of AZ8010 on tumor progression in vivo was evaluated using a VCaP xenograft model. AZ8010 completely inhibits FGFR-1 and significantly inhibits FGFR-4 signaling at 100 nmol/L, which is an achievable in vivo concentration. This results in marked inhibition of extracellular signal-regulated kinase (ERK) phosphorylation and invasion in PNT1a cells expressing FGFR-1 and FGFR-4 and all prostate cancer cell lines tested. Treatment in vivo completely inhibited VCaP tumor growth and significantly inhibited angiogenesis and proliferation and increased cell death in treated tumors. This was associated with marked inhibition of ERK phosphorylation in treated tumors. Targeting FGFR signaling is a promising new approach to treating aggressive prostate cancer.

Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

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Philip M Tan

2017-11-01

Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways

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Sébastien De Landtsheer

2018-05-01

Full Text Available 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.

Network features and pathway analyses of a signal transduction cascade

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Ryoji Yanashima

2009-05-01

Full Text Available The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

The role of the Hedgehog signaling pathway in cancer: A comprehensive review

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Ana Marija Skoda

2018-02-01

Full Text Available The Hedgehog (Hh signaling pathway was first identified in the common fruit fly. It is a highly conserved evolutionary pathway of signal transmission from the cell membrane to the nucleus. The Hh signaling pathway plays an important role in the embryonic development. It exerts its biological effects through a signaling cascade that culminates in a change of balance between activator and repressor forms of glioma-associated oncogene (Gli transcription factors. The components of the Hh signaling pathway involved in the signaling transfer to the Gli transcription factors include Hedgehog ligands (Sonic Hh [SHh], Indian Hh [IHh], and Desert Hh [DHh], Patched receptor (Ptch1, Ptch2, Smoothened receptor (Smo, Suppressor of fused homolog (Sufu, kinesin protein Kif7, protein kinase A (PKA, and cyclic adenosine monophosphate (cAMP. The activator form of Gli travels to the nucleus and stimulates the transcription of the target genes by binding to their promoters. The main target genes of the Hh signaling pathway are PTCH1, PTCH2, and GLI1. Deregulation of the Hh signaling pathway is associated with developmental anomalies and cancer, including Gorlin syndrome, and sporadic cancers, such as basal cell carcinoma, medulloblastoma, pancreatic, breast, colon, ovarian, and small-cell lung carcinomas. The aberrant activation of the Hh signaling pathway is caused by mutations in the related genes (ligand-independent signaling or by the excessive expression of the Hh signaling molecules (ligand-dependent signaling – autocrine or paracrine. Several Hh signaling pathway inhibitors, such as vismodegib and sonidegib, have been developed for cancer treatment. These drugs are regarded as promising cancer therapies, especially for patients with refractory/advanced cancers.

Epithelial Plasticity in Cancer: Unmasking a MicroRNA Network for TGF-β-, Notch-, and Wnt-Mediated EMT

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Eugenio Zoni

2015-01-01

Full Text Available Epithelial-to-mesenchymal transition (EMT is a reversible process by which cancer cells can switch from a sessile epithelial phenotype to an invasive mesenchymal state. EMT enables tumor cells to become invasive, intravasate, survive in the circulation, extravasate, and colonize distant sites. Paracrine heterotypic stroma-derived signals as well as paracrine homotypic or autocrine signals can mediate oncogenic EMT and contribute to the acquisition of stem/progenitor cell properties, expansion of cancer stem cells, development of therapy resistance, and often lethal metastatic disease. EMT is regulated by a variety of stimuli that trigger specific intracellular signalling pathways. Altered microRNA (miR expression and perturbed signalling pathways have been associated with epithelial plasticity, including oncogenic EMT. In this review we analyse and describe the interaction between experimentally validated miRs and their target genes in TGF-β, Notch, and Wnt signalling pathways. Interestingly, in this process, we identified a “signature” of 30 experimentally validated miRs and a cluster of validated target genes that seem to mediate the cross talk between TGF-β, Notch, and Wnt signalling networks during EMT and reinforce their connection to the regulation of epithelial plasticity in health and disease.

Seismic signal auto-detecing from different features by using Convolutional Neural Network

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Huang, Y.; Zhou, Y.; Yue, H.; Zhou, S.

2017-12-01

We try Convolutional Neural Network to detect some features of seismic data and compare their efficience. The features include whether a signal is seismic signal or noise and the arrival time of P and S phase and each feature correspond to a Convolutional Neural Network. We first use traditional STA/LTA to recongnize some events and then use templete matching to find more events as training set for the Neural Network. To make the training set more various, we add some noise to the seismic data and make some synthetic seismic data and noise. The 3-component raw signal and time-frequancy ananlyze are used as the input data for our neural network. Our Training is performed on GPUs to achieve efficient convergence. Our method improved the precision in comparison with STA/LTA and template matching. We will move to recurrent neural network to see if this kind network is better in detect P and S phase.

Simultaneous multichannel signal transfers via chaos in a recurrent neural network.

Science.gov (United States)

Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Furumai, Noriyuki; Nara, Shigetoshi

2015-05-01

We propose neural network model that demonstrates the phenomenon of signal transfer between separated neuron groups via other chaotic neurons that show no apparent correlations with the input signal. The model is a recurrent neural network in which it is supposed that synchronous behavior between small groups of input and output neurons has been learned as fragments of high-dimensional memory patterns, and depletion of neural connections results in chaotic wandering dynamics. Computer experiments show that when a strong oscillatory signal is applied to an input group in the chaotic regime, the signal is successfully transferred to the corresponding output group, although no correlation is observed between the input signal and the intermediary neurons. Signal transfer is also observed when multiple signals are applied simultaneously to separate input groups belonging to different memory attractors. In this sense simultaneous multichannel communications are realized, and the chaotic neural dynamics acts as a signal transfer medium in which the signal appears to be hidden.

A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.

Science.gov (United States)

Jacobson, Rebecca S; Becich, Michael J; Bollag, Roni J; Chavan, Girish; Corrigan, Julia; Dhir, Rajiv; Feldman, Michael D; Gaudioso, Carmelo; Legowski, Elizabeth; Maihle, Nita J; Mitchell, Kevin; Murphy, Monica; Sakthivel, Mayurapriyan; Tseytlin, Eugene; Weaver, JoEllen

2015-12-15

Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the Text Information Extraction System (TIES) Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that are de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies, and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network. ©2015 American Association for Cancer Research.

Calcium and Nuclear Signaling in Prostate Cancer

OpenAIRE

Ivan V. Maly; Wilma A. Hofmann

2018-01-01

Recently, there have been a number of developments in the fields of calcium and nuclear signaling that point to new avenues for a more effective diagnosis and treatment of prostate cancer. An example is the discovery of new classes of molecules involved in calcium-regulated nuclear import and nuclear calcium signaling, from the G protein-coupled receptor (GPCR) and myosin families. This review surveys the new state of the calcium and nuclear signaling fields with the aim of identifying the un...

All-optical signal processing for optical packet switching networks

NARCIS (Netherlands)

Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

2005-01-01

We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

CBL-CIPK network for calcium signaling in higher plants

Science.gov (United States)

Luan, Sheng

Plants sense their environment by signaling mechanisms involving calcium. Calcium signals are encoded by a complex set of parameters and decoded by a large number of proteins including the more recently discovered CBL-CIPK network. The calcium-binding CBL proteins specifi-cally interact with a family of protein kinases CIPKs and regulate the activity and subcellular localization of these kinases, leading to the modification of kinase substrates. This represents a paradigm shift as compared to a calcium signaling mechanism from yeast and animals. One example of CBL-CIPK signaling pathways is the low-potassium response of Arabidopsis roots. When grown in low-K medium, plants develop stronger K-uptake capacity adapting to the low-K condition. Recent studies show that the increased K-uptake is caused by activation of a specific K-channel by the CBL-CIPK network. A working model for this regulatory pathway will be discussed in the context of calcium coding and decoding processes.

Robust gene network analysis reveals alteration of the STAT5a network as a hallmark of prostate cancer.

Science.gov (United States)

Reddy, Anupama; Huang, C Chris; Liu, Huiqing; Delisi, Charles; Nevalainen, Marja T; Szalma, Sandor; Bhanot, Gyan

2010-01-01

We develop a general method to identify gene networks from pair-wise correlations between genes in a microarray data set and apply it to a public prostate cancer gene expression data from 69 primary prostate tumors. We define the degree of a node as the number of genes significantly associated with the node and identify hub genes as those with the highest degree. The correlation network was pruned using transcription factor binding information in VisANT (http://visant.bu.edu/) as a biological filter. The reliability of hub genes was determined using a strict permutation test. Separate networks for normal prostate samples, and prostate cancer samples from African Americans (AA) and European Americans (EA) were generated and compared. We found that the same hubs control disease progression in AA and EA networks. Combining AA and EA samples, we generated networks for low low (cancer (e.g. possible turning on of oncogenes). (ii) Some hubs reduced their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with loss of regulatory control in cancer (e.g. possible loss of tumor suppressor genes). A striking result was that for both AA and EA tumor samples, STAT5a, CEBPB and EGR1 are major hubs that gain neighbors compared to the normal prostate network. Conversely, HIF-lα is a major hub that loses connections in the prostate cancer network compared to the normal prostate network. We also find that the degree of these hubs changes progressively from normal to low grade to high grade disease, suggesting that these hubs are master regulators of prostate cancer and marks disease progression. STAT5a was identified as a central hub, with ~120 neighbors in the prostate cancer network and only 81 neighbors in the normal prostate network. Of the 120 neighbors of STAT5a, 57 are known cancer related genes, known to be involved in functional pathways associated with tumorigenesis. Our method is general and can easily

PPARs Signaling and Cancer in the Gastrointestinal System

Directory of Open Access Journals (Sweden)

Valerio Pazienza

2012-01-01

Full Text Available Nowadays, the study of the peroxisome proliferators activated receptors (PPARs as potential targets for cancer prevention and therapy has gained a strong interest. From a biological point of view, the overall responsibility of PPARs in cancer development and progression is still controversial since several studies report both antiproliferative and tumor-promoting actions for these signaling molecules in human cancer cells and animal models. In this paper, we discuss PPARs functions in the context of different types of gastrointestinal cancer.

Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

Science.gov (United States)

Hu, Peizhen; Chung, Leland W K; Berel, Dror; Frierson, Henry F; Yang, Hua; Liu, Chunyan; Wang, Ruoxiang; Li, Qinlong; Rogatko, Andre; Zhau, Haiyen E

2013-01-01

We reported (PLoS One 6 (12):e28670, 2011) that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC) tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE) tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1) expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

Directory of Open Access Journals (Sweden)

Chen Bor-Sen

2011-01-01

Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

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Li Wang

2013-01-01

Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

G Protein-Coupled Receptor Signaling in Stem Cells and Cancer.

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Lynch, Jennifer R; Wang, Jenny Yingzi

2016-05-11

G protein-coupled receptors (GPCRs) are a large superfamily of cell-surface signaling proteins that bind extracellular ligands and transduce signals into cells via heterotrimeric G proteins. GPCRs are highly tractable drug targets. Aberrant expression of GPCRs and G proteins has been observed in various cancers and their importance in cancer stem cells has begun to be appreciated. We have recently reported essential roles for G protein-coupled receptor 84 (GPR84) and G protein subunit Gαq in the maintenance of cancer stem cells in acute myeloid leukemia. This review will discuss how GPCRs and G proteins regulate stem cells with a focus on cancer stem cells, as well as their implications for the development of novel targeted cancer therapies.

G Protein-Coupled Receptor Signaling in Stem Cells and Cancer

Directory of Open Access Journals (Sweden)

Jennifer R. Lynch

2016-05-01

Full Text Available G protein-coupled receptors (GPCRs are a large superfamily of cell-surface signaling proteins that bind extracellular ligands and transduce signals into cells via heterotrimeric G proteins. GPCRs are highly tractable drug targets. Aberrant expression of GPCRs and G proteins has been observed in various cancers and their importance in cancer stem cells has begun to be appreciated. We have recently reported essential roles for G protein-coupled receptor 84 (GPR84 and G protein subunit Gαq in the maintenance of cancer stem cells in acute myeloid leukemia. This review will discuss how GPCRs and G proteins regulate stem cells with a focus on cancer stem cells, as well as their implications for the development of novel targeted cancer therapies.

Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

Science.gov (United States)

Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2018-01-01

In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

Neural network committees for finger joint angle estimation from surface EMG signals

Directory of Open Access Journals (Sweden)

Reddy Narender P

2009-01-01

Full Text Available Abstract Background In virtual reality (VR systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

Bitter gourd (Momordica charantia) as a rich source of bioactive components to combat cancer naturally: Are we on the right track to fully unlock its potential as inhibitor of deregulated signaling pathways.

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Farooqi, Ammad Ahmad; Khalid, Sumbul; Tahir, Fatima; Sabitaliyevich, Uteuliev Yerzhan; Yaylim, Ilhan; Attar, Rukset; Xu, Baojun

2018-05-10

Research over decades has progressively explored pharmacological actions of bitter gourd (Momordica charantia). Biologically and pharmacologically active molecules isolated from M. charantia have shown significant anti-cancer activity in cancer cell lines and xenografted mice. In this review spotlight was set on the bioactive compounds isolated from M. charantia that effectively inhibited cancer development and progression via regulation of protein network in cancer cells. We summarize most recent high-quality research work in cancer cell lines and xenografted mice related to tumor suppressive role-play of M. charantia and its bioactive compounds. Although M. charantia mediated health promoting, anti-diabetic, hepatoprotective, anti-inflammatory effects have been extensively investigated, there is insufficient information related to regulation of signaling networks by bioactive molecules obtained from M. charantia in different cancers. M. charantia has been shown to modulate AKT/mTOR/p70S6K signaling, p38MAPK-MAPKAPK-2/HSP-27 pathway, cell cycle regulatory proteins and apoptosis-associated proteins in different cancers. However, still there are visible knowledge gaps related to the drug targets in different cancers because we have not yet developed comprehensive understanding of the M. charantia mediated regulation of signal transduction pathways. To explore these questions, experimental platforms are needed that can prove to be helpful in getting a step closer to personalized medicine. Copyright © 2018 Elsevier Ltd. All rights reserved.

A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes.

Science.gov (United States)

Yuan, Yinyin; Curtis, Christina; Caldas, Carlos; Markowetz, Florian

2012-01-01

Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation. An R package named lol is available from www.markowetzlab.org/software/lol.html.

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

Science.gov (United States)

Young-Rae Cho; Yanan Xin; Speegle, Greg

2015-01-01

Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

Science Signaling, Perspective – Cancer: Wnt/β-Catenin and MAPK Signaling: Allies and Enemies in Different Battlefields, April 2012 [Science Signaling, Ausblick – Krebs: Wnt/β-Catenin- und MAPK-Signaltransduktion: Verbündete und Feinde in unterschiedlichen Kampfzonen, April 2012

Directory of Open Access Journals (Sweden)

Forsythe, Katherine H.

2012-07-01

Full Text Available [english] Research published in represents major advances in cell signaling in many disciplines, including the rapidly expanding areas of signaling networks, systems biology, synthetic biology, computation and modeling of regulatory pathways, and drug discovery. The published research content offers discoveries that substantially refine current understanding of important signaling processes, provide new concepts, and are likely to find application in multiple biological systems. Two papers this year in describe previously unknown links between two signaling pathways that are associated with cancer – melanoma and colon cancer. The Perspective, and MAPK Signaling: Allies and Enemies in Different Battlefields,” describes how both studies have implications for the development of combination therapies for skin and colon cancer .[german] Die in veröffentlichten Forschungsarbeiten stellen die wichtigsten Fortschritte zur Zellsignaltransduktion in vielen Fachbereichen dar und umfassen die schnell wachsenden Gebiete der Signaltransduktionsnetzwerke, der Systembiologie, der synthetischen Biologie, der Berechnung und Modelldarstellung regulatorischer Pfade sowie der Pharmaforschung. Die veröffentlichten Forschungsergebnisse bieten Entdeckungen, die das derzeitige Wissen zu wichtigen Signaltransduktionsprozessen beträchtlich vertiefen, neue Konzepte anbieten und wahrscheinlich Anwendung in mehreren biologischen Systemen finden werden. Zwei Arbeiten, die dieses Jahr in erschienen sind, beschreiben zuvor noch nicht bekannte Zusammenhänge zwischen zwei Signaltransduktionswegen, die mit Krebs (Melanom und Darmkrebs assoziiert sind. Der Ausblick „Wnt/β-Catenin- und MAPK-Signaltransduktion: Verbündete und Feinde in unterschiedlichen Kampfzonen“ beschreibt, wie beide Studien Auswirkungen auf die Entwicklung von Kombinationstherapien gegen Haut- und Darmkrebs haben .

Optimal Signal Design for Mixed Equilibrium Networks with Autonomous and Regular Vehicles

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Nan Jiang

2017-01-01

Full Text Available A signal design problem is studied for efficiently managing autonomous vehicles (AVs and regular vehicles (RVs simultaneously in transportation networks. AVs and RVs move on separate lanes and two types of vehicles share the green times at the same intersections. The signal design problem is formulated as a bilevel program. The lower-level model describes a mixed equilibrium where autonomous vehicles follow the Cournot-Nash (CN principle and RVs follow the user equilibrium (UE principle. In the upper-level model, signal timings are optimized at signalized intersections to allocate appropriate green times to both autonomous and RVs to minimize system travel cost. The sensitivity analysis based method is used to solve the bilevel optimization model. Various signal control strategies are evaluated through numerical examples and some insightful findings are obtained. It was found that the number of phases at intersections should be reduced for the optimal control of the AVs and RVs in the mixed networks. More importantly, incorporating AVs into the transportation network would improve the system performance due to the value of AV technologies in reducing random delays at intersections. Meanwhile, travelers prefer to choose AVs when the networks turn to be congested.

Postdiagnosis social networks and breast cancer mortality in the After Breast Cancer Pooling Project.

Science.gov (United States)

Kroenke, Candyce H; Michael, Yvonne L; Poole, Elizabeth M; Kwan, Marilyn L; Nechuta, Sarah; Leas, Eric; Caan, Bette J; Pierce, John; Shu, Xiao-Ou; Zheng, Ying; Chen, Wendy Y

2017-04-01

Large social networks have been associated with better overall survival, though not consistently with breast cancer (BC)-specific outcomes. This study evaluated associations of postdiagnosis social networks and BC outcomes in a large cohort. Women from the After Breast Cancer Pooling Project (n = 9267) provided data on social networks within approximately 2 years of their diagnosis. A social network index was derived from information about the presence of a spouse/partner, religious ties, community ties, friendship ties, and numbers of living first-degree relatives. Cox models were used to evaluate associations, and a meta-analysis was used to determine whether effect estimates differed by cohort. Stratification by demographic, social, tumor, and treatment factors was performed. There were 1448 recurrences and 1521 deaths (990 due to BC). Associations were similar in 3 of 4 cohorts. After covariate adjustments, socially isolated women (small networks) had higher risks of recurrence (hazard ratio [HR], 1.43; 95% confidence interval [CI], 1.15-1.77), BC-specific mortality (HR, 1.64; 95% CI, 1.33-2.03), and total mortality (HR, 1.69; 95% CI, 1.43-1.99) than socially integrated women; associations were stronger in those with stage I/II cancer. In the fourth cohort, there were no significant associations with BC-specific outcomes. A lack of a spouse/partner (P = .02) and community ties (P = .04) predicted higher BC-specific mortality in older white women but not in other women. However, a lack of relatives (P = .02) and friendship ties (P = .01) predicted higher BC-specific mortality in nonwhite women only. In a large pooled cohort, larger social networks were associated with better BC-specific and overall survival. Clinicians should assess social network information as a marker of prognosis because critical supports may differ with sociodemographic factors. Cancer 2017;123:1228-1237. © 2016 American Cancer Society. © 2016 American Cancer Society.

Plant morphogenesis, auxin, and the signal-trafficking network incompleteness theorem

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Karl J. Niklas

2012-03-01

Full Text Available Plant morphogenesis (the development of form and function requires signal-trafficking and cross-talking among all levels of organization to coordinate the operation of metabolic and genomic networked systems. Many if not all of these biological features can be rendered as logic circuits supervising the operation of one or more signal-activated metabolic or genome networks. This approach simplifies complex morphogenetic phenomena and allows for their aggregation into diagrams of larger, more "global" networked systems. This conceptualization is illustrated for morphogenesis in model plants such as maize (Zea mays and Thale cress (Arabidopsis thaliana from an evolutionary perspective. The phytohormone indole-acetic acid (IAA is used as an example for a well-known signaling chemical and discussed in terms of the logic circuits and signal-activated sub-systems for hormone-mediated wall loosening and cell expansion as well as polar/lateral intercellular IAA transport. For each of these phenomena, a circuit/sub-system diagram highlights missing components, either in the logic circuit or in the sub-system it supervises, that must be identified experimentally if each of these basic phenomena is to be fully understood within a phylogen

Signal Processing Device (SPD) for networked radiation monitoring system

International Nuclear Information System (INIS)

Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

2010-01-01

A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

Activin and TGFβ use diverging mitogenic signaling in advanced colon cancer

OpenAIRE

Bauer, Jessica; Ozden, Ozkan; Akagi, Naomi; Carroll, Timothy; Principe, Daniel R.; Staudacher, Jonas J.; Spehlmann, Martina E.; Eckmann, Lars; Grippo, Paul J.; Jung, Barbara

2015-01-01

Background Understanding cell signaling pathways that contribute to metastatic colon cancer is critical to risk stratification in the era of personalized therapeutics. Here, we dissect the unique involvement of mitogenic pathways in a TGFβ or activin-induced metastatic phenotype of colon cancer. Method Mitogenic signaling/growth factor receptor status and p21 localization were correlated in primary colon cancers and intestinal tumors from either AOM/DSS treated ACVR2A (activin receptor 2) −/−...

[Cellular adhesion signal transduction network of tumor necrosis factor-alpha induced hepatocellular carcinoma cells].

Science.gov (United States)

Zheng, Yongchang; Du, Shunda; Xu, Haifeng; Xu, Yiyao; Zhao, Haitao; Chi, Tianyi; Lu, Xin; Sang, Xinting; Mao, Yilei

2014-11-18

To systemically explore the cellular adhesion signal transduction network of tumor necrosis factor-alpha (TNF-α)-induced hepatocellular carcinoma cells with bioinformatics tools. Published microarray dataset of TNF-α-induced HepG2, human transcription factor database HTRI and human protein-protein interaction database HPRD were used to construct and analyze the signal transduction network. In the signal transduction network, MYC and SP1 were the key nodes of signaling transduction. Several genes from the network were closely related with cellular adhesion.Epidermal growth factor receptor (EGFR) is a possible key gene of effectively regulating cellular adhesion during the induction of TNF-α. EGFR is a possible key gene for TNF-α-induced metastasis of hepatocellular carcinoma.

Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

Science.gov (United States)

Zhang, Zipeng; Fan, Tao; Wang, Shuqing

It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

Comparative indicators for cancer network management in England: Availability, characteristics and presentation

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Coleman Michel P

2008-02-01

Full Text Available Abstract Background In 2000, the national cancer plan for England created 34 cancer networks, new organisational structures to coordinate services across populations varying between a half and three million people. We investigated the availability of data sets reflecting measures of structure, process and outcome that could be used to support network management. Methods We investigated the properties of national data sets relating to four common cancers – breast, colorectal, lung and prostate. We reviewed the availability and completeness of these data sets, identified leading items within each set and put them into tables of the 34 cancer networks. We also investigated methods of presentation. Results The Acute Hospitals Portfolio and the Cancer Standards Peer Review recorded structural characteristics at hospital and cancer service level. Process measures included Hospital Episode Statistics, recording admissions, and Hospital Waiting-List data. Patient outcome measures included the National Survey of Patient Satisfaction for cancer, and cancer survival, drawn from cancer registration. Data were drawn together to provide an exemplar indicator set a single network, and methods of graphical presentation were considered. Conclusion While not as yet used together in practice, comparative indicators are available within the National Health Service in England for use in performance assessment by cancer networks.

Trends in intensity modulated radiation therapy use for locally advanced rectal cancer at National Comprehensive Cancer Network centers

OpenAIRE

Marsha Reyngold, MD, PhD; Joyce Niland, PhD; Anna ter Veer, MS; Tanios Bekaii-Saab, MD; Lily Lai, MD; Joshua E. Meyer, MD; Steven J. Nurkin, MD, MS; Deborah Schrag, MD, MPH; John M. Skibber, MD, FACS; Al B. Benson, MD; Martin R. Weiser, MD; Christopher H. Crane, MD; Karyn A. Goodman, MD, MS

2018-01-01

Purpose: Intensity modulated radiation therapy (IMRT) has been rapidly incorporated into clinical practice because of its technological advantages over 3-dimensional conformal radiation therapy (CRT). We characterized trends in IMRT utilization in trimodality treatment of locally advanced rectal cancer at National Comprehensive Cancer Network cancer centers between 2005 and 2011. Methods and materials: Using the prospective National Comprehensive Cancer Network Colorectal Cancer Database, ...

Traffic signal synchronization in the saturated high-density grid road network.

Science.gov (United States)

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

NT2 derived neuronal and astrocytic network signalling.

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Eric J Hill

Full Text Available A major focus of stem cell research is the generation of neurons that may then be implanted to treat neurodegenerative diseases. However, a picture is emerging where astrocytes are partners to neurons in sustaining and modulating brain function. We therefore investigated the functional properties of NT2 derived astrocytes and neurons using electrophysiological and calcium imaging approaches. NT2 neurons (NT2Ns expressed sodium dependent action potentials, as well as responses to depolarisation and the neurotransmitter glutamate. NT2Ns exhibited spontaneous and coordinated calcium elevations in clusters and in extended processes, indicating local and long distance signalling. Tetrodotoxin sensitive network activity could also be evoked by electrical stimulation. Similarly, NT2 astrocytes (NT2As exhibited morphology and functional properties consistent with this glial cell type. NT2As responded to neuronal activity and to exogenously applied neurotransmitters with calcium elevations, and in contrast to neurons, also exhibited spontaneous rhythmic calcium oscillations. NT2As also generated propagating calcium waves that were gap junction and purinergic signalling dependent. Our results show that NT2 derived astrocytes exhibit appropriate functionality and that NT2N networks interact with NT2A networks in co-culture. These findings underline the utility of such cultures to investigate human brain cell type signalling under controlled conditions. Furthermore, since stem cell derived neuron function and survival is of great importance therapeutically, our findings suggest that the presence of complementary astrocytes may be valuable in supporting stem cell derived neuronal networks. Indeed, this also supports the intriguing possibility of selective therapeutic replacement of astrocytes in diseases where these cells are either lost or lose functionality.

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

Science.gov (United States)

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Determination of outdoor signal propagation via visibility analysis in outdoor wireless networks

Directory of Open Access Journals (Sweden)

Mustafa Coşar

2017-02-01

Full Text Available Wireless networks on university campuses has gained importance in recent years. These networks in major areas such as university campuses, are faced with many problems during the planning, design and establishment. These problems are among the first that comes to mind, the physical properties of the campus and is selected according to the characteristics of network equipment. There is no doubt at all points of a wireless network set up in order to provide uninterrupted service and quality of the signal is expected to be good. However, it should be understood literally cannot meet these expectations. Therefore, to solve many problems to campus planning and design can be made to have acceptable signal distribution will have the appropriate use of and satisfaction with increasing effect. In this study, due to the start of construction on the North Campus of Hitit University, wireless signal spread using the current spread has been determined with the help of geographic information systems visibility analysis. An area of 56 hectares, with the total of 9 AP the acceptable signal distribution was obtained.

Stochastic effects as a force to increase the complexity of signaling networks

KAUST Repository

Kuwahara, Hiroyuki; Gao, Xin

2013-01-01

Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism

The Loss of TGF-β Signaling Promotes Prostate Cancer Metastasis

Directory of Open Access Journals (Sweden)

William H. Tu

2003-05-01

Full Text Available In breast and colon cancers, transforming growth factor (TGIF-β signaling initially has an antineoplastic effect, inhibiting tumor growth, but eventually exerts a proneoplastic effect, increasing motility and cancer spread. In prostate cancer, studies using human samples have correlated the loss of the TGIF-β type II receptor (TβRll with higher tumor grade. To determine the effect of an inhibited TGIF-β pathway on prostate cancer, we bred transgenic mice expressing the tumorigenic SV40 large T antigen in the prostate with transgenic mice expressing a dominant negative TβRII mutant (DNIIR in the prostate. Transgene(s and TGIF-β expression were identified in the prostate and decreased protein levels of plasminogen activator inhibitor type I, as a marker for TGIF-β signaling, correlated with expression of the DNIIR. Although the sizes of the neoplastic prostates were not enlarged, increased amounts of metastasis were observed in mice expressing both transgenes compared to age-matched control mice expressing only the large T antigen transgene. Our study demonstrates for the first time that a disruption of TGIF-β signaling in prostate cancer plays a causal role in promoting tumor metastasis.

EGF signalling pathway regulates colon cancer stem cell proliferation and apoptosis.

Science.gov (United States)

Feng, Y; Dai, X; Li, X; Wang, H; Liu, J; Zhang, J; Du, Y; Xia, L

2012-10-01

Cancer stem cells (CSCs) compose a subpopulation of cells within a tumour that can self-renew and proliferate. Growth factors such as epidermal growth factor (EGF) and basic fibroblast growth factor (b-FGF) promote cancer stem cell proliferation in many solid tumours. This study assesses whether EGF, bFGF and IGF signalling pathways are essential for colon CSC proliferation and self-renewal. Colon CSCs were cultured in serum-free medium (SFM) with one of the following growth factors: EGF, bFGF or IGF. Characteristics of CSC gene expression were evaluated by real time PCR. Tumourigenicity of CSCs was determined using a xenograft model in vivo. Effects of EGF receptor inhibitors, Gefitinib and PD153035, on CSC proliferation, apoptosis and signalling were evaluated using fluorescence-activated cell sorting and western blotting. Colon cancer cell HCT116 transformed to CSCs in SFM. Compared to other growth factors, EGF was essential to support proliferation of CSCs that expressed higher levels of progenitor genes (Musashi-1, LGR5) and lower levels of differential genes (CK20). CSCs promoted more rapid tumour growth than regular cancer cells in xenografts. EGFR inhibitors suppressed proliferation and induced apoptosis of CSCs by inhibiting autophosphorylation of EGFR and downstream signalling proteins, such as Akt kinase, extracellular signal-regulated kinase 1/2 (ERK 1/2). This study indicates that EGF signalling was essential for formation and maintenance of colon CSCs. Inhibition of the EGF signalling pathway may provide a useful strategy for treatment of colon cancer. © 2012 Blackwell Publishing Ltd.

Negative feedback and adaptive resistance to the targeted therapy of cancer.

Science.gov (United States)

Chandarlapaty, Sarat

2012-04-01

Mutational activation of growth factor signaling pathways is commonly observed and often necessary for oncogenic transformation. Under physiologic conditions, these pathways are subject to tight regulation through negative feedback, which limits the extent and duration of signaling events after physiologic stimulation. Until recently, the role of these negative feedback pathways in oncogene-driven cancers has been poorly understood. In this review, I discuss the evidence for the existence and relevance of negative feedback pathways within oncogenic signaling networks, the selective advantages such feedback pathways may confer, and the effects such feedback might have on therapies aimed at inhibiting oncogenic signaling. Negative feedback pathways are ubiquitous features of growth factor signaling networks. Because growth factor signaling networks play essential roles in the majority of cancers, their therapeutic targeting has become a major emphasis of clinical oncology. Drugs targeting these networks are predicted to inhibit the pathway but also to relieve the negative feedback. This loss of negative feedback can itself promote oncogenic signals and cancer cell survival. Drug-induced relief of feedback may be viewed as one of the major consequences of targeted therapy and a key contributor to therapeutic resistance.

Epsin is required for Dishevelled stability and Wnt signalling activation in colon cancer development.

Science.gov (United States)

Chang, Baojun; Tessneer, Kandice L; McManus, John; Liu, Xiaolei; Hahn, Scott; Pasula, Satish; Wu, Hao; Song, Hoogeun; Chen, Yiyuan; Cai, Xiaofeng; Dong, Yunzhou; Brophy, Megan L; Rahman, Ruby; Ma, Jian-Xing; Xia, Lijun; Chen, Hong

2015-03-16

Uncontrolled canonical Wnt signalling supports colon epithelial tumour expansion and malignant transformation. Understanding the regulatory mechanisms involved is crucial for elucidating the pathogenesis of and will provide new therapeutic targets for colon cancer. Epsins are ubiquitin-binding adaptor proteins upregulated in several human cancers; however, the involvement of epsins in colon cancer is unknown. Here we show that loss of intestinal epithelial epsins protects against colon cancer by significantly reducing the stability of the crucial Wnt signalling effector, dishevelled (Dvl2), and impairing Wnt signalling. Consistently, epsins and Dvl2 are correspondingly upregulated in colon cancer. Mechanistically, epsin binds Dvl2 via its epsin N-terminal homology domain and ubiquitin-interacting motifs and prohibits Dvl2 polyubiquitination and degradation. Our findings reveal an unconventional role for epsins in stabilizing Dvl2 and potentiating Wnt signalling in colon cancer cells to ensure robust colon cancer progression. The pro-carcinogenic role of Epsins suggests that they are potential therapeutic targets to combat colon cancer.

Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

Science.gov (United States)

Dasgupta, Hirak

2016-12-01

The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

Tyk2 expression and its signaling enhances the invasiveness of prostate cancer cells

International Nuclear Information System (INIS)

Ide, Hisamitsu; Nakagawa, Takashi; Terado, Yuichi; Kamiyama, Yutaka; Muto, Satoru; Horie, Shigeo

2008-01-01

Protein tyrosine kinase plays a central role in the proliferation and differentiation of various types of cells. One of these protein kinases, Tyk2, a member of the Jak family kinases, is known to play important roles in receptor signal transduction by interferons, interleukins, growth factors, and other hormones. In the present study, we investigated Tyk2 expression and its role in the growth and invasiveness of human prostate cancer cells. We used a small interfering RNA targeting Tyk2 and an inhibitor of Tyk2, tyrphostin A1, to suppress the expression and signaling of Tyk2 in prostate cancer cells. We detected mRNAs for Jak family kinases in prostate cancer cell lines by RT-PCR and Tyk2 protein in human prostate cancer specimens by immunohistochemistry. Inhibition of Tyk2 signaling resulted in attenuation of the urokinase-type plasminogen activator-enhanced invasiveness of prostate cancer cells in vitro without affecting the cellular growth rate. These results suggest that Tyk2 signaling in prostate cancer cells facilitate invasion of these cells, and interference with this signaling may be a potential therapeutic pathway

Notch Signaling Mediates Skeletal Muscle Atrophy in Cancer Cachexia Caused by Osteosarcoma

Directory of Open Access Journals (Sweden)

Xiaodong Mu

2016-01-01

Full Text Available Skeletal muscle atrophy in cancer cachexia is mediated by the interaction between muscle stem cells and various tumor factors. Although Notch signaling has been known as a key regulator of both cancer development and muscle stem cell activity, the potential involvement of Notch signaling in cancer cachexia and concomitant muscle atrophy has yet to be elucidated. The murine K7M2 osteosarcoma cell line was used to generate an orthotopic model of sarcoma-associated cachexia, and the role of Notch signaling was evaluated. Skeletal muscle atrophy was observed in the sarcoma-bearing mice, and Notch signaling was highly active in both tumor tissues and the atrophic skeletal muscles. Systemic inhibition of Notch signaling reduced muscle atrophy. In vitro coculture of osteosarcoma cells with muscle-derived stem cells (MDSCs isolated from normal mice resulted in decreased myogenic potential of MDSCs, while the application of Notch inhibitor was able to rescue this repressed myogenic potential. We further observed that Notch-activating factors reside in the exosomes of osteosarcoma cells, which activate Notch signaling in MDSCs and subsequently repress myogenesis. Our results revealed that signaling between tumor and muscle via the Notch pathway may play an important role in mediating the skeletal muscle atrophy seen in cancer cachexia.

Gα12/13 signaling promotes cervical cancer invasion through the RhoA/ROCK-JNK signaling axis

International Nuclear Information System (INIS)

Yuan, Bo; Cui, Jinquan; Wang, Wuliang; Deng, Kehong

2016-01-01

Several reports have indicated a role for the members of the G12 family of heterotrimeric G proteins (Gα12 and Gα13) in oncogenesis and tumor cell growth. The aims of the present study were to evaluate the role of G12 signaling in cervical cancer. We demonstrated that expression of the G12 proteins was highly upregulated in cervical cancer cells. Additionally, expression of the activated forms of Gα12/Gα13 but not expression of activated Gαq induced cell invasion through the activation of the RhoA family of G proteins, but had no effect on cell proliferation in the cervical cancer cells. Inhibition of G12 signaling by expression of the RGS domain of the p115-Rho-specific guanine nucleotide exchange factor (p115-RGS) blocked thrombin-stimulated cell invasion, but did not inhibit cell proliferation in cervical cells, whereas the inhibition of Gαq (RGS2) had no effect. Furthermore, G12 signaling was able to activate Rho proteins, and this stimulation was inhibited by p115-RGS, and Gα12-induced invasion was blocked by an inhibitor of RhoA/B/C (C3 toxin). Pharmacological inhibition of JNK remarkably decreased G12-induced JNK activation. Both a JNK inhibitor (SP600125) and a ROCK inhibitor (Y27632) reduced G12-induced JNK and c-Jun activation, and markedly inhibited G12-induced cellular invasion. Collectively, these findings demonstrate that stimulation of G12 proteins is capable of promoting invasion through RhoA/ROCK-JNK activation. -- Highlights: •Gα12/Gα13 is upregulated in cervical cancer cell lines. •Gα12/Gα13 is not involved in cervical cancer cell proliferation. •Gα12/Gα13 promotes cervical cancer cell invasion. •The role of Rho G proteins in G12-promoted cervical cancer cell invasion. •G12 promotes cell invasion through activation of the ROCK-JNK signaling axis.

Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

Directory of Open Access Journals (Sweden)

Peizhen Hu

Full Text Available We reported (PLoS One 6 (12:e28670, 2011 that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1 expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

Experimental and computational tools for analysis of signaling networks in primary cells

DEFF Research Database (Denmark)

Schoof, Erwin M; Linding, Rune

2014-01-01

Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis, or differ......Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis......; this information is critical when trying to elucidate key proteins involved in specific cellular responses. Here, methods to generate high-quality quantitative phosphorylation data from cell lysates originating from primary cells, and how to analyze the generated data to construct quantitative signaling network...

Data-driven quantification of the robustness and sensitivity of cell signaling networks

International Nuclear Information System (INIS)

Mukherjee, Sayak; Seok, Sang-Cheol; Vieland, Veronica J; Das, Jayajit

2013-01-01

Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data-driven maximum entropy based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems. (paper)

Responses to olfactory signals reflect network structure of flower-visitor interactions.

Science.gov (United States)

Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

2010-07-01

1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

Collective signaling behavior in a networked-oscillator model

Science.gov (United States)

Liu, Z.-H.; Hui, P. M.

2007-09-01

We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

Science.gov (United States)

Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

Directory of Open Access Journals (Sweden)

Guihua Wen

2017-01-01

Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Novel links in the plant TOR kinase signaling network.

Science.gov (United States)

Xiong, Yan; Sheen, Jen

2015-12-01

Nutrient and energy sensing and signaling mechanisms constitute the most ancient and fundamental regulatory networks to control growth and development in all life forms. The target of rapamycin (TOR) protein kinase is modulated by diverse nutrient, energy, hormone and stress inputs and plays a central role in regulating cell proliferation, growth, metabolism and stress responses from yeasts to plants and animals. Recent chemical, genetic, genomic and metabolomic analyses have enabled significant progress toward molecular understanding of the TOR signaling network in multicellular plants. This review discusses the applications of new chemical tools to probe plant TOR functions and highlights recent findings and predictions on TOR-mediate biological processes. Special focus is placed on novel and evolutionarily conserved TOR kinase effectors as positive and negative signaling regulators that control transcription, translation and metabolism to support cell proliferation, growth and maintenance from embryogenesis to senescence in the plant system. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systems Medicine in Oncology: Signaling Network Modeling and New-Generation Decision-Support Systems.

Science.gov (United States)

Parodi, Silvio; Riccardi, Giuseppe; Castagnino, Nicoletta; Tortolina, Lorenzo; Maffei, Massimo; Zoppoli, Gabriele; Nencioni, Alessio; Ballestrero, Alberto; Patrone, Franco

2016-01-01

Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive. Rational associations of selective drug inhibitors will become progressively a more realistic goal within the next 3-5 years. Toward the possibility of an implementation in standard oncologic structures of technologically sufficiently advanced countries, new (legal) rules probably will have to be established through a consensus process, at the level of both diagnostic and therapeutic behaviors.(2) The cancer patient of today is not the patient of 5-10 years from now. How to support the choice of the most convenient (and already clinically allowed) treatment for an individual cancer patient, as of today? We will consider the present level of artificial intelligence (AI) sophistication and the continuous feeding, updating, and integration of cancer-related new data, in AI systems. We will also report briefly about one of the most important projects in this field: IBM Watson US Cancer Centers. Allowing for a temporal shift, in the long term the two perspectives should move in the same direction, with a necessary time lag between them.

Onco-GPCR signaling and dysregulated expression of microRNAs in human cancer.

Science.gov (United States)

Nohata, Nijiro; Goto, Yusuke; Gutkind, J Silvio

2017-01-01

The G-protein-coupled receptor (GPCR) family is the largest family of cell-surface receptors involved in signal transduction. Aberrant expression of GPCRs and G proteins are frequently associated with prevalent human diseases, including cancer. In fact, GPCRs represent the therapeutic targets of more than a quarter of the clinical drugs currently on the market. MiRNAs (miRNAs) are also aberrantly expressed in many human cancers, and they have significant roles in the initiation, development and metastasis of human malignancies. Recent studies have revealed that dysregulation of miRNAs and their target genes expression are associated with cancer progression. The emerging information suggests that miRNAs play an important role in the fine tuning of many signaling pathways, including GPCR signaling. We summarize our current knowledge of the individual functions of miRNAs regulated by GPCRs and GPCR signaling-associated molecules, and miRNAs that regulate the expression and activity of GPCRs, their endogenous ligands and their coupled heterotrimeric G proteins in human cancer.

Fibroblast growth factor receptor 3 interacts with and activates TGFβ-activated kinase 1 tyrosine phosphorylation and NFκB signaling in multiple myeloma and bladder cancer.

Directory of Open Access Journals (Sweden)

Lisa Salazar

Full Text Available Cancer is a major public health problem worldwide. In the United States alone, 1 in 4 deaths is due to cancer and for 2013 a total of 1,660,290 new cancer cases and 580,350 cancer-related deaths are projected. Comprehensive profiling of multiple cancer genomes has revealed a highly complex genetic landscape in which a large number of altered genes, varying from tumor to tumor, impact core biological pathways and processes. This has implications for therapeutic targeting of signaling networks in the development of treatments for specific cancers. The NFκB transcription factor is constitutively active in a number of hematologic and solid tumors, and many signaling pathways implicated in cancer are likely connected to NFκB activation. A critical mediator of NFκB activity is TGFβ-activated kinase 1 (TAK1. Here, we identify TAK1 as a novel interacting protein and target of fibroblast growth factor receptor 3 (FGFR3 tyrosine kinase activity. We further demonstrate that activating mutations in FGFR3 associated with both multiple myeloma and bladder cancer can modulate expression of genes that regulate NFκB signaling, and promote both NFκB transcriptional activity and cell adhesion in a manner dependent on TAK1 expression in both cancer cell types. Our findings suggest TAK1 as a potential therapeutic target for FGFR3-associated cancers, and other malignancies in which TAK1 contributes to constitutive NFκB activation.

Brain Network Analysis from High-Resolution EEG Signals

Science.gov (United States)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

Stromal COX-2 signaling activated by deoxycholic acid mediates proliferation and invasiveness of colorectal epithelial cancer cells

International Nuclear Information System (INIS)

Zhu, Yingting; Zhu, Min; Lance, Peter

2012-01-01

Highlights: ► Human colonic cancer associated fibroblasts are major sources of COX-2 and PGE 2 . ► The fibroblasts interact with human colonic epithelial cancer cells. ► Activation of COX-2 signaling in the fibroblasts affects behavior of the epithelia. ► Protein Kinase C controls the activation of COX-2 signaling. -- Abstract: COX-2 is a major regulator implicated in colonic cancer. However, how COX-2 signaling affects colonic carcinogenesis at cellular level is not clear. In this article, we investigated whether activation of COX-2 signaling by deoxycholic acid (DCA) in primary human normal and cancer associated fibroblasts play a significant role in regulation of proliferation and invasiveness of colonic epithelial cancer cells. Our results demonstrated while COX-2 signaling can be activated by DCA in both normal and cancer associated fibroblasts, the level of activation of COX-2 signaling is significantly greater in cancer associated fibroblasts than that in normal fibroblasts. In addition, we discovered that the proliferative and invasive potential of colonic epithelial cancer cells were much greater when the cells were co-cultured with cancer associated fibroblasts pre-treated with DCA than with normal fibroblasts pre-treated with DCA. Moreover, COX-2 siRNA attenuated the proliferative and invasive effect of both normal and cancer associate fibroblasts pre-treated with DCA on the colonic cancer cells. Further studies indicated that the activation of COX-2 signaling by DCA is through protein kinase C signaling. We speculate that activation of COX-2 signaling especially in cancer associated fibroblasts promotes progression of colonic cancer.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

Science.gov (United States)

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT

OpenAIRE

Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-01-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelli...

Effect of placement of droop based generators in distribution network on small signal stability margin and network loss

DEFF Research Database (Denmark)

Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.

2017-01-01

, small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...... loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues...

The role of nutraceuticals in the regulation of Wnt and Hedgehog signaling in cancer

Science.gov (United States)

Li, Yiwei; Wang, Zhiwei; Kong, Dejuan

2010-01-01

Multiple cellular signaling pathways have been involved in the processes of cancer cell invasion and metastasis. Among many signaling pathways, Wnt and Hedgehog (Hh) signaling pathways are critically involved in embryonic development, in the biology of cancer stem cells (CSCs) and in the acquisition of epithelial to mesenchymal transition (EMT), and thus this article will remain focused on Wnt and Hh signaling. Since CSCs and EMT are also known to be responsible for cancer cell invasion and metastasis, the Wnt and Hedgehog signaling pathways are also intimately associated with cancer invasion and metastasis. Emerging evidence suggests the beneficial role of chemopreventive agents commonly known as nutraceutical in cancer. Among many such agents, soy isoflavones, curcumin, green tea polyphenols, 3,3′-diindolylmethane, resveratrol, lycopene, vitamin D, etc. have been found to prevent, reverse, or delay the carcinogenic process. Interestingly, these agents have also shown to prevent or delay the progression of cancer, which could in part be due to their ability to attack CSCs or EMT-type cells by attenuating the Wnt and Hedgehog signaling pathways. In this review, we summarize the current state of our knowledge on the role of Wnt and Hedgehog signaling pathways, and their targeted inactivation by chemopreventive agents (nutraceuticals) for the prevention of tumor progression and/or treatment of human malignancies. PMID:20711635

A cloud-based data network approach for translational cancer research.

Science.gov (United States)

Xing, Wei; Tsoumakos, Dimitrios; Ghanem, Moustafa

2015-01-01

We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.

Role of Notch signalling pathway in cancer and its association with ...

Indian Academy of Sciences (India)

The Notch signalling pathway is an evolutionarily conserved cell signalling pathway involved in the development of organ- ... Abnormal Notch signalling is seen in many cancers like T-cell acute ...... Morgan T. H. 1917 The theory of the gene.

The interplay between HIF-1 and calcium signalling in cancer.

Science.gov (United States)

Azimi, Iman

2018-04-01

The interplay between hypoxia-inducible factor-1 (HIF-1) and calcium in cancer has begun to be unravelled with recent findings demonstrating the relationships between the two in different cancer types. This is an area of significance considering the crucial roles of both HIF-1 and calcium signalling in cancer progression and metastasis. This review summarises the experimental evidence of the crosstalk between HIF-1 and specific calcium channels, pumps and regulators in the context of cancer. HIF-1 as a master regulator of hypoxic transcriptional responses, mediates transcription of several calcium modulators. On the other hand, specific calcium channels and pumps regulate HIF-1 activity through controlling its transcription, translation, stabilisation, or nuclear translocation. Identifying the interplay between HIF-1 and components of the calcium signal will give new insights into mechanisms underlying cellular responses to physiological and pathophysiological cues, and may provide novel and more efficient therapeutic strategies for the control of cancer progression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis.

Directory of Open Access Journals (Sweden)

Shoba Ramanadhan

Full Text Available Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT. As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate. Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity. We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications. We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement. The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities

Biophysical constraints on the computational capacity of biochemical signaling networks

Science.gov (United States)

Wang, Ching-Hao; Mehta, Pankaj

Biophysics fundamentally constrains the computations that cells can carry out. Here, we derive fundamental bounds on the computational capacity of biochemical signaling networks that utilize post-translational modifications (e.g. phosphorylation). To do so, we combine ideas from the statistical physics of disordered systems and the observation by Tony Pawson and others that the biochemistry underlying protein-protein interaction networks is combinatorial and modular. Our results indicate that the computational capacity of signaling networks is severely limited by the energetics of binding and the need to achieve specificity. We relate our results to one of the theoretical pillars of statistical learning theory, Cover's theorem, which places bounds on the computational capacity of perceptrons. PM and CHW were supported by a Simons Investigator in the Mathematical Modeling of Living Systems Grant, and NIH Grant No. 1R35GM119461 (both to PM).

Traffic analysis and signal processing in optical packet switched networks

DEFF Research Database (Denmark)

Fjelde, Tina

2002-01-01

/s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

Voltage-gated Na+ channel SCN5A is a key regulator of a gene transcriptional network that controls colon cancer invasion

Science.gov (United States)

House, Carrie D.; Vaske, Charles J.; Schwartz, Arnold M.; Obias, Vincent; Frank, Bryan; Luu, Truong; Sarvazyan, Narine; Irby, Rosalyn; Strausberg, Robert L.; Hales, Tim G.; Stuart, Joshua M.; Lee, Norman H.

2010-01-01

Voltage-gated Na+ channels (VGSCs) have been implicated in the metastatic potential of human breast, prostate and lung cancer cells. Specifically, the SCN5A gene encoding the VGSC isotype Nav1.5 has been defined as a key driver of human cancer cell invasion. In this study, we examined the expression and function of VGSCs in a panel of colon cancer cell lines by electrophysiological recordings. Na+ channel activity and invasive potential were inhibited pharmacologically by tetrodotoxin or genetically by siRNAs specifically targeting SCN5A. Clinical relevance was established by immunohistochemistry of patient biopsies, where there was strong Nav1.5 protein staining in colon cancer specimens but little to no staining in matched-paired normal colon tissues. We explored the mechanism of VGSC-mediated invasive potential on the basis of reported links between VGSC activity and gene expression in excitable cells. Probabilistic modeling of loss-of-function screens and microarray data established an unequivocal role of VGSC SCN5A as a high level regulator of a colon cancer invasion network, involving genes that encompass Wnt signaling, cell migration, ectoderm development, response to biotic stimulus, steroid metabolic process and cell cycle control. siRNA-mediated knockdown of predicted downstream network components caused a loss of invasive behavior, demonstrating network connectivity and its function in driving colon cancer invasion. PMID:20651255

Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

Directory of Open Access Journals (Sweden)

Cheng-Wei Ma

Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

Science.gov (United States)

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

A new traffic control design method for large networks with signalized intersections

Science.gov (United States)

Leininger, G. G.; Colony, D. C.; Seldner, K.

1979-01-01

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

1st International Conference on Signal, Networks, Computing, and Systems

CERN Document Server

Mohapatra, Durga; Nagar, Atulya; Sahoo, Manmath

2016-01-01

The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on Signal, Networks, Computing, and Systems (ICSNCS 2016) held at Jawaharlal Nehru University, New Delhi, India during February 25–27, 2016. The book is organized in to two volumes and primarily focuses on theory and applications in the broad areas of communication technology, computer science and information security. The book aims to bring together the latest scientific research works of academic scientists, professors, research scholars and students in the areas of signal, networks, computing and systems detailing the practical challenges encountered and the solutions adopted.

Stromal COX-2 signaling activated by deoxycholic acid mediates proliferation and invasiveness of colorectal epithelial cancer cells

Energy Technology Data Exchange (ETDEWEB)

Zhu, Yingting, E-mail: yitizhu@yahoo.com [Arizona Cancer Center, The University of Arizona, Tucson, AZ 85724 (United States); Tissue Tech Inc., Miami, FL 33173 (United States); Zhu, Min; Lance, Peter [Arizona Cancer Center, The University of Arizona, Tucson, AZ 85724 (United States)

2012-08-31

Highlights: Black-Right-Pointing-Pointer Human colonic cancer associated fibroblasts are major sources of COX-2 and PGE{sub 2}. Black-Right-Pointing-Pointer The fibroblasts interact with human colonic epithelial cancer cells. Black-Right-Pointing-Pointer Activation of COX-2 signaling in the fibroblasts affects behavior of the epithelia. Black-Right-Pointing-Pointer Protein Kinase C controls the activation of COX-2 signaling. -- Abstract: COX-2 is a major regulator implicated in colonic cancer. However, how COX-2 signaling affects colonic carcinogenesis at cellular level is not clear. In this article, we investigated whether activation of COX-2 signaling by deoxycholic acid (DCA) in primary human normal and cancer associated fibroblasts play a significant role in regulation of proliferation and invasiveness of colonic epithelial cancer cells. Our results demonstrated while COX-2 signaling can be activated by DCA in both normal and cancer associated fibroblasts, the level of activation of COX-2 signaling is significantly greater in cancer associated fibroblasts than that in normal fibroblasts. In addition, we discovered that the proliferative and invasive potential of colonic epithelial cancer cells were much greater when the cells were co-cultured with cancer associated fibroblasts pre-treated with DCA than with normal fibroblasts pre-treated with DCA. Moreover, COX-2 siRNA attenuated the proliferative and invasive effect of both normal and cancer associate fibroblasts pre-treated with DCA on the colonic cancer cells. Further studies indicated that the activation of COX-2 signaling by DCA is through protein kinase C signaling. We speculate that activation of COX-2 signaling especially in cancer associated fibroblasts promotes progression of colonic cancer.

The Hippo/YAP pathway interacts with EGFR signaling and HPV oncoproteins to regulate cervical cancer progression

Science.gov (United States)

He, Chunbo; Mao, Dagan; Hua, Guohua; Lv, Xiangmin; Chen, Xingcheng; Angeletti, Peter C; Dong, Jixin; Remmenga, Steven W; Rodabaugh, Kerry J; Zhou, Jin; Lambert, Paul F; Yang, Peixin; Davis, John S; Wang, Cheng

2015-01-01

The Hippo signaling pathway controls organ size and tumorigenesis through a kinase cascade that inactivates Yes-associated protein (YAP). Here, we show that YAP plays a central role in controlling the progression of cervical cancer. Our results suggest that YAP expression is associated with a poor prognosis for cervical cancer. TGF-α and amphiregulin (AREG), via EGFR, inhibit the Hippo signaling pathway and activate YAP to induce cervical cancer cell proliferation and migration. Activated YAP allows for up-regulation of TGF-α, AREG, and EGFR, forming a positive signaling loop to drive cervical cancer cell proliferation. HPV E6 protein, a major etiological molecule of cervical cancer, maintains high YAP protein levels in cervical cancer cells by preventing proteasome-dependent YAP degradation to drive cervical cancer cell proliferation. Results from human cervical cancer genomic databases and an accepted transgenic mouse model strongly support the clinical relevance of the discovered feed-forward signaling loop. Our study indicates that combined targeting of the Hippo and the ERBB signaling pathways represents a novel therapeutic strategy for prevention and treatment of cervical cancer. PMID:26417066

Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators.

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Gunn, Christine M; Parker, Victoria A; Bak, Sharon M; Ko, Naomi; Nelson, Kerrie P; Battaglia, Tracy A

2017-08-01

Minority women in the U.S. continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models like patient navigation focus on social barriers, but evidence demonstrating how these models increase social capital is lacking. This pilot study describes the social networks of newly diagnosed breast cancer patients and explores the contributing role of patient navigators. Twenty-five women completed a one hour interview about their social networks related to cancer care support. Network metrics identified important structural attributes and influential individuals. Bivariate associations between network metrics, type of network, and whether the network included a navigator were measured. Secondary analyses explored associations between network structures and clinical outcomes. We identified three types of networks: kin-based, role and/or affect-based, or heterogeneous. Network metrics did not vary significantly by network type. There was a low prevalence of navigators included in the support networks (25%). Network density scores were significantly higher in those networks without a navigator. Network metrics were not predictive of clinical outcomes in multivariate models. Patient navigators were not frequently included in support networks, but provided distinctive types of support. If navigators can identify patients with poorly integrated (less dense) social networks, or who have unmet tangible support needs, the intensity of navigation services could be tailored. Services and systems that address gaps and variations in patient social networks should be explored for their potential to reduce cancer health disparities. This study used a new method to identify the breadth and strength of social support following a diagnosis of breast cancer, especially examining the role of patient navigators in providing support. While navigators were only included in one quarter of patient

Programs for control of an analog-signal switching network

International Nuclear Information System (INIS)

D'Ottavio, T.; Enriquez, R.; Katz, R.; Skelly, J.

1989-01-01

A suite of programs has been developed to control the network of analog-signal switching multiplexers in the AGS complex. The software is driven by a relational database which describes the architecture of the multiplexer tree and the set of available analog signals. Signals are routed through a three-layer multiplexer tree, to be made available at four consoles each with three 4-trace oscilloscopes. A menu-structured operator interface program is available at each console, to accept requests to route any available analog signal to any of that console's 12 oscilloscope traces. A common routing-server program provides automatic routing-server program provides automatic routing of requested signals through the layers of multiplexers, maintaining a reservation database to denote free and in-use trunks. Expansion of the analog signal system is easily accommodated in software by adding new signals, trunks, multiplexers, or consoles to the database. Programmatic control of the triggering signals for each of the oscilloscopes is also provided. 3 refs., 4 figs., 3 tabs

Non-Coding RNAs in Castration-Resistant Prostate Cancer: Regulation of Androgen Receptor Signaling and Cancer Metabolism.

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Shih, Jing-Wen; Wang, Ling-Yu; Hung, Chiu-Lien; Kung, Hsing-Jien; Hsieh, Chia-Ling

2015-12-04

Hormone-refractory prostate cancer frequently relapses from therapy and inevitably progresses to a bone-metastatic status with no cure. Understanding of the molecular mechanisms conferring resistance to androgen deprivation therapy has the potential to lead to the discovery of novel therapeutic targets for type of prostate cancer with poor prognosis. Progression to castration-resistant prostate cancer (CRPC) is characterized by aberrant androgen receptor (AR) expression and persistent AR signaling activity. Alterations in metabolic activity regulated by oncogenic pathways, such as c-Myc, were found to promote prostate cancer growth during the development of CRPC. Non-coding RNAs represent a diverse family of regulatory transcripts that drive tumorigenesis of prostate cancer and various other cancers by their hyperactivity or diminished function. A number of studies have examined differentially expressed non-coding RNAs in each stage of prostate cancer. Herein, we highlight the emerging impacts of microRNAs and long non-coding RNAs linked to reactivation of the AR signaling axis and reprogramming of the cellular metabolism in prostate cancer. The translational implications of non-coding RNA research for developing new biomarkers and therapeutic strategies for CRPC are also discussed.

Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

OpenAIRE

Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari

2014-01-01

Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...

Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

Science.gov (United States)

CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

2016-01-01

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

The Transcriptional Landscape of p53 Signalling Pathway

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Chizu Tanikawa

2017-06-01

Full Text Available Although recent cancer genomics studies have identified a large number of genes that were mutated in human cancers, p53 remains as the most frequently mutated gene. To further elucidate the p53-signalling network, we performed transcriptome analysis on 24 tissues in p53+/+ or p53−/− mice after whole-body X-ray irradiation. Here we found transactivation of a total of 3551 genes in one or more of the 24 tissues only in p53+/+ mice, while 2576 genes were downregulated. p53 mRNA expression level in each tissue was significantly associated with the number of genes upregulated by irradiation. Annotation using TCGA (The Cancer Genome Atlas database revealed that p53 negatively regulated mRNA expression of several cancer therapeutic targets or pathways such as BTK, SYK, and CTLA4 in breast cancer tissues. In addition, stomach exhibited the induction of Krt6, Krt16, and Krt17 as well as loricrin, an epidermal differentiation marker, after the X-ray irradiation only in p53+/+ mice, implying a mechanism to protect damaged tissues by rapid induction of differentiation. Our comprehensive transcriptome analysis elucidated tissue specific roles of p53 and its signalling networks in DNA-damage response that will enhance our understanding of cancer biology.

Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

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Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

Science.gov (United States)

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

Inference of cancer-specific gene regulatory networks using soft computing rules.

Science.gov (United States)

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Ovarian cancer stem-like cells differentiate into endothelial cells and participate in tumor angiogenesis through autocrine CCL5 signaling.

Science.gov (United States)

Tang, Shu; Xiang, Tong; Huang, Shuo; Zhou, Jie; Wang, Zhongyu; Xie, Rongkai; Long, Haixia; Zhu, Bo

2016-06-28

Cancer stem cells (CSCs) are well known for their self-regeneration and tumorigenesis potential. In addition, the multi-differentiation potential of CSCs has become a popular issue and continues to attract increased research attention. Recent studies demonstrated that CSCs are able to differentiate into functional endothelial cells and participate in tumor angiogenesis. In this study, we found that ovarian cancer stem-like cells (CSLCs) activate the NF-κB and STAT3 signal pathways through autocrine CCL5 signaling and mediate their own differentiation into endothelial cells (ECs). Our data demonstrate that CSLCs differentiate into ECs morphologically and functionally. Anti-CCL5 antibodies and CCL5-shRNA lead to markedly inhibit EC differentiation and the tube formation of CSLCs, both in vitro and in vivo. Recombinant human-CCL5 significantly promotes ovarian CSLCs that differentiate into ECs and form microtube network. The CCL5-mediated EC differentiation of CSLCs depends on binding to receptors, such as CCR1, CCR3, and CCR5. The results demonstrated that CCL5-CCR1/CCR3/CCR5 activates the NF-κB and STAT3 signal pathways, subsequently mediating the differentiation of CSLCs into ECs. Therefore, this study was conducted based on the theory that CSCs improve tumor angiogenesis and provides a novel strategy for anti-angiogenesis in ovarian cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Curcumin and emodin down-regulate TGF-β signaling pathway in human cervical cancer cells.

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Pooja Chandrakant Thacker

Full Text Available Cervical cancer is the major cause of cancer related deaths in women, especially in developing countries and Human Papilloma Virus infection in conjunction with multiple deregulated signaling pathways leads to cervical carcinogenesis. TGF-β signaling in later stages of cancer is known to induce epithelial to mesenchymal transition promoting tumor growth. Phytochemicals, curcumin and emodin, are effective as chemopreventive and chemotherapeutic compounds against several cancers including cervical cancer. The main objective of this work was to study the effect of curcumin and emodin on TGF-β signaling pathway and its functional relevance to growth, migration and invasion in two cervical cancer cell lines, SiHa and HeLa. Since TGF-β and Wnt/β-catenin signaling pathways are known to cross talk having common downstream targets, we analyzed the effect of TGF-β on β-catenin (an important player in Wnt/β-catenin signaling and also studied whether curcumin and emodin modulate them. We observed that curcumin and emodin effectively down regulate TGF-β signaling pathway by decreasing the expression of TGF-β Receptor II, P-Smad3 and Smad4, and also counterbalance the tumorigenic effects of TGF-β by inhibiting the TGF-β-induced migration and invasion. Expression of downstream effectors of TGF-β signaling pathway, cyclinD1, p21 and Pin1, was inhibited along with the down regulation of key mesenchymal markers (Snail and Slug upon curcumin and emodin treatment. Curcumin and emodin were also found to synergistically inhibit cell population and migration in SiHa and HeLa cells. Moreover, we found that TGF-β activates Wnt/β-catenin signaling pathway in HeLa cells, and curcumin and emodin down regulate the pathway by inhibiting β-catenin. Taken together our data provide a mechanistic basis for the use of curcumin and emodin in the treatment of cervical cancer.

Design principles of nuclear receptor signaling: how complex networking improves signal transduction

Science.gov (United States)

Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

2010-01-01

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

Fox Chase Network: Fox Chase Cancer Center's community hospital affiliation program.

Science.gov (United States)

Higman, S A; McKay, F J; Engstrom, P F; O'Grady, M A; Young, R C

2000-01-01

Fox Chase Cancer Center developed a format for affiliation with community providers in 1986. Fox Chase Network was formed to establish hospital-based community cancer centers to increase access to patients involved in clinical research. Under this program, the Fox Chase Network now contributes 500 patients per year to prevention and clinical research studies. As relationships with community providers form, patient referrals have increased at Fox Chase Cancer Center and for each Fox Chase Network member. A dedicated staff is required to operate the central office on a day-to-day basis as well as at each affiliate. We have found this to be a critical element in each program's success. New challenges in the cancer business-increasing volumes with declining revenue-have caused us to reconfigure the services offered to affiliates, while maintaining true to our mission: to reduce the burden of human cancer.

Hedgehog Signaling Regulates the Survival of Gastric Cancer Cells by Regulating the Expression of Bcl-2

Science.gov (United States)

Han, Myoung-Eun; Lee, Young-Suk; Baek, Sun-Yong; Kim, Bong-Seon; Kim, Jae-Bong; Oh, Sae-Ock

2009-01-01

Gastric cancer is the second most common cause of cancer deaths worldwide. The underlying molecular mechanisms of its carcinogenesis are relatively poorly characterized. Hedgehog (Hh) signaling, which is critical for development of various organs including the gastrointestinal tract, has been associated with gastric cancer. The present study was undertaken to reveal the underlying mechanism by which Hh signaling controls gastric cancer cell proliferation. Treatment of gastric cancer cells with cyclopamine, a specific inhibitor of Hh signaling pathway, reduced proliferation and induced apoptosis of gastric cancer cells. Cyclopamine treatment induced cytochrome c release from mitochondria and cleavage of caspase 9. Moreover, Bcl-2 expression was significantly reduced by cyclopamine treatment. These results suggest that Hh signaling regulates the survival of gastric cancer cells by regulating the expression of Bcl-2. PMID:19742123

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Science.gov (United States)

2015-01-01

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

Integrated analysis of breast cancer cell lines reveals unique signaling pathways

Energy Technology Data Exchange (ETDEWEB)

Heiser, Laura M.; Wang, Nicholas J.; Talcott, Carolyn L.; Laderoute, Keith R.; Knapp, Merrill; Guan, Yinghui; Hu, Zhi; Ziyad, Safiyyah; Weber, Barbara L.; Laquerre, Sylvie; Jackson, Jeffrey R.; Wooster, Richard F.; Kuo, Wen-Lin; Gray, Joe W.; Spellman, Paul T.

2009-03-31

Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EGFR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes. We were interested in identifying subnetworks within the EGFR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EGFR-MEK signaling. This model was comprised of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype specific subnetworks, including one that suggested PAK1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that PAK1 overexpressing cell lines would have increased sensitivity to MEK inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three MEK inhibitors. We found that PAK1 over-expressing luminal breast cancer cell lines are significantly more sensitive to MEK inhibition as compared to those that express PAK1 at low levels. This indicates that PAK1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to MEK inhibitors. All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Integrated analysis of breast cancer cell lines reveals unique signaling pathways.

Science.gov (United States)

Heiser, Laura M; Wang, Nicholas J; Talcott, Carolyn L; Laderoute, Keith R; Knapp, Merrill; Guan, Yinghui; Hu, Zhi; Ziyad, Safiyyah; Weber, Barbara L; Laquerre, Sylvie; Jackson, Jeffrey R; Wooster, Richard F; Kuo, Wen Lin; Gray, Joe W; Spellman, Paul T

2009-01-01

Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes. We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors. All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Best Signal Quality in Cellular Networks: Asymptotic Properties and Applications to Mobility Management in Small Cell Networks

Directory of Open Access Journals (Sweden)

Baccelli François

2010-01-01

Full Text Available The quickly increasing data traffic and the user demand for a full coverage of mobile services anywhere and anytime are leading mobile networking into a future of small cell networks. However, due to the high-density and randomness of small cell networks, there are several technical challenges. In this paper, we investigate two critical issues: best signal quality and mobility management. Under the assumptions that base stations are uniformly distributed in a ring-shaped region and that shadowings are lognormal, independent, and identically distributed, we prove that when the number of sites in the ring tends to infinity, then (i the maximum signal strength received at the center of the ring tends in distribution to a Gumbel distribution when properly renormalized, and (ii it is asymptotically independent of the interference. Using these properties, we derive the distribution of the best signal quality. Furthermore, an optimized random cell scanning scheme is proposed, based on the evaluation of the optimal number of sites to be scanned for maximizing the user data throughput.

Flavonoids and Wnt/β-Catenin Signaling: Potential Role in Colorectal Cancer Therapies

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Nathália G. Amado

2014-07-01

Full Text Available It is now well documented that natural products have played an important role in anticancer therapy. Many studies focus on the ability of these natural compounds to modulate tumor-related signaling pathways and the relationship of these properties to an anticancer effect. According to the World Health Organization (WHO, colorectal cancer (CRC is the third most common cancer and the fourth leading cause of cancer death among men and women. Therefore, finding strategies to fight against CRC is an emergent health problem. CRC has a strong association with deregulation of Wnt/β-catenin signaling pathway. As some types of natural compounds are capable of modulating the Wnt/β-catenin signaling, one important question is whether they could counteract CRC. In this review, we discuss the role of flavonoids, a class of natural compounds, on Wnt/β-catenin regulation and its possible potential for therapeutic usage on colorectal cancer.

Crosstalk between long non-coding RNAs and Wnt/β-catenin signalling in cancer.

Science.gov (United States)

Yang, Gang; Shen, Tianyi; Yi, Xiaoming; Zhang, Zhengyu; Tang, Chaopeng; Wang, Longxin; Zhou, Yulin; Zhou, Wenquan

2018-04-01

Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts in the human genome which perform crucial functions in diverse biological processes. The abnormal expression of some lncRNAs has been found in tumorigenesis, development and therapy resistance of cancers. They may act as oncogenes or tumour suppressors and can be used as diagnostic or prognostic markers, prompting their therapeutic potentials in cancer treatments. Studies have indicated that many lncRNAs are involved in the regulation of several signal pathways, including Wnt/β-catenin signalling pathway, which has been reported to play a significant role in regulating embryogenesis, cell proliferation and controlling tumour biology. Emerging evidences have suggested that lncRNAs can interact with several components of the Wnt/β-catenin signalling pathway to regulate the expression of Wnt target genes in cancer. Moreover, the expression of lncRNAs can also be influenced by the pathway. Nevertheless, Wnt/β-catenin signalling pathway-related lncRNAs and their interactions in cancer are not systematically analysed before. Considering these, this review emphasized the associations between lncRNAs and Wnt/β-catenin signalling pathway in cancer initiation, progression and their therapeutic influence. We also provided an overview on characteristics of lncRNAs and Wnt/β-catenin signalling pathway and discussed their functions in tumour biology. Finally, targeting lncRNAs or/and molecules associated with the Wnt/β-catenin signalling pathway may be a feasible therapeutic method in the future. © 2018 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Characterization of Radar Signals Using Neural Networks

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1990-12-01

e***e*e*eeeeeeeeeeeesseeeeeese*eee*e*e************s /* Function Name: load.input.ptterns Number: 4.1 /* Description: This function determines wether ...XSE.last.layer Number: 8.5 */ /* Description: The function determines wether to backpropate the *f /* parameter by the sigmoidal or linear update...Sigmoidal Function," Mathematics of Control, Signals and Systems, 2:303-314 (March 1989). 6. Dayhoff, Judith E. Neural Network Architectures. New York: Van

Targeting Wnt signaling in colorectal cancer. A Review in the Theme: Cell Signaling: Proteins, Pathways and Mechanisms

Science.gov (United States)

Novellasdemunt, Laura; Antas, Pedro

2015-01-01

The evolutionarily conserved Wnt signaling pathway plays essential roles during embryonic development and tissue homeostasis. Notably, comprehensive genetic studies in Drosophila and mice in the past decades have demonstrated the crucial role of Wnt signaling in intestinal stem cell maintenance by regulating proliferation, differentiation, and cell-fate decisions. Wnt signaling has also been implicated in a variety of cancers and other diseases. Loss of the Wnt pathway negative regulator adenomatous polyposis coli (APC) is the hallmark of human colorectal cancers (CRC). Recent advances in high-throughput sequencing further reveal many novel recurrent Wnt pathway mutations in addition to the well-characterized APC and β-catenin mutations in CRC. Despite attractive strategies to develop drugs for Wnt signaling, major hurdles in therapeutic intervention of the pathway persist. Here we discuss the Wnt-activating mechanisms in CRC and review the current advances and challenges in drug discovery. PMID:26289750

Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

Science.gov (United States)

Naderi, Elnaz; Mostafaei, Mehdi; Pourshams, Akram

2014-01-01

Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches. PMID:24895587

Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

Directory of Open Access Journals (Sweden)

Elnaz Naderi

2014-01-01

Full Text Available Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches.

Loss of claudin-3 expression induces IL6/gp130/Stat3 signaling to promote colon cancer malignancy by hyperactivating Wnt/β-catenin signaling.

Science.gov (United States)

Ahmad, R; Kumar, B; Chen, Z; Chen, X; Müller, D; Lele, S M; Washington, M K; Batra, S K; Dhawan, P; Singh, A B

2017-11-23

The hyperactivated Wnt/β-catenin signaling acts as a switch to induce epithelial to mesenchymal transition and promote colorectal cancer. However, due to its essential role in gut homeostasis, therapeutic targeting of this pathway has proven challenging. Additionally, IL-6/Stat-3 signaling, activated by microbial translocation through the dysregulated mucosal barrier in colon adenomas, facilitates the adenoma to adenocarcinomas transition. However, inter-dependence between these signaling pathways and key mucosal barrier components in regulating colon tumorigenesis and cancer progression remains unclear. In current study, we have discovered, using a comprehensive investigative regimen, a novel and tissue-specific role of claudin-3, a tight junction integral protein, in inhibiting colon cancer progression by serving as the common rheostat of Stat-3 and Wnt-signaling activation. Loss of claudin-3 also predicted poor patient survival. These findings however contrasted an upregulated claudin-3 expression in other cancer types and implicated role of the epigenetic regulation. Claudin-3-/- mice revealed dedifferentiated and leaky colonic epithelium, and developed invasive adenocarcinoma when subjected to colon cancer. Wnt-signaling hyperactivation, albeit in GSK-3β independent manner, differentiated colon cancer in claudin-3-/- mice versus WT-mice. Claudin-3 loss also upregulated the gp130/IL6/Stat3 signaling in colonic epithelium potentially assisted by infiltrating immune components. Genetic and pharmacological studies confirmed that claudin-3 loss induces Wnt/β-catenin activation, which is further exacerbated by Stat-3-activation and help promote colon cancer. Overall, these novel findings identify claudin-3 as a therapeutic target for inhibiting overactivation of Wnt-signaling to prevent CRC malignancy.

CLIC4 Moves Into Nucleus to Stabilize Anti-Growth Signal | Center for Cancer Research

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In cancer, the delicate balance of signaling pathways that control cell growth and function is disrupted. One signaling pathway commonly altered in cancer is the TGF-beta pathway. TGF-beta significantly inhibits growth of normal cells, particularly epithelial cells. Many cancer cells have developed ways to bypass one or more steps of this pathway in order to achieve

Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

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S. N. Kale

2009-01-01

Full Text Available Electromyography (EMG signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

International Nuclear Information System (INIS)

Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

2009-01-01

Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

Polyclonal immune responses to antigens associated with cancer signaling pathways and new strategies to enhance cancer vaccines.

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Clay, Timothy M; Osada, Takuya; Hartman, Zachary C; Hobeika, Amy; Devi, Gayathri; Morse, Michael A; Lyerly, H Kim

2011-04-01

Aberrant signaling pathways are a hallmark of cancer. A variety of strategies for inhibiting signaling pathways have been developed, but monoclonal antibodies against receptor tyrosine kinases have been among the most successful. A challenge for these therapies is therapeutic unresponsiveness and acquired resistance due to mutations in the receptors, upregulation of alternate growth and survival pathways, or inadequate function of the monoclonal antibodies. Vaccines are able to induce polyclonal responses that can have a multitude of affects against the target molecule. We began to explore therapeutic vaccine development to antigens associated with these signaling pathways. We provide an illustrative example in developing therapeutic cancer vaccines inducing polyclonal adaptive immune responses targeting the ErbB family member HER2. Further, we will discuss new strategies to augment the clinical efficacy of cancer vaccines by enhancing vaccine immunogenicity and reversing the immunosuppressive tumor microenvironment.

The Role of Cyclic Nucleotide Signaling Pathways in Cancer: Targets for Prevention and Treatment

Energy Technology Data Exchange (ETDEWEB)

Fajardo, Alexandra M.; Piazza, Gary A. [Drug Discovery Research Center, Mitchell Cancer Institute, University of South Alabama, 1660 Springhill Ave, Suite 3029, Mobile, AL 36604 (United States); Tinsley, Heather N., E-mail: htinsley@montevallo.edu [Department of Biology, Chemistry, and Mathematics, University of Montevallo, Station 6480, Montevallo, AL 35115 (United States)

2014-02-26

For more than four decades, the cyclic nucleotides cyclic AMP (cAMP) and cyclic GMP (cGMP) have been recognized as important signaling molecules within cells. Under normal physiological conditions, cyclic nucleotides regulate a myriad of biological processes such as cell growth and adhesion, energy homeostasis, neuronal signaling, and muscle relaxation. In addition, altered cyclic nucleotide signaling has been observed in a number of pathophysiological conditions, including cancer. While the distinct molecular alterations responsible for these effects vary depending on the specific cancer type, several studies have demonstrated that activation of cyclic nucleotide signaling through one of three mechanisms—induction of cyclic nucleotide synthesis, inhibition of cyclic nucleotide degradation, or activation of cyclic nucleotide receptors—is sufficient to inhibit proliferation and activate apoptosis in many types of cancer cells. These findings suggest that targeting cyclic nucleotide signaling can provide a strategy for the discovery of novel agents for the prevention and/or treatment of selected cancers.

A Comprehensive Nuclear Receptor Network for Breast Cancer Cells

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Ralf Kittler

2013-02-01

Full Text Available In breast cancer, nuclear receptors (NRs play a prominent role in governing gene expression, have prognostic utility, and are therapeutic targets. We built a regulatory map for 24 NRs, six chromatin state markers, and 14 breast-cancer-associated transcription factors (TFs that are expressed in the breast cancer cell line MCF-7. The resulting network reveals a highly interconnected regulatory matrix where extensive crosstalk occurs among NRs and other breast -cancer-associated TFs. We show that large numbers of factors are coordinately bound to highly occupied target regions throughout the genome, and these regions are associated with active chromatin state and hormone-responsive gene expression. This network also provides a framework for stratifying and predicting patient outcomes, and we use it to show that the peroxisome proliferator-activated receptor delta binds to a set of genes also regulated by the retinoic acid receptors and whose expression is associated with poor prognosis in breast cancer.

Logical network of genotoxic stress-induced NF-kappaB signal transduction predicts putative target structures for therapeutic intervention strategies

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Rainer Poltz

2009-12-01

Full Text Available Rainer Poltz1, Raimo Franke1,#, Katrin Schweitzer1, Steffen Klamt2, Ernst-Dieter Gilles2, Michael Naumann11Institute of Experimental Internal Medicine, Otto von Guericke University, Magdeburg, Germany; 2Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany; #Present address: Department of Chemical Biology, Helmholtz Centre for Infection Research, Braunschweig, GermanyAbstract: Genotoxic stress is induced by a broad range of DNA-damaging agents and could lead to a variety of human diseases including cancer. DNA damage is also therapeutically induced for cancer treatment with the aim to eliminate tumor cells. However, the effectiveness of radio- and chemotherapy is strongly hampered by tumor cell resistance. A major reason for radio- and chemotherapeutic resistances is the simultaneous activation of cell survival pathways resulting in the activation of the transcription factor nuclear factor-kappa B (NF-κB. Here, we present a Boolean network model of the NF-κB signal transduction induced by genotoxic stress in epithelial cells. For the representation and analysis of the model, we used the formalism of logical interaction hypergraphs. Model reconstruction was based on a careful meta-analysis of published data. By calculating minimal intervention sets, we identified p53-induced protein with a death domain (PIDD, receptor-interacting protein 1 (RIP1, and protein inhibitor of activated STAT y (PIASy as putative therapeutic targets to abrogate NF-κB activation resulting in apoptosis. Targeting these structures therapeutically may potentiate the effectiveness of radio- and chemotherapy. Thus, the presented model allows a better understanding of the signal transduction in tumor cells and provides candidates as new therapeutic target structures.Keywords: apoptosis, Boolean network, cancer therapy, DNA-damage response, NF-κB

Analysis of variants in DNA damage signalling genes in bladder cancer

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Bishop D Timothy

2008-07-01

Full Text Available Abstract Background Chemicals from occupational exposure and components of cigarette smoke can cause DNA damage in bladder urothelium. Failure to repair DNA damage by DNA repair proteins may result in mutations leading to genetic instability and the development of bladder cancer. Immunohistochemistry studies have shown DNA damage signal activation in precancerous bladder lesions which is lost on progression, suggesting that the damage signalling mechanism acts as a brake to further tumorigenesis. Single nucleotide polymorphisms (SNPs in DSB signalling genes may alter protein function. We hypothesized that SNPs in DSB signalling genes may modulate predisposition to bladder cancer and influence the effects of environmental exposures. Methods We recruited 771 cases and 800 controls (573 hospital-based and 227 population-based from a previous case-control study and interviewed them regarding their smoking habits and occupational history. DNA was extracted from a peripheral blood sample and genotyping of 24 SNPs in MRE11, NBS1, RAD50, H2AX and ATM was undertaken using an allelic discrimination method (Taqman. Results Smoking and occupational dye exposure were strongly associated with bladder cancer risk. Using logistic regression adjusting for age, sex, smoking and occupational dye exposure, there was a marginal increase in risk of bladder cancer for an MRE11 3'UTR SNP (rs2155209, adjusted odds ratio 1.54 95% CI (1.13–2.08, p = 0.01 for individuals homozygous for the rare allele compared to those carrying the common homozygous or heterozygous genotype. However, in the hospital-based controls, the genotype distribution for this SNP deviated from Hardy-Weinberg equilibrium. None of the other SNPs showed an association with bladder cancer and we did not find any significant interaction between any of these polymorphisms and exposure to smoking or dye exposure. Conclusion Apart from a possible effect for one MRE11 3'UTR SNP, our study does not support

Music Signal Processing Using Vector Product Neural Networks

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Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

TRAIL, Wnt, Sonic Hedgehog, TGFβ, and miRNA Signalings Are Potential Targets for Oral Cancer Therapy.

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Farooqi, Ammad Ahmad; Shu, Chih-Wen; Huang, Hurng-Wern; Wang, Hui-Ru; Chang, Yung-Ting; Fayyaz, Sundas; Yuan, Shyng-Shiou F; Tang, Jen-Yang; Chang, Hsueh-Wei

2017-07-14

Clinical studies and cancer cell models emphasize the importance of targeting therapies for oral cancer. The tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is highly expressed in cancer, and is a selective killing ligand for oral cancer. Signaling proteins in the wingless-type mouse mammary tumor virus (MMTV) integration site family (Wnt), Sonic hedgehog (SHH), and transforming growth factor β (TGFβ) pathways may regulate cell proliferation, migration, and apoptosis. Accordingly, the genes encoding these signaling proteins are potential targets for oral cancer therapy. In this review, we focus on recent advances in targeting therapies for oral cancer and discuss the gene targets within TRAIL, Wnt, SHH, and TGFβ signaling for oral cancer therapies. Oncogenic microRNAs (miRNAs) and tumor suppressor miRNAs targeting the genes encoding these signaling proteins are summarized, and the interactions between Wnt, SHH, TGFβ, and miRNAs are interpreted. With suitable combination treatments, synergistic effects are expected to improve targeting therapies for oral cancer.

TRAIL, Wnt, Sonic Hedgehog, TGFβ, and miRNA Signalings Are Potential Targets for Oral Cancer Therapy

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Farooqi, Ammad Ahmad; Shu, Chih-Wen; Huang, Hurng-Wern; Wang, Hui-Ru; Chang, Yung-Ting; Fayyaz, Sundas; Yuan, Shyng-Shiou F.; Tang, Jen-Yang

2017-01-01

Clinical studies and cancer cell models emphasize the importance of targeting therapies for oral cancer. The tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is highly expressed in cancer, and is a selective killing ligand for oral cancer. Signaling proteins in the wingless-type mouse mammary tumor virus (MMTV) integration site family (Wnt), Sonic hedgehog (SHH), and transforming growth factor β (TGFβ) pathways may regulate cell proliferation, migration, and apoptosis. Accordingly, the genes encoding these signaling proteins are potential targets for oral cancer therapy. In this review, we focus on recent advances in targeting therapies for oral cancer and discuss the gene targets within TRAIL, Wnt, SHH, and TGFβ signaling for oral cancer therapies. Oncogenic microRNAs (miRNAs) and tumor suppressor miRNAs targeting the genes encoding these signaling proteins are summarized, and the interactions between Wnt, SHH, TGFβ, and miRNAs are interpreted. With suitable combination treatments, synergistic effects are expected to improve targeting therapies for oral cancer. PMID:28708091

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

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Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

2017-09-29

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

Transfer of optical signals around bends in two-dimensional linear photonic networks

International Nuclear Information System (INIS)

Nikolopoulos, G M

2015-01-01

The ability to navigate light signals in two-dimensional networks of waveguide arrays is a prerequisite for the development of all-optical integrated circuits for information processing and networking. In this article, we present a theoretical analysis of bending losses in linear photonic lattices with engineered couplings, and discuss possible ways for their minimization. In contrast to previous work in the field, the lattices under consideration operate in the linear regime, in the sense that discrete solitons cannot exist. The present results suggest that the functionality of linear waveguide networks can be extended to operations that go beyond the recently demonstrated point-to-point transfer of signals, such as blocking, routing, logic functions, etc. (paper)

The Multifaceted Roles of STAT3 Signaling in the Progression of Prostate Cancer

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Bishop, Jennifer L.; Thaper, Daksh; Zoubeidi, Amina

2014-01-01

The signal transducer and activator of transcription (STAT)3 governs essential functions of epithelial and hematopoietic cells that are often dysregulated in cancer. While the role for STAT3 in promoting the progression of many solid and hematopoietic malignancies is well established, this review will focus on the importance of STAT3 in prostate cancer progression to the incurable metastatic castration-resistant prostate cancer (mCRPC). Indeed, STAT3 integrates different signaling pathways involved in the reactivation of androgen receptor pathway, stem like cells and the epithelial to mesenchymal transition that drive progression to mCRPC. As equally important, STAT3 regulates interactions between tumor cells and the microenvironment as well as immune cell activation. This makes it a major factor in facilitating prostate cancer escape from detection of the immune response, promoting an immunosuppressive environment that allows growth and metastasis. Based on the multifaceted nature of STAT3 signaling in the progression to mCRPC, the promise of STAT3 as a therapeutic target to prevent prostate cancer progression and the variety of STAT3 inhibitors used in cancer therapies is discussed

Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

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Xiaosheng Wang

2010-03-01

Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

The Role of Notch Signaling Pathway in Breast Cancer Pathogenesis

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2005-07-01

breast cancer cells, I tested whether ErbB2 overexpression will cooperate with Notch in HMLE cells. While overexpression of activated Notch1 failed to...tyrosine kinase upstream of Ras normally found overexpressed in many breast cancers , also failed to transform HMLE cells. These observations suggested...cooperation between Notch1IC and ErbB2 signaling in transforming HMLE cells. Breast cancers typically do not harbor oncogenic Ras mutations; nevertheless

Nonlinear signal processing using neural networks: Prediction and system modelling

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Lapedes, A.; Farber, R.

1987-06-01

The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

Analysis of market signals in a competitive electricity market using components of network rental

International Nuclear Information System (INIS)

Amarasinghe, L.Y.C.; Annakkage, U.D.

2009-01-01

In the competitive electricity market, Locational Marginal Prices (LMPs) are important pricing signals for the participants as the effects of transmission losses and binding constraints are embedded in LMPs. While these LMPs provide valuable information at each location, they do not provide a detailed description in terms of contributing terms. The LMP components, on the other hand, show the explicit decomposition of LMP into contributing components, and thus, can be considered as better market signals. However, the effects of transmission losses cannot be explicitly seen from the LMP components. In this paper, the components of network rental is proposed to be used as a method in analyzing market signals, by decomposing the network rental into contributing components among the consumers. Since, the network rental is the surplus paid by all the consumers, components of network rental show how each consumer has actually overpaid due to losses and each binding constraint separately. A case study is also presented to demonstrate the potential of this proposed method in market signal analysis. (author)

Reconstruction of Micropattern Detector Signals using Convolutional Neural Networks

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Flekova, L.; Schott, M.

2017-10-01

Micropattern gaseous detector (MPGD) technologies, such as GEMs or MicroMegas, are particularly suitable for precision tracking and triggering in high rate environments. Given their relatively low production costs, MPGDs are an exemplary candidate for the next generation of particle detectors. Having acknowledged these advantages, both the ATLAS and CMS collaborations at the LHC are exploiting these new technologies for their detector upgrade programs in the coming years. When MPGDs are utilized for triggering purposes, the measured signals need to be precisely reconstructed within less than 200 ns, which can be achieved by the usage of FPGAs. In this work, we present a novel approach to identify reconstructed signals, their timing and the corresponding spatial position on the detector. In particular, we study the effect of noise and dead readout strips on the reconstruction performance. Our approach leverages the potential of convolutional neural network (CNNs), which have recently manifested an outstanding performance in a range of modeling tasks. The proposed neural network architecture of our CNN is designed simply enough, so that it can be modeled directly by an FPGA and thus provide precise information on reconstructed signals already in trigger level.

Histological evaluation of AMPK signalling in primary breast cancer

International Nuclear Information System (INIS)

Hadad, Sirwan M; Hardie, David G; Fleming, Stewart; Thompson, Alastair M; Baker, Lee; Quinlan, Philip R; Robertson, Katherine E; Bray, Susan E; Thomson, George; Kellock, David; Jordan, Lee B; Purdie, Colin A

2009-01-01

AMP-activated protein kinase (AMPK) acts as a cellular fuel gauge that responds to energy stress by suppressing cell growth and biosynthetic processes, thus ensuring that energy-consuming processes proceed only if there are sufficient metabolic resources. Malfunction of the AMPK pathway may allow cancer cells to undergo uncontrolled proliferation irrespective of their molecular energy levels. The aim of this study was to examine the state of AMPK phosphorylation histologically in primary breast cancer in relation to clinical and pathological parameters. Immunohistochemistry was performed using antibodies to phospho-AMPK (pAMPK), phospho-Acetyl Co-A Carboxylase (pACC) an established target for AMPK, HER2, ERα, and Ki67 on Tissue Micro-Array (TMA) slides of two cohorts of 117 and 237 primary breast cancers. The quick score method was used for scoring and patterns of protein expression were compared with clinical and pathological data, including a minimum 5 years follow up. Reduced signal, compared with the strong expression in normal breast epithelium, using a pAMPK antibody was demonstrated in 101/113 (89.4%) and 217/236 (91.9%) of two cohorts of patients. pACC was significantly associated with pAMPK expression (p = 0.007 & p = 0.014 respectively). For both cohorts, reduced pAMPK signal was significantly associated with higher histological grade (p = 0.010 & p = 0.021 respectively) and axillary node metastasis (p = 0.061 & p = 0.039 respectively). No significant association was found between pAMPK and any of HER2, ERα, or Ki67 expression, disease-free survival or overall survival. This study extends in vitro evidence through immunohistochemistry to confirm that AMPK is dysfunctional in primary breast cancer. Reduced signalling via the AMPK pathway, and the inverse relationship with histological grade and axillary node metastasis, suggests that AMPK re-activation could have therapeutic potential in breast cancer

Analysing 21cm signal with artificial neural network

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Shimabukuro, Hayato; a Semelin, Benoit

2018-05-01

The 21cm signal at epoch of reionization (EoR) should be observed within next decade. We expect that cosmic 21cm signal at the EoR provides us both cosmological and astrophysical information. In order to extract fruitful information from observation data, we need to develop inversion method. For such a method, we introduce artificial neural network (ANN) which is one of the machine learning techniques. We apply the ANN to inversion problem to constrain astrophysical parameters from 21cm power spectrum. We train the architecture of the neural network with 70 training datasets and apply it to 54 test datasets with different value of parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameter sets at a given redshift and also find that the accuracy of reconstruction is improved by increasing the number of given redshifts. We conclude that the ANN is viable inversion method whose main strength is that they require a sparse extrapolation of the parameter space and thus should be usable with full simulation.

Sphingosine Kinase 1 and Sphingosine-1-Phosphate Signaling in Colorectal Cancer

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Yonghua Bao

2017-10-01

Full Text Available Sphingosine kinase 1 (Sphk1 is a highly conserved lipid kinase that phosphorylates sphingosine to form sphingosine-1-phosphate (S1P. Growing studies have demonstrated that Sphk1 is overexpressed in various types of solid cancers and can be induced by growth factors, cytokines, and carcinogens, leading to the increase of S1P production. Subsequently, the increased Sphk1/S1P facilitates cancer cell proliferation, mobility, angiogenesis, invasion, and metastasis. Therefore, Sphk1/S1P signaling plays oncogenic roles. This review summarizes the features of Sphk1/S1P signaling and their functions in colorectal cancer cell growth, tumorigenesis, and metastasis, as well as the possible underlying mechanisms.

Targeting CB2-GPR55 Receptor Heteromers Modulates Cancer Cell Signaling*

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Moreno, Estefanía; Andradas, Clara; Medrano, Mireia; Caffarel, María M.; Pérez-Gómez, Eduardo; Blasco-Benito, Sandra; Gómez-Cañas, María; Pazos, M. Ruth; Irving, Andrew J.; Lluís, Carme; Canela, Enric I.; Fernández-Ruiz, Javier; Guzmán, Manuel; McCormick, Peter J.; Sánchez, Cristina

2014-01-01

The G protein-coupled receptors CB2 (CB2R) and GPR55 are overexpressed in cancer cells and human tumors. Because a modulation of GPR55 activity by cannabinoids has been suggested, we analyzed whether this receptor participates in cannabinoid effects on cancer cells. Here we show that CB2R and GPR55 form heteromers in cancer cells, that these structures possess unique signaling properties, and that modulation of these heteromers can modify the antitumoral activity of cannabinoids in vivo. These findings unveil the existence of previously unknown signaling platforms that help explain the complex behavior of cannabinoids and may constitute new targets for therapeutic intervention in oncology. PMID:24942731

A sensor-based wrist pulse signal processing and lung cancer recognition.

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Zhang, Zhichao; Zhang, Yuan; Yao, Lina; Song, Houbing; Kos, Anton

2018-03-01

Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate. Copyright © 2018 Elsevier Inc. All rights reserved.

EEG signal classification using PSO trained RBF neural network for epilepsy identification

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Sandeep Kumar Satapathy

Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

Molecular Signaling Pathways Mediating Osteoclastogenesis Induced by Prostate Cancer Cells

International Nuclear Information System (INIS)

Rafiei, Shahrzad; Komarova, Svetlana V

2013-01-01

Advanced prostate cancer commonly metastasizes to bone leading to osteoblastic and osteolytic lesions. Although an osteolytic component governed by activation of bone resorbing osteoclasts is prominent in prostate cancer metastasis, the molecular mechanisms of prostate cancer-induced osteoclastogenesis are not well-understood. We studied the effect of soluble mediators released from human prostate carcinoma cells on osteoclast formation from mouse bone marrow and RAW 264.7 monocytes. Soluble factors released from human prostate carcinoma cells significantly increased viability of naïve bone marrow monocytes, as well as osteoclastogenesis from precursors primed with receptor activator of nuclear factor κ-B ligand (RANKL). The prostate cancer-induced osteoclastogenesis was not mediated by RANKL as it was not inhibited by osteoprotegerin (OPG). However inhibition of TGFβ receptor I (TβRI), or macrophage-colony stimulating factor (MCSF) resulted in attenuation of prostate cancer-induced osteoclastogenesis. We characterized the signaling pathways induced in osteoclast precursors by soluble mediators released from human prostate carcinoma cells. Prostate cancer factors increased basal calcium levels and calcium fluctuations, induced nuclear localization of nuclear factor of activated t-cells (NFAT)c1, and activated prolonged phosphorylation of ERK1/2 in RANKL-primed osteoclast precursors. Inhibition of calcium signaling, NFATc1 activation, and ERK1/2 phosphorylation significantly reduced the ability of prostate cancer mediators to stimulate osteoclastogenesis. This study reveals the molecular mechanisms underlying the direct osteoclastogenic effect of prostate cancer derived factors, which may be beneficial in developing novel osteoclast-targeting therapeutic approaches

High-dimensional single-cell cancer biology.

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Irish, Jonathan M; Doxie, Deon B

2014-01-01

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

The Limitation of Primary Signals Entering DVB-T On-Channel-Repeater Working in SFN Network

Directory of Open Access Journals (Sweden)

Marek Dvorsky

2013-01-01

Full Text Available This paper considers an issue of signal coverage in uncovered places using a broadcasting device called a Gap Filler. The main focus is placed on the analysis of potential negative effects while signals from two and more primary transmitters simultaneously enter to the Gap Filler. In particular, in the measurements the impact of reception cross delayed signals received by the Gap Filler from two adjacent primary transmitters operating in the Single Frequency Network was analysed. The influence of different receive signal levels from two adjacent primary transmitters was also examined. In the conclusion, based on the experiments, the limiting factors useful for individual transmitters in the Single Frequency Network were determined. The analysis and finding the limit parameters can help bradcasters in further setting and debugging of the Gap Filler network. Finally, the described laboratory experiment was also verified under the real SFN network condition in border region Vsetinsko to verify the laboratory findings.

Oncogenic Signaling Pathways in The Cancer Genome Atlas

NARCIS (Netherlands)

Sanchez-Vega, Francisco; Mina, Marco; Armenia, Joshua; Chatila, Walid K.; Luna, Augustin; La, Konnor C.; Dimitriadoy, Sofia; Liu, David L.; Kantheti, Havish S.; Saghafinia, Sadegh; Chakravarty, Debyani; Daian, Foysal; Gao, Qingsong; Bailey, Matthew H.; Liang, Wen Wei; Foltz, Steven M.; Shmulevich, Ilya; Ding, Li; Heins, Zachary J.; Ochoa, Angelica; Gross, Benjamin E.; Gao, Jianjiong; Zhang, Hongxin; Kundra, Ritika; Kandoth, Cyriac; Bahceci, Istemi; Dervishi, Leonard; Dogrusoz, Ugur; Zhou, Wanding; Shen, Hui; Laird, Peter W.; Way, Gregory P.; Greene, Casey S.; Liang, Han; Xiao, Yonghong; Wang, Chen; Iavarone, Antonio; Berger, Alice H.; Bivona, Trever G.; Lazar, Alexander J.; Hammer, Gary D.; Giordano, Thomas; Kwong, Lawrence N.; McArthur, Grant; Huang, Chenfei; Tward, Aaron D.; Frederick, Mitchell J.; McCormick, Frank; Meyerson, Matthew; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Van Allen, Eliezer M.; Cherniack, Andrew D.; Ciriello, Giovanni; Sander, Chris; Schultz, Nikolaus

2018-01-01

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number

Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

Directory of Open Access Journals (Sweden)

Fei Long

2015-01-01

Full Text Available Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC and non-small-cell lung cancer (NSCLC that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Science.gov (United States)

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using neural networks to enhance the Higgs boson signal at hadron colliders

International Nuclear Information System (INIS)

Field, R.D.; Kanev, Y.; Tayebnejad, M.; Griffin, P.A.

1995-01-01

Neural networks are used to help distinguish the ZZ → ell + ell - -jet-jet signal produced by the decay of a 400 GeV Higgs boson at a proton-proton collider energy of 15 TeV from the ''ordinary'' QCD Z + jets background. The ideal case where only one event at a time enters the detector (no pile-up) and the case of multiple interactions per beam crossing (pile-up) are examined. In both cases, when used in conjunction with the standard cuts, neural networks provide an additional signal to background enhancement

The National Cancer Institute's Physical Sciences - Oncology Network

Science.gov (United States)

Espey, Michael Graham

In 2009, the NCI launched the Physical Sciences - Oncology Centers (PS-OC) initiative with 12 Centers (U54) funded through 2014. The current phase of the Program includes U54 funded Centers with the added feature of soliciting new Physical Science - Oncology Projects (PS-OP) U01 grant applications through 2017; see NCI PAR-15-021. The PS-OPs, individually and along with other PS-OPs and the Physical Sciences-Oncology Centers (PS-OCs), comprise the Physical Sciences-Oncology Network (PS-ON). The foundation of the Physical Sciences-Oncology initiative is a high-risk, high-reward program that promotes a `physical sciences perspective' of cancer and fosters the convergence of physical science and cancer research by forming transdisciplinary teams of physical scientists (e.g., physicists, mathematicians, chemists, engineers, computer scientists) and cancer researchers (e.g., cancer biologists, oncologists, pathologists) who work closely together to advance our understanding of cancer. The collaborative PS-ON structure catalyzes transformative science through increased exchange of people, ideas, and approaches. PS-ON resources are leveraged to fund Trans-Network pilot projects to enable synergy and cross-testing of experimental and/or theoretical concepts. This session will include a brief PS-ON overview followed by a strategic discussion with the APS community to exchange perspectives on the progression of trans-disciplinary physical sciences in cancer research.

eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.

Science.gov (United States)

Clarke, Daniel J B; Kuleshov, Maxim V; Schilder, Brian M; Torre, Denis; Duffy, Mary E; Keenan, Alexandra B; Lachmann, Alexander; Feldmann, Axel S; Gundersen, Gregory W; Silverstein, Moshe C; Wang, Zichen; Ma'ayan, Avi

2018-05-25

While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases (X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.

Research advances in sorafenib-induced apoptotic signaling pathways in liver cancer cells

Directory of Open Access Journals (Sweden)

ZHANG Chaoya

2016-04-01

Full Text Available Currently, sorafenib is the multi-target inhibitor for the treatment of advanced primary liver cancer, and can effectively prolong the progression-free survival and overall survival in patients with advanced primary liver cancer. The application of sorafenib in the targeted therapy for liver cancer has become a hot topic. Major targets or signaling pathways include Raf/Mek/Erk, Jak/Stat, PI3K/Akt/mTOR, VEGFR and PDGFR, STAT, microRNA, Wnt/β-catenin, autolysosome, and tumor-related proteins, and sorafenib can regulate the proliferation, differentiation, metastasis, and apoptosis of liver cancer cells through these targets. This article reviews the current research on the action of sorafenib on these targets or signaling pathways to provide useful references for further clinical research on sorafenib.

Signalling design and architecture for a proposed mobile satellite network

Science.gov (United States)

Yan, T.-Y.; Cheng, U.; Wang, C.

1990-01-01

In a frequency-division/demand-assigned multiple-access (FD/DAMA) architecture, each mobile subscriber must make a connection request to the Network Management Center before transmission for either open-end or closed-end services. Open-end services are for voice calls and long file transfer and are processed on a blocked-call-cleared basis. Closed-end services are for transmitting burst data and are processed on a first-come first-served basis. This paper presents the signalling design and architecture for non-voice services of an FD/DAMA mobile satellite network. The connection requests are made through the recently proposed multiple channel collision resolution scheme which provides a significantly higher throughput than the traditional slotted ALOHA scheme. For non-voice services, it is well known that retransmissions are necessary to ensure the delivery of a message in its entirety from the source to destination. Retransmission protocols for open-end and closed-end data transfer are investigated. The signal structure for the proposed network is derived from X-25 standards with appropriate modifications. The packet types and their usages are described in this paper.

The Rare Cancer Network: ongoing studies and future strategy

Directory of Open Access Journals (Sweden)

Mahmut Ozsahin

2014-08-01

Full Text Available The Rare Cancer Network (RCN was formed in the early 1990’s to create a global network that could pool knowledge and resources in the studies of rare malignancies whose infrequency prevented both their study with prospective clinical trials. To date, the RCN has initiated 74 studies resulting in 46 peer reviewed publications. The First International Symposium of the Rare Cancer Network took place in Nice in March of 2014. Status updates and proposals for new studies were heard for fifteen topics. Ongoing studies continue for cardiac sarcomas, thyroid cancers, glomus tumors, and adult medulloblastomas. New proposals were presented at the symposium for primary hepatic lymphoma, solitary fibrous tumors, Rosai-Dorfman disease, tumors of the ampulla of Vater, salivary gland tumors, anorectal melanoma, midline nuclear protein in testes carcinoma, pulmonary lymphoepithelioma-like carcinoma, adenoid cystic carcinoma of the trachea, osteosarcomas of the mandible, and extra-cranial hemangiopericytoma. This manuscript presents the abstracts of those proposals and updates on ongoing studies, as well a brief summary of the vision and future of the RCN.

Phosphoproteomic Analysis Identifies Signaling Pathways Regulated by Curcumin in Human Colon Cancer Cells.

Science.gov (United States)

Sato, Tatsuhiro; Higuchi, Yutaka; Shibagaki, Yoshio; Hattori, Seisuke

2017-09-01

Curcumin, a major polyphenol of the spice turmeric, acts as a potent chemopreventive and chemotherapeutic agent in several cancer types, including colon cancer. Although various proteins have been shown to be affected by curcumin, how curcumin exerts its anticancer activity is not fully understood. Phosphoproteomic analyses were performed using SW480 and SW620 human colon cancer cells to identify curcumin-affected signaling pathways. Curcumin inhibited the growth of the two cell lines in a dose-dependent manner. Thirty-nine curcumin-regulated phosphoproteins were identified, five of which are involved in cancer signaling pathways. Detailed analyses revealed that the mTORC1 and p53 signaling pathways are main targets of curcumin. Our results provide insight into the molecular mechanisms of the anticancer activities of curcumin and future molecular targets for its clinical application. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

New advances of TMEM88 in cancer initiation and progression, with special emphasis on Wnt signaling pathway.

Science.gov (United States)

Ge, Yun-Xuan; Wang, Chang-Hui; Hu, Fu-Yong; Pan, Lin-Xin; Min, Jie; Niu, Kai-Yuan; Zhang, Lei; Li, Jun; Xu, Tao

2018-01-01

Transmembrane protein 88 (TMEM88), a newly discovered protein localized on the cell membrane. Recent studies showed that TMEM88 was involved in the regulation of several types of cancer. TMEM88 was expressed at significantly higher levels in breast cancer (BC) cell line than in normal breast cell line with co-localized with Dishevelled (DVL) in the cytoplasm of BC cell line. TMEM88 silencing in the ovarian cancer cell line CP70 resulted in significant upregulation of Wnt downstream genes (c-Myc, cyclin-D1) and other Wnt target genes including JUN, PTIX2, CTNNB1 (β-catenin), further supporting that TMEM88 inhibits canonical Wnt signaling pathway. Wnt signaling pathway has been known to play important roles in many diseases, especially in cancer. For instance, hepatocellular carcinoma (HCC) has become one of the most common tumors harboring mutations in the Wnt signaling pathway. As the inhibitor of Wnt signaling, TMEM88 has been considered to act as an oncogene or a tumor suppressor. Up-regulated TMEM88 or gene therapy approaches could be an effective therapeutic approach against tumor as TMEM88 inhibits Wnt signaling through direct interaction with DVL. Here, we review the current knowledge on the functional role and potential clinical application of TMEM88 in the control of various cancers. Highlights Wnt signaling displays an important role in several pathogenesis of cancer. Wnt signaling pathway is activated during cancer development. TMEM88 has an impact on cancer by inhibiting canonical Wnt signaling. We discuss the importance and new applications of TMEM88 in cancer therapy. © 2017 Wiley Periodicals, Inc.

Filtering and spectral processing of 1-D signals using cellular neural networks

NARCIS (Netherlands)

Moreira-Tamayo, O.; Pineda de Gyvez, J.

1996-01-01

This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

FXR silencing in human colon cancer by DNA methylation and KRAS signaling.

Science.gov (United States)

Bailey, Ann M; Zhan, Le; Maru, Dipen; Shureiqi, Imad; Pickering, Curtis R; Kiriakova, Galina; Izzo, Julie; He, Nan; Wei, Caimiao; Baladandayuthapani, Veerabhadran; Liang, Han; Kopetz, Scott; Powis, Garth; Guo, Grace L

2014-01-01

Farnesoid X receptor (FXR) is a bile acid nuclear receptor described through mouse knockout studies as a tumor suppressor for the development of colon adenocarcinomas. This study investigates the regulation of FXR in the development of human colon cancer. We used immunohistochemistry of FXR in normal tissue (n = 238), polyps (n = 32), and adenocarcinomas, staged I-IV (n = 43, 39, 68, and 9), of the colon; RT-quantitative PCR, reverse-phase protein array, and Western blot analysis in 15 colon cancer cell lines; NR1H4 promoter methylation and mRNA expression in colon cancer samples from The Cancer Genome Atlas; DNA methyltransferase inhibition; methyl-DNA immunoprecipitation (MeDIP); bisulfite sequencing; and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) knockdown assessment to investigate FXR regulation in colon cancer development. Immunohistochemistry and quantitative RT-PCR revealed that expression and function of FXR was reduced in precancerous lesions and silenced in a majority of stage I-IV tumors. FXR expression negatively correlated with phosphatidylinositol-4, 5-bisphosphate 3 kinase signaling and the epithelial-to-mesenchymal transition. The NR1H4 promoter is methylated in ~12% colon cancer The Cancer Genome Atlas samples, and methylation patterns segregate with tumor subtypes. Inhibition of DNA methylation and KRAS silencing both increased FXR expression. FXR expression is decreased early in human colon cancer progression, and both DNA methylation and KRAS signaling may be contributing factors to FXR silencing. FXR potentially suppresses epithelial-to-mesenchymal transition and other oncogenic signaling cascades, and restoration of FXR activity, by blocking silencing mechanisms or increasing residual FXR activity, represents promising therapeutic options for the treatment of colon cancer.

Clinical Implications of Hedgehog Pathway Signaling in Prostate Cancer

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Daniel L. Suzman

2015-09-01

Full Text Available Activity in the Hedgehog pathway, which regulates GLI-mediated transcription, is important in organogenesis and stem cell regulation in self-renewing organs, but is pathologically elevated in many human malignancies. Mutations leading to constitutive activation of the pathway have been implicated in medulloblastoma and basal cell carcinoma, and inhibition of the pathway has demonstrated clinical responses leading to the approval of the Smoothened inhibitor, vismodegib, for the treatment of advanced basal cell carcinoma. Aberrant Hedgehog pathway signaling has also been noted in prostate cancer with evidence suggesting that it may render prostate epithelial cells tumorigenic, drive the epithelial-to-mesenchymal transition, and contribute towards the development of castration-resistance through autocrine and paracrine signaling within the tumor microenvironment and cross-talk with the androgen pathway. In addition, there are emerging clinical data suggesting that inhibition of the Hedgehog pathway may be effective in the treatment of recurrent and metastatic prostate cancer. Here we will review these data and highlight areas of active clinical research as they relate to Hedgehog pathway inhibition in prostate cancer.

CGI-99 promotes breast cancer metastasis via autocrine interleukin-6 signaling.

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Lin, C; Liao, W; Jian, Y; Peng, Y; Zhang, X; Ye, L; Cui, Y; Wang, B; Wu, X; Xiong, Z; Wu, S; Li, J; Wang, X; Song, L

2017-06-29

Metastatic relapse remains largely incurable and a major challenge of clinical management in breast cancer, but the underlying mechanisms are poorly understood. Herein, we report that CGI-99 is overexpressed in breast cancer tissues from patients with metastatic recurrence within 5 years. High CGI-99 significantly predicts poorer 5-year metastasis-free patient survival. We find that CGI-99 increases breast cancer stem cell properties, and potentiates efficient tumor lung colonization and outgrowth in vivo. Furthermore, we demonstrate that CGI-99 activates the autocrine interleukin-6 (IL-6)/STAT3 signaling by increasing the accumulation and activity of RNA polymerase II and p300 cofactor at the proximal promoter of IL-6. Importantly, delivery of the IL-6-receptor humanized monoclonal antibody tocilizumab robustly abrogates CGI-99-induced metastasis in vivo. Finally, we find that high levels of CGI-99 are significantly correlated with STAT3 hyperactivation in breast cancer patients. These findings reveal a potential mechanism for constitutive activation of autocrine IL-6/STAT3 signaling and may suggest a novel target for clinical intervention in breast cancer.

BAG3 promotes tumour cell proliferation by regulating EGFR signal transduction pathways in triple negative breast cancer.

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Shields, Sarah; Conroy, Emer; O'Grady, Tony; McGoldrick, Alo; Connor, Kate; Ward, Mark P; Useckaite, Zivile; Dempsey, Eugene; Reilly, Rebecca; Fan, Yue; Chubb, Anthony; Matallanas, David Gomez; Kay, Elaine W; O'Connor, Darran; McCann, Amanda; Gallagher, William M; Coppinger, Judith A

2018-03-20

Triple-negative breast cancer (TNBC), is a heterogeneous disease characterised by absence of expression of the estrogen receptor (ER), progesterone receptor (PR) and lack of amplification of human epidermal growth factor receptor 2 (HER2). TNBC patients can exhibit poor prognosis and high recurrence stages despite early response to chemotherapy treatment. In this study, we identified a pro-survival signalling protein BCL2- associated athanogene 3 (BAG3) to be highly expressed in a subset of TNBC cell lines and tumour tissues. High mRNA expression of BAG3 in TNBC patient cohorts significantly associated with a lower recurrence free survival. The epidermal growth factor receptor (EGFR) is amplified in TNBC and EGFR signalling dynamics impinge on cancer cell survival and disease recurrence. We found a correlation between BAG3 and EGFR expression in TNBC cell lines and determined that BAG3 can regulate tumour cell proliferation, migration and invasion in EGFR expressing TNBC cells lines. We identified an interaction between BAG3 and components of the EGFR signalling networks using mass spectrometry. Furthermore, BAG3 contributed to regulation of proliferation in TNBC cell lines by reducing the activation of components of the PI3K/AKT and FAK/Src signalling subnetworks. Finally, we found that combined targeting of BAG3 and EGFR was more effective than inhibition of EGFR with Cetuximab alone in TNBC cell lines. This study demonstrates a role for BAG3 in regulation of distinct EGFR modules and highlights the potential of BAG3 as a therapeutic target in TNBC.

A switchable spin-wave signal splitter for magnonic networks

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Heussner, F.; Serga, A. A.; Brächer, T.; Hillebrands, B.; Pirro, P.

2017-09-01

The influence of an inhomogeneous magnetization distribution on the propagation of caustic-like spin-wave beams in unpatterned magnetic films has been investigated by utilizing micromagnetic simulations. Our study reveals a locally controllable and reconfigurable tractability of the beam directions. This feature is used to design a device combining split and switch functionalities for spin-wave signals on the micrometer scale. A coherent transmission of spin-wave signals through the device is verified. This attests the applicability in magnonic networks where the information is encoded in the phase of the spin waves.

Quantitative proteomics reveals middle infrared radiation-interfered networks in breast cancer cells.

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Chang, Hsin-Yi; Li, Ming-Hua; Huang, Tsui-Chin; Hsu, Chia-Lang; Tsai, Shang-Ru; Lee, Si-Chen; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-02-06

Breast cancer is one of the leading cancer-related causes of death worldwide. Treatment of triple-negative breast cancer (TNBC) is complex and challenging, especially when metastasis has developed. In this study, we applied infrared radiation as an alternative approach for the treatment of TNBC. We used middle infrared (MIR) with a wavelength range of 3-5 μm to irradiate breast cancer cells. MIR significantly inhibited cell proliferation in several breast cancer cells but did not affect the growth of normal breast epithelial cells. We performed iTRAQ-coupled LC-MS/MS analysis to investigate the MIR-triggered molecular mechanisms in breast cancer cells. A total of 1749 proteins were identified, quantified, and subjected to functional enrichment analysis. From the constructed functionally enriched network, we confirmed that MIR caused G2/M cell cycle arrest, remodeled the microtubule network to an astral pole arrangement, altered the actin filament formation and focal adhesion molecule localization, and reduced cell migration activity and invasion ability. Our results reveal the coordinative effects of MIR-regulated physiological responses in concentrated networks, demonstrating the potential implementation of infrared radiation in breast cancer therapy.

The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain

Institute of Scientific and Technical Information of China (English)

田允; 黄继云; 王锐; 陶蓉蓉; 卢应梅; 廖美华; 陆楠楠; 李静; 芦博; 韩峰

2012-01-01

Autism is a highly heritable neurodevelopmental condition characterized by impaired social interaction and communication. However, the role of synaptic dysfunction during development of autism remains unclear. In the present study, we address the alterations of biochemical signaling in hippocampal network following induction of the autism in experimental animals. Here, the an- imal disease model and DNA array being used to investigate the differences in transcriptome or- ganization between autistic and normal brain by gene co--expression network analysis.

The signal extraction of fetal heart rate based on wavelet transform and BP neural network

Science.gov (United States)

Yang, Xiao Hong; Zhang, Bang-Cheng; Fu, Hu Dai

2005-04-01

This paper briefly introduces the collection and recognition of bio-medical signals, designs the method to collect FM signals. A detailed discussion on the system hardware, structure and functions is also given. Under LabWindows/CVI,the hardware and the driver do compatible, the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively, expedites program reflect speed, improves the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network; Finally the results of collecting signals and BP networks are discussed. 8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.

Estrogen signalling and the DNA damage response in hormone dependent breast cancers

Directory of Open Access Journals (Sweden)

C Elizabeth Caldon

2014-05-01

Full Text Available Estrogen is necessary for the normal growth and development of breast tissue, but high levels of estrogen are a major risk factor for breast cancer. One mechanism by which estrogen could contribute to breast cancer is via the induction of DNA damage. This perspective discusses the mechanisms by which estrogen alters the DNA damage response (DDR and DNA repair through the regulation of key effector proteins including ATM, ATR, CHK1, BRCA1 and p53 and the feedback on estrogen receptor signalling from these proteins. We put forward the hypothesis that estrogen receptor signalling converges to suppress effective DNA repair and apoptosis in favour of proliferation. This is important in hormone-dependent breast cancer as it will affect processing of estrogen-induced DNA damage, as well as other genotoxic insults. DDR and DNA repair proteins are frequently mutated or altered in estrogen responsive breast cancer which will further change the processing of DNA damage. Finally the action of estrogen signalling on DNA damage is also relevant to the therapeutic setting as the suppression of a DNA damage response by estrogen has the potential to alter the response of cancers to anti-hormone treatment or chemotherapy that induces DNA damage.

Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

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Taosheng Xu

Full Text Available Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.In this paper, we propose a method, weighted similarity network fusion (WSNF, to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs, transcription factors (TFs and messenger RNAs (mRNAs and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA and glioblastoma multiforme (GBM datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

Analysis of FOXO transcriptional networks

NARCIS (Netherlands)

van der Vos, K.E.

2010-01-01

The PI3K-PKB-FOXO signalling module plays a pivotal role in a wide variety of cellular processes, including proliferation, survival, differentiation and metabolism. Inappropriate activation of this network is frequently observed in human cancer and causes uncontrolled proliferation and survival. In

Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

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Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

2011-01-01

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

Science.gov (United States)

Anderson, Brian A

2017-03-01

Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Model-based design of self-Adapting networked signal processing systems

NARCIS (Netherlands)

Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

2013-01-01

The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors

Directory of Open Access Journals (Sweden)

N. Sriraam

2011-01-01

Full Text Available A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

A KST framework for correlation network construction from time series signals

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Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

2018-04-01

A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

Nonreciprocal signal routing in an active quantum network

Science.gov (United States)

Metelmann, A.; Türeci, H. E.

2018-04-01

As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. Here, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

Tolerance to drought and salt stress in plants: Unraveling the signaling networks

Directory of Open Access Journals (Sweden)

Dortje eGolldack

2014-04-01

Full Text Available Tolerance of plants to abiotic stressors such as drought and salinity is triggered by complex multicomponent signaling pathways to restore cellular homeostasis and promote survival. Major plant transcription factor families such as bZIP, NAC, AP2/ERF and MYB orchestrate regulatory networks underlying abiotic stress tolerance. Sucrose nonfermenting 1-related protein kinase 2 (SnRK2 and MAPK pathways contribute to initiation of stress adaptive downstream responses and promote plant growth and development. As a convergent point of multiple abiotic cues, cellular effects of environmental stresses are not only imbalances of ionic and osmotic homeostasis but also impaired photosynthesis, cellular energy depletion, and redox imbalances. Recent evidence of regulatory systems that link sensing and signaling of environmental conditions and the intracellular redox status have shed light on interfaces of stress and energy signaling. ROS (reactive oxygen species cause severe cellular damage by peroxidation and de-esterification of membrane lipids, however, current models also define a pivotal signaling function of ROS in triggering tolerance against stress. Recent research advances suggest and support a regulatory role of ROS in the cross talks of stress triggered hormonal signaling such as the abscisic acid (ABA pathway and endogenously induced redox and metabolite signals. Here, we discuss and review the versatile molecular convergence in the abiotic stress responsive signaling networks in the context of ROS and lipid derived signals and the specific role of stomatal signaling.

MET network in PubMed: a text-mined network visualization and curation system.

Science.gov (United States)

Dai, Hong-Jie; Su, Chu-Hsien; Lai, Po-Ting; Huang, Ming-Siang; Jonnagaddala, Jitendra; Rose Jue, Toni; Rao, Shruti; Chou, Hui-Jou; Milacic, Marija; Singh, Onkar; Syed-Abdul, Shabbir; Hsu, Wen-Lian

2016-01-01

Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL: http://btm.tmu.edu.tw/metastasisway. © The Author(s) 2016. Published by Oxford University Press.

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

Science.gov (United States)

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

2012-10-15

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.