Quantifying crosstalk among interferon-γ, interleukin-12, and tumor necrosis factor signaling pathways within a TH1 cell model

Evaluation of the Immunomodulatory Effects of Radiation for Chimeric Antigen Receptor T Cell Therapy in Glioblastoma Multiforme

Standard-of-care treatment for Glioblastoma Multiforme (GBM) is comprised of surgery and adjuvant chemoradiation. Chimeric Antigen Receptor (CAR) T cell therapy has demonstrated disease-modifying activity in GBM and holds great promise. Radiation, a standard-of-care treatment for GBM, has well-known immunomodulatory properties and may overcome the immunosuppressive tumor microenvironment (TME); however, radiation dose optimization and integration with CAR T cell therapy is not well defined. Murine immunocompetent models of GBM were treated with titrated doses of stereotactic radiosurgery (SRS) of 5, 10, and 20 Gray (Gy), and the TME was analyzed using Nanostring. A conditioning dose of 10 Gy was determined based on tumor growth kinetics and gene expression changes in the TME. We demonstrate that a conditioning dose of 10 Gy activates innate and adaptive immune cells in the TME. Mice treated with 10 Gy in combination with mCAR T cells demonstrated enhanced antitumor activity and superior memory responses to rechallenge with IL13Rα2-positive tumors. Furthermore, 10 Gy plus mCAR T cells also protected against IL13Rα2-negative tumors through a mechanism that was, in part, c-GAS-STING pathway-dependent. Together, these findings support combination conditioning with low-dose 10 Gy radiation in combination with mCAR T cells as a therapeutic strategy for GBM.

Effect of nonsteroidal anti-inflammatory drugs on pelvic floor muscle regeneration in a preclinical birth injury rat model

BACKGROUND

Pelvic floor muscle injury is a common consequence of vaginal childbirth. Nonsteroidal anti-inflammatory drugs are widely used postpartum analgesics. Multiple studies have reported negative effects of these drugs on limb muscle regeneration, but their impact on pelvic floor muscle recovery following birth injury has not been explored.

OBJECTIVE

Using a validated rat model, we assessed the effects of nonsteroidal anti-inflammatory drug on acute and longer-term pelvic floor muscle recovery following simulated birth injury.

STUDY DESIGN

Three-month old Sprague Dawley rats were randomly assigned to the following groups: (1) controls, (2) simulated birth injury, (3) simulated birth injury+nonsteroidal anti-inflammatory drug, or (4) nonsteroidal anti-inflammatory drug. Simulated birth injury was induced using a well-established vaginal balloon distension protocol. Ibuprofen was administered in drinking water (0.2 mg/mL), which was consumed by the animals ad libitum. Animals were euthanized at 1, 3, 5, 7, 10, and 28 days after birth injury/ibuprofen administration. The pubocaudalis portion of the rat levator ani, which, like the human pubococcygeus, undergoes greater parturition-associated strains, was harvested (N=3-9/time point/group). The cross-sectional areas of regenerating (embryonic myosin heavy chain+) and mature myofibers were assessed at the acute and 28-day time points, respectively. The intramuscular collagen content was assessed at the 28-day time point. Myogenesis was evaluated using anti-Pax7 and anti-myogenin antibodies to identify activated and differentiated muscle stem cells, respectively. The overall immune infiltrate was assessed using anti-CD45 antibody. Expression of genes coding for pro- and anti-inflammatory cytokines was assessed by quantitative reverse transcriptase polymerase chain reaction at 3, 5, and 10 days after injury.

RESULTS

The pubocaudalis fiber size was significantly smaller in the simulated birth injury+nonsteroidal anti-inflammatory drug compared with the simulated birth injury group at 28 days after injury (P<.0001). The median size of embryonic myosin heavy chain+ fibers was also significantly reduced, with the fiber area distribution enriched with smaller fibers in the simulated birth injury+nonsteroidal anti-inflammatory drug group relative to the simulated birth injury group at 3 days after injury (P<.0001), suggesting a delay in the onset of regeneration in the presence of nonsteroidal anti-inflammatory drugs. By 10 days after injury, the median embryonic myosin heavy chain+ fiber size in the simulated birth injury group decreased from 7 days after injury (P<.0001) with a tight cross-sectional area distribution, indicating nearing completion of this state of regeneration. However, in the simulated birth injury+nonsteroidal anti-inflammatory drug group, the size of embryonic myosin heavy chain+ fibers continued to increase (P<.0001) with expansion of the cross-sectional area distribution, signifying a delay in regeneration in these animals. Nonsteroidal anti-inflammatory drugs decreased the muscle stem cell pool at 7 days after injury (P<.0001) and delayed muscle stem cell differentiation, as indicated by persistently elevated number of myogenin+ cells 7 days after injury (P<.05). In contrast, a proportion of myogenin+ cells returned to baseline by 5 days after injury in the simulated birth injury group. The analysis of expression of genes coding for pro- and anti-inflammatory cytokines demonstrated only transient elevation of Tgfb1 in the simulated birth injury+nonsteroidal anti-inflammatory drug group at 5 but not at 10 days after injury. Consistently with previous studies, nonsteroidal anti-inflammatory drug administration following simulated birth injury resulted in increased deposition of intramuscular collagen relative to uninjured animals. There were no significant differences in any outcomes of interest between the nonsteroidal anti-inflammatory drug group and the unperturbed controls.

CONCLUSION

Nonsteroidal anti-inflammatory drugs negatively impacted pelvic floor muscle regeneration in a preclinical simulated birth injury model. This appears to be driven by the negative impact of these drugs on pelvic muscle stem cell function, resulting in delayed temporal progression of pelvic floor muscle regeneration following birth injury. These findings provide impetus to investigate the impact of postpartum nonsteroidal anti-inflammatory drug administration on muscle regeneration in women at high risk for pelvic floor muscle injury.

Pleiotropy enables specific and accurate signaling in the presence of ligand cross talk

Living cells sense their environment through the binding of extracellular molecular ligands to cell surface receptors. Puzzlingly, vast numbers of signaling pathways exhibit a high degree of cross talk between different signals whereby different ligands act through the same receptor or shared components downstream. It remains unclear how a cell can accurately process information from the environment in such cross-wired pathways. We show that a feature which commonly accompanies cross talk-signaling pleiotropy (the ability of a receptor to produce multiple outputs)-offers a solution to the cross-talk problem. In a minimal model we show that a single pleiotropic receptor can simultaneously identify and accurately sense the concentrations of arbitrary unknown ligands present individually or in a mixture. We calculate the fundamental limits of the signaling specificity and accuracy of such signaling schemes. The model serves as an elementary "building block" toward understanding more complex cross-wired receptor-ligand signaling networks.

Endoscopic Activity and Serum TNF-α Level at Baseline Are Associated With Clinical Response to Ustekinumab in Crohn's Disease Patients

BACKGROUND AND AIMS

The therapeutic efficacy and safety of ustekinumab for Crohn's disease (CD) have been reported from randomized controlled trials and real-world data. However, there are few studies describing the identification of patients most suitable for ustekinumab therapy. The aim of this study was to prospectively evaluate the patients receiving ustekinumab and identify predictors of the treatment efficacy.

METHODS

Patients with moderate to severe active CD scheduled to receive ustekinumab were enrolled. The responders and nonresponders were compared at weeks 0, 8, 24, and 48 by evaluating patient demographics, simple endoscopic scores (SES-CD), ustekinumab and cytokine concentrations, and cellular fractions.

RESULTS

The clinical response and clinical remission rates in the 22 enrolled patients were 59.1% and 31. 8% at week 8, 68.2% and 45.5% at week 24, and 54.4% and 40.9% at week 48, respectively. There were no significant differences in patients' demographic and disease characteristics at baseline between responders and nonresponders. A combination of low SES-CD and high serum TNF-α concentration at baseline showed a good correlation with the clinical response. Serum TNF-α concentration was decreased because of the therapy. The ratio of CD4+TNF-α cells at baseline was significantly higher in responders than in nonresponders; however, the ratios of CD45+CD11b+TNF-α and CD45+CD11c+TNF-α cells were not different. The ratio of CD4+ TNF-α cells decreased with the treatment in the responders but not in the nonresponders.

CONCLUSIONS

The combination of 2 factors, namely higher serum TNF-α concentration and lower SES-CD at baseline, may assist clinicians in selecting the appropriate therapy for patients with moderate to severe CD.

IL-12, IL-23 and IL-17 in IBD: immunobiology and therapeutic targeting

IL-12 and IL-23 are closely related cytokines with important roles in the regulation of tissue inflammation. Converging evidence from studies in mice, human observational studies and population genetics supports the importance of these cytokines in the regulation of mucosal inflammation in the gut in particular. Ustekinumab, a therapeutic antibody targeting both cytokines is now widely licensed for the treatment of Crohn's disease, including in Europe, the USA, Canada and Japan, whilst agents targeting IL-23 specifically are in late-phase clinical trials. We review the emerging understanding of the biology of IL-12 and IL-23, as well as that of their major downstream cytokines, including IL-17. In particular, we discuss how their biology has influenced the development of clinical trials and therapeutic strategies in IBD, as well as how findings from clinical trials, at times surprising, have in turn refocused our understanding of the underlying biology.

Melanoma exosomes deliver a complex biological payload that upregulates PTPN11 to suppress T lymphocyte function

As exosomes are emerging as a new mode of intercellular communication, we hypothesized that the payload contained within exosomes is shaped by somatic evolution. To test this, we assayed the impact on primary CD8+ T-cell function, a key mechanism for antitumor immunity, of exosomes derived from three melanoma-related cell lines. While morphologically similar, exosomes from each cell line were functionally different, as B16F0 exosomes dose-dependently suppressed T-cell proliferation. In contrast, Cloudman S91 exosomes promoted T-cell proliferation and Melan-A exosomes had a negligible effect on primary CD8+ T cells. Mechanistically, transcript profiling suggested that exosomal mRNA is enriched for full-length mRNAs that target immune-related pathways. Interestingly, B16F0 exosomes were unique in that they contained both protein and mRNA for PTPN11, which inhibited T-cell proliferation. Collectively, the results suggest that upregulation of PTPN11 by B16F0 exosomes to tumor infiltrating lymphocytes would bypass the extracellular control of the immune checkpoints.

Inferring the Impact of Regulatory Mechanisms that Underpin CD8+ T Cell Control of B16 Tumor Growth In vivo Using Mechanistic Models and Simulation

A major barrier for broadening the efficacy of immunotherapies for cancer is identifying key mechanisms that limit the efficacy of tumor infiltrating lymphocytes. Yet, identifying these mechanisms using human samples and mouse models for cancer remains a challenge. While interactions between cancer and the immune system are dynamic and non-linear, identifying the relative roles that biological components play in regulating anti-tumor immunity commonly relies on human intuition alone, which can be limited by cognitive biases. To assist natural intuition, modeling and simulation play an emerging role in identifying therapeutic mechanisms. To illustrate the approach, we developed a multi-scale mechanistic model to describe the control of tumor growth by a primary response of CD8+ T cells against defined tumor antigens using the B16 C57Bl/6 mouse model for malignant melanoma. The mechanistic model was calibrated to data obtained following adenovirus-based immunization and validated to data obtained following adoptive transfer of transgenic CD8+ T cells. More importantly, we use simulation to test whether the postulated network topology, that is the modeled biological components and their associated interactions, is sufficient to capture the observed anti-tumor immune response. Given the available data, the simulation results also provided a statistical basis for quantifying the relative importance of different mechanisms that underpin CD8+ T cell control of B16F10 growth. By identifying conditions where the postulated network topology is incomplete, we illustrate how this approach can be used as part of an iterative design-build-test cycle to expand the predictive power of the model.

Synergistic Communication between CD4+ T Cells and Monocytes Impacts the Cytokine Environment

Physiological cytokine environments arise from factors produced by diverse cell types in coordinated concert. Understanding the contributions of each cell type in the context of cell-cell communication is important for effectively designing disease modifying interventions. Here, we present multi-plexed measurement of 48 cytokines from a coculture system of primary human CD4+ T cells and monocytes across a spectrum of stimuli and for a range of relative T cell/monocyte compositions, coupled with corresponding measurements from PBMCs and plasma from the same donors. Computational analysis of the resulting data-sets elucidated communication-independent and communication-dependent contributions, including both positive and negative synergies. We find that cytokines in cell supernatants were uncorrelated to those found in plasma. Additionally, as an example of positive synergy, production levels of CXCR3 cytokines IP-10 and MIG, depend non-linearly on both IFNγ and TNFα levels in cross-talk between T cells and monocytes. Overall, this work demonstrates that communication between cell types can significantly impact the consequent cytokine environment, emphasizing the value of mixed cell population studies.

In silico model-based inference: an emerging approach for inverse problems in engineering better medicines

Identifying the network of biochemical interactions that underpin disease pathophysiology is a key hurdle in drug discovery. While many components involved in these biological processes are identified, how components organize differently in health and disease remains unclear. In chemical engineering, mechanistic modeling provides a quantitative framework to capture our understanding of a reactive system and test this knowledge against data. Here, we describe an emerging approach to test this knowledge against data that leverages concepts from probability, Bayesian statistics, and chemical kinetics by focusing on two related inverse problems. The first problem is to identify the causal structure of the reaction network, given uncertainty as to how the reactive components interact. The second problem is to identify the values of the model parameters, when a network is known a priori.

Interlocked positive and negative feedback network motifs regulate β-catenin activity in the adherens junction pathway

The integrity of epithelial tissue architecture is maintained through adherens junctions that are created through extracellular homotypic protein-protein interactions between cadherin molecules. Cadherins also provide an intracellular scaffold for the formation of a multiprotein complex that contains signaling proteins, including β-catenin. Environmental factors and controlled tissue reorganization disrupt adherens junctions by cleaving the extracellular binding domain and initiating a series of transcriptional events that aim to restore tissue homeostasis. However, it remains unclear how alterations in cell adhesion coordinate transcriptional events, including those mediated by β-catenin in this pathway. Here were used quantitative single-cell and population-level in vitro assays to quantify the endogenous pathway dynamics after the proteolytic disruption of the adherens junctions. Using prior knowledge of isolated elements of the overall network, we interpreted these data using in silico model-based inference to identify the topology of the regulatory network. Collectively the data suggest that the regulatory network contains interlocked network motifs consisting of a positive feedback loop, which is used to restore the integrity of adherens junctions, and a negative feedback loop, which is used to limit β-catenin-induced gene expression.

Enhancing the discovery and development of immunotherapies for cancer using quantitative and systems pharmacology: Interleukin-12 as a case study

Recent clinical successes of immune checkpoint modulators have unleashed a wave of enthusiasm associated with cancer immunotherapy. However, this enthusiasm is dampened by persistent translational hurdles associated with cancer immunotherapy that mirror the broader pharmaceutical industry. Specifically, the challenges associated with drug discovery and development stem from an incomplete understanding of the biological mechanisms in humans that are targeted by a potential drug and the financial implications of clinical failures. Sustaining progress in expanding the clinical benefit provided by cancer immunotherapy requires reliably identifying new mechanisms of action. Along these lines, quantitative and systems pharmacology (QSP) has been proposed as a means to invigorate the drug discovery and development process. In this review, I discuss two central themes of QSP as applied in the context of cancer immunotherapy. The first theme focuses on a network-centric view of biology as a contrast to a "one-gene, one-receptor, one-mechanism" paradigm prevalent in contemporary drug discovery and development. This theme has been enabled by the advances in wet-lab capabilities to assay biological systems at increasing breadth and resolution. The second theme focuses on integrating mechanistic modeling and simulation with quantitative wet-lab studies. Drawing from recent QSP examples, large-scale mechanistic models that integrate phenotypic signaling-, cellular-, and tissue-level behaviors have the potential to lower many of the translational hurdles associated with cancer immunotherapy. These include prioritizing immunotherapies, developing mechanistic biomarkers that stratify patient populations and that reflect the underlying strength and dynamics of a protective host immune response, and facilitate explicit sharing of our understanding of the underlying biology using mechanistic models as vehicles for dialogue. However, creating such models require a modular approach that assumes that the biological networks remain similar in health and disease. As oncogenesis is associated with re-wiring of these biological networks, I also describe an approach that combines mechanistic modeling with quantitative wet-lab experiments to identify ways in which malignant cells alter these networks, using Interleukin-12 as an example. Collectively, QSP represents a new holistic approach that may have profound implications for how translational science is performed.

Downregulation of Runx3 is closely related to the decreased Th1-associated factors in patients with gastric carcinoma

Runt-related transcription factor 3 (Runx3) is a tumor-suppressor gene and plays an important role in immune regulation, whose reduced expression may play an important role in the development and progression of gastric carcinoma. The aim of this study was to investigate the role of Runx3 on the levels of transcription factors in patients with gastric carcinoma and analyze the relationship between the expression of Runx3 and Th1-type cytokines in peripheral blood mononuclear cells (PBMCs). Our results showed that the expression levels of Runx3, T-bet, and IFN-γ in patients with gastric carcinoma were obviously lower than those in control groups, and there was a positive correlation between the expression of Runx3 and T-bet or IFN-γ in patients (p < 0.01). In order to further confirm this result, the Runx3 gene was constructed into pIRES2-eGFP and the recombined plasmid was transfected into SGC-7901 cells with liposome in vitro, the results obtained from the reverse transcription PCR indicated that the mRNA of Runx3, T-bet, or IFN-γ was significantly upregulated individually in Runx3 gene-transfected SGC-7901 cells. It suggested that the Runx3 and Th1-associated factors including T-bet and IFN-γ synchronization declines in gastric carcinoma may contribute to the development of cancer.

Targeted depletion of tumour-associated macrophages by an alendronate-glucomannan conjugate for cancer immunotherapy

Tumour-associated macrophages (TAMs) are a set of macrophages residing in the tumour microenvironment. They play essential roles in mediating tumour angiogenesis, metastasis and immune evasion. Delivery of therapeutic agents to eliminate TAMs can be a promising strategy for cancer immunotherapy but an efficient vehicle to target these cells is still in pressing need. In this study, we developed a bisphosphonate-glucomannan conjugate that could efficiently target and specifically eliminate TAMs in the tumour microenvironment. We employed the polysaccharide from Bletilla striata (BSP), a glucomannan affinitive for macrophages that express abundant mannose receptors, to conjugate alendronate (ALN), a bisphosphonate compound with in vitro macrophage-inhibiting activities. In both in vitro and in vivo tests, the prepared ALN-BSP conjugate could preferentially accumulate in macrophages and induced them into apoptosis. In the subcutaneous S180 tumour-bearing mice model, the treatment using ALN-BSP effectively eliminated TAMs, remarkably inhibited angiogenesis, recovered local immune surveillance, and eventually suppressed tumour progression, without eliciting any unwanted effect such as systematic immune response. Interestingly, ALN alone failed to exhibit any anti-TAM activity in vivo, probably because this compound was susceptible to the mildly acidic tumour microenvironment. Taken together, these results demonstrate the potential of ALN-BSP as a safe and efficient tool targeted at direct depletion of TAMs for cancer immunotherapy.

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics.

Negative interactions and feedback regulations are required for transient cellular response

Signal transduction is a process required to conduct information from a receptor to the nucleus. This process is vital for the control of cellular function and fate. The dynamics of signaling activation and inhibition determine processes such as apoptosis, proliferation, and differentiation. Thus, it is important to understand the factors modulating transient and sustained response. To address this question, by applying mathematical approach we have studied the factors which can alter the activation nature of downstream signaling molecules. The factors which we have investigated are loops (feed forward and feedback loops), cross-talk of signal transduction pathways, and the change in the concentration of the signaling molecules. Based on our results we conclude that among these factors feedback loop and the cross-talks which directly inhibit the target protein dominantly controls the transient cellular response.

Induction of Wnt-inducible signaling protein-1 correlates with invasive breast cancer oncogenesis and reduced type 1 cell-mediated cytotoxic immunity: a retrospective study

Innate and type 1 cell-mediated cytotoxic immunity function as important extracellular control mechanisms that maintain cellular homeostasis. Interleukin-12 (IL12) is an important cytokine that links innate immunity with type 1 cell-mediated cytotoxic immunity. We recently observed in vitro that tumor-derived Wnt-inducible signaling protein-1 (WISP1) exerts paracrine action to suppress IL12 signaling. The objective of this retrospective study was three fold: 1) to determine whether a gene signature associated with type 1 cell-mediated cytotoxic immunity was correlated with overall survival, 2) to determine whether WISP1 expression is increased in invasive breast cancer, and 3) to determine whether a gene signature consistent with inhibition of IL12 signaling correlates with WISP1 expression. Clinical information and mRNA expression for genes associated with anti-tumor immunity were obtained from the invasive breast cancer arm of the Cancer Genome Atlas study. Patient cohorts were identified using hierarchical clustering. The immune signatures associated with the patient cohorts were interpreted using model-based inference of immune polarization. Reverse phase protein array, tissue microarray, and quantitative flow cytometry in breast cancer cell lines were used to validate observed differences in gene expression. We found that type 1 cell-mediated cytotoxic immunity was correlated with increased survival in patients with invasive breast cancer, especially in patients with invasive triple negative breast cancer. Oncogenic transformation in invasive breast cancer was associated with an increase in WISP1. The gene expression signature in invasive breast cancer was consistent with WISP1 as a paracrine inhibitor of type 1 cell-mediated immunity through inhibiting IL12 signaling and promoting type 2 immunity. Moreover, model-based inference helped identify appropriate immune signatures that can be used as design constraints in genetically engineering better pre-clinical models of breast cancer.

Effective anti-tumor immunity is proportional to the number and to the cytotoxic activity of immune cells that enter the tumor microenvironment. Recent advances in cancer immunotherapy stem from increasing the number of tumor-infiltrating immune cells by inhibiting immune checkpoints or adoptive T cell therapy. Here, we used computational methods to identify potential mechanisms present within the tumor microenvironment that limit the efficacy of anti-tumor immunity. Specifically, we found that oncogenic transformation is associated with the induction of tumor-derived biochemical cues, namely Wnt-inducible signaling protein-1, that locally suppress anti-tumor immunity. Moreover, we used model-based inference to demonstrate that a gene signature consistent with effective type 1 cell-mediated cytotoxic immunity is a predictor of overall survival independent of molecular pathology. Interestingly, patients with triple negative breast cancer were more enriched in the cohort associated with type 1 cell-mediated immunity. As this immune gene signature is not present in current genetically engineered mouse models of breast cancer, the results help identify design constraints for engineering better pre-clinical models of breast cancer. Demonstrating efficacy in pre-clinical animal models is a pre-requisite for bringing improved cancer immunotherapies into the clinic.

Exploring higher-order EGFR oligomerisation and phosphorylation--a combined experimental and theoretical approach

The epidermal growth factor receptor (EGFR) kinase is generally considered to be activated by either ligand-induced dimerisation or a ligand-induced conformational change within pre-formed dimers. Ligand-induced higher-order EGFR oligomerisation or clustering has been reported but it is not clear how EGFR oligomers, as distinct from EGFR dimers, influence signaling outputs. To address this question, we combined measures of receptor clustering (microscopy; image correlation spectroscopy) and phosphorylation (Western blots) with modelling of mass-action chemical kinetics. A stable BaF/3 cell-line that contains a high proportion (>90%) of inactive dimers of EGFR-eGFP but no secreted ligand and no other detectable ErbB receptors was used as the model cell system. EGF at concentrations of greater than 1 nM was found to cluster EGFR-eGFP dimers into higher-order complexes and cause parallel increases in EGFR phosphorylation. The kinetics of EGFR clustering and phosphorylation were both rapid, plateauing within 2 minutes after stimulation with 30 nM EGF. A rule-based model was formulated to interpret the data. This model took into account ligand binding, ligand-induced conformational changes in the cytosolic tail, monomer-dimer-trimer-tetramer transitions via ectodomain- and kinase-mediated interactions, and phosphorylation. The model predicts that cyclic EGFR tetramers are the predominant phosphorylated species, in which activated receptor dimers adopt a cyclic side-by-side orientation, and that receptor kinase activation is stabilised by the intramolecular interactions responsible for cyclic tetramerization.

Analytical solution of steady-state equations for chemical reaction networks with bilinear rate laws

True steady states are a rare occurrence in living organisms, yet their knowledge is essential for quasi-steady-state approximations, multistability analysis, and other important tools in the investigation of chemical reaction networks (CRN) used to describe molecular processes on the cellular level. Here, we present an approach that can provide closed form steady-state solutions to complex systems, resulting from CRN with binary reactions and mass-action rate laws. We map the nonlinear algebraic problem of finding steady states onto a linear problem in a higher-dimensional space. We show that the linearized version of the steady-state equations obeys the linear conservation laws of the original CRN. We identify two classes of problems for which complete, minimally parameterized solutions may be obtained using only the machinery of linear systems and a judicious choice of the variables used as free parameters. We exemplify our method, providing explicit formulae, on CRN describing signal initiation of two important types of RTK receptor-ligand systems, VEGF and EGF-ErbB1.

Collapse of the tumor stroma is triggered by IL-12 induction of Fas

Engineering CD8⁺ T cells to deliver interleukin 12 (IL-12) to the tumor site can lead to striking improvements in the ability of adoptively transferred T cells to induce the regression of established murine cancers. We have recently shown that IL-12 triggers an acute inflammatory environment that reverses dysfunctional antigen presentation by myeloid-derived cells within tumors and leads to an increase in the infiltration of adoptively transferred antigen-specific CD8⁺ T cells. Here, we find that local delivery of IL-12 increased the expression of Fas within tumor-infiltrating macrophages, dendritic cells, and myeloid-derived suppressor cells (MDSC), and that these changes were abrogated in mice deficient in IL-12-receptor signaling. Importantly, upregulation of Fas in host mice played a critical role in the proliferation and antitumor activity of adoptively transferred IL-12-modified CD8⁺ T cells. We also observed higher percentages of myeloid-derived cell populations within tumors in Fas-deficient mice, indicating that tumor stromal destruction was dependent on the Fas death receptor. Taken together, these results describe the likely requirement for costimulatory reverse signaling through Fasl on T cells that successfully infiltrate tumors, a mechanism triggered by the induction of Fas expression on myeloid-derived cells by IL-12 and the subsequent collapse of the tumor stroma.

Systems modeling of molecular mechanisms controlling cytokine-driven CD4+ T cell differentiation and phenotype plasticity

Differentiation of CD4+ T cells into effector or regulatory phenotypes is tightly controlled by the cytokine milieu, complex intracellular signaling networks and numerous transcriptional regulators. We combined experimental approaches and computational modeling to investigate the mechanisms controlling differentiation and plasticity of CD4+ T cells in the gut of mice. Our computational model encompasses the major intracellular pathways involved in CD4+ T cell differentiation into T helper 1 (Th1), Th2, Th17 and induced regulatory T cells (iTreg). Our modeling efforts predicted a critical role for peroxisome proliferator-activated receptor gamma (PPARγ) in modulating plasticity between Th17 and iTreg cells. PPARγ regulates differentiation, activation and cytokine production, thereby controlling the induction of effector and regulatory responses, and is a promising therapeutic target for dysregulated immune responses and inflammation. Our modeling efforts predict that following PPARγ activation, Th17 cells undergo phenotype switch and become iTreg cells. This prediction was validated by results of adoptive transfer studies showing an increase of colonic iTreg and a decrease of Th17 cells in the gut mucosa of mice with colitis following pharmacological activation of PPARγ. Deletion of PPARγ in CD4+ T cells impaired mucosal iTreg and enhanced colitogenic Th17 responses in mice with CD4+ T cell-induced colitis. Thus, for the first time we provide novel molecular evidence in vivo demonstrating that PPARγ in addition to regulating CD4+ T cell differentiation also plays a major role controlling Th17 and iTreg plasticity in the gut mucosa.

CD4+ T cells can differentiate into different phenotypes depending on the cytokine milieu. Due to the complexity of this process, we have constructed a computational and mathematical model with sixty ordinary differential equations representing a CD4+ T cell differentiating into either Th1, Th2, Th17 or iTreg cells. The model includes cytokines, nuclear receptors and transcription factors that define fate and function of CD4+ T cells. Computational simulations illustrate how a proinflammatory Th17 cell can undergo reprogramming into an anti-inflammatory iTreg phenotype following PPARγ activation. This modeling-derived hypothesis has been validated with in vitro and in vivo experiments. Experimental data support the modeling-derived prediction and demonstrate that the loss of PPARγ enhances a proinflammatory response characterized by Th17 in colitis-induced mice. Moreover, pharmacological activation of PPARγ in vivo can affect the Th17/iTreg balance by upregulating FOXP3 and downregulating IL-17A and RORγt. In summary, we demonstrate that computational simulations using our CD4+ T cell model provide novel unforeseen hypotheses related to the molecular mechanisms controlling differentiation and function of CD4+ T cells. In vivo findings validated the modeling prediction that PPARγ modulates differentiation and plasticity of CD4+ T cells in mice.

An evolutionary perspective on anti-tumor immunity

The challenges associated with demonstrating a durable response using molecular-targeted therapies in cancer has sparked a renewed interest in viewing cancer from an evolutionary perspective. Evolutionary processes have three common traits: heterogeneity, dynamics, and a selective fitness landscape. Mutagens randomly alter the genome of host cells creating a population of cells that contain different somatic mutations. This genomic rearrangement perturbs cellular homeostasis through changing how cells interact with their tissue microenvironment. To counterbalance the ability of mutated cells to outcompete for limited resources, control structures are encoded within the cell and within the organ system, such as innate and adaptive immunity, to restore cellular homeostasis. These control structures shape the selective fitness landscape and determine whether a cell that harbors particular somatic mutations is retained or eliminated from a cell population. While next-generation sequencing has revealed the complexity and heterogeneity of oncogenic transformation, understanding the dynamics of oncogenesis and how cancer cells alter the selective fitness landscape remain unclear. In this technology review, we will summarize how recent advances in technology have impacted our understanding of these three attributes of cancer as an evolutionary process. In particular, we will focus on how advances in genome sequencing have enabled quantifying cellular heterogeneity, advances in computational power have enabled explicit testing of postulated intra- and intercellular control structures against the available data using simulation, and advances in proteomics have enabled identifying novel mechanisms of cellular cross-talk that cancer cells use to alter the fitness landscape.

Downregulation of Hlx closely related to the decreased expressions of T-bet and Runx3 in patients with gastric cancer may be associated with a pathological event leading to the imbalance of Th1/Th2

T-bet plays an important role in immunoregulation; it induces the differentiation of Th1 together with the homeobox transcription factor gene Hlx. Recent studies show that T-bet and Th1-associated factors are critical in regulating tumor development. However, the contributions of Hlx in the occurrence and development of cancer remain unknown. In this study, the Hlx, T-bet, Runx3, and IFN-γ were measured in PBMC from patients with gastric cancer and the correlation between Hlx and T-bet or IFN-γ was assessed. The expression levels of Hlx, T-bet, and IFN-γwere significantly decreased, and there was a positive correlation between Hlx and T-bet or IFN-γ. In addition, the Runx3 expression was also downregulated with the lower T-bet mRNA level. These results suggested that the decreased Hlx expression was closely associated with T-bet and Runx3 downregulations and may contribute to the development of gastric cancer.

A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model

Interleukin-12 (IL12) enhances anti-tumor immunity when delivered to the tumor microenvironment. However, local immunoregulatory elements dampen the efficacy of IL12. The identity of these local mechanisms used by tumors to suppress immunosurveillance represents a key knowledge gap for improving tumor immunotherapy. From a systems perspective, local suppression of anti-tumor immunity is a closed-loop system - where system response is determined by an unknown combination of external inputs and local cellular cross-talk. Here, we recreated this closed-loop system in vitro and combined quantitative high content assays, in silico model-based inference, and a proteomic workflow to identify the biochemical cues responsible for immunosuppression. Following an induction period, the B16 melanoma cell model, a transplantable model for spontaneous malignant melanoma, inhibited the response of a T helper cell model to IL12. This paracrine effect was not explained by induction of apoptosis or creation of a cytokine sink, despite both mechanisms present within the co-culture assay. Tumor-derived Wnt-inducible signaling protein-1 (WISP-1) was identified to exert paracrine action on immune cells by inhibiting their response to IL12. Moreover, WISP-1 was expressed in vivo following intradermal challenge with B16F10 cells and was inferred to be expressed at the tumor periphery. Collectively, the data suggest that (1) biochemical cues associated with epithelial-to-mesenchymal transition can shape anti-tumor immunity through paracrine action and (2) remnants of the immunoselective pressure associated with evolution in cancer include both sculpting of tumor antigens and expression of proteins that proactively shape anti-tumor immunity.