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Illustration of the Signaling Pathways and Interactions Initiated by TNF-R1. Ligand stimulated TNF-R1 activates two major signaling pathways, pro- and anti-apoptotic cellular responses (red and blue background, respectively). The ligand-receptor interaction and signal complex formation is outlined in the green area.
Source publication
Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation,...
Contexts in source publication
Context 1
... reaction network considered here is schematically depicted in Figure 1 and consists of three modules: the TNF-R1 receptor signaling complex (green background), the NF-B pathway (blue background) and the caspase activation pathway (red background). The pro-and anti- apoptotic TNF-R1 signaling pathways are internally and mutually regulated via feedback loops leading to a highly complex and dynamic behavior. ...Context 2
... gain further insight into the regulatory mechanisms of this system, we first developed a mechanistic single cell model of TNF induced pro and anti-apoptotic signaling describing the signal transduc- tion within a median cell. The model structure corre- sponds to the pathway shown in Figure 1. See Additional File 2 for a detailed description of the model and Additional File 3 for its SBML code. ...Similar publications
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Citations
... On the other hand, as Figures 2b and 2c show, the macro-variables y 1 , y 2 , y 3 have much faster dynamics and reach the steady state after less than one second. In this subsection, we consider a model designed in [34] in order to study the sensitivity of the apoptosis (programmed cell death) to the TNF (tumor necrosis factor) stimulation. The overall model involves 47 chemical species and numerous interactions between them schematically described in [34, Figure 1]. ...
Dynamical models described by ordinary differential equations (ODEs) are a fundamental tool in the sciences and engineering. Exact reduction aims at producing a lower-dimensional model in which each macro-variable can be directly related to the original variables, and it is thus a natural step towards the model's formal analysis and mechanistic understanding. We present an algorithm which, given a polynomial ODE model, computes a longest possible chain of exact linear reductions of the model such that each reduction refines the previous one, thus giving a user control of the level of detail preserved by the reduction. This significantly generalizes over the existing approaches which compute only the reduction of the lowest dimension subject to an approach-specific constraint. The algorithm reduces finding exact linear reductions to a question about representations of finite-dimensional algebras. We provide an implementation of the algorithm, demonstrate its performance on a set of benchmarks, and illustrate the applicability via case studies. Our implementation is freely available at https://github.com/x3042/ExactODEReduction.jl
... This could be attributed to not considering pJNK, which is a crucial Caspase3 regulator, as shown by our predictions (Fig 5A). While arresting the pro-survival pathways is expected to alter the cell-death decisions [82,83], our study demonstrates that a semi-quantitative correlation establishes the connection between the Caspase3 dynamics and the apoptotic response ( Fig 5B). The premise of this correlation is to relate the Caspase3 levels over a range of time duration represented by accumulated levels to the phenotypic response. ...
Tumor necrosis factor alpha (TNFα) is a well-known modulator of apoptosis by maintaining a balance between proliferation and cell-death in normal cells. Cancer cells often evade apoptotic response following TNFα stimulation by altering signaling cross-talks. Thus, varying the extent of signaling cross-talk could enable optimal TNFα mediated apoptotic dynamics. Herein, we use an experimental data-driven mathematical modeling to quantitate the extent of synergistic signaling cross-talk between the intracellular entities phosphorylated JNK (pJNK) and phosphorylated AKT (pAKT) that orchestrate the phenotypic apoptosis level by modulating the activated Caspase3 dynamics. Our study reveals that this modulation is orchestrated by the distinct dynamic nature of the synergism at early and late phases. We show that this synergism in signal flow is governed by branches originating from either TNFα receptor and NFκB, which facilitates signaling through survival pathways. We demonstrate that the experimentally quantified apoptosis levels semi-quantitatively correlates with the model simulated Caspase3 transients. Interestingly, perturbing pJNK and pAKT transient dynamics fine-tunes this accumulated Caspase3 guided apoptotic response. Thus, our study offers useful insights for identifying potential targeted therapies for optimal apoptotic response.
... Several mathematical models have been published for NFκB signaling as well. Some of these mathematical models have mostly focused on downstream events of the pathway, replacing the dynamics of IKKβ with an assumed activation profile [22][23][24], while other models have incorporated a more explicit account of upstream processes [25][26][27]. Mathematical modeling was also used to analyze the NFκB pathway as an information transmission channel. This work has shown that the pathway can encode approximately 1 bit of information at most, i.e., whether the extracellular stimulus is present or absent [28,29]. ...
Background
Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.
Methods
We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.
Results
In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation.
Conclusions
Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter.
... Schlatter et al. have proposed a Boolean model of the processes of apoptosis, which considers several stimuli [56]. Schliemann et al. have merged two existing models to an ODE model with pro-and anti-apoptotic responses of TNFR1 signaling [57]. Melas et al. have introduced a hybrid model, covering the stimulation of seven receptors and 22 cytokine stimuli in immunological pathways [58]. ...
The paper describes a mathematical model of the molecular switches of cell survival, apoptosis, and necroptosis in cellular signaling pathways initiated by tumor necrosis factor 1. Based on experimental findings in the literature, we constructed a Petri net model based on detailed molecular reactions of the molecular players, protein complexes, post-translational modifications, and cross talk. The model comprises 118 biochemical entities, 130 reactions, and 299 edges. We verified the model by evaluating invariant properties of the system at steady state and by in silico knockout analysis. Applying Petri net analysis techniques, we found 279 pathways, which describe signal flows from receptor activation to cellular response, representing the combinatorial diversity of functional pathways.120 pathways steered the cell to survival, whereas 58 and 35 pathways led to apoptosis and necroptosis, respectively. For 65 pathways, the triggered response was not deterministic and led to multiple possible outcomes. We investigated the in silico knockout behavior and identified important checkpoints of the TNFR1 signaling pathway in terms of ubiquitination within complex I and the gene expression dependent on NF-κB, which controls the caspase activity in complex II and apoptosis induction. Despite not knowing enough kinetic data of sufficient quality, we estimated system’s dynamics using a discrete, semi-quantitative Petri net model.
... Several mathematical models have been published for NFκB signaling as well. Some of these mathematical models have mostly focused on downstream events of the pathway, replacing the dynamics of IKKβ with an assumed activation profile (22)(23)(24), while other models have incorporated a more explicit account of upstream processes (25)(26)(27). Mathematical modeling was also used to analyze signal transduction capabilities of the NFκB pathway used by viewing it as an information transmission channel. This work has shown that the pathway can encode approximately 1 bit of information at most, i.e., whether the extracellular stimulus is present or absent (28,29). ...
Background
Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The strength and dynamics of signaling events initiated upon antigen binding depend on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.
Methods
We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CAR-4-1BB. We first performed a global sensitivity analysis on our model to quantify the impact of kinetic parameters and initial protein concentrations. We ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and used Kraskov’s algorithm to quantify the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.
Results
We determined that in response to a wide range of antigen concentrations, the magnitude of the transient peak in the nuclear concentration of NFκB varies significantly, while the timing of this peak is relatively consistent. Our global sensitivity analysis showed that the model is robust to variations in parameter values, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. Next, we found that overexpressing NEMO and disabling IKKβ deactivation are predicted to increase the mutual information between antigen levels and NFκB activation.
Conclusions
Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CAR-4-1BB cells to the antigen concentrations they are likely to encounter.
... If caspase 8 is absent or inactivated, kinase-active RIPK1 recruits and activates RIPK3, resulting in the formation of the necrosome and further execution of necroptosis via membrane permeabilization (Vanden Berghe et al., 2014;Grootjans et al., 2017). Caspases and their inhibitors are pivotal elements in deciding the cell's fate after TNF-α/TNFR1 triggering, along with the engagement of NF-κB-mediated anti-apoptotic signaling pathways, which are able to delay the time of death (Schliemann et al., 2011). ...
Newly discovered anti-cancer immunotherapies, such as immune checkpoint inhibitors and chimeric antigen receptor T cells, focus on spurring the anti-tumor effector T cell (Teff) response. Although such strategies have already demonstrated a sustained beneficial effect in certain malignancies, a substantial proportion of treated patients does not respond. CD4+FOXP3+ regulatory T cells (Tregs), a suppressive subset of T cells, can impair anti-tumor responses and reduce the efficacy of currently available immunotherapies. An alternative view that has emerged over the last decade proposes to tackle this immune brake by targeting the suppressive action of Tregs on the anti-tumoral response. It was recently demonstrated that the tumor necrosis factor alpha (TNF-α) tumor necrosis factor receptor 2 (TNFR2) is critical for the phenotypic stabilization and suppressive function of human and mouse Tregs. The broad non-specific effects of TNF-α infusion in patients initially led clinicians to abandon this signaling pathway as first-line therapy against neoplasms. Previously unrecognized, TNFR2 has emerged recently as a legitimate target for anti-cancer immune checkpoint therapy. Considering the accumulation of pre-clinical data on the role of TNFR2 and clinical reports of TNFR2+ Tregs and tumor cells in cancer patients, it is now clear that a TNFR2-centered approach could be a viable strategy, once again making the TNF-α pathway a promising anti-cancer target. Here, we review the role of the TNFR2 signaling pathway in tolerance and the equilibrium of T cell responses and its connections with oncogenesis. We analyze recent discoveries concerning the targeting of TNFR2 in cancer, as well as the advantages, limitations, and perspectives of such a strategy.
... Hence, anti-TNF therapies is widely used in clinic as an appropriate way in the management of UC (Lawrance, 2015). Especially, TNF signaling pathway exerts a broad spectrum of activities, including regulation of inflammation and the migration of intestinal epithelial cells (Armaka et al., 2008;Schliemann et al., 2011), and it has been confirmed that ErbB signaling can be activated by the phosphorylation of TNF-α-induced receptor, which modulates the intestinal wound healing of inflammatory bowel disease (Frey et al., 2009). And PI3K/AKT signaling pathway is active in cells infiltrating inflamed human colon tissue via the participation of PTEN, GSK3B and mTOR, which may lead to over-transcription of downstream target genes, proliferation of intestinal epithelial cells, and even dysplasia and cancerization (Castellano and Downward, 2011;Matsuda et al., 2013;Chen et al., 2015). ...
Ulcerative colitis (UC) is a chronic inflammatory bowel disease, and Gegen Qinlian Decoction (GQD), a Chinese botanical formula, has exhibited beneficial efficacy against UC. However, the mechanisms underlying the effect of GQD still remain to be elucidated. In this study, network pharmacology approach and molecular docking in silico were applied to uncover the potential multicomponent synergetic effect and molecular mechanisms. The targets of ingredients in GQD were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM) database, while the UC targets were retrieved from Genecards, therapeutic target database (TTD) and Online Mendelian Inheritance in Man (OMIM) database. The topological parameters of Protein-Protein Interaction (PPI) data were used to screen the hub targets in the network. The possible mechanisms were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was used to verify the binding affinity between the active compounds and hub targets. Network pharmacology analysis successfully identified 77 candidate compounds and 56 potential targets. The targets were further mapped to 20 related pathways to construct a compound-target-pathway network and an integrated network of GQD treating UC. Among these pathways, PI3K-AKT, HIF-1, VEGF, Ras, and TNF signaling pathways may exert important effects in the treatment of UC via inflammation suppression and anti-carcinogenesis. In the animal experiment, treatment with GQD and sulfasalazine (SASP) both ameliorated inflammation in UC. The proinflammatory cytokines (TNF-α, IL-1β, and IL-6) induced by UC were significantly decreased by GQD and SASP. Moreover, the protein expression of EGFR, PI3K, and phosphorylation of AKT were reduced after GQD and SASP treatment, and there was no significance between the GQD group and SASP group. Our study systematically dissected the molecular mechanisms of GQD on the treatment of UC using network pharmacology, as well as uncovered the therapeutic effects of GQD against UC through ameliorating inflammation via downregulating EGFR/PI3K/AKT signaling pathway and the pro-inflammatory cytokines such as TNF-α, IL-1β and IL-6.
... A global sensitivity analysis uncovered that concentrations of Caspase-8 and Caspase-3, and their respective inhibitors FLIP, BAR, and XIAP are key elements for deciding the cell's fate. In contrast, NFκB-mediated anti-apoptotic signaling pathways delayed the time of death (Schliemann et al., 2011). When caspase 8 is absent or inactivated, kinase-active RIPK1 recruits and activates RIPK3, resulting in the formation of the necrosome. ...
Tumor necrosis factor (TNF) is a central regulator of immunity. Due to its dominant pro-inflammatory effects, drugs that neutralize TNF were developed and are clinically used to treat inflammatory and autoimmune diseases, such as rheumatoid arthritis, inflammatory bowel disease and psoriasis. However, despite their clinical success the use of anti-TNF drugs is limited, in part due to unwanted, severe side effects and in some diseases its use even is contraindicative. With gaining knowledge about the signaling mechanisms of TNF and the differential role of the two TNF receptors (TNFR), alternative therapeutic concepts based on receptor selective intervention have led to the development of novel protein therapeutics targeting TNFR1 with antagonists and TNFR2 with agonists. These antibodies and bio-engineered ligands are currently in preclinical and early clinical stages of development. Preclinical data obtained in different disease models show that selective targeting of TNFRs has therapeutic potential and may be superior to global TNF blockade in several disease indications.
... Upon secretion, TNFα binds to the TNFα receptor (TNFR) to activate the TNFα signaling pathway. 52,53 Interestingly, the TNFα-TNFR signaling pathway induces two divergent cellular responses: apoptosis and cell-survival. 53 Specifically, the activated TNFR initiates the canonical NFκB pathway that promotes the transcription of a number of antiapoptotic genes such as X-linked inhibitor of apoptosis protein and FLICE-like inhibitory protein. ...
... 52,53 Interestingly, the TNFα-TNFR signaling pathway induces two divergent cellular responses: apoptosis and cell-survival. 53 Specifically, the activated TNFR initiates the canonical NFκB pathway that promotes the transcription of a number of antiapoptotic genes such as X-linked inhibitor of apoptosis protein and FLICE-like inhibitory protein. 53 On the other hand, the activated TNFR also induces the proapoptotic pathway through the activation of caspases. ...
... 53 Specifically, the activated TNFR initiates the canonical NFκB pathway that promotes the transcription of a number of antiapoptotic genes such as X-linked inhibitor of apoptosis protein and FLICE-like inhibitory protein. 53 On the other hand, the activated TNFR also induces the proapoptotic pathway through the activation of caspases. 53 The mechanisms of coactivation of pro-and anti-apoptotic pathways by TNFα were modeled by Chaves et al., 51 which is illustrated in Figure 2. ...
Cells in a genetically homogeneous cell‐population exhibit a significant degree of heterogeneity in their responses to an external stimulus. To understand origins and importance of this heterogeneity, individual‐based population model (IBPM), where parameters follow probability density functions (PDFs) instead of being constants, has been previously developed. However, parameter identification for an IBPM is challenging as estimating PDFs is computationally expensive. Also, because of experimental limitations and nonlinearity of models, not all parameters' PDFs are identifiable. Motivated by the above considerations, a new methodology is proposed in this study. First, a subset of parameters whose PDFs is identifiable are determined through sensitivity analysis, and only these PDFs are estimated. Second, an artificial neural network model is developed to find an empirical relation between these parameter and output PDFs to reduce computational costs of the parameter identification. The proposed approach is validated by estimating PDFs of parameters of a tumor necrosis factor‐α signaling model.
... The origin of this heterogeneity is generally unknown but may be related to cell cycle, microenvironmental factors, previous signaling events, etc. Introducing cell-to-cell variability in signaling response in a computational model has been approached in different ways. Ideally, the parameter values should be drawn from a concentration distribution established experimentally using techniques such as flow cytometry (20,(31)(32)(33)(34)(35). However, most often, it is not practical to quantify distribution for each signaling component in the pathway. ...
Mammalian cells respond in a variable manner when provided with physiological pulses of ligand, such as low concentrations of acetylcholine present for just tens of seconds or TNFα for just tens of minutes. For a two-pulse stimulation, some cells respond to both pulses, some do not respond, and yet others respond to only one or the other pulse. Are these different response patterns the result of the small number of ligands being able to only stochastically activate the pathway at random times or an output pattern from a deterministic algorithm responding differently to different stimulation intervals? If the response is deterministic in nature, what parameters determine whether a response is generated or skipped? To answer these questions, we developed a two-pulse test that utilizes different rest periods between stimulation pulses. This “rest-period test” revealed that cells skip responses predictably as the rest period is shortened. By combining these experimental results with a mathematical model of the pathway, we further obtained mechanistic insight into potential sources of response variability. Our analysis indicates that in both intracellular calcium and NFκB signaling, response variability is consistent with extrinsic noise (cell-to-cell variability in protein levels), a short-term memory of stimulation, and high Hill coefficient processes. Furthermore, these results support recent works that have emphasized the role of deterministic processes for explaining apparently stochastic cellular response variability and indicate that even weak stimulations likely guide mammalian cells to appropriate fates rather than leaving outcomes to chance. We envision that the rest-period test can be applied to other signaling pathways to extract mechanistic insight.
