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Yang Y, Wu H, Fan S, Bi Y, Hao M, Shang J. Cancer‑associated fibroblast‑derived LRRC15 promotes the migration and invasion of triple‑negative breast cancer cells via Wnt/β‑catenin signalling pathway regulation. Mol Med Rep 2021; 25:2. [PMID: 34726255 PMCID: PMC8600416 DOI: 10.3892/mmr.2021.12518] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 09/27/2021] [Indexed: 12/31/2022] Open
Abstract
Triple-negative breast cancer (TNBC) is a highly aggressive tumour subtype associated with poor prognosis. The function of leucine-rich repeat-containing protein 15 (LRRC15), a member of the leucine-rich repeat superfamily, in TNBC has not yet been elucidated. The aim of this study was to identify the combined role of LRRC15 and Wnt/β-catenin signalling pathway in the development of TNBC. The expression of LRRC15 in TNBC tissues was analysed using data from The Cancer Genome Atlas. Cell migration and invasion assays were conducted to study the function of LRRC15 in TNBC. The expression of Wnt/β-catenin signalling proteins was analysed via western blotting. The effect of LRRC15 on β-catenin nuclear localisation was measured by performing western blotting and luciferase assays. It was found that high LRRC15 expression was associated with poor prognosis in patients with TNBC. High expression of LRRC15 in cancer-associated fibroblasts (CAFs) promoted cell migration and invasion in TNBC cells. In addition, TNBC cells with LRRC15 overexpression in CAFs showed an aberrant increase in β-catenin activity concomitant with nuclear localisation of β-catenin, which inhibited its degradation. These results showed that LRRC15 promoted tumour migration and invasion in TNBC cells by regulating the Wnt/β-catenin signalling pathway.
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Affiliation(s)
- Yang Yang
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
| | - Haiying Wu
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
| | - Shaoxia Fan
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
| | - Yanqing Bi
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
| | - Min Hao
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
| | - Jian Shang
- Department of Breast and Thyroid Surgery, Dongying People's Hospital, Dongying, Shandong 257091, P.R. China
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2
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Ranes M, Zaleska M, Sakalas S, Knight R, Guettler S. Reconstitution of the destruction complex defines roles of AXIN polymers and APC in β-catenin capture, phosphorylation, and ubiquitylation. Mol Cell 2021; 81:3246-3261.e11. [PMID: 34352208 PMCID: PMC8403986 DOI: 10.1016/j.molcel.2021.07.013] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 05/18/2021] [Accepted: 07/13/2021] [Indexed: 12/24/2022]
Abstract
The Wnt/β-catenin pathway is a highly conserved, frequently mutated developmental and cancer pathway. Its output is defined mainly by β-catenin's phosphorylation- and ubiquitylation-dependent proteasomal degradation, initiated by the multi-protein β-catenin destruction complex. The precise mechanisms underlying destruction complex function have remained unknown, largely because of the lack of suitable in vitro systems. Here we describe the in vitro reconstitution of an active human β-catenin destruction complex from purified components, recapitulating complex assembly, β-catenin modification, and degradation. We reveal that AXIN1 polymerization and APC promote β-catenin capture, phosphorylation, and ubiquitylation. APC facilitates β-catenin's flux through the complex by limiting ubiquitylation processivity and directly interacts with the SCFβ-TrCP E3 ligase complex in a β-TrCP-dependent manner. Oncogenic APC truncation variants, although part of the complex, are functionally impaired. Nonetheless, even the most severely truncated APC variant promotes β-catenin recruitment. These findings exemplify the power of biochemical reconstitution to interrogate the molecular mechanisms of Wnt/β-catenin signaling.
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Affiliation(s)
- Michael Ranes
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, UK; Division of Cancer Biology, The Institute of Cancer Research (ICR), London, UK
| | - Mariola Zaleska
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, UK; Division of Cancer Biology, The Institute of Cancer Research (ICR), London, UK
| | - Saira Sakalas
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, UK; Division of Cancer Biology, The Institute of Cancer Research (ICR), London, UK
| | - Ruth Knight
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, UK
| | - Sebastian Guettler
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, UK; Division of Cancer Biology, The Institute of Cancer Research (ICR), London, UK.
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3
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Khetan J, Barua D. Analysis of Fn14-NF-κB signaling response dynamics using a mechanistic model. J Theor Biol 2019; 480:34-42. [PMID: 31374284 DOI: 10.1016/j.jtbi.2019.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 07/17/2019] [Accepted: 07/29/2019] [Indexed: 11/29/2022]
Abstract
Fn14 is a transmembrane receptor protein belonging to the tumor necrosis factor receptor (TNFR) superfamily. Many experimental reports have shown that crosslinking of the receptor by its extracellular ligand TWEAK induces prolonged activation of transcription factor NF-κB. This behavior is distinct from TNF-α receptor, which is a more well-characterized member of the TNFR family. TNF-α receptor, despite sharing many similar molecular interactions with Fn14, only transiently activates NF-κB in response to TNF-α stimulation. Here, we investigate molecular mechanisms that enable Fn14 to display such distinctive behavior. In particular, we focus on two specific features of the Fn14 pathway that potentially give rise to a positive feedback regulation and differentiate it from the TNF-α receptor signaling. By developing a mechanistic model, we analyze how these features may determine the dynamics of an Fn14-NF-κB response. Our analysis reveals that stimulation of Fn14 by TWEAK may generate highly non-linear dynamics, including stable limit cycles and bistable responses. The type of response depends both on the strength and duration of a TWEAK signal. Our predictions and analyses also show that the molecular interactions underlying the positive feedback explain the prolonged activation of NF-κB under certain parameter regimes. In light of the model predictions, we propose possible deregulations of Fn14 leading to its overexpression in solid tumors and tissue injuries.
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Affiliation(s)
- Jawahar Khetan
- Department of Chemical and Biochemical Engineering, Missouri University of Science and Technology, Rolla, MO, USA
| | - Dipak Barua
- Department of Chemical and Biochemical Engineering, Missouri University of Science and Technology, Rolla, MO, USA.
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Norton KA, Gong C, Jamalian S, Popel AS. Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment. Processes (Basel) 2019; 7:37. [PMID: 30701168 PMCID: PMC6349239 DOI: 10.3390/pr7010037] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Multiscale systems biology and systems pharmacology are powerful methodologies that are playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena and in clinical applications. In this review, we summarize the state of the art in the applications of agent-based models (ABM) and hybrid modeling to the tumor immune microenvironment and cancer immune response, including immunotherapy. Heterogeneity is a hallmark of cancer; tumor heterogeneity at the molecular, cellular, and tissue scales is a major determinant of metastasis, drug resistance, and low response rate to molecular targeted therapies and immunotherapies. Agent-based modeling is an effective methodology to obtain and understand quantitative characteristics of these processes and to propose clinical solutions aimed at overcoming the current obstacles in cancer treatment. We review models focusing on intra-tumor heterogeneity, particularly on interactions between cancer cells and stromal cells, including immune cells, the role of tumor-associated vasculature in the immune response, immune-related tumor mechanobiology, and cancer immunotherapy. We discuss the role of digital pathology in parameterizing and validating spatial computational models and potential applications to therapeutics.
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Affiliation(s)
- Kerri-Ann Norton
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
- Computer Science Program, Department of Science, Mathematics, and Computing, Bard College, Annandale-on-Hudson, NY 12504, USA
| | - Chang Gong
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Samira Jamalian
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Aleksander S. Popel
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
- Department of Oncology and the Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
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Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics. Processes (Basel) 2018. [DOI: 10.3390/pr6110217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular functions, such as death, division, or phenotype change. Cell death is implemented by terminating a parallel process, while cell division is carried out by creating a new process (daughter cell) from an existing one (mother cell). We first demonstrate these capabilities by creating two simple example models. In one model, we consider a relatively simple scenario where cells can evolve independently. In the other model, we consider interdependency among the cells, where cellular communication determines their collective behavior and evolution under a temporally evolving growth condition. We then demonstrate the framework’s capability by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment.
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Choi Y, Kwon CH, Lee SJ, Park J, Shin JY, Park DY. Integrative analysis of oncogenic fusion genes and their functional impact in colorectal cancer. Br J Cancer 2018; 119:230-240. [PMID: 29955133 PMCID: PMC6048111 DOI: 10.1038/s41416-018-0153-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2018] [Revised: 05/22/2018] [Accepted: 05/29/2018] [Indexed: 12/21/2022] Open
Abstract
Background Fusion genes are good candidates of molecular targets for cancer therapy. However, there is insufficient research on the clinical implications and functional characteristics of fusion genes in colorectal cancer (CRC). Methods In this study, we analysed RNA sequencing data of CRC patients (147 tumour and 47 matched normal tissues) to identify oncogenic fusion genes and evaluated their role in CRC. Results We validated 24 fusion genes, including novel fusions, by three algorithms and Sanger sequencing. Fusions from most patients were mutually exclusive CRC oncogenes and included tumour suppressor gene mutations. Eleven fusion genes from 13 patients (8.8%) were determined as oncogenic fusion genes by analysing their gene expression and function. To investigate their oncogenic impact, we performed proliferation and migration assays of CRC cell lines expressing fusion genes of GTF3A-CDK8, NAGLU- IKZF3, RNF121- FOLR2, and STRN-ALK. Overexpression of these fusion genes increased cell proliferation except GTF3A-CDK8. In addition, overexpression of NAGLU-IKZF3 enhanced migration of CRC cells. We demonstrated that NAGLU-IKZF3, RNF121-FOLR2, and STRN-ALK had tumourigenic effects in CRC. Conclusion In summary, we identified and characterised oncogenic fusion genes and their function in CRC, and implicated NAGLU-IKZF3 and RNF121-FOLR2 as novel molecular targets for personalised medicine development.
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Affiliation(s)
- Yuri Choi
- Department of Pathology, Pusan National University School of Medicine, and Biomedical Research Institute, Pusan National University Hospital, Gudeok-ro 179, Seo-Gu, Busan, 49241, Republic of Korea
| | - Chae Hwa Kwon
- Department of Pathology, Pusan National University School of Medicine, and Biomedical Research Institute, Pusan National University Hospital, Gudeok-ro 179, Seo-Gu, Busan, 49241, Republic of Korea
| | - Seon Jin Lee
- Department of Pathology, Pusan National University School of Medicine, and Biomedical Research Institute, Pusan National University Hospital, Gudeok-ro 179, Seo-Gu, Busan, 49241, Republic of Korea
| | - Joonghoon Park
- Graduate School of International Agricultural Technology and Institute of Green-Bio Science and Technology, Seoul National University, Pyeongchang-gun, Gangwon-do, 232-916, Republic of Korea
| | - Jong-Yeon Shin
- Genomic Medicine Institute (GMI), Medical Research Center, Seoul National University, Seoul, 159-781, Republic of Korea
| | - Do Youn Park
- Department of Pathology, Pusan National University School of Medicine, and Biomedical Research Institute, Pusan National University Hospital, Gudeok-ro 179, Seo-Gu, Busan, 49241, Republic of Korea.
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Timescale Separation of Positive and Negative Signaling Creates History-Dependent Responses to IgE Receptor Stimulation. Sci Rep 2017; 7:15586. [PMID: 29138425 PMCID: PMC5686181 DOI: 10.1038/s41598-017-15568-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 10/26/2017] [Indexed: 02/02/2023] Open
Abstract
The high-affinity receptor for IgE expressed on the surface of mast cells and basophils interacts with antigens, via bound IgE antibody, and triggers secretion of inflammatory mediators that contribute to allergic reactions. To understand how past inputs (memory) influence future inflammatory responses in mast cells, a microfluidic device was used to precisely control exposure of cells to alternating stimulatory and non-stimulatory inputs. We determined that the response to subsequent stimulation depends on the interval of signaling quiescence. For shorter intervals of signaling quiescence, the second response is blunted relative to the first response, whereas longer intervals of quiescence induce an enhanced second response. Through an iterative process of computational modeling and experimental tests, we found that these memory-like phenomena arise from a confluence of rapid, short-lived positive signals driven by the protein tyrosine kinase Syk; slow, long-lived negative signals driven by the lipid phosphatase Ship1; and slower degradation of Ship1 co-factors. This work advances our understanding of mast cell signaling and represents a generalizable approach for investigating the dynamics of signaling systems.
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Hochman G, Halevi-Tobias K, Kogan Y, Agur Z. Extracellular inhibitors can attenuate tumorigenic Wnt pathway activity in adenomatous polyposis coli mutants: Predictions of a validated mathematical model. PLoS One 2017; 12:e0179888. [PMID: 28708837 PMCID: PMC5510801 DOI: 10.1371/journal.pone.0179888] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 06/06/2017] [Indexed: 12/21/2022] Open
Abstract
Background Despite considerable investigational efforts, no method to overcome the pathogenesis caused by loss of function (LoF) mutations in tumor suppressor genes has been successfully translated to the clinic. The most frequent LoF mutation in human cancers is Adenomatous polyposis coli (APC), causing aberrant activation of the Wnt pathway. In nearly all colon cancer tumors, the APC protein is truncated, but still retains partial binding abilities. Objective & methods Here, we tested the hypothesis that extracellular inhibitors of the Wnt pathway, although acting upstream of the APC mutation, can restore normal levels of pathway activity in colon cancer cells. To this end, we developed and simulated a mathematical model for the Wnt pathway in different APC mutants, with or without the effects of the extracellular inhibitors, Secreted Frizzled-Related Protein1 (sFRP1) and Dickhopf1 (Dkk1). We compared our model predictions to experimental data in the literature. Results Our model accurately predicts T-cell factor (TCF) activity in mutant cells that vary in APC mutation. Model simulations suggest that both sFRP1 and DKK1 can reduce TCF activity in APC1638N/1572T and Apcmin/min mutants, but restoration of normal activity levels is possible only in the former. When applied in combination, synergism between the two inhibitors can reduce their effective doses to one-fourth of the doses required under single inhibitor application. Overall, re-establishment of normal Wnt pathway activity is predicted for every APC mutant in whom TCF activity is increased by up to 11 fold. Conclusions Our work suggests that extracellular inhibitors can effectively restore normal Wnt pathway activity in APC-truncated cancer cells, even though these LoF mutations occur downstream of the inhibitory action. The insufficient activity of the truncated APC can be quantitatively balanced by the upstream intervention. This new concept of upstream intervention to control the effects of downstream mutations may be considered also for other partial LoF mutations in other signaling pathways.
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Affiliation(s)
- Gili Hochman
- Institute for Medical BioMathematics, Bene Ataroth, Israel
| | | | - Yuri Kogan
- Institute for Medical BioMathematics, Bene Ataroth, Israel
| | - Zvia Agur
- Institute for Medical BioMathematics, Bene Ataroth, Israel
- * E-mail:
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9
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Lai X, Friedman A. Exosomal microRNA concentrations in colorectal cancer: A mathematical model. J Theor Biol 2017; 415:70-83. [DOI: 10.1016/j.jtbi.2016.12.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 12/06/2016] [Accepted: 12/10/2016] [Indexed: 12/19/2022]
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10
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Quantitative Abstractions for Collective Adaptive Systems. FORMAL METHODS FOR THE QUANTITATIVE EVALUATION OF COLLECTIVE ADAPTIVE SYSTEMS 2016. [DOI: 10.1007/978-3-319-34096-8_7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
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11
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Cardelli L, Tribastone M, Tschaikowski M, Vandin A. Efficient Syntax-Driven Lumping of Differential Equations. TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS 2016. [DOI: 10.1007/978-3-662-49674-9_6] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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12
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Ogilvie LA, Wierling C, Kessler T, Lehrach H, Lange BMH. Predictive Modeling of Drug Treatment in the Area of Personalized Medicine. Cancer Inform 2015; 14:95-103. [PMID: 26692759 DOI: 10.4137/cin.s1933] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Revised: 10/18/2015] [Accepted: 10/24/2015] [Indexed: 12/27/2022] Open
Abstract
Despite a growing body of knowledge on the mechanisms underlying the onset and progression of cancer, treatment success rates in oncology are at best modest. Current approaches use statistical methods that fail to embrace the inherent and expansive complexity of the tumor/patient/drug interaction. Computational modeling, in particular mechanistic modeling, has the power to resolve this complexity. Using fundamental knowledge on the interactions occurring between the components of a complex biological system, large-scale in silico models with predictive capabilities can be generated. Here, we describe how mechanistic virtual patient models, based on systematic molecular characterization of patients and their diseases, have the potential to shift the theranostic paradigm for oncology, both in the fields of personalized medicine and targeted drug development. In particular, we highlight the mechanistic modeling platform ModCell™ for individualized prediction of patient responses to treatment, emphasizing modeling techniques and avenues of application.
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Affiliation(s)
| | - Christoph Wierling
- Alacris Theranostics GmbH, Berlin, Germany. ; Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Thomas Kessler
- Alacris Theranostics GmbH, Berlin, Germany. ; Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Hans Lehrach
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. ; Dahlem Centre for Genome Research and Medical Systems Biology, Berlin, Germany
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Network and systems biology: essential steps in virtualising drug discovery and development. DRUG DISCOVERY TODAY. TECHNOLOGIES 2015; 15:33-40. [PMID: 26464088 DOI: 10.1016/j.ddtec.2015.07.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 07/06/2015] [Accepted: 07/14/2015] [Indexed: 02/08/2023]
Abstract
The biological processes that keep us healthy or cause disease, as well as the mechanisms of action of possible drugs are inherently complex. In the face of this complexity, attempts at discovering new drugs to treat diseases have alternated between trial-and-error (typically on experimental systems) and grand simplification, usually based on much too little information. We now have the chance to combine these strategies through establishment of 'virtual patient' models, centred on a detailed molecular characterisation of thousands or even, in the future, millions of patients. In doing so, we lay the foundations for truly personalised therapy, as well as a far-reaching virtualisation of drug discovery and development in oncology and other areas of medicine.
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Chylek LA, Harris LA, Faeder JR, Hlavacek WS. Modeling for (physical) biologists: an introduction to the rule-based approach. Phys Biol 2015; 12:045007. [PMID: 26178138 PMCID: PMC4526164 DOI: 10.1088/1478-3975/12/4/045007] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.
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Affiliation(s)
- Lily A Chylek
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
- Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - Leonard A Harris
- Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37212, USA
| | - James R Faeder
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA
| | - William S Hlavacek
- Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
- New Mexico Consortium, Los Alamos, NM 87544, USA
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15
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Benary U, Kofahl B, Hecht A, Wolf J. Mathematical modelling suggests a differential impact of β-transducin repeat-containing protein paralogues on Wnt/β-catenin signalling dynamics. FEBS J 2015; 282:1080-96. [PMID: 25601154 DOI: 10.1111/febs.13204] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Revised: 12/15/2014] [Accepted: 01/15/2015] [Indexed: 12/12/2022]
Abstract
The Wnt/β-catenin signalling pathway is involved in the regulation of a multitude of cellular processes by controlling the concentration of the transcriptional regulator β-catenin. Proteasomal degradation of β-catenin is mediated by two β-transducin repeat-containing protein paralogues, homologous to Slimb protein (HOS) and F-box/WD repeat-containing protein 1A (FWD1), which are functionally interchangeable and thereby considered to function redundantly in the pathway. HOS and FWD1 are both regulated by Wnt/β-catenin signalling, albeit in opposite directions, thus establishing interlocked negative and positive feedback loops. The functional relevance of the opposite regulation of HOS and FWD1 by Wnt/β-catenin signalling in conjunction with their redundant activities in proteasomal degradation of β-catenin remains unresolved. Using a detailed ordinary differential equation model, we investigated the specific influence of each individual feedback mechanism and their combination on Wnt/β-catenin signal transduction under wild-type and cancerous conditions. We found that, under wild-type conditions, the signalling dynamics are predominantly affected by the HOS feedback as a result of a higher concentration of HOS than FWD1. Transcriptional up-regulation of FWD1 by other signalling pathways reduced the impact of the HOS feedback. The opposite regulation of HOS and FWD1 expression by Wnt/β-catenin signalling allows the FWD1 feedback to be employed as a compensation mechanism against aberrant pathway activation as a result of a reduced HOS concentration. By contrast, the FWD1 feedback provides no protection against aberrant activation in adenomatous polyposis coli protein mutant cancer cells.
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Affiliation(s)
- Uwe Benary
- Mathematical Modelling of Cellular Processes, Max Delbrück Center for Molecular Medicine Berlin-Buch, Germany
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16
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Ogilvie LA, Wierling C, Kessler T, Lehrach H, Lange BMH. Article Commentary: Predictive Modeling of Drug Treatment in the Area of Personalized Medicine. Cancer Inform 2015. [PMID: 26692759 PMCID: PMC4671548 DOI: 10.4137/cin.s19330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Despite a growing body of knowledge on the mechanisms underlying the onset and progression of cancer, treatment success rates in oncology are at best modest. Current approaches use statistical methods that fail to embrace the inherent and expansive complexity of the tumor/patient/drug interaction. Computational modeling, in particular mechanistic modeling, has the power to resolve this complexity. Using fundamental knowledge on the interactions occurring between the components of a complex biological system, large-scale in silico models with predictive capabilities can be generated. Here, we describe how mechanistic virtual patient models, based on systematic molecular characterization of patients and their diseases, have the potential to shift the theranostic paradigm for oncology, both in the fields of personalized medicine and targeted drug development. In particular, we highlight the mechanistic modeling platform ModCell™ for individualized prediction of patient responses to treatment, emphasizing modeling techniques and avenues of application.
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Affiliation(s)
| | - Christoph Wierling
- Alacris Theranostics GmbH, Berlin, Germany
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Thomas Kessler
- Alacris Theranostics GmbH, Berlin, Germany
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Hans Lehrach
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Dahlem Centre for Genome Research and Medical Systems Biology, Berlin, Germany
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17
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Chylek LA, Holowka DA, Baird BA, Hlavacek WS. An Interaction Library for the FcεRI Signaling Network. Front Immunol 2014; 5:172. [PMID: 24782869 PMCID: PMC3995055 DOI: 10.3389/fimmu.2014.00172] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Accepted: 03/31/2014] [Indexed: 12/20/2022] Open
Abstract
Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein–protein and protein–lipid interactions. This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP3 at the plasma membrane and the soluble second messenger IP3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.
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Affiliation(s)
- Lily A Chylek
- Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY , USA ; Los Alamos National Laboratory, Theoretical Division, Center for Non-linear Studies , Los Alamos, NM , USA
| | - David A Holowka
- Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY , USA
| | - Barbara A Baird
- Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY , USA
| | - William S Hlavacek
- Los Alamos National Laboratory, Theoretical Division, Center for Non-linear Studies , Los Alamos, NM , USA
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Chylek LA, Harris LA, Tung CS, Faeder JR, Lopez CF, Hlavacek WS. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2014; 6:13-36. [PMID: 24123887 PMCID: PMC3947470 DOI: 10.1002/wsbm.1245] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Revised: 08/20/2013] [Accepted: 08/21/2013] [Indexed: 01/04/2023]
Abstract
Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation).
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Affiliation(s)
- Lily A. Chylek
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA
| | - Leonard A. Harris
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA
| | - Chang-Shung Tung
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - James R. Faeder
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA
| | - Carlos F. Lopez
- Department of Cancer Biology and Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee 37212, USA
| | - William S. Hlavacek
- Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
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