Integrating signals from the T-cell receptor and the interleukin-2 receptor

IL-2-mediated hepatotoxicity: knowledge gap identification based on the irAOP concept

Drug-induced hepatotoxicity constitutes a major reason for non-approval and post-marketing withdrawal of pharmaceuticals. In many cases, preclinical models lack predictive capacity for hepatic damage in humans. A vital concern is the integration of immune system effects in preclinical safety assessment. The immune-related Adverse Outcome Pathway (irAOP) approach, which is applied within the Immune Safety Avatar (imSAVAR) consortium, presents a novel method to understand and predict immune-mediated adverse events elicited by pharmaceuticals and thus targets this issue. It aims to dissect the molecular mechanisms involved and identify key players in drug-induced side effects. As irAOPs are still in their infancy, there is a need for a model irAOP to validate the suitability of this tool. For this purpose, we developed a hepatotoxicity-based model irAOP for recombinant human IL-2 (aldesleukin). Besides producing durable therapeutic responses against renal cell carcinoma and metastatic melanoma, the boosted immune activation upon IL-2 treatment elicits liver damage. The availability of extensive data regarding IL-2 allows both the generation of a comprehensive putative irAOP and to validate the predictability of the irAOP with clinical data. Moreover, IL-2, as one of the first cancer immunotherapeutics on the market, is a blueprint for various biological and novel treatment regimens that are under investigation today. This review provides a guideline for further irAOP-directed research in immune-mediated hepatotoxicity.

Simulating the Evolution of Signaling Signatures during CART-Cell - Tumor Cell Interactions

Immunotherapies have been proven to have significant therapeutic efficacy in the treatment of cancer. The last decade has seen adoptive cell therapies, such as chimeric antigen receptor T-cell (CART-cell) therapy, gain FDA approval against specific cancers. Additionally, there are numerous clinical trials ongoing investigating additional designs and targets. Nevertheless, despite the excitement and promising potential of CART-cell therapy, response rates to therapy vary greatly between studies, patients, and cancers. There remains an unmet need to develop computational frameworks that more accurately predict CART-cell function and clinical efficacy. Here we present a coarse-grained model simulated with logical rules that demonstrates the evolution of signaling signatures following the interaction between CART-cells and tumor cells and allows for in silico based prediction of CART-cell functionality prior to experimentation.

A reengineered common chain cytokine augments CD8+ T cell–dependent immunotherapy

Cytokine therapy is limited by undesirable off-target side effects as well as terminal differentiation and exhaustion of chronically stimulated T cells. Here, we describe the signaling properties of a potentially unique cytokine by design, where T cell surface binding and signaling are separated between 2 different families of receptors. This fusion protein cytokine, called OMCPmutIL-2, bound with high affinity to the cytotoxic lymphocyte-defining immunoreceptor NKG2D but signaled through the common γ chain cytokine receptor. In addition to precise activation of cytotoxic T cells due to redirected binding, OMCPmutIL-2 resulted in superior activation of both human and murine CD8⁺ T cells by improving their survival and memory cell generation and decreasing exhaustion. This functional improvement was the direct result of altered signal transduction based on the reorganization of surface membrane lipid rafts that led to Janus kinase-3–mediated phosphorylation of the T cell receptor rather than STAT/AKT signaling intermediates. This potentially novel signaling pathway increased CD8⁺ T cell response to low-affinity antigens, activated nuclear factor of activated T cells transcription factors, and promoted mitochondrial biogenesis. OMCPmutIL-2 thus outperformed other common γ chain cytokines as a catalyst for in vitro CD8⁺ T cell expansion and in vivo CD8⁺ T cell–based immunotherapy.

Mass Spectrometry-Based Phosphoproteomics and Systems Biology: Approaches to Study T Lymphocyte Activation and Exhaustion

T lymphocytes respond to extracellular cues and recognize and clear foreign bodies. These functions are tightly regulated by receptor-mediated intracellular signal transduction pathways and phosphorylation cascades resulting in rewiring of transcription, cell adhesion, and metabolic pathways, which leads to changes in downstream effector functions including cytokine secretion and target-cell killing. Given that these pathways become dysregulated in chronic diseases such as cancer, auto-immunity, diabetes, and persistent infections, mapping T cell signaling dynamics in normal and pathological states is central to understanding and modulating immune system behavior. Despite recent advances, there remains much to be learned from the study of T cell signaling at a systems level. The application of global phospho-proteomic profiling technology has the potential to provide unprecedented insights into the molecular networks that govern T cell function. These include capturing the spatiotemporal dynamics of the T cell responses as an ensemble of interacting components, rather than a static view at a single point in time. In this review, we describe innovative experimental approaches to study signaling mechanisms in the TCR, co-stimulatory receptors, synthetic signaling molecules such as chimeric antigen receptors, inhibitory receptors, and T cell exhaustion. Technical advances in mass spectrometry and systems biology frameworks are emphasized as these are poised to identify currently unknown functional relationships and dependencies to create causal predictive models that expand from the traditional narrow reductionist lens of singular components in isolation.

Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis

Background

Multiple sclerosis (MS) is a major health problem, leading to a significant disability and patient suffering. Although chronic activation of the immune system is a hallmark of the disease, its pathogenesis is poorly understood, while current treatments only ameliorate the disease and may produce severe side effects.

Methods

Here, we applied a network-based modeling approach based on phosphoproteomic data to uncover the differential activation in signaling wiring between healthy donors, untreated patients, and those under different treatments. Based in the patient-specific networks, we aimed to create a new approach to identify drug combinations that revert signaling to a healthy-like state. We performed ex vivo multiplexed phosphoproteomic assays upon perturbations with multiple drugs and ligands in primary immune cells from 169 subjects (MS patients, n=129 and matched healthy controls, n=40). Patients were either untreated or treated with fingolimod, natalizumab, interferon-β, glatiramer acetate, or the experimental therapy epigallocatechin gallate (EGCG). We generated for each donor a dynamic logic model by fitting a bespoke literature-derived network of MS-related pathways to the perturbation data. Last, we developed an approach based on network topology to identify deregulated interactions whose activity could be reverted to a “healthy-like” status by combination therapy. The experimental autoimmune encephalomyelitis (EAE) mouse model of MS was used to validate the prediction of combination therapies.

Results

Analysis of the models uncovered features of healthy-, disease-, and drug-specific signaling networks. We predicted several combinations with approved MS drugs that could revert signaling to a healthy-like state. Specifically, TGF-β activated kinase 1 (TAK1) kinase, involved in Transforming growth factor β-1 proprotein (TGF-β), Toll-like receptor, B cell receptor, and response to inflammation pathways, was found to be highly deregulated and co-druggable with all MS drugs studied. One of these predicted combinations, fingolimod with a TAK1 inhibitor, was validated in an animal model of MS.

Conclusions

Our approach based on donor-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00925-8.

GATA3 induces mitochondrial biogenesis in primary human CD4+ T cells during DNA damage

GATA3 is as a lineage-specific transcription factor that drives the differentiation of CD4⁺ T helper 2 (Th2) cells, but is also involved in a variety of processes such as immune regulation, proliferation and maintenance in other T cell and non-T cell lineages. Here we show a mechanism utilised by CD4⁺ T cells to increase mitochondrial mass in response to DNA damage through the actions of GATA3 and AMPK. Activated AMPK increases expression of PPARG coactivator 1 alpha (PPARGC1A or PGC1α protein) at the level of transcription and GATA3 at the level of translation, while DNA damage enhances expression of nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2). PGC1α, GATA3 and NRF2 complex together with the ATR to promote mitochondrial biogenesis. These findings extend the pleotropic interactions of GATA3 and highlight the potential for GATA3-targeted cell manipulation for intervention in CD4⁺ T cell viability and function after DNA damage.

GATA3 has been considered to be primarily associated with CD4⁺ Th2 cell function. Using CD4⁺ effector memory that re-express CD45RA (EMRA) T cells the authors show that in response to DNA damage GATA3 can regulate increase of mitochondrial mass and biogenesis involving AMPK.

TNF-α and IL-1β sensitize human MSC for IFN-γ signaling and enhance neutrophil recruitment

During inflammatory processes, tissue environmental cues are influencing the immunoregulatory properties of tissue-resident mesenchymal stem/stromal cells (MSC). In this study, we elucidated one of the molecular and cellular responses of human MSC exposed to combinations of inflammatory cytokines. We showed that during multi-cytokine priming by TNF-α, IL-1β, and IFN-γ, IL-1β further augmented the well-established immunoregulatory activity induced by TNF-α/IFN-γ. On the molecular level, TNF-α and IL-1β enhanced the expression of IFN-γ receptor (IFN-γR) via NF 'kappa-light-chain-enhancer' of activated B-cells (NF-κΒ) signaling. In turn, enhanced responsiveness to IFN-γ stimulation activated STAT5 and p38-MAPK signaling. This molecular feedback resulted in an increased IL-8 release and augmented recruitment of polymorphonuclear granulocytes (PMN). Our study suggests the possibility that responses of MSC to multi-cytokine priming regimens may be exploited therapeutically to fine-tune inflammatory activity in tissues. This study elucidates molecular mechanisms underlying the immunological priming of mesenchymal stromal cells (MSC) and their interaction with neutrophils.

A mathematical model of combined CD8 T cell costimulation by 4-1BB (CD137) and OX40 (CD134) receptors

Combined agonist stimulation of the TNFR costimulatory receptors 4-1BB (CD137) and OX40(CD134) has been shown to generate supereffector CD8 T cells that clonally expand to greater levels, survive longer, and produce a greater quantity of cytokines compared to T cells stimulated with an agonist of either costimulatory receptor individually. In order to understand the mechanisms for this effect, we have created a mathematical model for the activation of the CD8 T cell intracellular signaling network by mono- or dual-costimulation. We show that supereffector status is generated via downstream interacting pathways that are activated upon engagement of both receptors, and in silico simulations of the model are supported by published experimental results. The model can thus be used to identify critical molecular targets of T cell dual-costimulation in the context of cancer immunotherapy.

Coupled feedback regulation of nuclear factor of activated T-cells (NFAT) modulates activation-induced cell death of T cells

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 amplified 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 amplification 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.

Akt and STAT5 mediate naïve human CD4+ T-cell early metabolic response to TCR stimulation

Metabolic pathways that regulate T-cell function show promise as therapeutic targets in diverse diseases. Here, we show that at rest cultured human effector memory and central memory CD4+ T-cells have elevated levels of glycolysis and oxidative phosphorylation (OXPHOS), in comparison to naïve T-cells. Despite having low resting metabolic rates, naive T-cells respond to TCR stimulation with robust and rapid increases in glycolysis and OXPHOS. This early metabolic switch requires Akt activity to support increased rates of glycolysis and STAT5 activity for amino acid biosynthesis and TCA cycle anaplerosis. Importantly, both STAT5 inhibition and disruption of TCA cycle anaplerosis are associated with reduced IL-2 production, demonstrating the functional importance of this early metabolic program. Our results define STAT5 as a key node in modulating the early metabolic program following activation in naive CD4+ T-cells and in turn provide greater understanding of how cellular metabolism shapes T-cell responses.

The Taishan Robinia pseudoacacia polysaccharides enhance immune effects of rabbit haemorrhagic disease virus inactivated vaccines

Robinia pseudoacacia flower, a common component in traditional Chinese medicine, has long been well-known for its high pharmaceutical value. This study aimed to assess the immunopotentiating effects of Taishan Robinia Pseudoacacia polysaccharides (TRPPS) in rabbits inoculated with a rabbit haemorrhagic disease virus (RHDV) inactivated vaccine. The rabbits were administered with the RHDV vaccine in conjunction with varying concentrations of TRPPS, and their blood samples were collected at different time points to analyze the ratio and number of blood lymphocytes. In addition, sera were prepared and analyzed to determine the overall antibody titer and the level of IL-2, a cytokine commonly used as an indicator of immune activity. The various TRPPS-supplemented vaccines were shown to be more effective in enhancing the immune functions of the inoculated rabbits compared to their polysaccharide-free counterpart, with 200 mg/mL of TRPPS exhibiting the most pronounced benefits that were comparable to those of propolis. In addition, the TRPPS-supplemented RHDV inactivated vaccines could significantly improve the survival rates of the immunized rabbits against RHDV infection. Our studies offered convincing experimental evidence for the development of TRPPS as a new type of plant-derived immunopotentiator.

Third-Kind Encounters in Biomedicine: Immunology Meets Mathematics and Informatics to Become Quantitative and Predictive

The understanding of the immune response is right now at the center of biomedical research. There are growing expectations that immune-based interventions will in the midterm provide new, personalized, and targeted therapeutic options for many severe and highly prevalent diseases, from aggressive cancers to infectious and autoimmune diseases. To this end, immunology should surpass its current descriptive and phenomenological nature, and become quantitative, and thereby predictive.Immunology is an ideal field for deploying the tools, methodologies, and philosophy of systems biology, an approach that combines quantitative experimental data, computational biology, and mathematical modeling. This is because, from an organism-wide perspective, the immunity is a biological system of systems, a paradigmatic instance of a multi-scale system. At the molecular scale, the critical phenotypic responses of immune cells are governed by large biochemical networks, enriched in nested regulatory motifs such as feedback and feedforward loops. This network complexity confers them the ability of highly nonlinear behavior, including remarkable examples of homeostasis, ultra-sensitivity, hysteresis, and bistability. Moving from the cellular level, different immune cell populations communicate with each other by direct physical contact or receiving and secreting signaling molecules such as cytokines. Moreover, the interaction of the immune system with its potential targets (e.g., pathogens or tumor cells) is far from simple, as it involves a number of attack and counterattack mechanisms that ultimately constitute a tightly regulated multi-feedback loop system. From a more practical perspective, this leads to the consequence that today's immunologists are facing an ever-increasing challenge of integrating massive quantities from multi-platforms.In this chapter, we support the idea that the analysis of the immune system demands the use of systems-level approaches to ensure the success in the search for more effective and personalized immune-based therapies.

Gene expression profiling in preterm infants: new aspects of bronchopulmonary dysplasia development

Rationale

Bronchopulmonary dysplasia is one of the most serious complications observed in premature infants. Thanks to microarray technique, expression of nearly all human genes can be reliably evaluated.

Objective

To compare whole genome expression in the first month of life in groups of infants with and without bronchopulmonary dysplasia.

Methods

111 newborns were included in the study. The mean birth weight was 1029g (SD:290), and the mean gestational age was 27.8 weeks (SD:2.5). Blood samples were drawn from the study participants on the 5th, 14th and 28th day of life. The mRNA samples were evaluated for gene expression with the use of GeneChip® Human Gene 1.0 ST microarrays. The infants were divided into two groups: bronchopulmonary dysplasia (n=68) and control (n=43).

Results

Overall 2086 genes were differentially expressed on the day 5, only 324 on the day 14 and 3498 on the day 28. Based on pathway enrichment analysis we found that the cell cycle pathway was up-regulated in the bronchopulmonary dysplasia group. The activation of this pathway does not seem to be related with the maturity of the infant. Four pathways related to inflammatory response were continuously on the 5^th, 14^th and 28^th day of life down-regulated in the bronchopulmonary dysplasia group. However, the expression of genes depended on both factors: immaturity and disease severity. The most significantly down-regulated pathway was the T cell receptor signaling pathway.

Conclusion

The results of the whole genome expression study revealed alteration of the expression of nearly 10% of the genome in bronchopulmonary dysplasia patients.

Dynamics of influenza virus and human host interactions during infection and replication cycle

The replication and life cycle of the influenza virus is governed by an intricate network of intracellular regulatory events during infection, including interactions with an even more complex system of biochemical interactions of the host cell. Computational modeling and systems biology have been successfully employed to further the understanding of various biological systems, however, computational studies of the complexity of intracellular interactions during influenza infection is lacking. In this work, we present the first large-scale dynamical model of the infection and replication cycle of influenza, as well as some of its interactions with the host's signaling machinery. Specifically, we focus on and visualize the dynamics of the internalization and endocytosis of the virus, replication and translation of its genomic components, as well as the assembly of progeny virions. Simulations and analyses of the models dynamics qualitatively reproduced numerous biological phenomena discovered in the laboratory. Finally, comparisons of the dynamics of existing and proposed drugs, our results suggest that a drug targeting PB1:PA would be more efficient than existing Amantadin/Rimantaine or Zanamivir/Oseltamivir.

Bio-logic builder: a non-technical tool for building dynamical, qualitative models

Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized “bio-logic” modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.

TCR-mediated Erk activation does not depend on Sos and Grb2 in peripheral human T cells

Sos proteins are ubiquitously expressed activators of Ras. Lymphoid cells also express RasGRP1, another Ras activator. Sos and RasGRP1 are thought to cooperatively control full Ras activation upon T-cell receptor triggering. Using RNA interference, we evaluated whether this mechanism operates in primary human T cells. We found that T-cell antigen receptor (TCR)-mediated Erk activation requires RasGRP1, but not Grb2/Sos. Conversely, Grb2/Sos—but not RasGRP1—are required for IL2-mediated Erk activation. Thus, RasGRP1 and Grb2/Sos are insulators of signals that lead to Ras activation induced by different stimuli, rather than cooperating downstream of the TCR.

Meeting report: Signal transduction meets systems biology

In the 21^st century, systems-wide analyses of biological processes are getting more and more realistic. Especially for the in depth analysis of signal transduction pathways and networks, various approaches of systems biology are now successfully used. The EU FP7 large integrated project SYBILLA (Systems Biology of T-cell Activation in Health and Disease) coordinates such an endeavor. By using a combination of experimental data sets and computational modelling, the consortium strives for gaining a detailed and mechanistic understanding of signal transduction processes that govern T-cell activation. In order to foster the interaction between systems biologists and experimentally working groups, SYBILLA co-organized the 15th meeting “Signal Transduction: Receptors, Mediators and Genes” together with the Signal Transduction Society (STS). Thus, the annual STS conference, held from November 7 to 9, 2011 in Weimar, Germany, provided an interdisciplinary forum for research on signal transduction with a major focus on systems biology addressing signalling events in T-cells. Here we report on a selection of ongoing projects of SYBILLA and how they were discussed at this interdisciplinary conference.

Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations.

Infections with different infecting agents can alter the immune response against any one parasite and the relative abundance and persistence of the infections within the host. This is because the immune system is not compartmentalized but acts as a whole to allow the host to maintain control of the infections as well as repair damaged tissues and avoid immuno-pathology. There is no comprehensive understanding of the immune responses during co-infections and of how systemic and local mechanisms interact. Here we integrated experimental data with mathematical modelling to describe the network of immune responses of single and co-infection by a respiratory bacterium and a gastrointestinal helminth. We were able to identify key cells and functions responsible for clearing or reducing both parasites and showed that some mechanisms differed between type of infection as a result of different signal outputs and cells contributing to the immune processes. This study highlights the importance of understanding the immuno-dynamics of co-infection as a host response, how immune mechanisms differ from single infections and how they may alter parasite persistence, impact and abundance.