ORCID Profile
0000-0002-1447-9687
Current Organisation
Monash University
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Biological Mathematics | Biochemistry and Cell Biology | Signal Transduction | Systems Biology
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in the Biological Sciences | Expanding Knowledge in the Mathematical Sciences |
Related Links
Publications
Run-to-run overlay control of steppers in semiconductor manufacturing systems based on history data analysis and neural network modeling
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2005
Simulation Sudy of the TNFα Mediated NF-κB Signaling Pathway
Publisher: Springer Berlin Heidelberg
Date: 2003
Experimental Design in Systems Biology, Based on Parameter Sensitivity Analysis Using a Monte Carlo Method: A Case Study for the TNFα-Mediated NF-κ B Signal Transduction
Publisher: SAGE Publications
Date: 12-2003
Abstract: Mathematical modeling and dynamic simulation of signal transduction pathways is a central theme in systems biology and is increasingly attracting attention in the postgenomic era. The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in this area. This study’s aim is to introduce a new strategy for experimental design based on parameter sensitivity analysis. The approach identifies key parameters/variables in a signal transduction pathway model and can thereby provide experimental biologists with guidance on which proteins to consider for measurement. The article focuses on applying this approach to the TNFα-mediated NF-κB pathway, which plays an important role in immunity and inflammation and in the control of cell proliferation, differentiation, and apoptosis. A mathematical model of this pathway is proposed, and the sensitivity analysis of model parameters is illustrated for this model by employing the Monte Carlo method over a broad range of parameter values.
Unravelling the functional interaction structure of a cellular network from temporal slope information of experimental data
Publisher: Wiley
Date: 19-07-2005
DOI: 10.1111/J.1742-4658.2005.04815.X
Abstract: Due to the unavoidable nonbiological variations accompanying many experiments, it is imperative to consider a way of unravelling the functional interaction structure of a cellular network (e.g. signalling cascades or gene networks) by using the qualitative information of time-series experimental data instead of computation through the measured absolute values. In this spirit, we propose a very simple but effective method of identifying the functional interaction structure of a cellular network based on temporal ascending or descending slope information from given time-series measurements. From this method, we can gain insight into the acceptable measurement error ranges in order to estimate the correct functional interaction structure and we can also find guidance for a new experimental design to complement the insufficient information of a given experimental dataset. We developed experimental sign equations, making use of the temporal slope sign information from time-series experimental data, without a specific assumption on parameter perturbations for each network node. Based on these equations, we further describe the available specific information from each part of experimental data in detail and show the functional interaction structure obtained by integrating such information. In this procedure, we use only simple algebra on sign changes without complicated computations on the measured absolute values of the experimental data. The result is, however, verified through rigorous mathematical definitions and proofs. The present method provides us with information about the acceptable measurement error ranges for correct estimation of the functional interaction structure and it further leads to a new experimental design to complement the given experimental data by informing us about additional specific s ling points to be chosen for further required information.
Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer
Publisher: Public Library of Science (PLoS)
Date: 19-06-2018
SynDISCO: A Mechanistic Modeling-Based Framework for Predictive Prioritization of Synergistic Drug Combinations Directed at Cell Signaling Networks
Publisher: Cold Spring Harbor Laboratory
Date: 08-04-2023
DOI: 10.1101/2023.04.07.536087
Abstract: The widespread development of resistance to cancer monotherapies has prompted the need to identify combinatorial treatment approaches that circumvent drug resistance and achieve more durable clinical benefit. However, given the vast space of possible combinations of existing drugs, the inaccessibility of drug screens to candidate targets with no available drugs, and the significant heterogeneity of cancers, exhaustive experimental testing of combination treatments remains highly impractical. There is thus an urgent need to develop computational approaches that complement experimental efforts and aid the identification and prioritization of effective drug combinations. Here, we provide a practical guide to SynDISCO, a computational framework that leverages mechanistic ODE modeling to predict and prioritize synergistic combination treatments directed at signaling networks. We demonstrate the key steps of SynDISCO and its application to the EGFR-MET signaling network in triple negative breast cancer as an illustrative ex le. SynDISCO is, however, a network- and cancer-independent framework, and given a suitable ODE model of the network of interest, it could be leveraged to discover cancer-specific combination treatments.
A regulated double-negative feedback decodes the temporal gradient of input stimulation in a cell signaling network
Publisher: Public Library of Science (PLoS)
Date: 09-2016
The hidden switches underlying RORα-mediated circuits that critically regulate uncontrolled cell proliferation
Publisher: Oxford University Press (OUP)
Date: 15-05-2014
DOI: 10.1093/JMCB/MJU023
Abstract: Prostaglandin E2 (PGE2) is known to have a key role in the development of colorectal cancer, but previous experiments showed its contrasting (i.e. tumor-promoting or tumor-suppressive) roles depending on experimental conditions. To elucidate the mechanisms underlying such contrasting roles of PGE2 in tumorigenesis, we investigated all the previous experiments and found a new signal transduction pathway mediated by retinoic acid receptor-related orphan receptor (ROR)α, in which PGE2/PKCα-dependent phosphorylation of RORα attenuates Wnt target gene expression in colon cancer cells. From mathematical simulations combined with biochemical experimentation, we revealed that RORα induces a biphasic response of Wnt target genes to PGE2 stimulation through a regulatory switch formed by an incoherent feedforward loop, which provides a mechanistic explanation on the contrasting roles of PGE2 observed in previous experiments. More interestingly, we found that RORα constitutes another regulatory switch formed by coupled positive and negative feedback loops, which regulates the hysteretic response of Wnt signaling and eventually converts a proliferative cellular state into an anti-proliferative state in a very delicate way. Our results indicate that RORα is the key regulator at the center of these hidden switches that critically regulate cancer cell proliferation and thereby being a promising anti-cancer therapeutic target.
The crossregulation between ERK and PI3K signaling pathways determines the tumoricidal efficacy of MEK inhibitor
Publisher: Oxford University Press (OUP)
Date: 04-05-2012
DOI: 10.1093/JMCB/MJS021
Abstract: MEK inhibitor has been highlighted as a promising anti-tumor drug but its effect has been reported as varying over a wide range depending on patho-physiological conditions. In this study, we employed a systems approach by combining biochemical experimentation with in silico simulations to investigate the resistance mechanism and functional consequences of MEK inhibitor. To this end, we have developed an extended integrative model of ERK and PI3K signaling pathways by considering the crosstalk between Ras and PI3K, and analyzed the resistance mechanism to the MEK inhibitor under various mutational conditions. We found that the phospho-Akt level under the Raf mutation was remarkably augmented by MEK inhibitor, while the phospho-ERK level was almost completely repressed. These results suggest that bypassing of the ERK signal to the PI3K signal causes the resistance to the MEK inhibitor in a complex oncogenic signaling network. We further investigated the underlying mechanism of the drug resistance and revealed that the MEK inhibitor disrupts the negative feedback loops from ERK to SOS and GAB1, but activates the positive feedback loop composed of GAB1, Ras, and PI3K, which induces the bypass of the ERK signal to the PI3K signal. Based on these core feedback circuits, we suggested promising candidates for combination therapy and examined the improved inhibitory effects.
Systematic Analysis of Network-driven Adaptive Resistance to CDK4/6 and Estrogen Receptor Inhibition using Meta-Dynamic Network Modelling
Publisher: eLife Sciences Publications, Ltd
Date: 09-2023
DOI: 10.7554/ELIFE.87710
Dynamical analysis of the calcium signaling pathway in cardiac myocytes based on logarithmic sensitivity analysis
Publisher: Wiley
Date: 05-2008
Abstract: Many cellular functions are regulated by the Ca(2+) signal which contains specific information in the form of frequency, litude, and duration of the oscillatory dynamics. Any alterations or dysfunctions of components in the calcium signaling pathway of cardiac myocytes may lead to a erse range of cardiac diseases including hypertrophy and heart failure. In this study, we have investigated the hidden dynamics of the intracellular Ca(2+) signaling and the functional roles of its regulatory mechanism through in silico simulations and parameter sensitivity analysis based on an experimentally verified mathematical model. It was revealed that the Ca(2+) dynamics of cardiac myocytes are determined by the balance among various system parameters. Moreover, it was found through the parameter sensitivity analysis that the self-oscillatory Ca(2+) dynamics are most sensitive to the Ca(2+) leakage rate of the sarcolemmal membrane and the maximum rate of NCX, suggesting that these two components have dominant effects on circulating the cytosolic Ca(2+).
Dissecting cell-fate determination through integrated mathematical modeling of the ERK/MAPK signaling pathway
Publisher: Springer New York
Date: 07-12-2017
DOI: 10.1007/978-1-4939-6424-6_29
Abstract: The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three ex les of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.
Dynamic modelling of the PI3K/MTOR signalling network uncovers biphasic dependence of mTORC1 activity on the mTORC2 subunit SIN1
Publisher: Public Library of Science (PLoS)
Date: 16-09-2021
DOI: 10.1371/JOURNAL.PCBI.1008513
Abstract: The PI3K/MTOR signalling network regulates a broad array of critical cellular processes, including cell growth, metabolism and autophagy. The mechanistic target of rapamycin (MTOR) kinase functions as a core catalytic subunit in two physically and functionally distinct complexes mTORC1 and mTORC2, which also share other common components including MLST8 (also known as GβL) and DEPTOR. Despite intensive research, how mTORC1 and 2 assembly and activity are coordinated, and how they are functionally linked remain to be fully characterized. This is due in part to the complex network wiring, featuring multiple feedback loops and intricate post-translational modifications. Here, we integrate predictive network modelling, in vitro experiments and -omics data analysis to elucidate the emergent dynamic behaviour of the PI3K/MTOR network. We construct new mechanistic models that encapsulate critical mechanistic details, including mTORC1/2 coordination by MLST8 (de)ubiquitination and the Akt-to-mTORC2 positive feedback loop. Model simulations validated by experimental studies revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit SIN1, which is robust against cell-to-cell variation in protein expression. In addition, our integrative analysis demonstrates that ubiquitination of MLST8, which is reversed by OTUD7B, is regulated by IRS1/2. Our results further support the essential role of MLST8 in enabling both mTORC1 and 2’s activity and suggest MLST8 as a viable therapeutic target in breast cancer. Overall, our study reports a new mechanistic model of PI3K/MTOR signalling incorporating MLST8-mediated mTORC1/2 formation and unveils a novel regulatory linkage between mTORC1 and mTORC2.
A hidden incoherent switch regulates RCAN1 in the calcineurin–NFAT signaling network
Publisher: The Company of Biologists
Date: 2011
DOI: 10.1242/JCS.076034
Abstract: Regulator of calcineurin 1 (RCAN1) is a key regulator of the calcineurin–NFAT signaling network in organisms ranging from yeast to human, but its functional role is still under debate because different roles of RCAN1 have been suggested under various experimental conditions. To elucidate the mechanisms underlying the RCAN1 regulatory system, we used a systems approach by combining single-cell experimentation with in silico simulations. In particular, we found that the nuclear export of GSK3β, which switches on the facilitative role of RCAN1 in the calcineurin–NFAT signaling pathway, is promoted by PI3K signaling. Based on this, along with integrated information from previous experiments, we developed a mathematical model in which the functional role of RCAN1 changes in a dose-dependent manner: RCAN1 functions as an inhibitor when its levels are low, but as a facilitator when its levels are high. Furthermore, we identified a hidden incoherent regulation switch that mediates this role change, which entails negative regulation through RCAN1 binding to calcineurin and positive regulation through sequential phosphorylation of RCAN1.
Evaluation of FGFR targeting in breast cancer through interrogation of patient-derived models
Publisher: Springer Science and Business Media LLC
Date: 03-08-2021
DOI: 10.1186/S13058-021-01461-4
Abstract: Particular breast cancer subtypes pose a clinical challenge due to limited targeted therapeutic options and/or poor responses to the existing targeted therapies. While cell lines provide useful pre-clinical models, patient-derived xenografts (PDX) and organoids (PDO) provide significant advantages, including maintenance of genetic and phenotypic heterogeneity, 3D architecture and for PDX, tumor–stroma interactions. In this study, we applied an integrated multi-omic approach across panels of breast cancer PDXs and PDOs in order to identify candidate therapeutic targets, with a major focus on specific FGFRs. MS-based phosphoproteomics, RNAseq, WES and Western blotting were used to characterize aberrantly activated protein kinases and effects of specific FGFR inhibitors. PDX and PDO were treated with the selective tyrosine kinase inhibitors AZD4547 (FGFR1-3) and BLU9931 (FGFR4). FGFR4 expression in cancer tissue s les and PDOs was assessed by immunohistochemistry. METABRIC and TCGA datasets were interrogated to identify specific FGFR alterations and their association with breast cancer subtype and patient survival. Phosphoproteomic profiling across 18 triple-negative breast cancers (TNBC) and 1 luminal B PDX revealed considerable heterogeneity in kinase activation, but 1/3 of PDX exhibited enhanced phosphorylation of FGFR1, FGFR2 or FGFR4. One TNBC PDX with high FGFR2 activation was exquisitely sensitive to AZD4547. Integrated ‘omic analysis revealed a novel FGFR2-SKI fusion that comprised the majority of FGFR2 joined to the C-terminal region of SKI containing the coiled-coil domains. High FGFR4 phosphorylation characterized a luminal B PDX model and treatment with BLU9931 significantly decreased tumor growth. Phosphoproteomic and transcriptomic analyses confirmed on-target action of the two anti-FGFR drugs and also revealed novel effects on the spliceosome, metabolism and extracellular matrix (AZD4547) and RIG-I-like and NOD-like receptor signaling (BLU9931). Interrogation of public datasets revealed FGFR2 lification, fusion or mutation in TNBC and other breast cancer subtypes, while FGFR4 overexpression and lification occurred in all breast cancer subtypes and were associated with poor prognosis. Characterization of a PDO panel identified a luminal A PDO with high FGFR4 expression that was sensitive to BLU9931 treatment, further highlighting FGFR4 as a potential therapeutic target. This work highlights how patient-derived models of human breast cancer provide powerful platforms for therapeutic target identification and analysis of drug action, and also the potential of specific FGFRs, including FGFR4, as targets for precision treatment.
In Silico Analysis of Combined Therapeutics Strategy for Heart Failure
Publisher: Wiley
Date: 14-01-2010
Switching feedback mechanisms realize the dual role of MCIP in the regulation of calcineurin activity
Publisher: Wiley
Date: 05-10-2006
DOI: 10.1016/J.FEBSLET.2006.09.064
Abstract: Calcineurin (CaN) assists T-cell activation, growth and differentiation of skeletal and cardiac myocytes, memory, and apoptosis. It also activates transcription of the nuclear factor of activated T-cells (NFAT) family including hypertrophic target genes. It has been reported that the modulatory calcineurin-interacting protein (MCIP) inhibits the CaN activity and thereby reduces the hypertrophic response. However, it has been shown that MCIP facilitates or permits the hypertrophic response under some stress conditions such as isoproterenol infusion or pressure overload by transverse aortic constriction. As there is no direct experimental evidence that can explain these paradoxical phenomena, there has been a controversy concerning the functional role of MCIP in developing the hypertrophic response. It is therefore crucial to establish a hypothesis that can clearly explain these phenomena. Towards this end, we propose in this paper a hypothesis that is based on available experimental evidence as well as mathematical modeling and computer simulations. We hypothesize that there is a threshold in the nuclear NFAT concentration above which MCIP is switched on. Below this threshold, the inhibition of active CaN by MCIP is negligible, while the activated protein kinase increases the dissociation rate of the CaN/MCIP complex. This leads to an augmentation of active CaN. This mechanism realizes the positive effect (i.e., removing any negative feedback) of MCIP in the hypertrophic response. On the other hand, the over-expression of active CaN increases nuclear NFAT to values above the threshold, while CaN is inhibited through binding of MCIP (expressed by the nuclear NFAT). This mechanism realizes the introduction of a negative feedback mechanism. To unravel this switching feedback mechanism, we have developed a mathematical model for which computer simulations are in agreement with the existing experimental data. The simulations demonstrate how the apparently paradoxical behavior can emerge as a result of cellular conditions.
Modelling Spatially Regulated β-Catenin Dynamics and Invasion in Intestinal Crypts
Publisher: Elsevier BV
Date: 08-2010
The pseudokinase NRBP1 activates Rac1/Cdc42 via P-Rex1 to drive oncogenic signalling in triple-negative breast cancer
Publisher: Springer Science and Business Media LLC
Date: 24-01-2023
DOI: 10.1038/S41388-023-02594-W
Abstract: We have determined that expression of the pseudokinase NRBP1 positively associates with poor prognosis in triple negative breast cancer (TNBC) and is required for efficient migration, invasion and proliferation of TNBC cells in culture as well as growth of TNBC orthotopic xenografts and experimental metastasis. Application of BioID/MS profiling identified P-Rex1, a known guanine nucleotide exchange factor for Rac1, as a NRBP1 binding partner. Importantly, NRBP1 overexpression enhanced levels of GTP-bound Rac1 and Cdc42 in a P-Rex1-dependent manner, while NRBP1 knockdown reduced their activation. In addition, NRBP1 associated with P-Rex1, Rac1 and Cdc42, suggesting a scaffolding function for this pseudokinase. NRBP1-mediated promotion of cell migration and invasion was P-Rex1-dependent, while constitutively-active Rac1 rescued the effect of NRBP1 knockdown on cell proliferation and invasion. Generation of reactive oxygen species via a NRBP1/P-Rex1 pathway was implicated in these oncogenic roles of NRBP1. Overall, these findings define a new function for NRBP1 and a novel oncogenic signalling pathway in TNBC that may be amenable to therapeutic intervention.
Mathematical Modeling of the Influence of RKIP on the ERK Signaling Pathway
Publisher: Springer Berlin Heidelberg
Date: 2003
Targeting of PYK2 Synergizes with EGFR Antagonists in Basal-like TNBC and Circumvents HER3-Associated Resistance via the NEDD4–NDRG1 Axis
Publisher: American Association for Cancer Research (AACR)
Date: 2017
DOI: 10.1158/0008-5472.CAN-16-1797
Abstract: Triple-negative breast cancer (TNBC) is a highly aggressive, heterogeneous disease with poor prognosis and no effective targeted therapies. EGFR is highly expressed in basal-like TNBC and is considered as a potential therapeutic target. However, EGFR targeting exerts only marginal clinical benefits, possibly due to activation of compensatory signaling pathways, which are frequently associated with HER3 upregulation. Here we show that concomitant targeting of EGFR and the nonreceptor tyrosine kinases PYK2/FAK synergistically inhibits the proliferation of basal-like TNBC cells in vitro and attenuates tumor growth in a mouse xenograft model. Dual targeting of EGFR and PYK2/FAK inhibited complementary key growth and survival pathways mediated by AKT, S6K, STAT3, and ERK1/2 activation. PYK2 inhibition also abrogated HER3 upregulation in response to EGFR antagonists, thereby circumventing HER3-associated drug resistance. Mechanistically, PYK2 inhibition facilitated the proteasomal degradation of HER3 while inducing upregulation of NDRG1 (N-myc downstream regulated 1 gene). NDRG1 enhanced the interaction of HER3 with the ubiquitin ligase NEDD4, while PYK2, which interacts with NEDD4 and HER3, interfered with NEDD4–HER3 binding, suggesting that the PYK2–NDRG1–NEDD4 circuit has a critical role in receptor degradation, drug response, and resistance mechanism. Our studies offer a preclinical proof of concept for a strategy of cotargeting the EGFR and PYK2/FAK kinases to improve TNBC therapy. Cancer Res 77(1) 86–99. ©2016 AACR.
System-level investigation into the regulatory mechanism of the calcineurin/NFAT signaling pathway
Publisher: Elsevier BV
Date: 06-2008
DOI: 10.1016/J.CELLSIG.2008.01.023
Abstract: Calcineurn/nuclear factor of the activated T cell (CaN/NFAT) signaling pathway plays crucial roles in the development of cardiac hypertrophy, Down's syndrome, and autoimmune diseases in response to pathological stimuli. The aim of the present study is to get a system-level understanding on the regulatory mechanism of CaN/NFAT signaling pathway in consideration of the controversial roles of myocyte-enriched calcineurin interacting protein1 (MCIP1) for varying stress stimuli. To this end, we have developed an experimentally validated mathematical model and carried out computer simulations as well as cell-based experiments. Quantitative overexpression and knock-down experiments in C2C12 myoblasts have revealed that MCIP1 functions only as a calcineurin inhibitor. We have also observed a biphasic response of the NFAT activity with increasing stimuli of isoproterenol. Through extensive in silico simulations, we have discovered that the NFAT activity is primarily modulated by ERK5 and MCIP1 under mild isoproterenol stimuli whereas it is mainly modulated by atrogin1 (muscle atrophy F-box protein) under strong isoproterenol stimuli. This study shows that a system-level analysis may help understanding CaN/NFAT signaling-associated disease.
ELECANS - An integrated model development environment for multiscale cancer systems biology
Publisher: Oxford University Press (OUP)
Date: 06-02-2013
DOI: 10.1093/BIOINFORMATICS/BTT063
Abstract: Motivation: Computational multiscale models help cancer biologists to study the spatiotemporal dynamics of complex biological systems and to reveal the underlying mechanism of emergent properties. Results: To facilitate the construction of such models, we have developed a next generation modelling platform for cancer systems biology, termed ‘ELECANS’ (electronic cancer system). It is equipped with a graphical user interface-based development environment for multiscale modelling along with a software development kit such that hierarchically complex biological systems can be conveniently modelled and simulated by using the graphical user interface/software development kit combination. Associated software accessories can also help users to perform post-processing of the simulation data for visualization and further analysis. In summary, ELECANS is a new modelling platform for cancer systems biology and provides a convenient and flexible modelling and simulation environment that is particularly useful for those without an intensive programming background. Availability and implementation: ELECANS, its associated software accessories, demo ex les, documentation and issues database are freely available at sbie.kaist.ac.kr/sub_0204.php Contact: ckh@kaist.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online.
Global redox proteome and phosphoproteome analysis reveals redox switch in Akt
Publisher: Springer Science and Business Media LLC
Date: 02-12-2019
DOI: 10.1038/S41467-019-13114-4
Abstract: Protein oxidation sits at the intersection of multiple signalling pathways, yet the magnitude and extent of crosstalk between oxidation and other post-translational modifications remains unclear. Here, we delineate global changes in adipocyte signalling networks following acute oxidative stress and reveal considerable crosstalk between cysteine oxidation and phosphorylation-based signalling. Oxidation of key regulatory kinases, including Akt, mTOR and AMPK influences the fidelity rather than their absolute activation state, highlighting an unappreciated interplay between these modifications. Mechanistic analysis of the redox regulation of Akt identified two cysteine residues in the pleckstrin homology domain (C60 and C77) to be reversibly oxidized. Oxidation at these sites affected Akt recruitment to the plasma membrane by stabilizing the PIP 3 binding pocket. Our data provide insights into the interplay between oxidative stress-derived redox signalling and protein phosphorylation networks and serve as a resource for understanding the contribution of cellular oxidation to a range of diseases.
A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer
Publisher: Frontiers Media SA
Date: 19-01-2023
DOI: 10.3389/FMOLB.2023.1094321
Abstract: Precision medicine has emerged as an important paradigm in oncology, driven by the significant heterogeneity of in idual patients’ tumour. A key prerequisite for effective implementation of precision oncology is the development of companion biomarkers that can predict response to anti-cancer therapies and guide patient selection for clinical trials and/or treatment. However, reliable predictive biomarkers are currently lacking for many anti-cancer therapies, h ering their clinical application. Here, we developed a novel machine learning-based framework to derive predictive multi-gene biomarker panels and associated expression signatures that accurately predict cancer drug sensitivity. We demonstrated the power of the approach by applying it to identify response biomarker panels for an Hsp90-based therapy in prostate cancer, using proteomic data profiled from prostate cancer patient-derived explants. Our approach employs a rational feature section strategy to maximise model performance, and innovatively utilizes Boolean algebra methods to derive specific expression signatures of the marker proteins. Given suitable data for model training, the approach is also applicable to other cancer drug agents in different tumour settings.
The switching role of i 2-adrenergic receptor signalling in cell survival or death decision of cardiomyocytes
Publisher: Springer Science and Business Media LLC
Date: 17-12-2014
DOI: 10.1038/NCOMMS6777
Abstract: How cell fate (survival or death) is determined and whether such determination depends on the strength of stimulation has remained unclear. In this study, we discover that the cell fate of cardiomyocytes switches from survival to death with the increase of β-adrenergic receptor (β-AR) stimulation. Mathematical simulations combined with biochemical experimentation of β-AR signalling pathways show that the gradual increment of isoproterenol (a non-selective β 1 /β 2 -AR agonist) induces the switching response of Bcl-2 expression from the initial increase followed by a decrease below its basal level. The ERK1/2 and ICER-mediated feed-forward loop is the hidden design principle underlying such cell fate switching characteristics. Moreover, we find that β1-blocker treatment increases the survival effect of β-AR stimuli through the regulation of Bcl-2 expression leading to the resistance to cell death, providing new insight into the mechanism of therapeutic effects. Our systems analysis further suggests a novel potential therapeutic strategy for heart disease.
Cardiac Systems Biology and Parameter Sensitivity Analysis: Intracellular Ca2+ Regulatory Mechanisms in Mouse Ventricular Myocytes
Publisher: Springer Berlin Heidelberg
Date: 2008
DOI: 10.1007/10_2007_093
Abstract: Intracellular Ca(2+) dynamics of cardiac myocytes are regulated by complex mechanisms of a variety of ion channels, transporters, and exchangers. Alterations of these Ca(2+) regulatory components might lead to development of cardiac diseases. To investigate the regulatory mechanisms and hidden Ca(2+) dynamics we use integrative systems analysis. Herein, we briefly summarize cardiac systems biology and, within the context of cardiac systems biology, identify the functional role of key Ca(2+) regulatory proteins and their influence on intracellular Ca(2+) dynamics (i.e., Ca(2+) transient, SR Ca(2+) content, CICR gain, half-decay time) using parameter sensitivity analysis based on an experimentally validated mathematical model of mouse ventricular myocytes. In addition, we analyze the influence of the pacing period (frequency) of a stimulus current since most of the Ca(2+) regulatory proteins react with different timescales. Throughout the parameter sensitivity analysis, we found that alteration of SERCA or LTCC has a more significant effect on the Ca(2+) dynamics than that of RyR or NCX. In particular, for the 70% down-regulation of LTCC, the Ca(2+) influx through LTCC failed to initialize the SR Ca(2+) release and thereby the intracellular Ca(2+) dynamics was dramatically changed. We also found that the pacing period has a significant effect on the half-decay time of the Ca(2+) transients. These findings provide us with new insights into the pathophysiology of cardiac failure as well as the development of new therapeutic strategies.
Dynamic modelling of the PI3K/mTOR signalling network uncovers biphasic dependence of mTORC1 activation on the mTORC2 subunit Sin1
Publisher: Cold Spring Harbor Laboratory
Date: 30-11-2020
DOI: 10.1101/2020.11.30.403774
Abstract: The PI3K/mTOR signalling network critically regulates a broad array of important biological processes, including cell growth, metabolism and autophagy. Dysregulation of PI3K/mTOR signalling is associated with a variety of human diseases, including cancer and metabolic disorders. The mechanistic target of rapamycin (mTOR) is a kinase that functions as a core catalytic subunit in two physically and functionally distinct complexes termed mTOR complex 1 (mTORC1) and mTORC2, which also share other common components such as mLTS8 (also known as GβL) and DEPTOR. Despite being the subject of intensive research, a full picture of how mTORC1/2 assembly and activity are coordinated, and how they are functionally connected remain to be fully characterised. This is due primarily to the complex network wiring, featuring a growing number of intricate feedback loops and post-translational modifications, which require quantitative systems-level approaches to decipher. Here, we integrate predictive computational modelling, in vitro experiments and -omics data analysis to elucidate the dynamic and emergent features of the PI3K/mTOR network behavior. We construct new mechanistic models of the network that encapsulate novel critical mechanistic details, including mTORC1/2 coordination by mLTS8 (de)ubiquitination, and Akt-to-mTORC2 positive feedback loop. Model simulations subsequently confirmed by experimental validation revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit Sin1, which is robust against cell-to-cell variation in protein expression. Furthermore, our results support the essential role of mLST8 in both mTORC1 and 2 activity, and suggest mLST8 could serve as a viable therapeutic target in breast cancer. Overall, our integrated analyses provide fresh systems-level insights into the dynamic behavior of PI3K/mTOR signalling and shed new light on the complexity of this important network. Signalling networks are the key information-processing machineries that underpin the ability of living cells to respond proportionately to extra- (and intra-) cellular cues. The PI3K/mTOR signalling network is one of the most important signalling networks in human cells that regulates cellular response to hormones such as insulin, yet our understanding of the network behaviour remains far from complete. Here, we employed a highly integrative approach that combines predictive mathematical modelling, biological experimentation, and data analysis to gain novel systems-level insights into PI3K/mTOR signalling. We constructed new mathematical models of this complex network incorporating important regulatory mechanisms. In contrary to commonly held views that mTORC2 lies upstream and is a positive regulator of mTORC1, we found that their relationship is highly nonlinear and dose dependent. This finding has major implications for mTORC2-directed anti-cancer strategies as depending on the cellular contexts, blocking mTORC2 may reduce or even enhance mTORC1 activation, the latter could inadvertently blunt the effect of mTORC2 blockade. Furthermore, our results demonstrate that mLST8 is required for the assembly and activity of both mTOR complexes, and suggest mLST8 is a viable therapeutic target in breast cancer, notably breast cancer.
Multiscale Modeling of Tumorigenesis Induced by Mitochondrial Incapacitation in Cell Death
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2011
Systematic Analysis of Network-driven Adaptive Resistance to CDK4/6 and Estrogen Receptor Inhibition using Meta-Dynamic Network Modelling
Publisher: Cold Spring Harbor Laboratory
Date: 25-01-2023
DOI: 10.1101/2023.01.24.525460
Abstract: Drug resistance inevitably emerges during the treatment of cancer by targeted therapy. Adaptive resistance is a major form of drug resistance, wherein the rewiring of protein signalling networks in response to drug perturbation allows the drug-targeted protein’s activity to recover, despite the continuous presence of the drug, enabling the cells to survive/grow. Simultaneously, molecular heterogeneity enables the selection of drug-resistant cancer clones that can survive an initial drug insult, proliferate, and eventually cause disease relapse. Despite their importance, the link between heterogeneity and adaptive resistance, specifically how heterogeneity influences protein signalling dynamics to drive adaptive resistance, remains poorly understood. Here, we have explored the relationship between heterogeneity, protein signalling dynamics and adaptive resistance through the development of a novel modelling technique coined Meta Dynamic Network (MDN) modelling. We use MDN modelling to characterise how heterogeneity influences the drug-response signalling dynamics of the proteins that regulate early cell cycle progression and demonstrate that heterogeneity can robustly facilitate adaptive resistance associated dynamics for key cell cycle regulators. We determined the influence of heterogeneity at the level of both protein interactions and protein expression and show that protein interactions are a much stronger driver of adaptive resistance. Owing to the mechanistic nature of the underpinning ODE framework, we then identified a full spectrum of subnetworks that drive adaptive resistance dynamics in the key early cell cycle regulators. Finally, we show that single-cell dynamic data supports the validity of our MDN modelling technique and a comparison between our predicted resistance mechanisms and known CDK4/6 and Estrogen Receptor inhibitor resistance mechanisms suggests MDN can be deployed to robustly predict network-level resistance mechanisms for novel drugs and additional protein signalling networks.
Investigations Into the Analysis and Modeling of the TNFα-Mediated NF-κB-Signaling Pathway
Publisher: Cold Spring Harbor Laboratory
Date: 2003
DOI: 10.1101/GR.1195703
Abstract: In this study, we propose a system-theoretic approach to the analysis and quantitative modeling of the TNFα-mediated NF-κB-signaling pathway. Tumor necrosis factor α (TNFα) is a potent proinflammatory cytokine that plays an important role in immunity and inflammation, in the control of cell proliferation, differentiation, and apoptosis. To date, there have been numerous approaches to model cellular dynamics. The most prominent uses ordinary differential equations (ODEs) to describe biochemical reactions. This approach can provide us with mathematically well-founded and tractable interpretations regarding pathways, especially those best described by enzyme reactions. This work first introduces a graphical method to intuitively represent the TNFα-mediated NF-κB-signaling pathway and then utilizes ODEs to quantitatively model the pathway. The simulation study shows qualitative validation of the proposed model compared with experimental results for this pathway. The proposed system-theoretic approach is expected to be further applicable to predict the signaling behavior of NF-κB in a quantitative manner for any variation of the ligand, TNFα.
Coupled feedback regulation of nuclear factor of activated T-cells (NFAT) modulates activation-induced cell death of T cells
Publisher: Springer Science and Business Media LLC
Date: 23-07-2019
DOI: 10.1038/S41598-019-46592-Z
Abstract: A properly functioning immune system is vital for an organism’s wellbeing. Immune tolerance is a critical feature of the immune system that allows immune cells to mount effective responses against exogenous pathogens such as viruses and bacteria, while preventing attack to self-tissues. Activation-induced cell death (AICD) in T lymphocytes, in which repeated stimulations of the T-cell receptor (TCR) lead to activation and then apoptosis of T cells, is a major mechanism for T cell homeostasis and helps maintain peripheral immune tolerance. Defects in AICD can lead to development of autoimmune diseases. Despite its importance, the regulatory mechanisms that underlie AICD remain poorly understood, particularly at an integrative network level. Here, we develop a dynamic multi-pathway model of the integrated TCR signalling network and perform model-based analysis to characterize the network-level properties of AICD. Model simulation and analysis show that lified activation of the transcriptional factor NFAT in response to repeated TCR stimulations, a phenomenon central to AICD, is tightly modulated by a coupled positive-negative feedback mechanism. NFAT lification is predominantly enabled by a positive feedback self-regulated by NFAT, while opposed by a NFAT-induced negative feedback via Carabin. Furthermore, model analysis predicts an optimal therapeutic window for drugs that help minimize proliferation while maximize AICD of T cells. Overall, our study provides a comprehensive mathematical model of TCR signalling and model-based analysis offers new network-level insights into the regulation of activation-induced cell death in T cells.
Control of Glucocorticoid Receptor Levels by PTEN Establishes a Failsafe Mechanism for Tumor Suppression
Publisher: Elsevier BV
Date: 10-2020
Systematic Analysis of Network-driven Adaptive Resistance to CDK4/6 and Estrogen Receptor Inhibition using Meta-Dynamic Network Modelling
Publisher: eLife Sciences Publications, Ltd
Date: 09-2023
Unveiling hidden dynamics of hippo signalling
Publisher: MDPI AG
Date: 05-08-2016
DOI: 10.3390/GENES7080044
MLK3 is part of a feedback mechanism that regulates different cellular responses to reactive oxygen species
Publisher: American Association for the Advancement of Science (AAAS)
Date: 03-06-2014
DOI: 10.1126/SCISIGNAL.2005260
Abstract: Computational analysis of signaling networks reveals how cells can choose between proliferation and death in response to oxidative stress.
Feedback, Crosstalk and Competition: Ingredients for Emergent Non-Linear Behaviour in the PI3K/mTOR Signalling Network
Publisher: MDPI AG
Date: 28-06-2021
DOI: 10.3390/IJMS22136944
Abstract: The PI3K/mTOR signalling pathway plays a central role in the governing of cell growth, survival and metabolism. As such, it must integrate and decode information from both external and internal sources to guide efficient decision-making by the cell. To facilitate this, the pathway has evolved an intricate web of complex regulatory mechanisms and elaborate crosstalk with neighbouring signalling pathways, making it a highly non-linear system. Here, we describe the mechanistic biological details that underpin these regulatory mechanisms, covering a multitude of negative and positive feedback loops, feed-forward loops, competing protein interactions, and crosstalk with major signalling pathways. Further, we highlight the non-linear and dynamic network behaviours that arise from these regulations, uncovered through computational and experimental studies. Given the pivotal role of the PI3K/mTOR network in cellular homeostasis and its frequent dysregulation in pathologies including cancer and diabetes, a coherent and systems-level understanding of the complex regulation and consequential dynamic signalling behaviours within this network is imperative for advancing biology and development of new therapeutic approaches.
Related Organisations
Gwangju Institute Of Science And Technology
Location: Korea, Republic of
Korea Advanced Institute Of Science And Technology
Location: Korea, Republic of
Related Funding Activities
Discovery Projects - Grant ID: DP220103638
Start Date: 05-2022
End Date: 05-2025
Amount: $602,000.00
Funder: Australian Research Council
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