1
|
Qian X, Angerbauer S, Egan M, Renzo MD, Haselmayr W. A Molecular Communication Perspective on Synchronization of Coupled Microfluidic-Spectroscopy. IEEE Trans Nanobioscience 2024; 23:458-471. [PMID: 38564355 DOI: 10.1109/tnb.2024.3384082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
A challenge for real-time monitoring of biochemical processes, such as cells, is detection of biologically relevant molecules. This is due to the fact that spectroscopy methods for detection may perturb the cellular environment. One approach to overcome this problem is coupled microfluidic-spectroscopy, where a microfluidic output channel is introduced in order to observe biologically relevant molecules. This approach allows for non-passive spectroscopy methods, such as mass spectrometry, to identify the structure of molecules released by the cell. Due to the non-negligible length of the microfluidic channel, when a sequence of stimuli are applied to a cell it is not straightforward to determine which spectroscopy samples correspond to a given stimulus. In this paper, we propose a solution to this problem by taking a molecular communication (MC) perspective on the coupled microfluidic-spectroscopy system. In particular, assignment of samples to a stimulus is viewed as a synchronization problem. We develop two new algorithms for synchronization in this context and carry out a detailed theoretical and numerical study of their performance. Our results show improvements over maximum-likelihood synchronization algorithms in terms of detection performance when there are uncertainties in the composition of the microfluidic channel.
Collapse
|
2
|
Hegazy AN, Peine C, Niesen D, Panse I, Vainshtein Y, Kommer C, Zhang Q, Brunner TM, Peine M, Fröhlich A, Ishaque N, Marek RM, Zhu J, Höfer T, Löhning M. Plasticity and lineage commitment of individual T H1 cells are determined by stable T-bet expression quantities. SCIENCE ADVANCES 2024; 10:eadk2693. [PMID: 38838155 PMCID: PMC11152138 DOI: 10.1126/sciadv.adk2693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 05/01/2024] [Indexed: 06/07/2024]
Abstract
T helper 1 (TH1) cell identity is defined by the expression of the lineage-specifying transcription factor T-bet. Here, we examine the influence of T-bet expression heterogeneity on subset plasticity by leveraging cell sorting of distinct in vivo-differentiated TH1 cells based on their quantitative expression of T-bet and interferon-γ. Heterogeneous T-bet expression states were regulated by virus-induced type I interferons and were stably maintained even after secondary viral infection. Exposed to alternative differentiation signals, the sorted subpopulations exhibited graded levels of plasticity, particularly toward the TH2 lineage: T-bet quantities were inversely correlated with the ability to express the TH2 lineage-specifying transcription factor GATA-3 and TH2 cytokines. Reprogramed TH1 cells acquired graded mixed TH1 + TH2 phenotypes with a hybrid epigenetic landscape. Continuous presence of T-bet in differentiated TH1 cells was essential to ensure TH1 cell stability. Thus, innate cytokine signals regulate TH1 cell plasticity via an individual cell-intrinsic rheostat to enable T cell subset adaptation to subsequent challenges.
Collapse
Affiliation(s)
- Ahmed N. Hegazy
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Medical Department of Gastroenterology, Infectious Diseases and Rheumatology, 12203 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Inflammatory Mechanisms, 10117 Berlin, Germany
- Berlin Institute of Health (BIH) at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Caroline Peine
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Dominik Niesen
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Isabel Panse
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Yevhen Vainshtein
- German Cancer Research Center (DKFZ), Division of Theoretical Systems Biology, 69120 Heidelberg, Germany
- University of Heidelberg, Bioquant Center, 69120 Heidelberg, Germany
| | - Christoph Kommer
- German Cancer Research Center (DKFZ), Division of Theoretical Systems Biology, 69120 Heidelberg, Germany
- University of Heidelberg, Bioquant Center, 69120 Heidelberg, Germany
| | - Qin Zhang
- German Cancer Research Center (DKFZ), Division of Theoretical Systems Biology, 69120 Heidelberg, Germany
- University of Heidelberg, Bioquant Center, 69120 Heidelberg, Germany
| | - Tobias M. Brunner
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Michael Peine
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Anja Fröhlich
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Naveed Ishaque
- German Cancer Research Center (DKFZ), Division of Theoretical Systems Biology, 69120 Heidelberg, Germany
- University of Heidelberg, Bioquant Center, 69120 Heidelberg, Germany
| | - Roman M. Marek
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| | - Jinfang Zhu
- National Institute of Allergy and Infectious Diseases, Laboratory of Immune System Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Thomas Höfer
- German Cancer Research Center (DKFZ), Division of Theoretical Systems Biology, 69120 Heidelberg, Germany
- University of Heidelberg, Bioquant Center, 69120 Heidelberg, Germany
| | - Max Löhning
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental Immunology and Osteoarthritis Research, Department of Rheumatology and Clinical Immunology, 10117 Berlin, Germany
- German Rheumatism Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research, 10117 Berlin, Germany
| |
Collapse
|
3
|
Gottumukkala SB, Ganesan TS, Palanisamy A. Comprehensive molecular interaction map of TGFβ induced epithelial to mesenchymal transition in breast cancer. NPJ Syst Biol Appl 2024; 10:53. [PMID: 38760412 PMCID: PMC11101644 DOI: 10.1038/s41540-024-00378-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 04/29/2024] [Indexed: 05/19/2024] Open
Abstract
Breast cancer is one of the prevailing cancers globally, with a high mortality rate. Metastatic breast cancer (MBC) is an advanced stage of cancer, characterised by a highly nonlinear, heterogeneous process involving numerous singling pathways and regulatory interactions. Epithelial-mesenchymal transition (EMT) emerges as a key mechanism exploited by cancer cells. Transforming Growth Factor-β (TGFβ)-dependent signalling is attributed to promote EMT in advanced stages of breast cancer. A comprehensive regulatory map of TGFβ induced EMT was developed through an extensive literature survey. The network assembled comprises of 312 distinct species (proteins, genes, RNAs, complexes), and 426 reactions (state transitions, nuclear translocations, complex associations, and dissociations). The map was developed by following Systems Biology Graphical Notation (SBGN) using Cell Designer and made publicly available using MINERVA ( http://35.174.227.105:8080/minerva/?id=Metastatic_Breast_Cancer_1 ). While the complete molecular mechanism of MBC is still not known, the map captures the elaborate signalling interplay of TGFβ induced EMT-promoting MBC. Subsequently, the disease map assembled was translated into a Boolean model utilising CaSQ and analysed using Cell Collective. Simulations of these have captured the known experimental outcomes of TGFβ induced EMT in MBC. Hub regulators of the assembled map were identified, and their transcriptome-based analysis confirmed their role in cancer metastasis. Elaborate analysis of this map may help in gaining additional insights into the development and progression of metastatic breast cancer.
Collapse
Affiliation(s)
| | - Trivadi Sundaram Ganesan
- Department of Medical Oncology, Sri Ramachandra Institute of Higher Education and Research, Chennai, India
| | - Anbumathi Palanisamy
- Department of Biotechnology, National Institute of Technology Warangal, Warangal, India.
| |
Collapse
|
4
|
Rashid M, Devi BM, Banerjee M. Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial-Mesenchymal Transition. Bull Math Biol 2024; 86:48. [PMID: 38555331 DOI: 10.1007/s11538-024-01277-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 02/27/2024] [Indexed: 04/02/2024]
Abstract
Carcinomas often utilize epithelial-mesenchymal transition (EMT) programs for cancer progression and metastasis. Numerous studies report SNAIL-induced miR200/Zeb feedback circuit as crucial in regulating EMT by placing cancer cells in at least three phenotypic states, viz. epithelial (E), hybrid (h-E/M), mesenchymal (M), along the E-M phenotypic spectrum. However, a coherent molecular-level understanding of how such a tiny circuit controls carcinoma cell entrance into and residence in various states is lacking. Here, we use molecular binding data and mathematical modeling to report that the miR200/Zeb circuit can essentially utilize combinatorial cooperativity to control E-M phenotypic plasticity. We identify minimal combinatorial cooperativities that give rise to E, h-E/M, and M phenotypes. We show that disrupting a specific number of miR200 binding sites on Zeb as well as Zeb binding sites on miR200 can have phenotypic consequences-the circuit can dynamically switch between two (E, M) and three (E, h-E/M, M) phenotypes. Further, we report that in both SNAIL-induced and SNAIL knock-out miR200/Zeb circuits, cooperative transcriptional feedback on Zeb as well as Zeb translation inhibition due to miR200 are essential for the occurrence of intermediate h-E/M phenotype. Finally, we demonstrate that SNAIL can be dispensable for EMT, and in the absence of SNAIL, the transcriptional feedback can control cell state transition from E to h-E/M, to M state. Our results thus highlight molecular-level regulation of EMT in miR200/Zeb circuit and we expect these findings to be crucial to future efforts aiming to prevent EMT-facilitated dissemination of carcinomas.
Collapse
Affiliation(s)
- Mubasher Rashid
- Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, 208016, India.
| | - Brasanna M Devi
- Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, 208016, India
| | - Malay Banerjee
- Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, 208016, India
| |
Collapse
|
5
|
Zhang K, Wang E, Liu QA, Wang J. High CO2 adaptation mechanisms revealed in the miR156-regulated flowering time pathway. PLoS Comput Biol 2023; 19:e1011738. [PMID: 38117849 PMCID: PMC10775972 DOI: 10.1371/journal.pcbi.1011738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 01/09/2024] [Accepted: 12/03/2023] [Indexed: 12/22/2023] Open
Abstract
Elevated CO2 concentrations have been observed to accelerate flowering time in Arabidopsis through the action of a highly conserved regulatory network controlled by miR156 and miR172. However, the network's robustness to the impact of increasing CO2 concentrations on flowering time remains poorly understood. In this study, we investigate this question by conducting a comprehensive analysis of the global landscape of network dynamics, including quantifying the probabilities associated with juvenile and flowering states and assessing the speed of the transition between them. Our findings reveal that a CO2 concentration range of 400-800ppm only mildly advances flowering time, contrasting with the dramatic changes from 200 to 300ppm. Notably, the feedback regulation of miR156 by squamosal promoter binding protein-like proteins (SPLs) plays a substantial role in mitigating the effects of increasing CO2 on flowering time. Intriguingly, we consistently observe a correlation between delayed flowering time and increased variance in flowering time, and vice versa, suggesting that this might be an intrinsic adaptation mechanism embedded within the network. To gain a deeper understanding of this network's dynamics, we identified the sensitive features within the feedback loops of miR156 SPLs and miR172-APETALA2 family proteins (AP2s), with the latter proving to be the most sensitive. Strikingly, our study underscores the indispensability of all feedback regulations in maintaining both juvenile and adult states as well as the transition time between them. Together, our research provides the first physical basis in plant species, aiding in the elucidation of novel regulatory mechanisms and the robustness of the miRNAs-regulated network in response to increasing CO2, therefore influencing the control of flowering time. Moreover, this study provides a promising strategy for engineering plant flowering time to enhance their adaptation and resilience.
Collapse
Affiliation(s)
- Kun Zhang
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, P. R. China
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R. China
| | - Erkang Wang
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, P. R. China
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R. China
| | | | - Jin Wang
- Department of Chemistry and of Physics, Stony Brook University, Stony Brook, New York, United States of America
| |
Collapse
|
6
|
Jain P, Pillai M, Duddu AS, Somarelli JA, Goyal Y, Jolly MK. Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity. Semin Cancer Biol 2023; 96:48-63. [PMID: 37788736 DOI: 10.1016/j.semcancer.2023.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/24/2023] [Accepted: 09/28/2023] [Indexed: 10/05/2023]
Abstract
Phenotypic plasticity was recently incorporated as a hallmark of cancer. This plasticity can manifest along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. In particular, the knowledge necessary for a predictive understanding of how individual cancer cells and populations of cells dynamically switch their phenotypes in response to the intensity and/or duration of their current and past environmental stimuli remains far from complete. Here, we present recent investigations of phenotypic plasticity from a systems-level perspective using two exemplars: epithelial-mesenchymal plasticity in carcinomas and phenotypic switching in melanoma. We highlight how an integrated computational-experimental approach has helped unravel insights into specific dynamical hallmarks of phenotypic plasticity in different cancers to address the following questions: a) how many distinct cell-states or phenotypes exist?; b) how reversible are transitions among these cell-states, and what factors control the extent of reversibility?; and c) how might cell-cell communication be able to alter rates of cell-state switching and enable diverse patterns of phenotypic heterogeneity? Understanding these dynamic features of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach.
Collapse
Affiliation(s)
- Paras Jain
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
| | - Maalavika Pillai
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India; Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Center for Synthetic Biology, Northwestern University, Chicago, IL 60611, USA
| | | | - Jason A Somarelli
- Department of Medicine, Duke Cancer Institute, Duke University, Durham, NC 27710, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Center for Synthetic Biology, Northwestern University, Chicago, IL 60611, USA; Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Mohit Kumar Jolly
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India.
| |
Collapse
|
7
|
Bocci F, Jia D, Nie Q, Jolly MK, Onuchic J. Theoretical and computational tools to model multistable gene regulatory networks. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2023; 86:10.1088/1361-6633/acec88. [PMID: 37531952 PMCID: PMC10521208 DOI: 10.1088/1361-6633/acec88] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/02/2023] [Indexed: 08/04/2023]
Abstract
The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.
Collapse
Affiliation(s)
- Federico Bocci
- The NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
- Department of Mathematics, University of California, Irvine, CA 92697, USA
| | - Dongya Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
| | - Qing Nie
- The NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
- Department of Mathematics, University of California, Irvine, CA 92697, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - José Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
- Department of Physics and Astronomy, Rice University, Houston, TX 77005, USA
- Department of Chemistry, Rice University, Houston, TX 77005, USA
- Department of Biosciences, Rice University, Houston, TX 77005, USA
| |
Collapse
|
8
|
Lems CM, Burger GA, Beltman JB. Tumor-mediated immunosuppression and cytokine spreading affects the relation between EMT and PD-L1 status. Front Immunol 2023; 14:1219669. [PMID: 37638024 PMCID: PMC10449452 DOI: 10.3389/fimmu.2023.1219669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 06/30/2023] [Indexed: 08/29/2023] Open
Abstract
Epithelial-mesenchymal transition (EMT) and immune resistance mediated by Programmed Death-Ligand 1 (PD-L1) upregulation are established drivers of tumor progression. Their bi-directional crosstalk has been proposed to facilitate tumor immunoevasion, yet the impact of immunosuppression and spatial heterogeneity on the interplay between these processes remains to be characterized. Here we study the role of these factors using mathematical and spatial models. We first designed models incorporating immunosuppressive effects on T cells mediated via PD-L1 and the EMT-inducing cytokine Transforming Growth Factor beta (TGFβ). Our models predict that PD-L1-mediated immunosuppression merely reduces the difference in PD-L1 levels between EMT states, while TGFβ-mediated suppression also causes PD-L1 expression to correlate negatively with TGFβ within each EMT phenotype. We subsequently embedded the models in multi-scale spatial simulations to explicitly describe heterogeneity in cytokine levels and intratumoral heterogeneity. Our multi-scale models show that Interferon gamma (IFNγ)-induced partial EMT of a tumor cell subpopulation can provide some, albeit limited protection to bystander tumor cells. Moreover, our simulations show that the true relationship between EMT status and PD-L1 expression may be hidden at the population level, highlighting the importance of studying EMT and PD-L1 status at the single-cell level. Our findings deepen the understanding of the interactions between EMT and the immune response, which is crucial for developing novel diagnostics and therapeutics for cancer patients.
Collapse
Affiliation(s)
| | | | - Joost B. Beltman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| |
Collapse
|
9
|
Pillai M, Hojel E, Jolly MK, Goyal Y. Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools. NATURE COMPUTATIONAL SCIENCE 2023; 3:301-313. [PMID: 38177938 DOI: 10.1038/s43588-023-00427-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 03/03/2023] [Indexed: 01/06/2024]
Abstract
Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies.
Collapse
Affiliation(s)
- Maalavika Pillai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Emilia Hojel
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA.
| |
Collapse
|
10
|
Kardynska M, Kogut D, Pacholczyk M, Smieja J. Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods. Comput Struct Biotechnol J 2023; 21:1523-1532. [PMID: 36851915 PMCID: PMC9958294 DOI: 10.1016/j.csbj.2023.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/03/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract knowledge from existing databases. This review is focused on mathematical modeling used to analyze dynamics and robustness of these networks. This paper presents a review of selected modeling methods that facilitate advances in molecular biology.
Collapse
Affiliation(s)
- Malgorzata Kardynska
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland
| | - Daria Kogut
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Marcin Pacholczyk
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Jaroslaw Smieja
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| |
Collapse
|
11
|
Sabuwala B, Hari K, Shanmuga Vengatasalam A, Jolly MK. Coupled Mutual Inhibition and Mutual Activation Motifs as Tools for Cell-Fate Control. Cells Tissues Organs 2023; 213:283-296. [PMID: 36758523 DOI: 10.1159/000529558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/18/2022] [Indexed: 02/11/2023] Open
Abstract
Multistability is central to biological systems. It plays a crucial role in adaptation, evolvability, and differentiation. The presence of positive feedback loops can enable multistability. The simplest of such feedback loops are (a) a mutual inhibition (MI) loop, (b) a mutual activation (MA) loop, and (c) self-activation. While it is established that all three motifs can give rise to bistability, the characteristic differences in the bistability exhibited by each of these motifs is relatively less understood. Here, we use dynamical simulations across a large ensemble of parameter sets and initial conditions to study the bistability characteristics of these motifs. Furthermore, we investigate the utility of these motifs for achieving coordinated expression through cyclic and parallel coupling amongst them. Our analysis revealed that MI-based architectures offer discrete and robust control over gene expression, multistability, and coordinated expression among multiple genes, as compared to MA-based architectures. We then devised a combination of MI and MA architectures to improve coordination and multistability. Such designs help enhance our understanding of the control structures involved in robust cell-fate decisions and provide a way to achieve controlled decision-making in synthetic systems.
Collapse
Affiliation(s)
- Burhanuddin Sabuwala
- Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | | | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| |
Collapse
|
12
|
Roy U, Singh D, Vincent N, Haritas CK, Jolly MK. Spatiotemporal Patterning Enabled by Gene Regulatory Networks. ACS OMEGA 2023; 8:3713-3725. [PMID: 36743018 PMCID: PMC9893257 DOI: 10.1021/acsomega.2c04581] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 11/24/2022] [Indexed: 06/18/2023]
Abstract
Spatiotemporal pattern formation plays a key role in various biological phenomena including embryogenesis and neural network formation. Though the reaction-diffusion systems enabling pattern formation have been studied phenomenologically, the biomolecular mechanisms behind these processes have not been modeled in detail. Here, we study the emergence of spatiotemporal patterns due to simple, synthetic and commonly observed two- and three-node gene regulatory network motifs coupled with their molecular diffusion in one- and two-dimensional space. We investigate the patterns formed due to the coupling of inherent multistable and oscillatory behavior of the toggle switch, toggle switch with double self-activation, toggle triad, and repressilator with the effect of spatial diffusion of these molecules. We probe multiple parameter regimes corresponding to different regions of stability (monostable, multistable, oscillatory) and assess the impact of varying diffusion coefficients. This analysis offers valuable insights into the design principles of pattern formation facilitated by these network motifs, and it suggests the mechanistic underpinnings of biological pattern formation.
Collapse
Affiliation(s)
- Ushasi Roy
- Centre
for BioSystems Science and Engineering, Indian Institute of Science, Bangalore560012, India
| | - Divyoj Singh
- Undergraduate
Programme, Indian Institute of Science, Bangalore560012, India
| | - Navin Vincent
- Undergraduate
Programme, Indian Institute of Science, Bangalore560012, India
| | - Chinmay K. Haritas
- Undergraduate
Programme, Indian Institute of Science, Bangalore560012, India
| | - Mohit Kumar Jolly
- Centre
for BioSystems Science and Engineering, Indian Institute of Science, Bangalore560012, India
| |
Collapse
|
13
|
Clauss B, Lu M. A quantitative evaluation of topological motifs and their coupling in gene circuit state distributions. iScience 2023; 26:106029. [PMID: 36824273 PMCID: PMC9941213 DOI: 10.1016/j.isci.2023.106029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 12/19/2022] [Accepted: 01/17/2023] [Indexed: 01/24/2023] Open
Abstract
One of the major challenges in biology is to understand how gene interactions collaborate to determine overall functions of biological systems. Here, we present a new computational framework that enables systematic, high-throughput, and quantitative evaluation of how small transcriptional regulatory circuit motifs, and their coupling, contribute to functions of a dynamical biological system. We illustrate how this approach can be applied to identify four-node gene circuits, circuit motifs, and motif coupling responsible for various gene expression state distributions, including those derived from single-cell RNA sequencing data. We also identify seven major classes of four-node circuits from clustering analysis of state distributions. The method is applied to establish phenomenological models of gene circuits driving human neuron differentiation, revealing important biologically relevant regulatory interactions. Our study will shed light on a better understanding of gene regulatory mechanisms in creating and maintaining cellular states.
Collapse
Affiliation(s)
- Benjamin Clauss
- Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA,Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA 02111, USA,The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Mingyang Lu
- Department of Bioengineering, Northeastern University, Boston, MA 02115, USA,Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA,Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA 02111, USA,The Jackson Laboratory, Bar Harbor, ME 04609, USA,Corresponding author
| |
Collapse
|
14
|
Hari K, Harlapur P, Gopalan A, Ullanat V, Duddu AS, Jolly MK. Emergent properties of coupled bistable switches. J Biosci 2022. [DOI: 10.1007/s12038-022-00310-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
15
|
Galbraith M, Levine H, Onuchic JN, Jia D. Decoding the coupled decision-making of the epithelial-mesenchymal transition and metabolic reprogramming in cancer. iScience 2022; 26:105719. [PMID: 36582834 PMCID: PMC9792913 DOI: 10.1016/j.isci.2022.105719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 11/03/2022] [Accepted: 11/30/2022] [Indexed: 12/11/2022] Open
Abstract
Cancer metastasis relies on an orchestration of traits driven by different interacting functional modules, including metabolism and epithelial-mesenchymal transition (EMT). During metastasis, cancer cells can acquire a hybrid metabolic phenotype (W/O) by increasing oxidative phosphorylation without compromising glycolysis and they can acquire a hybrid epithelial/mesenchymal (E/M) phenotype by engaging EMT. Both the W/O and E/M states are associated with high metastatic potentials, and many regulatory links coupling metabolism and EMT have been identified. Here, we investigate the coupled decision-making networks of metabolism and EMT. Their crosstalk can exhibit synergistic or antagonistic effects on the acquisition and stability of different coupled metabolism-EMT states. Strikingly, the aggressive E/M-W/O state can be enabled and stabilized by the crosstalk irrespective of these hybrid states' availability in individual metabolism or EMT modules. Our work emphasizes the mutual activation between metabolism and EMT, providing an important step toward understanding the multifaceted nature of cancer metastasis.
Collapse
Affiliation(s)
- Madeline Galbraith
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA,Department of Physics and Astronomy, Rice University, Houston, TX77005, USA
| | - Herbert Levine
- Center for Theoretical Biological Physics, Department of Physics, and Department of Bioengineering, Northeastern University, Boston, MA02115, USA,Corresponding author
| | - José N. Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA,Department of Physics and Astronomy, Rice University, Houston, TX77005, USA,Department of Chemistry, Rice University, Houston, TX77005, USA,Department of Biosciences, Rice University, Houston, TX77005, USA,Corresponding author
| | - Dongya Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA,Corresponding author
| |
Collapse
|
16
|
Burger GA, Nesenberend DN, Lems CM, Hille SC, Beltman JB. Bidirectional crosstalk between epithelial-mesenchymal plasticity and IFN γ-induced PD-L1 expression promotes tumour progression. ROYAL SOCIETY OPEN SCIENCE 2022; 9:220186. [PMID: 36397970 PMCID: PMC9626257 DOI: 10.1098/rsos.220186] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Epithelial-mesenchymal transition (EMT) and immunoevasion through upregulation of programmed death-ligand 1 (PD-L1) are important drivers of cancer progression. While EMT has been proposed to facilitate PD-L1-mediated immunosuppression, molecular mechanisms of their interaction remain obscure. Here, we provide insight into these mechanisms by proposing a mathematical model that describes the crosstalk between EMT and interferon gamma (IFNγ)-induced PD-L1 expression. Our model shows that via interaction with microRNA-200 (miR-200), the multi-stability of the EMT regulatory circuit is mirrored in PD-L1 levels, which are further amplified by IFNγ stimulation. This IFNγ-mediated effect is most prominent for cells in a fully mesenchymal state and less strong for those in an epithelial or partially mesenchymal state. In addition, bidirectional crosstalk between miR-200 and PD-L1 implies that IFNγ stimulation allows cells to undergo EMT for lower amounts of inducing signal, and the presence of IFNγ accelerates EMT and decelerates mesenchymal-epithelial transition (MET). Overall, our model agrees with published findings and provides insight into possible mechanisms behind EMT-mediated immune evasion, and primary, adaptive, or acquired resistance to immunotherapy. Our model can be used as a starting point to explore additional crosstalk mechanisms, as an improved understanding of these mechanisms is indispensable for developing better diagnostic and therapeutic options for cancer patients.
Collapse
Affiliation(s)
- Gerhard A. Burger
- Division of Drug Discovery and Safety, Leiden University, Leiden, The Netherlands
| | - Daphne N. Nesenberend
- Division of Drug Discovery and Safety, Leiden University, Leiden, The Netherlands
- Mathematical Institute, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Carlijn M. Lems
- Division of Drug Discovery and Safety, Leiden University, Leiden, The Netherlands
| | - Sander C. Hille
- Mathematical Institute, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Joost B. Beltman
- Division of Drug Discovery and Safety, Leiden University, Leiden, The Netherlands
| |
Collapse
|
17
|
Nordick B, Chae-Yeon Park M, Quaranta V, Hong T. Cooperative RNA degradation stabilizes intermediate epithelial-mesenchymal states and supports a phenotypic continuum. iScience 2022; 25:105224. [PMID: 36248730 PMCID: PMC9557027 DOI: 10.1016/j.isci.2022.105224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/21/2022] [Accepted: 09/23/2022] [Indexed: 11/29/2022] Open
Abstract
Multiple intermediate epithelial-mesenchymal transition (EMT) states reflecting hybrid epithelial and mesenchymal phenotypes were observed in physiological and pathological conditions. Previous theoretical models explaining multiple EMT states rely on regulatory loops involving transcriptional feedback, which produce three or four attractors. This is incompatible with the observed continuum-like EMT spectrum. Here, we used mass-action-based models to describe post-transcriptional regulations, finding that cooperative RNA degradation via multiple microRNA binding sites can generate four-attractor systems without transcriptional feedback. Furthermore, the newly identified intermediates-enabling circuits are common in the EMT regulatory network, and they can synergize with transcriptional feedback to support phenotypic continuum. Finally, our model predicted a role of miR-101 in multistate EMT, and we identified evidence from single-cell RNA-sequencing data that support the prediction. Our work reveals a previously unknown role of cooperative RNA degradation and microRNAs in EMT, providing a framework that can bridge the gap between mechanistic models and single-cell experiments.
Collapse
Affiliation(s)
- Benjamin Nordick
- School of Genome Science and Technology, The University of Tennessee, Knoxville, TN 37916, USA
| | - Mary Chae-Yeon Park
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37916, USA
| | - Vito Quaranta
- Department of Biochemistry, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN 37232, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37916, USA
- National Institute for Mathematical and Biological Synthesis, Knoxville, TN 37916, USA
| |
Collapse
|
18
|
Epigenetic factor competition reshapes the EMT landscape. Proc Natl Acad Sci U S A 2022; 119:e2210844119. [PMID: 36215492 PMCID: PMC9586264 DOI: 10.1073/pnas.2210844119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The emergence of and transitions between distinct phenotypes in isogenic cells can be attributed to the intricate interplay of epigenetic marks, external signals, and gene-regulatory elements. These elements include chromatin remodelers, histone modifiers, transcription factors, and regulatory RNAs. Mathematical models known as gene-regulatory networks (GRNs) are an increasingly important tool to unravel the workings of such complex networks. In such models, epigenetic factors are usually proposed to act on the chromatin regions directly involved in the expression of relevant genes. However, it has been well-established that these factors operate globally and compete with each other for targets genome-wide. Therefore, a perturbation of the activity of a regulator can redistribute epigenetic marks across the genome and modulate the levels of competing regulators. In this paper, we propose a conceptual and mathematical modeling framework that incorporates both local and global competition effects between antagonistic epigenetic regulators, in addition to local transcription factors, and show the counterintuitive consequences of such interactions. We apply our approach to recent experimental findings on the epithelial-mesenchymal transition (EMT). We show that it can explain the puzzling experimental data, as well as provide verifiable predictions.
Collapse
|
19
|
Jia W, Duddu AS, Jolly MK, Levine H. Lack of Correlation between Landscape Geometry and Transition Rates. J Phys Chem B 2022; 126:5613-5618. [PMID: 35876849 DOI: 10.1021/acs.jpcb.2c02837] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Biological cells can exist in a variety of distinct phenotypes, determined by the steady-state solutions of genetic networks governing their cell fate. A popular way of representing these states relies on the creation of landscape related to the relative occupation of these states. It is often assumed that this landscape offers direct information regarding the state-to-state transition rates, suggesting that these are related to barrier heights separating landscape minima. Here, we study a toggle triad network exhibiting multistability and directly demonstrate the lack of any direct correlation between properties of the landscape and corresponding transition rates.
Collapse
Affiliation(s)
- Wen Jia
- Center for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts 02115, United States.,Department of Physics and Astronomy, Rice University, Houston, Texas 77005, United States
| | - Atchuta Srinivas Duddu
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Herbert Levine
- Center for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts 02115, United States.,Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States.,Department of Physics, Northeastern University, Boston, Massachusetts 02115, United States
| |
Collapse
|
20
|
Li X, Guo Z, Luo G, Miao P. Fluorescence DNA Switch for Highly Sensitive Detection of miRNA Amplified by Duplex-Specific Nuclease. SENSORS 2022; 22:s22093252. [PMID: 35590941 PMCID: PMC9104181 DOI: 10.3390/s22093252] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 04/21/2022] [Accepted: 04/21/2022] [Indexed: 02/01/2023]
Abstract
DNA is a type of promising material for the construction of sensors owing to its sequence programmability to control the formation of certain structures. MicroRNA (miRNA) can be applied as promising biomarkers for the diagnosis of a range of diseases. Herein, a novel fluorescent sensing strategy for miRNA is proposed combining duplex-specific nuclease (DSN)-mediated amplification and dumbbell DNA structural switch. Gold nanoparticles (AuNPs) are employed, which provide a 3D reaction interface. They also act as effective fluorescence quenchers. The proposed sensor exhibits high sensitivity (sub-femtomolar level) with a wide dynamic range. In addition, excellent selectivity to distinguish homology sequences is achieved. It also performs satisfactorily in biological samples. Overall, this fluorescent sensor provides a powerful tool for the analysis of miRNA levels and can be applied for related biological studies and clinical diagnosis.
Collapse
Affiliation(s)
- Xiaoqiang Li
- School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China;
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China; (Z.G.); (G.L.)
| | - Zhenzhen Guo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China; (Z.G.); (G.L.)
- Ji Hua Laboratory, Foshan 528200, China
| | - Gangyin Luo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China; (Z.G.); (G.L.)
| | - Peng Miao
- School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China;
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China; (Z.G.); (G.L.)
- Correspondence:
| |
Collapse
|
21
|
Biswas K, Jolly MK, Ghosh A. Mean residence times of TF-TF and TF-miRNA toggle switches. J Biosci 2022. [DOI: 10.1007/s12038-022-00261-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
22
|
Duddu AS, Majumdar SS, Sahoo S, Jhunjhunwala S, Jolly MK. Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity: a case study of Th1/Th2/Th17 cell differentiation. Mol Biol Cell 2022; 33:ar46. [PMID: 35353012 PMCID: PMC9265159 DOI: 10.1091/mbc.e21-10-0521] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Naïve helper (CD4+) T-cells can differentiate into distinct functional subsets including Th1, Th2, and Th17 phenotypes. Each of these phenotypes has a 'master regulator' - T-bet (Th1), GATA3 (Th2) and RORγT (Th17) - that inhibits the other two master regulators. Such mutual repression among them at a transcriptional level can enable multistability, giving rise to six experimentally observed phenotypes - Th1, Th2, Th17, hybrid Th/Th2, hybrid Th2/Th17 and hybrid Th1/Th17. However, the dynamics of switching among these phenotypes, particularly in the case of epigenetic influence, remains unclear. Here, through mathematical modeling, we investigated the coupled transcription-epigenetic dynamics in a three-node mutually repressing network to elucidate how epigenetic changes mediated by any 'master regulator' can influence the transition rates among different cellular phenotypes. We show that the degree of plasticity exhibited by one phenotype depends on relative strength and duration of mutual epigenetic repression mediated among the master regulators in a three-node network. Further, our model predictions can offer putative mechanisms underlying relatively higher plasticity of Th17 phenotype as observed in vitro and in vivo. Together, our modeling framework characterizes phenotypic plasticity and heterogeneity as an outcome of emergent dynamics of a three-node regulatory network, such as the one mediated by T-bet/GATA3/RORγT.
Collapse
Affiliation(s)
- Atchuta Srinivas Duddu
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Sauma Suvra Majumdar
- epartment of Biotechnology, National Institute of Technology, Durgapur 713216, India
| | - Sarthak Sahoo
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Siddharth Jhunjhunwala
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| |
Collapse
|
23
|
Morrison AJ, Wonderlick DR, Harms MJ. Ensemble epistasis: thermodynamic origins of nonadditivity between mutations. Genetics 2021; 219:iyab105. [PMID: 34849909 PMCID: PMC8633102 DOI: 10.1093/genetics/iyab105] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 06/19/2021] [Indexed: 01/02/2023] Open
Abstract
Epistasis-when mutations combine nonadditively-is a profoundly important aspect of biology. It is often difficult to understand its mechanistic origins. Here, we show that epistasis can arise from the thermodynamic ensemble, or the set of interchanging conformations a protein adopts. Ensemble epistasis occurs because mutations can have different effects on different conformations of the same protein, leading to nonadditive effects on its average, observable properties. Using a simple analytical model, we found that ensemble epistasis arises when two conditions are met: (1) a protein populates at least three conformations and (2) mutations have differential effects on at least two conformations. To explore the relative magnitude of ensemble epistasis, we performed a virtual deep-mutational scan of the allosteric Ca2+ signaling protein S100A4. We found that 47% of mutation pairs exhibited ensemble epistasis with a magnitude on the order of thermal fluctuations. We observed many forms of epistasis: magnitude, sign, and reciprocal sign epistasis. The same mutation pair could even exhibit different forms of epistasis under different environmental conditions. The ubiquity of thermodynamic ensembles in biology and the pervasiveness of ensemble epistasis in our dataset suggests that it may be a common mechanism of epistasis in proteins and other macromolecules.
Collapse
Affiliation(s)
- Anneliese J Morrison
- Institute of Molecular Biology, University of Oregon, Eugene, OR 97403, USA
- Department of Chemistry and Biochemistry, University of Oregon, Eugene OR 97403, USA
| | - Daria R Wonderlick
- Institute of Molecular Biology, University of Oregon, Eugene, OR 97403, USA
- Department of Chemistry and Biochemistry, University of Oregon, Eugene OR 97403, USA
| | - Michael J Harms
- Institute of Molecular Biology, University of Oregon, Eugene, OR 97403, USA
- Department of Chemistry and Biochemistry, University of Oregon, Eugene OR 97403, USA
| |
Collapse
|
24
|
Govindaraj V, Kar S. Role of microRNAs in oncogenesis: Insights from computational and systems‐level modeling approaches. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2021. [DOI: 10.1002/cso2.1028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
| | - Sandip Kar
- Department of Chemistry IIT Bombay Mumbai India
| |
Collapse
|
25
|
Hati S, Duddu AS, Jolly MK. Operating principles of circular toggle polygons. Phys Biol 2021; 18. [PMID: 33730700 DOI: 10.1088/1478-3975/abef79] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/17/2021] [Indexed: 11/12/2022]
Abstract
Decoding the dynamics of cellular decision-making and cell differentiation is a central question in cell and developmental biology. A common network motif involved in many cell-fate decisions is a mutually inhibitory feedback loop between two self-activating 'master regulators' A and B, also called as toggle switch. Typically, it can allow for three stable states-(high A, low B), (low A, high B) and (medium A, medium B). A toggle triad-three mutually repressing regulators A, B and C, i.e. three toggle switches arranged circularly (between A and B, between B and C, and between A and C)-can allow for six stable states: three 'single positive' and three 'double positive' ones. However, the operating principles of larger toggle polygons, i.e. toggle switches arranged circularly to form a polygon, remain unclear. Here, we simulate using both discrete and continuous methods the dynamics of different sized toggle polygons. We observed a pattern in their steady state frequency depending on whether the polygon was an even or odd numbered one. The even-numbered toggle polygons result in two dominant states with consecutive components of the network expressing alternating high and low levels. The odd-numbered toggle polygons, on the other hand, enable more number of states, usually twice the number of components with the states that follow 'circular permutation' patterns in their composition. Incorporating self-activations preserved these trends while increasing the frequency of multistability in the corresponding network. Our results offer insights into design principles of circular arrangement of regulatory units involved in cell-fate decision making, and can offer design strategies for synthesizing genetic circuits.
Collapse
Affiliation(s)
- Souvadra Hati
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.,Undergraduate Programme, Indian Institute of Science, Bangalore, India
| | - Atchuta Srinivas Duddu
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| |
Collapse
|
26
|
Li C, Liau ES, Lee Y, Huang Y, Liu Z, Willems A, Garside V, McGlinn E, Chen J, Hong T. MicroRNA governs bistable cell differentiation and lineage segregation via a noncanonical feedback. Mol Syst Biol 2021; 17:e9945. [PMID: 33890404 PMCID: PMC8062999 DOI: 10.15252/msb.20209945] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 03/21/2021] [Accepted: 03/23/2021] [Indexed: 11/09/2022] Open
Abstract
Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription-driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA-mRNA reaction circuits that differ from known feedback loop-like structures. Strikingly, we show that a wide range of biologically plausible post-transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA-mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning.
Collapse
Affiliation(s)
- Chung‐Jung Li
- Molecular and Cell BiologyTaiwan International Graduate ProgramAcademia Sinica and Graduate Institute of Life ScienceNational Defense Medical CenterTaipeiTaiwan
- Institute of Molecular BiologyAcademia SinicaTaipeiTaiwan
| | - Ee Shan Liau
- Molecular and Cell BiologyTaiwan International Graduate ProgramAcademia Sinica and Graduate Institute of Life ScienceNational Defense Medical CenterTaipeiTaiwan
- Institute of Molecular BiologyAcademia SinicaTaipeiTaiwan
| | - Yi‐Han Lee
- Institute of Molecular BiologyAcademia SinicaTaipeiTaiwan
| | - Yang‐Zhe Huang
- Institute of Molecular BiologyAcademia SinicaTaipeiTaiwan
| | - Ziyi Liu
- Genome Science and Technology ProgramThe University of TennesseeKnoxvilleTNUSA
| | - Andrew Willems
- Genome Science and Technology ProgramThe University of TennesseeKnoxvilleTNUSA
| | - Victoria Garside
- EMBL AustraliaAustralian Regenerative Medicine InstituteMonash UniversityClaytonVicAustralia
| | - Edwina McGlinn
- EMBL AustraliaAustralian Regenerative Medicine InstituteMonash UniversityClaytonVicAustralia
| | - Jun‐An Chen
- Molecular and Cell BiologyTaiwan International Graduate ProgramAcademia Sinica and Graduate Institute of Life ScienceNational Defense Medical CenterTaipeiTaiwan
- Institute of Molecular BiologyAcademia SinicaTaipeiTaiwan
- Neuroscience Program Academia SinicaTaipeiTaiwan
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular BiologyThe University of TennesseeKnoxvilleTNUSA
- National Institute for Mathematical and Biological SynthesisKnoxvilleTNUSA
| |
Collapse
|
27
|
Akdeniz BC, Egan M. Molecular Communication for Equilibrium State Estimation in Biochemical Processes on a Lab-on-a-Chip. IEEE Trans Nanobioscience 2021; 20:193-201. [PMID: 33635792 DOI: 10.1109/tnb.2021.3062473] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
A basic problem in molecular biology is to estimate equilibrium states of biochemical processes. To this end, advanced spectroscopy methods have been developed in order to estimate chemical concentrations in situ or in vivo. However, such spectroscopy methods can require special conditions that do not allow direct observation of the biochemical process. A natural means of resolving this problem is to transmit chemical signals to another location within a lab-on-a-chip device; that is, employing molecular communication in order to perform spectroscopy in a different location. In this paper, we develop such a signaling strategy and estimation algorithms for equilibrium states of a biochemical process. In two biologically-inspired models, we then study via simulation the tradeoff between the rate of obtaining spectroscopy measurements and the estimation error, providing insights into requirements of spectroscopy devices for high-throughput biological assays.
Collapse
|
28
|
Chauhan L, Ram U, Hari K, Jolly MK. Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer. eLife 2021; 10:e64522. [PMID: 33729159 PMCID: PMC8012062 DOI: 10.7554/elife.64522] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 03/16/2021] [Indexed: 02/07/2023] Open
Abstract
Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.
Collapse
Affiliation(s)
- Lakshya Chauhan
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Uday Ram
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
| |
Collapse
|
29
|
Abstract
Bistable switches that produce all-or-none responses have been found to regulate a number of natural cellular decision making processes, and subsequently synthetic switches were designed to exploit their potential. However, an increasing number of studies, particularly in the context of cellular differentiation, highlight the existence of a mixed state that can be explained by tristable switches. The criterion for designing robust tristable switches still remains to be understood from the perspective of network topology. To address such a question, we calculated the robustness of several 2- and 3-component network motifs, connected via only two positive feedback loops, in generating tristable signal response curves. By calculating the effective potential landscape and following its modifications with the bifurcation parameter, we constructed one-parameter bifurcation diagrams of these models in a high-throughput manner for a large combinations of parameters. We report here that introduction of a self-activatory positive feedback loop, directly or indirectly, into a mutual inhibition loop leads to generating the most robust tristable response. The high-throughput approach of our method further allowed us to determine the robustness of four types of tristable responses that originate from the relative locations of four bifurcation points. Using the method, we also analyzed the role of additional mutual inhibition loops in stabilizing the mixed state.
Collapse
Affiliation(s)
- Anupam Dey
- School of Chemistry, University of Hyderabad, Central University
P.O., Hyderabad 500046, Telangana, India
| | - Debashis Barik
- School of Chemistry, University of Hyderabad, Central University
P.O., Hyderabad 500046, Telangana, India
| |
Collapse
|
30
|
Frank AS, Larripa K, Ryu H, Snodgrass RG, Röblitz S. Bifurcation and sensitivity analysis reveal key drivers of multistability in a model of macrophage polarization. J Theor Biol 2020; 509:110511. [PMID: 33045246 DOI: 10.1016/j.jtbi.2020.110511] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 09/24/2020] [Accepted: 10/01/2020] [Indexed: 12/13/2022]
Abstract
In this paper, we present and analyze a mathematical model for polarization of a single macrophage which, despite its simplicity, exhibits complex dynamics in terms of multistability. In particular, we demonstrate that an asymmetry in the regulatory mechanisms and parameter values is important for observing multiple phenotypes. Bifurcation and sensitivity analyses show that external signaling cues are necessary for macrophage commitment and emergence to a phenotype, but that the intrinsic macrophage pathways are equally important. Based on our numerical results, we formulate hypotheses that could be further investigated by laboratory experiments to deepen our understanding of macrophage polarization.
Collapse
Affiliation(s)
- Anna S Frank
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.
| | - Kamila Larripa
- Department of Mathematics, Humboldt State University, Arcata, CA, USA.
| | - Hwayeon Ryu
- Department of Mathematics and Statistics, Elon University, Elon, NC, USA.
| | - Ryan G Snodgrass
- Institute of Biochemistry, Goethe-University, Frankfurt, Germany.
| | - Susanna Röblitz
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.
| |
Collapse
|
31
|
Marchetti M, Giaccherini C, Masci G, Verzeroli C, Russo L, Celio L, Sarmiento R, Gamba S, Tartari CJ, Diani E, Vignoli A, Malighetti P, Spinelli D, Kuderer NM, Nichetti F, Minelli M, Tondini C, Barni S, Giuliani F, Petrelli F, D'Alessio A, Gasparini G, Labianca R, Santoro A, De Braud F, Falanga A. Thrombin generation predicts early recurrence in breast cancer patients. J Thromb Haemost 2020; 18:2220-2231. [PMID: 32397009 DOI: 10.1111/jth.14891] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 04/28/2020] [Accepted: 04/30/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Cancer patients present with a hypercoagulable state often associated with poor disease prognosis. OBJECTIVES This study aims to evaluate whether thrombin generation (TG), a global coagulation test, may be a useful tool to improve the identification of patients at high risk of early disease recurrence (ie, E-DR within 2 years) after breast cancer surgery. PATIENTS/METHODS A cohort of 522 newly diagnosed patients with surgically resected high-risk breast cancer were enrolled in the ongoing prospective HYPERCAN study. TG potential was measured in plasma samples collected before starting systemic chemotherapy. Significant predictive hemostatic and clinic-pathological parameters were identified in the derivation cohort by Cox regression analysis. A risk prognostic score for E-DR was generated in the derivation and tested in the validation cohort. RESULTS After a median observation period of 3.4 years, DR occurred in 51 patients, 28 of whom were E-DR. E-DR subjects presented with the highest TG values as compared to both late-DR (from 2 to 5 years) and no relapse subjects (P < .01). Multivariate analysis in the derivation cohort identified TG, mastectomy, triple negative and Luminal B HER2-neg molecular subtypes as significant independent predictors for E-DR, which were utilized to generate a risk assessment score. In the derivation and validation cohorts, E-DR rates were 2.3% and 0% in the low-risk, 10.1% and 6.3% in the intermediate-risk, and 18.2% and 16.7%, in the high-risk categories, respectively. CONCLUSIONS Inclusion of TG in a risk-assessment model for E-DR significantly helps the identification of operated breast cancer patients at high risk of very early relapse.
Collapse
Affiliation(s)
- Marina Marchetti
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Cinzia Giaccherini
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Giovanna Masci
- Oncology Unit, IRCCS Humanitas Institute, Rozzano, Italy
| | - Cristina Verzeroli
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Laura Russo
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Luigi Celio
- Oncology Unit, IRCCS National Cancer Institute, Milan, Italy
| | | | - Sara Gamba
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Carmen J Tartari
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Erika Diani
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Alfonso Vignoli
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Paolo Malighetti
- Department of Management, Information and Production Engineering, University of Bergamo, Bergamo, Italy
| | - Daniele Spinelli
- Department of Management, Information and Production Engineering, University of Bergamo, Bergamo, Italy
| | | | | | - Mauro Minelli
- Oncology Unit, Hospital San Giovanni Addolorata, Rome, Italy
| | - Carlo Tondini
- Oncology Unit, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | - Sandro Barni
- Oncology Unit, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | | | - Fausto Petrelli
- Oncology Unit, Hospital Treviglio-Caravaggio, Treviglio, Italy
| | - Andrea D'Alessio
- Medical Oncology and Internal Medicine, Policlinico San Marco, Bergamo, Italy
| | | | - Roberto Labianca
- Department Oncology Bergamo Province, Hospital Papa Giovanni XXIII, Bergamo, Italy
| | | | | | - Anna Falanga
- Immunohematology and Transfusion Medicine, Hospital Papa Giovanni XXIII, Bergamo, Italy
- School of Medicine, University of Milan Bicocca, Italy
| |
Collapse
|
32
|
Li W, Wang J. Uncovering the Underlying Mechanisms of Cancer Metabolism through the Landscapes and Probability Flux Quantifications. iScience 2020; 23:101002. [PMID: 32276228 PMCID: PMC7150521 DOI: 10.1016/j.isci.2020.101002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 11/03/2019] [Accepted: 03/17/2020] [Indexed: 02/07/2023] Open
Abstract
Cancer metabolism is critical for understanding the mechanism of tumorigenesis, yet the understanding is still challenging. We studied gene-metabolism regulatory interactions and quantified the global driving forces for cancer-metabolism dynamics as the underlying landscape and probability flux. We uncovered four steady-state attractors: a normal state attractor, a cancer OXPHOS state attractor, a cancer glycolysis state attractor, and an intermediate cancer state attractor. We identified the key regulatory interactions through global sensitivity analysis based on the landscape topography. Different landscape topographies of glycolysis switch between normal cells and cancer cells were identified. We uncovered that the normal state to cancer state transformation is associated with the peaks of the probability flux and the thermodynamic dissipation, giving dynamical and thermodynamic origin of cancer formation. We found that cancer metabolism oscillations consume more energy to support cancer malignancy. This study provides a quantitative understanding of cancer metabolism and suggests a metabolic therapeutic strategy.
Collapse
Affiliation(s)
- Wenbo Li
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China
| | - Jin Wang
- Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY 11794-3400, USA.
| |
Collapse
|
33
|
Anticipating critical transitions in epithelial-hybrid-mesenchymal cell-fate determination. Proc Natl Acad Sci U S A 2019; 116:26343-26352. [PMID: 31843939 DOI: 10.1073/pnas.1913773116] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
In the vicinity of a tipping point, critical transitions occur when small changes in an input condition cause sudden, large, and often irreversible changes in the state of a system. Many natural systems ranging from ecosystems to molecular biosystems are known to exhibit critical transitions in their response to stochastic perturbations. In diseases, an early prediction of upcoming critical transitions from a healthy to a disease state by using early-warning signals is of prime interest due to potential application in forecasting disease onset. Here, we analyze cell-fate transitions between different phenotypes (epithelial, hybrid-epithelial/mesenchymal [E/M], and mesenchymal states) that are implicated in cancer metastasis and chemoresistance. These transitions are mediated by a mutually inhibitory feedback loop-microRNA-200/ZEB-driven by the levels of transcription factor SNAIL. We find that the proximity to tipping points enabling these transitions among different phenotypes can be captured by critical slowing down-based early-warning signals, calculated from the trajectory of ZEB messenger RNA level. Further, the basin stability analysis reveals the unexpectedly large basin of attraction for a hybrid-E/M phenotype. Finally, we identified mechanisms that can potentially elude the transition to a hybrid-E/M phenotype. Overall, our results unravel the early-warning signals that can be used to anticipate upcoming epithelial-hybrid-mesenchymal transitions. With the emerging evidence about the hybrid-E/M phenotype being a key driver of metastasis, drug resistance, and tumor relapse, our results suggest ways to potentially evade these transitions, reducing the fitness of cancer cells and restricting tumor aggressiveness.
Collapse
|
34
|
Fumagalli MR, Lionetti MC, Zapperi S, La Porta CAM. Cross-Talk Between circRNAs and mRNAs Modulates MiRNA-mediated Circuits and Affects Melanoma Plasticity. CANCER MICROENVIRONMENT : OFFICIAL JOURNAL OF THE INTERNATIONAL CANCER MICROENVIRONMENT SOCIETY 2019; 12:95-104. [PMID: 31734859 PMCID: PMC6937352 DOI: 10.1007/s12307-019-00230-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 08/20/2019] [Indexed: 12/14/2022]
Abstract
CircularRNAs (circRNAs) are non-coding RNAs which compete for microRNA (miRNA) binding, influencing the abundance and stability of other RNA species. Herein we have investigated the effect of circRNAs on the mir200-ZEB1 feedback loop in relationship with the aggressiveness of human melanoma cells. We first compared the level of expression of key factors in the mir200-ZEB1 feedback loop in primary human melanoma cells compared with their matching metastatic one and found a correlation between the aggressiveness of the cells and the level of expression of ZEB1 and SNAI1. We also analyzed factors in the mir200-ZEB1 feedback loop, including circZEB1, during the phenotypic switching of human melanoma cells. Our results showed a correlation between the level of ZEB1 and SNAI1 and the fraction of cancer stem cells in the population. The level of circZEB1 was, however, consistently high during the entire phenotypic transformation. To understand this result we propose a mathematical model of the regulatory circuit. According to the model, the experimental observations can be explained by the presence of a back-splicing factor limiting circRNA production.
Collapse
Affiliation(s)
- Maria Rita Fumagalli
- Consiglio Nazionale delle Ricerche, Istituto di Biofisica, via Celoria 26, Milano, 20133, Italy
- Center for Complexity and Biosystems, Department of Environmental Science and Policy, University of Milan, via Celoria 26, Milano, 20133, Italy
| | - Maria Chiara Lionetti
- Center for Complexity and Biosystems, Department of Environmental Science and Policy, University of Milan, via Celoria 26, Milano, 20133, Italy
| | - Stefano Zapperi
- Center for Complexity and Biosystems, Department of Physics, University of Milano, via Celoria 16, Milano, 20133, Italy
- CNR - Consiglio Nazionale delle Ricerche, Istituto di Chimica della Materia Condensata e di Tecnologie per l'Energia, Via R. Cozzi 53, Milano, 20125, Italy
| | - Caterina A M La Porta
- Center for Complexity and Biosystems, Department of Environmental Science and Policy, University of Milan, via Celoria 26, Milano, 20133, Italy.
- Consiglio Nazionale delle Ricerche, Istituto di Biofisica, via Celoria 26, Milano, 20133, Italy.
| |
Collapse
|
35
|
Posner R, Laubenbacher R. Connecting the molecular function of microRNAs to cell differentiation dynamics. J R Soc Interface 2019; 16:20190437. [PMID: 31551049 PMCID: PMC6769318 DOI: 10.1098/rsif.2019.0437] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
MicroRNAs form a class of short, non-coding RNA molecules which are essential for proper development in tissue-based plants and animals. To help explain their role in gene regulation, a number of mathematical and computational studies have demonstrated the potential canalizing effects of microRNAs. However, such studies have typically focused on the effects of microRNAs on only one or a few target genes. Consequently, it remains unclear how these small-scale effects add up to the experimentally observed developmental outcomes resulting from microRNA perturbation at the whole-genome level. To answer this question, we built a general computational model of cell differentiation to study the effect of microRNAs in genome-scale gene regulatory networks. Our experiments show that in large gene regulatory networks, microRNAs can control differentiation time without significantly changing steady-state gene expression profiles. This temporal regulatory role cannot be naturally replicated using protein-based transcription factors alone. While several microRNAs have been shown to regulate differentiation time in vivo, our findings provide a new explanation of how the cumulative molecular actions of individual microRNAs influence genome-scale cellular dynamics. Taken together, these results may help explain why tissue-based organisms exclusively depend on miRNA-mediated regulation, while their more primitive counterparts do not.
Collapse
Affiliation(s)
- Russell Posner
- Center for Quantitative Medicine, UConn Health, Farmington, CT, USA
| | - Reinhard Laubenbacher
- Center for Quantitative Medicine, UConn Health, Farmington, CT, USA.,The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| |
Collapse
|
36
|
Yu C, Liu Q, Chen C, Yu J, Wang J. Landscape perspectives of tumor, EMT, and development. Phys Biol 2019; 16:051003. [PMID: 31067516 DOI: 10.1088/1478-3975/ab2029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A tumor is rarely fatal until becoming metastatic. Recent discoveries suggest that epithelial mesenchymal transition(EMT) is an important process which contributes to not only cancer metastasis but also increased stemness. Cancer cells with stem cell characteristics are called cancer stem cells (CSCs). We review recent efforts to quantify and delineate the relationship among EMT, CSC and tumor development. When the gene regulatory network is tightly regulated through the effectively fast regulatory binding, Cancer, Premalignant, Normal, CSC, stem cell (SC), Lesion and Hyperplasia states emerged. The corresponding landscape topography for all of these states can be quantified to a global way for uncovering the relationship among the tumor, metastasis, and development. On the other hand, phenotypic and functional heterogeneity is regarded as one of the greatest challenge in cancer treatment. Cancer and CSCs are heterogeneous and give rise to tumorigenic and non-tumorigenic cells during self-renewal, differentiation and epigenetic diversification. Further, if the gene regulatory network is weakly regulated through the effective slow regulatory binding (by DNA methylation or histone modification etc), multiple meta-stable states can emerge. This model can provide an epigenetic and physical rather than genetic and fixed origin of heterogeneity. Elucidating the origin of and dynamic nature of tumor cells will likely help better understand the cellular basis of therapeutic response, resistance, and relapse.
Collapse
Affiliation(s)
- Chong Yu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China. University of Science and Technology of China, University of Science and Technology of China, Hefei, Anhui, People's Republic of China
| | | | | | | | | |
Collapse
|
37
|
Lin YT, Feng S, Hlavacek WS. Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks. J Chem Phys 2019; 150:244101. [PMID: 31255063 DOI: 10.1063/1.5096774] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Various kinetic Monte Carlo algorithms become inefficient when some of the population sizes in a system are large, which gives rise to a large number of reaction events per unit time. Here, we present a new acceleration algorithm based on adaptive and heterogeneous scaling of reaction rates and stoichiometric coefficients. The algorithm is conceptually related to the commonly used idea of accelerating a stochastic simulation by considering a subvolume λΩ (0 < λ < 1) within a system of interest, which reduces the number of reaction events per unit time occurring in a simulation by a factor 1/λ at the cost of greater error in unbiased estimates of first moments and biased overestimates of second moments. Our new approach offers two unique benefits. First, scaling is adaptive and heterogeneous, which eliminates the pitfall of overaggressive scaling. Second, there is no need for an a priori classification of populations as discrete or continuous (as in a hybrid method), which is problematic when discreteness of a chemical species changes during a simulation. The method requires specification of only a single algorithmic parameter, Nc, a global critical population size above which populations are effectively scaled down to increase simulation efficiency. The method, which we term partial scaling, is implemented in the open-source BioNetGen software package. We demonstrate that partial scaling can significantly accelerate simulations without significant loss of accuracy for several published models of biological systems. These models characterize activation of the mitogen-activated protein kinase ERK, prion protein aggregation, and T-cell receptor signaling.
Collapse
Affiliation(s)
- Yen Ting Lin
- Center for Nonlinear Studies and Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Song Feng
- Center for Nonlinear Studies and Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - William S Hlavacek
- Center for Nonlinear Studies and Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| |
Collapse
|
38
|
Ye Y, Kang X, Bailey J, Li C, Hong T. An enriched network motif family regulates multistep cell fate transitions with restricted reversibility. PLoS Comput Biol 2019; 15:e1006855. [PMID: 30845219 PMCID: PMC6424469 DOI: 10.1371/journal.pcbi.1006855] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 03/19/2019] [Accepted: 02/07/2019] [Indexed: 12/16/2022] Open
Abstract
Multistep cell fate transitions with stepwise changes of transcriptional profiles are common to many developmental, regenerative and pathological processes. The multiple intermediate cell lineage states can serve as differentiation checkpoints or branching points for channeling cells to more than one lineages. However, mechanisms underlying these transitions remain elusive. Here, we explored gene regulatory circuits that can generate multiple intermediate cellular states with stepwise modulations of transcription factors. With unbiased searching in the network topology space, we found a motif family containing a large set of networks can give rise to four attractors with the stepwise regulations of transcription factors, which limit the reversibility of three consecutive steps of the lineage transition. We found that there is an enrichment of these motifs in a transcriptional network controlling the early T cell development, and a mathematical model based on this network recapitulates multistep transitions in the early T cell lineage commitment. By calculating the energy landscape and minimum action paths for the T cell model, we quantified the stochastic dynamics of the critical factors in response to the differentiation signal with fluctuations. These results are in good agreement with experimental observations and they suggest the stable characteristics of the intermediate states in the T cell differentiation. These dynamical features may help to direct the cells to correct lineages during development. Our findings provide general design principles for multistep cell linage transitions and new insights into the early T cell development. The network motifs containing a large family of topologies can be useful for analyzing diverse biological systems with multistep transitions. The functions of cells are dynamically controlled in many biological processes including development, regeneration and disease progression. Cell fate transition, or the switch of cellular functions, often involves multiple steps. The intermediate stages of the transition provide the biological systems with the opportunities to regulate the transitions in a precise manner. These transitions are controlled by key regulatory genes of which the expression shows stepwise patterns, but how the interactions of these genes can determine the multistep processes was unclear. Here, we present a comprehensive analysis on the design principles of gene circuits that govern multistep cell fate transition. We found a large network family with common structural features that can generate systems with the ability to control three consecutive steps of the transition. We found that this type of networks is enriched in a gene circuit controlling the development of T lymphocyte, a crucial type of immune cells. We performed mathematical modeling using this gene circuit and we recapitulated the stepwise and irreversible loss of stem cell properties of the developing T lymphocytes. Our findings can be useful to analyze a wide range of gene regulatory networks controlling multistep cell fate transitions.
Collapse
Affiliation(s)
- Yujie Ye
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Tennessee, United States of America
| | - Xin Kang
- Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.,School of Mathematical Sciences, Fudan University, Shanghai, China
| | - Jordan Bailey
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Tennessee, United States of America
| | - Chunhe Li
- Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.,Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Tennessee, United States of America.,National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee, United States of America
| |
Collapse
|
39
|
De Caluwé J, Tosenberger A, Gonze D, Dupont G. Signalling-modulated gene regulatory networks in early mammalian development. J Theor Biol 2019; 463:56-66. [DOI: 10.1016/j.jtbi.2018.12.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 10/25/2018] [Accepted: 12/05/2018] [Indexed: 01/18/2023]
|
40
|
Uncovering the underlying physical mechanism for cancer-immunity of MHC class I diversity. Biochem Biophys Res Commun 2018; 504:532-537. [PMID: 30197004 DOI: 10.1016/j.bbrc.2018.08.170] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 08/27/2018] [Indexed: 11/20/2022]
Abstract
The cancer cells are heterogeneous populated, which can be classified as MHC class I positive and MHC I class negative. They influence the immune system differently. In this work, we build a core cancer-immune circuit of MHC class I diversity including MHC class I positive cancer type, MHC I class I negative cancer type and 4 immune cell types to uncover the underlying mechanism of the cancer immunity based on the underlying landscape topography. We quantify four steady state attractors, normal state, two low cancer states and a high cancer state. The landscape topography changes upon changes in cancer self-activation and the related killing rate of the killer cells are illustrated. It demonstrates that the competition between the two cancer cell types. We simulate the tumorigenesis and development of cancer according to its biological process and classify these into 7 stages. This landscape framework provides a quantitative way to understand characteristics of these two cancer cell types under immune microenvironment and the underlying physical mechanisms of cancer cell evolution along cancer development.
Collapse
|
41
|
Salgia R, Mambetsariev I, Hewelt B, Achuthan S, Li H, Poroyko V, Wang Y, Sattler M. Modeling small cell lung cancer (SCLC) biology through deterministic and stochastic mathematical models. Oncotarget 2018; 9:26226-26242. [PMID: 29899855 PMCID: PMC5995226 DOI: 10.18632/oncotarget.25360] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 04/24/2018] [Indexed: 12/14/2022] Open
Abstract
Mathematical cancer models are immensely powerful tools that are based in part on the fractal nature of biological structures, such as the geometry of the lung. Cancers of the lung provide an opportune model to develop and apply algorithms that capture changes and disease phenotypes. We reviewed mathematical models that have been developed for biological sciences and applied them in the context of small cell lung cancer (SCLC) growth, mutational heterogeneity, and mechanisms of metastasis. The ultimate goal is to develop the stochastic and deterministic nature of this disease, to link this comprehensive set of tools back to its fractalness and to provide a platform for accurate biomarker development. These techniques may be particularly useful in the context of drug development research, such as combination with existing omics approaches. The integration of these tools will be important to further understand the biology of SCLC and ultimately develop novel therapeutics.
Collapse
Affiliation(s)
- Ravi Salgia
- City of Hope, Department of Medical Oncology and Therapeutics Research, Duarte 91010, CA, USA
| | - Isa Mambetsariev
- City of Hope, Department of Medical Oncology and Therapeutics Research, Duarte 91010, CA, USA
| | - Blake Hewelt
- City of Hope, Department of Medical Oncology and Therapeutics Research, Duarte 91010, CA, USA
| | | | - Haiqing Li
- City of Hope, Center for Informatics, Duarte 91010, CA, USA
| | - Valeriy Poroyko
- City of Hope, Department of Medical Oncology and Therapeutics Research, Duarte 91010, CA, USA
| | - Yingyu Wang
- City of Hope, Center for Informatics, Duarte 91010, CA, USA
| | - Martin Sattler
- Dana-Farber Cancer Institute, Department of Medical Oncology, Boston 02215, MA, USA.,Harvard Medical School, Department of Medicine, Boston 02115, MA, USA
| |
Collapse
|
42
|
Negri T, Brich S, Bozzi F, Volpi CV, Gualeni AV, Stacchiotti S, De Cecco L, Canevari S, Gloghini A, Pilotti S. New transcriptional-based insights into the pathogenesis of desmoplastic small round cell tumors (DSRCTs). Oncotarget 2018; 8:32492-32504. [PMID: 28415643 PMCID: PMC5464804 DOI: 10.18632/oncotarget.16477] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 03/13/2017] [Indexed: 12/14/2022] Open
Abstract
To gain new insights into desmoplastic small round cell tumors (DSRCTs) by means of gene expression profiling (GEP). Formalin-fixed, paraffin-embedded surgical specimens obtained from seven pretreated DSRCT patients were interrogated using GEP complemented by immunohistochemistry, a cancer stem cell array, and miRNA in situ hybridisation, including the combined chimera modules miRNA-200/ZEB1 and miRNA-34/SLUG. The chimera modules divided the cases into three classes that respectively recapitulated the traits of mesenchymal epithelial reverse transition (MErT), epithelial mesenchymal transition (EMT), and hybrid/partial EMT. This indicates a close correlation between the reprogramming governed by EMT regulators and DSRCT biology, which was further confirmed by miRNA-21 and is consistent with the broad morphological spectrum of DSRCTs. Starting from the miRNA-200/ZEB1 axis, we also found that DSRCTs carry a signature of immunological ignorance that is not responsive to PD-L1 blockade. Evidence that the up-regulation of miRNA-200 and E-cadherin, and quite a high level of miRNA-21 expression segregate with the MErT supports the idea that, in addition to the hybrid/partial state, MErT is also enriched in stemness: the androgen-positive cases, whose stemness traits were confirmed by stem cell arrays, all fell into these two classes. Our findings also confirmed that tumoral cell PDGFRA expression correlates with desmoplasia, and demonstrated the co-expression of PDGFRA and ISLR/Meflin, another marker of pluripotency. Despite the limited number of cases, these findings provide unexpectedly relevant information concerning the pathogenesis of DSRCTs, and prove the validity of miRNA-based chimera circuit modelling in the clinico-pathological setting.
Collapse
Affiliation(s)
- Tiziana Negri
- Department of Diagnostic Pathology and Laboratory Medicine, Laboratory of Experimental Molecular Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Silvia Brich
- Department of Diagnostic Pathology and Laboratory Medicine, Laboratory of Experimental Molecular Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.,MOSE-DEA, University of Trieste, Trieste, Italy
| | - Fabio Bozzi
- Department of Diagnostic Pathology and Laboratory Medicine, Laboratory of Experimental Molecular Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Chiara V Volpi
- Department of Diagnostic Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Ambra V Gualeni
- Department of Diagnostic Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Silvia Stacchiotti
- Adult Mesenchymal Tumor and Rare Cancer Medical Oncology Unit, Cancer Medicine Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Loris De Cecco
- Department of Experimental Oncology and Molecular Medicine, Functional Genomics and Bioinformatics, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Silvana Canevari
- Department of Experimental Oncology and Molecular Medicine, Functional Genomics and Bioinformatics, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Annunziata Gloghini
- Department of Diagnostic Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Silvana Pilotti
- Department of Diagnostic Pathology and Laboratory Medicine, Laboratory of Experimental Molecular Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| |
Collapse
|
43
|
Evans MK, Brown MC, Geradts J, Bao X, Robinson TJ, Jolly MK, Vermeulen PB, Palmer GM, Gromeier M, Levine H, Morse MA, Van Laere SJ, Devi GR. XIAP Regulation by MNK Links MAPK and NFκB Signaling to Determine an Aggressive Breast Cancer Phenotype. Cancer Res 2018; 78:1726-1738. [PMID: 29351901 DOI: 10.1158/0008-5472.can-17-1667] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 11/07/2017] [Accepted: 01/16/2018] [Indexed: 12/20/2022]
Abstract
Hyperactivation of the NFκB pathway is a distinct feature of inflammatory breast cancer (IBC), a highly proliferative and lethal disease. Gene expression studies in IBC patient tissue have linked EGFR (EGFR/HER2)-mediated MAPK signaling to NFκB hyperactivity, but the mechanism(s) by which this occurs remain unclear. Here, we report that the X-linked inhibitor of apoptosis protein (XIAP) plays a central role in linking these two pathways. XIAP overexpression correlated with poor prognoses in breast cancer patients and was frequently observed in untreated IBC patient primary tumors. XIAP drove constitutive NFκB transcriptional activity, which mediated ALDH positivity (a marker of stem-like cells), in vivo tumor growth, and an IBC expression signature in patient-derived IBC cells. Using pathway inhibitors and mathematical models, we defined a new role for the MAPK interacting (Ser/Thr)-kinase (MNK) in enhancing XIAP expression and downstream NFκB signaling. Furthermore, targeted XIAP knockdown and treatment with a MNK inhibitor decreased tumor cell migration in a dorsal skin fold window chamber murine model that allowed for intravital imaging of local tumor growth and migration. Together, our results indicate a novel role for XIAP in the molecular cross-talk between MAPK and NFκB pathways in aggressive tumor growth, which has the potential to be therapeutically exploited.Significance: Signaling by the MNK kinase is essential in inflammatory breast cancer, and it can be targeted to inhibit XIAP-NFκB signaling and the aggressive phenotype of this malignancy. Cancer Res; 78(7); 1726-38. ©2018 AACR.
Collapse
Affiliation(s)
- Myron K Evans
- Department of Surgery, Division of Surgical Sciences, Duke University Medical Center, Durham, North Carolina.,Department of Pathology, Duke University Medical Center, Durham, North Carolina
| | - Michael C Brown
- Department of Neurosurgery, Duke University Medical Center, Durham, North Carolina
| | - Joseph Geradts
- Department of Pathology, Duke University Medical Center, Durham, North Carolina
| | - Xuhui Bao
- Department of Surgery, Division of Surgical Sciences, Duke University Medical Center, Durham, North Carolina
| | - Timothy J Robinson
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Mohit Kumar Jolly
- Center for Theoretical Biological Physics, Rice University, Houston, Texas
| | - Peter B Vermeulen
- Translational Cancer Research Unit, Oncology Center, General Hospital Sint-Augustinus, Antwerp, Belgium
| | - Gregory M Palmer
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina.,Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Matthias Gromeier
- Department of Neurosurgery, Duke University Medical Center, Durham, North Carolina
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, Texas
| | - Michael A Morse
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina.,Department of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Steven J Van Laere
- Translational Cancer Research Unit, Oncology Center, General Hospital Sint-Augustinus, Antwerp, Belgium.,Center for Oncological Research (CORE), University of Antwerp, Antwerp, Belgium
| | - Gayathri R Devi
- Department of Surgery, Division of Surgical Sciences, Duke University Medical Center, Durham, North Carolina. .,Department of Pathology, Duke University Medical Center, Durham, North Carolina.,Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina
| |
Collapse
|
44
|
Masiello MG, Verna R, Cucina A, Bizzarri M. Physical constraints in cell fate specification. A case in point: Microgravity and phenotypes differentiation. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 134:55-67. [PMID: 29307754 DOI: 10.1016/j.pbiomolbio.2018.01.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 12/30/2017] [Accepted: 01/02/2018] [Indexed: 12/12/2022]
Abstract
Data obtained by studying mammalian cells in absence of gravity strongly support the notion that cell fate specification cannot be understood according to the current molecular model. A paradigmatic case in point is provided by studying cell populations growing in absence of gravity. When the physical constraint (gravity) is 'experimentally removed', cells spontaneously allocate into two morphologically different phenotypes. Such phenomenon is likely enacted by the intrinsic stochasticity, which, in turn, is successively 'canalized' by a specific gene regulatory network. Both phenotypes are thermodynamically and functionally 'compatibles' with the new, modified environment. However, when the two cell subsets are reseeded into the 1g gravity field the two phenotypes collapse into one. Gravity constraints the system in adopting only one phenotype, not by selecting a pre-existing configuration, but more precisely shaping it de-novo through the modification of the cytoskeleton three-dimensional structure. Overall, those findings highlight how macro-scale features are irreducible to lower-scale explanations. The identification of macroscale control parameters - as those depending on the field (gravity, electromagnetic fields) or emerging from the cooperativity among the field's components (tissue stiffness, cell-to-cell connectivity) - are mandatory for assessing boundary conditions for models at lower scales, thus providing a concrete instantiation of top-down effects.
Collapse
Affiliation(s)
- Maria Grazia Masiello
- Department of Experimental Medicine, Sapienza University of Rome, viale Regina Elena 324, 00161 Rome, Italy; Department of Surgery "PietroValdoni", Sapienza University of Rome, via A. Scarpa 14, 00161 Rome, Italy.
| | - Roberto Verna
- Department of Experimental Medicine, Sapienza University of Rome, viale Regina Elena 324, 00161 Rome, Italy.
| | - Alessandra Cucina
- Department of Surgery "PietroValdoni", Sapienza University of Rome, via A. Scarpa 14, 00161 Rome, Italy; Azienda Policlinico Umberto I, viale del Policlinico 155, 00161 Rome, Italy.
| | - Mariano Bizzarri
- Department of Experimental Medicine, Sapienza University of Rome, viale Regina Elena 324, 00161 Rome, Italy.
| |
Collapse
|
45
|
Abstract
Background The Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done. Results Here, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E→E/M→M, the different responses of SNAIL and ZEB1 to exogenous TGF-β and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2. Conclusions These experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.
Collapse
|
46
|
Abstract
A long-standing goal in evolutionary biology is predicting evolution. Here, we show that the architecture of macromolecules fundamentally limits evolutionary predictability. Under physiological conditions, macromolecules, like proteins, flip between multiple structures, forming an ensemble of structures. A mutation affects all of these structures in slightly different ways, redistributing the relative probabilities of structures in the ensemble. As a result, mutations that follow the first mutation have a different effect than they would if introduced before. This implies that knowing the effects of every mutation in an ancestor would be insufficient to predict evolutionary trajectories past the first few steps, leading to profound unpredictability in evolution. We, therefore, conclude that detailed evolutionary predictions are not possible given the chemistry of macromolecules. Evolutionary prediction is of deep practical and philosophical importance. Here we show, using a simple computational protein model, that protein evolution remains unpredictable, even if one knows the effects of all mutations in an ancestral protein background. We performed a virtual deep mutational scan—revealing the individual and pairwise epistatic effects of every mutation to our model protein—and then used this information to predict evolutionary trajectories. Our predictions were poor. This is a consequence of statistical thermodynamics. Proteins exist as ensembles of similar conformations. The effect of a mutation depends on the relative probabilities of conformations in the ensemble, which in turn, depend on the exact amino acid sequence of the protein. Accumulating substitutions alter the relative probabilities of conformations, thereby changing the effects of future mutations. This manifests itself as subtle but pervasive high-order epistasis. Uncertainty in the effect of each mutation accumulates and undermines prediction. Because conformational ensembles are an inevitable feature of proteins, this is likely universal.
Collapse
|
47
|
Burger GA, Danen EHJ, Beltman JB. Deciphering Epithelial-Mesenchymal Transition Regulatory Networks in Cancer through Computational Approaches. Front Oncol 2017; 7:162. [PMID: 28824874 PMCID: PMC5540937 DOI: 10.3389/fonc.2017.00162] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Accepted: 07/18/2017] [Indexed: 12/14/2022] Open
Abstract
Epithelial–mesenchymal transition (EMT), the process by which epithelial cells can convert into motile mesenchymal cells, plays an important role in development and wound healing but is also involved in cancer progression. It is increasingly recognized that EMT is a dynamic process involving multiple intermediate or “hybrid” phenotypes rather than an “all-or-none” process. However, the role of EMT in various cancer hallmarks, including metastasis, is debated. Given the complexity of EMT regulation, computational modeling has proven to be an invaluable tool for cancer research, i.e., to resolve apparent conflicts in experimental data and to guide experiments by generating testable hypotheses. In this review, we provide an overview of computational modeling efforts that have been applied to regulation of EMT in the context of cancer progression and its associated tumor characteristics. Moreover, we identify possibilities to bridge different modeling approaches and point out outstanding questions in which computational modeling can contribute to advance our understanding of pathological EMT.
Collapse
Affiliation(s)
- Gerhard A Burger
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Erik H J Danen
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Joost B Beltman
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| |
Collapse
|
48
|
Jia D, Jolly MK, Kulkarni P, Levine H. Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory. Cancers (Basel) 2017; 9:E70. [PMID: 28640191 PMCID: PMC5532606 DOI: 10.3390/cancers9070070] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 06/13/2017] [Accepted: 06/13/2017] [Indexed: 01/11/2023] Open
Abstract
Waddington's epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of "landscape" in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an "attractor" that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of "cancer attractors"-hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes "recanalization", i.e., the exit from "cancer attractors" and re-entry into "normal attractors", is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.
Collapse
Affiliation(s)
- Dongya Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA.
- Graduate Program in Systems, Synthetic and Physical Biology, Rice University, Houston, TX 77005, USA.
| | - Mohit Kumar Jolly
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA.
| | - Prakash Kulkarni
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA.
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA.
- Department of Bioengineering, Rice University, Houston, TX 77005, USA.
- Department of Physics and Astronomy, Rice University, Houston, TX 77005, USA.
- Department of Biosciences, Rice University, Houston, TX 77005, USA.
| |
Collapse
|
49
|
Jolly MK, Levine H. Computational systems biology of epithelial-hybrid-mesenchymal transitions. ACTA ACUST UNITED AC 2017. [DOI: 10.1016/j.coisb.2017.02.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
50
|
Jia D, Jolly MK, Harrison W, Boareto M, Ben-Jacob E, Levine H. Operating principles of tristable circuits regulating cellular differentiation. Phys Biol 2017; 14:035007. [PMID: 28443829 DOI: 10.1088/1478-3975/aa6f90] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Many cell-fate decisions during embryonic development are governed by a motif comprised of two transcription factors (TFs) A and B that mutually inhibit each other and may self-activate. This motif, called as a self-activating toggle switch (SATS), can typically have three stable states (phenotypes)-two corresponding to differentiated cell fates, each of which has a much higher level of one TF than the other-[Formula: see text] or [Formula: see text]-and the third state corresponding to an 'undecided' stem-like state with similar levels of both A and B-[Formula: see text]. Furthermore, two or more SATSes can be coupled together in various topologies in different contexts, thereby affecting the coordination between multiple cellular decisions. However, two questions remain largely unanswered: (a) what governs the co-existence and relative stability of these three stable states? (b) What orchestrates the decision-making of coupled SATSes? Here, we first demonstrate that the co-existence and relative stability of the three stable states in an individual SATS can be governed by the relative strength of self-activation, external signals activating and/or inhibiting A and B, and mutual degradation between A and B. Simultaneously, we investigate the effects of these factors on the decision-making of two coupled SATSes. Our results offer novel understanding into the operating principles of individual and coupled tristable self-activating toggle switches (SATSes) regulating cellular differentiation and can yield insights into synthesizing three-way genetic circuits and understanding of cellular reprogramming.
Collapse
Affiliation(s)
- Dongya Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005-1827, United States of America. Program in Systems, Synthetic and Physical Biology, Rice University, Houston, TX 77005-1827, United States of America
| | | | | | | | | | | |
Collapse
|