Cellular characterisation of advanced osteoarthritis knee synovium.

OBJECTIVES: Osteoarthritis (OA) is increasingly recognised as a whole joint disease, with an important role for synovium. However, the repertoire of immune cells and fibroblasts that constitute OA synovium remains understudied. This study aims to characterise the cellular composition of advanced OA synovium and to explore potential correlations between different cell types and patient demographics or clinical scores. METHODS: Synovium, collected from 10 patients with advanced OA during total knee replacement surgery, was collagenase-digested, and cells were stained for flow cytometry analysis. Formalin-fixed paraffin-embedded synovium was sectioned, stained with immunofluorescence, and imaged using the multiplex Cell DIVE platform. Patient demographics and clinical scores were also collected. RESULTS: The proportion of immune cells in OA synovium varied between patients (8-38% of all cells). Macrophages and T cells were the dominant immune cell populations, together representing 76% of immune cells. Age positively correlated with the proportion of macrophages, and negatively correlated with T cells. CCR6+ T cells were found in 6/10 patients; these patients had a higher mean Kellgren-Lawrence grade across the three knee compartments. Immunofluorescence staining showed that macrophages were present in the lining as well as distributed throughout the sublining, while T and B cells were mainly localised near vessels in the sublining. Fibroblast subsets (CD45-PDPN+) based on the expression of CD34/CD90 or FAP/CD90 were identified in all patient samples, and some populations correlate with the percentage of immune cells or clinical scores. Immunofluorescence staining showed that FAP expression was particularly strong in the lining layer, but also present throughout the sublining layer. CD90 expression was exclusively found around vessels in the sublining, while CD34 was mostly found in the sublining but also occasionally in the lining layer. CONCLUSIONS: There are significant differences in the relative proportions and subsets of immune cells in OA synovium; exploratory correlative analyses suggest that these differences might be correlated with age, clinical scores, or fibroblast subsets. Additional studies are required to understand how different cell types affect OA pathobiology, and if the presence or proportion of cell subsets relates to disease phenotypes.

De-risking clinical trial failure through mechanistic simulation.

Drug development typically comprises a combination of pre-clinical experimentation, clinical trials, and statistical data-driven analyses. Therapeutic failure in late-stage clinical development costs the pharmaceutical industry billions of USD per year. Clinical trial simulation represents a key derisking strategy and combining them with mechanistic models allows one to test hypotheses for mechanisms of failure and to improve trial designs. This is illustrated with a T-cell activation model, used to simulate the clinical trials of IMA901, a short-peptide cancer vaccine. Simulation results were consistent with observed outcomes and predicted that responses are limited by peptide off-rates, peptide competition for dendritic cell (DC) binding, and DC migration times. These insights were used to hypothesise alternate trial designs predicted to improve efficacy outcomes. This framework illustrates how mechanistic models can complement clinical, experimental, and data-driven studies to understand, test, and improve trial designs, and how results may differ between humans and mice.

Analysis of cellular kinetic models suggest that physiologically based model parameters may be inherently, practically unidentifiable.

Physiologically-based pharmacokinetic and cellular kinetic models are used extensively to predict concentration profiles of drugs or adoptively transferred cells in patients and laboratory animals. Models are fit to data by the numerical optimisation of appropriate parameter values. When quantities such as the area under the curve are all that is desired, only a close qualitative fit to data is required. When the biological interpretation of the model that produced the fit is important, an assessment of uncertainties is often also warranted. Often, a goal of fitting PBPK models to data is to estimate parameter values, which can then be used to assess characteristics of the fit system or applied to inform new modelling efforts and extrapolation, to inform a prediction under new conditions. However, the parameters that yield a particular model output may not necessarily be unique, in which case the parameters are said to be unidentifiable. We show that the parameters in three published physiologically-based pharmacokinetic models are practically (deterministically) unidentifiable and that it is challenging to assess the associated parameter uncertainty with simple curve fitting techniques. This result could affect many physiologically-based pharmacokinetic models, and we advocate more widespread use of thorough techniques and analyses to address these issues, such as established Markov Chain Monte Carlo and Bayesian methodologies. Greater handling and reporting of uncertainty and identifiability of fit parameters would directly and positively impact interpretation and translation for physiologically-based model applications, enhancing their capacity to inform new model development efforts and extrapolation in support of future clinical decision-making.

A method for the inference of cytokine interaction networks.

Cell-cell communication is mediated by many soluble mediators, including over 40 cytokines. Cytokines, e.g. TNF, IL1ß, IL5, IL6, IL12 and IL23, represent important therapeutic targets in immune-mediated inflammatory diseases (IMIDs), such as inflammatory bowel disease (IBD), psoriasis, asthma, rheumatoid and juvenile arthritis. The identification of cytokines that are causative drivers of, and not just associated with, inflammation is fundamental for selecting therapeutic targets that should be studied in clinical trials. As in vitro models of cytokine interactions provide a simplified framework to study complex in vivo interactions, and can easily be perturbed experimentally, they are key for identifying such targets. We present a method to extract a minimal, weighted cytokine interaction network, given in vitro data on the effects of the blockage of single cytokine receptors on the secretion rate of other cytokines. Existing biological network inference methods typically consider the correlation structure of the underlying dataset, but this can make them poorly suited for highly connected, non-linear cytokine interaction data. Our method uses ordinary differential equation systems to represent cytokine interactions, and efficiently computes the configuration with the lowest Akaike information criterion value for all possible network configurations. It enables us to study indirect cytokine interactions and quantify inhibition effects. The extracted network can also be used to predict the combined effects of inhibiting various cytokines simultaneously. The model equations can easily be adjusted to incorporate more complicated dynamics and accommodate temporal data. We validate our method using synthetic datasets and apply our method to an experimental dataset on the regulation of IL23, a cytokine with therapeutic relevance in psoriasis and IBD. We validate several model predictions against experimental data that were not used for model fitting. In summary, we present a novel method specifically designed to efficiently infer cytokine interaction networks from cytokine perturbation data in the context of IMIDs.

The Cellular Composition of the Uveal Immune Environment.

The uveal tract consists of the iris, the ciliary body and the choroid; these three distinct tissues form a continuous layer within the eye. Uveitis refers to inflammation of any region of the uveal tract. Despite being grouped together anatomically, the iris, ciliary body and choroid are distinct functionally, and inflammatory diseases may affect only one part and not the others. Cellular structure of tissues direct their function, and understanding the cellular basis of the immune environment of a tissue in health, the "steady state" on which the perturbations of disease are superimposed, is vital to understanding the pathogenesis of those diseases. A contemporary understanding of the immune system accepts that haematopoietic and yolk sac derived leukocytes, though vital, are not the only players of importance. An array of stromal cells, connective tissue cells such as fibroblasts and endothelial cells, may also have a role in the inflammatory reaction seen in several immune-mediated diseases. In this review we summarise what is known about the cellular composition of the uveal tract and the roles these disparate cell types have to play in immune homeostasis. We also discuss some unanswered questions surrounding the constituents of the resident leukocyte population of the different uveal tissues, and we look ahead to the new understanding that modern investigative techniques such as single cell transcriptomics, multi-omic data integration and highly-multiplexed imaging techniques may bring to the study of the uvea and uveitis, as they already have to other immune mediated inflammatory diseases.

Simulating CXCR5 Dynamics in Complex Tissue Microenvironments.

To effectively navigate complex tissue microenvironments, immune cells sense molecular concentration gradients using G-protein coupled receptors. However, due to the complexity of receptor activity, and the multimodal nature of chemokine gradients in vivo, chemokine receptor activity in situ is poorly understood. To address this issue, we apply a modelling and simulation approach that permits analysis of the spatiotemporal dynamics of CXCR5 expression within an in silico B-follicle with single-cell resolution. Using this approach, we show that that in silico B-cell scanning is robust to changes in receptor numbers and changes in individual kinetic rates of receptor activity, but sensitive to global perturbations where multiple parameters are altered simultaneously. Through multi-objective optimization analysis we find that the rapid modulation of CXCR5 activity through receptor binding, desensitization and recycling is required for optimal antigen scanning rates. From these analyses we predict that chemokine receptor signaling dynamics regulate migration in complex tissue microenvironments to a greater extent than the total numbers of receptors on the cell surface.

Predicted limited redistribution of T cells to secondary lymphoid tissue correlates with increased risk of haematological malignancies in asplenic patients.

The spleen, a secondary lymphoid tissue (SLT), has an important role in generation of adaptive immune responses. Although splenectomy remains a common procedure, recent studies reported poor prognosis and increased risk of haematological malignancies in asplenic patients. The high baseline trafficking of T lymphocytes to splenic tissue suggests splenectomy may lead to loss of blood-borne malignant immunosurveillance that is not compensated for by the remaining SLT. To date, no quantitative analysis of the impact of splenectomy on the human T cell trafficking dynamics and tissue localisation has been reported. We developed a quantitative computational model that describes organ distribution and trafficking of human lymphocytes to explore the likely impact of splenectomy on immune cell distributions. In silico splenectomy resulted in an average reduction of T cell numbers in SLT by 35% (95%CI 0.12-0.97) and a comparatively lower, 9% (95%CI 0.17-1.43), mean decrease of T cell concentration in SLT. These results suggest that the surveillance capacity of the remaining SLT insufficiently compensates for the absence of the spleen. This may, in part, explain haematological malignancy risk in asplenic patients and raises the question of whether splenectomy has a clinically meaningful impact on patient responses to immunotherapy.

Quantifying the limits of CAR T-cell delivery in mice and men.

CAR (Chimeric Antigen Receptor) T cells have demonstrated clinical success for the treatment of multiple lymphomas and leukaemias, but not for various solid tumours, despite promising data from murine models. Lower effective CAR T-cell delivery rates to human solid tumours compared to haematological malignancies in humans and solid tumours in mice might partially explain these divergent outcomes. We used anatomical and physiological data for human and rodent circulatory systems to calculate the typical perfusion of healthy and tumour tissues, and estimated the upper limits of immune cell delivery rates across different organs, tumour types and species. Estimated maximum delivery rates were up to 10 000-fold greater in mice than humans yet reported CAR T-cell doses are typically only 10-100-fold lower in mice, suggesting that the effective delivery rates of CAR T cells into tumours in clinical trials are far lower than in corresponding mouse models. Estimated delivery rates were found to be consistent with published positron emission tomography data. Results suggest that higher effective human doses may be needed to drive efficacy comparable to mouse solid tumour models, and that lower doses should be tested in mice. We posit that quantitation of species and organ-specific delivery and homing of engineered T cells will be key to unlocking their potential for solid tumours.

Inducible ablation of CD11c+ cells to determine their role in skin wound repair.

Whether resident and recruited myeloid cells may impair or aid healing of acute skin wounds remains a debated question. To begin to address this, we examined the importance of CD11c+ myeloid cells in the early activation of skin wound repair. We find that an absence of CD11c+ cells delays wound closure and epidermal proliferation, likely due to defects in the activation of the IL-23-IL-22 axis that is required for wound healing.

B cell zone reticular cell microenvironments shape CXCL13 gradient formation.

Through the formation of concentration gradients, morphogens drive graded responses to extracellular signals, thereby fine-tuning cell behaviors in complex tissues. Here we show that the chemokine CXCL13 forms both soluble and immobilized gradients. Specifically, CXCL13+ follicular reticular cells form a small-world network of guidance structures, with computer simulations and optimization analysis predicting that immobilized gradients created by this network promote B cell trafficking. Consistent with this prediction, imaging analysis show that CXCL13 binds to extracellular matrix components in situ, constraining its diffusion. CXCL13 solubilization requires the protease cathepsin B that cleaves CXCL13 into a stable product. Mice lacking cathepsin B display aberrant follicular architecture, a phenotype associated with effective B cell homing to but not within lymph nodes. Our data thus suggest that reticular cells of the B cell zone generate microenvironments that shape both immobilized and soluble CXCL13 gradients.

Developing a 3D B Cell Lymphoma Culture System to Model Antibody Therapy.

Diffuse large cell B cell lymphoma (DLBCL) accounts for approximately 30%-40% of all non-Hodgkin lymphoma (NHL) cases. Current first line DLBCL treatment results in long-term remission in more than 60% of cases. However, those patients with primary refractory disease or early relapse exhibit poor prognosis, highlighting a requirement for alternative therapies. Our aim was to develop a novel model of DLBCL that facilitates in vitro testing of current and novel therapies by replicating key components of the tumor microenvironment (TME) in a three-dimensional (3D) culture system that would enable primary DLBCL cell survival and study ex vivo. The TME is a complex ecosystem, comprising malignant and non-malignant cells, including cancer-associated fibroblasts (CAF) and tumor-associated macrophages (TAM) whose reciprocal crosstalk drives tumor initiation and growth while fostering an immunosuppressive milieu enabling its persistence. The requirement to recapitulate, at least to some degree, this complex, interactive network is exemplified by the rapid cell death of primary DLBCL cells removed from their TME and cultured alone in vitro. Building on previously described methodologies to generate lymphoid-like fibroblasts from adipocyte derived stem cells (ADSC), we confirmed lymphocytes, specifically B cells, interacted with this ADSC-derived stroma, in the presence or absence of monocyte-derived macrophages (MDM), in both two-dimensional (2D) cultures and a 3D collagen-based spheroid system. Furthermore, we demonstrated that DLBCL cells cultured in this system interact with its constituent components, resulting in their improved viability as compared to ex-vivo 2D monocultures. We then assessed the utility of this system as a platform to study therapeutics in the context of antibody-directed phagocytosis, using rituximab as a model immunotherapeutic antibody. Overall, we describe a novel 3D spheroid co-culture system comprising key components of the DLBCL TME with the potential to serve as a testbed for novel therapeutics, targeting key cellular constituents of the TME, such as CAF and/or TAM.

Application of Modeling Approaches to Explore Vaccine Adjuvant Mode-of-Action.

Novel adjuvant technologies have a key role in the development of next-generation vaccines, due to their capacity to modulate the duration, strength and quality of the immune response. The AS01 adjuvant is used in the malaria vaccine RTS,S/AS01 and in the licensed herpes-zoster vaccine (Shingrix) where the vaccine has proven its ability to generate protective responses with both robust humoral and T-cell responses. For many years, animal models have provided insights into adjuvant mode-of-action (MoA), generally through investigating individual genes or proteins. Furthermore, modeling and simulation techniques can be utilized to integrate a variety of different data types; ranging from serum biomarkers to large scale "omics" datasets. In this perspective we present a framework to create a holistic integration of pre-clinical datasets and immunological literature in order to develop an evidence-based hypothesis of AS01 adjuvant MoA, creating a unified view of multiple experiments. Furthermore, we highlight how holistic systems-knowledge can serve as a basis for the construction of models and simulations supporting exploration of key questions surrounding adjuvant MoA. Using the Systems-Biology-Graphical-Notation, a tool for graphical representation of biological processes, we have captured high-level cellular behaviors and interactions, and cytokine dynamics during the early immune response, which are substantiated by a series of diagrams detailing cellular dynamics. Through explicitly describing AS01 MoA we have built a consensus of understanding across multiple experiments, and so we present a framework to integrate modeling approaches into exploring adjuvant MoA, in order to guide experimental design, interpret results and inform rational design of vaccines.

Immunofibroblasts are pivotal drivers of tertiary lymphoid structure formation and local pathology.

Resident fibroblasts at sites of infection, chronic inflammation, or cancer undergo phenotypic and functional changes to support leukocyte migration and, in some cases, aggregation into tertiary lymphoid structures (TLS). The molecular programming that shapes these changes and the functional requirements of this population in TLS development are unclear. Here, we demonstrate that external triggers at mucosal sites are able to induce the progressive differentiation of a population of podoplanin (pdpn)-positive stromal cells into a network of immunofibroblasts that are able to support the earliest phases of TLS establishment. This program of events, that precedes lymphocyte infiltration in the tissue, is mediated by paracrine and autocrine signals mainly regulated by IL13. This initial fibroblast network is expanded and stabilized, once lymphocytes are recruited, by the local production of the cytokines IL22 and lymphotoxin. Interfering with this regulated program of events or depleting the immunofibroblasts in vivo results in abrogation of local pathology, demonstrating the functional role of immunofibroblasts in supporting TLS maintenance in the tissue and suggesting novel therapeutic targets in TLS-associated diseases.

Combining Mathematical Models With Experimentation to Drive Novel Mechanistic Insights Into Macrophage Function.

This perspective outlines an approach to improve mechanistic understanding of macrophages in inflammation and tissue homeostasis, with a focus on human inflammatory bowel disease (IBD). The approach integrates wet-lab and in-silico experimentation, driven by mechanistic mathematical models of relevant biological processes. Although wet-lab experimentation with genetically modified mouse models and primary human cells and tissues have provided important insights, the role of macrophages in human IBD remains poorly understood. Key open questions include: (1) To what degree hyperinflammatory processes (e.g., gain of cytokine production) and immunodeficiency (e.g., loss of bacterial killing) intersect to drive IBD pathophysiology? and (2) What are the roles of macrophage heterogeneity in IBD onset and progression? Mathematical modeling offers a synergistic approach that can be used to address such questions. Mechanistic models are useful for informing wet-lab experimental designs and provide a knowledge constrained framework for quantitative analysis and interpretation of resulting experimental data. The majority of published mathematical models of macrophage function are based either on animal models, or immortalized human cell lines. These experimental models do not recapitulate important features of human gastrointestinal pathophysiology, and, therefore are limited in the extent to which they can fully inform understanding of human IBD. Thus, we envision a future where mechanistic mathematical models are based on features relevant to human disease and parametrized by richer human datasets, including biopsy tissues taken from IBD patients, human organ-on-a-chip systems and other high-throughput clinical data derived from experimental medicine studies and/or clinical trials on IBD patients.

High-Speed Single-Molecule Tracking of CXCL13 in the B-Follicle.

Soluble factors are an essential means of communication between cells and their environment. However, many molecules readily interact with extracellular matrix components, giving rise to multiple modes of diffusion. The molecular quantification of diffusion in situ is thus a challenging imaging frontier, requiring very high spatial and temporal resolution. Overcoming this methodological barrier is key to understanding the precise spatial patterning of the extracellular factors that regulate immune function. To address this, we have developed a high-speed light microscopy system capable of millisecond sampling in ex vivo tissue samples and submillisecond sampling in controlled in vitro samples to characterize molecular diffusion in a range of complex microenvironments. We demonstrate that this method outperforms competing tools for determining molecular mobility of fluorescence correlation spectroscopy (FCS) and fluorescence recovery after photobleaching (FRAP) for evaluation of diffusion. We then apply this approach to study the chemokine CXCL13, a key determinant of lymphoid tissue architecture, and B-cell-mediated immunity. Super-resolution single-molecule tracking of fluorescently labeled CCL19 and CXCL13 in collagen matrix was used to assess the heterogeneity of chemokine mobility behaviors, with results indicating an immobile fraction and a mobile fraction for both molecules, with distinct diffusion rates of 8.4 ± 0.2 and 6.2 ± 0.3 µm2s-1, respectively. To better understand mobility behaviors in situ, we analyzed CXCL13-AF647 diffusion in murine lymph node tissue sections and observed both an immobile fraction and a mobile fraction with an example diffusion coefficient of 6.6 ± 0.4 µm2s-1, suggesting that mobility within the follicle is also multimodal. In quantitatively studying mobility behaviors at the molecular level, we have obtained an increased understanding of CXCL13 bioavailability within the follicle. Our high-speed single-molecule tracking approach affords a novel perspective from which to understand the mobility of soluble factors relevant to the immune system.

Quantitative Methods for Measuring Repair Rates and Innate-Immune Cell Responses in Wounded Mouse Skin.

In skin wounds, innate-immune cells clear up tissue debris and microbial contamination, and also secrete cytokines and other growth factors that impact repair process such as re-epithelialization and wound closure. After injury, there is a rapid influx and efflux of immune cells at wound sites, yet the function of each innate cell population in skin repair is still under investigation. Flow cytometry is a valuable research tool for detecting and quantifying immune cells; however, in mouse back skin, the difficulty in extracting immune cells from small area of skin due to tissue complexity has made cytometric analysis an underutilized tool. In this paper, we provide detailed methods on the digestion of lesion-specific skin without disrupting antigen expression followed by multiplex cell staining that allows for identification of seven innate-immune populations, including rare subsets such as group-3 innate lymphoid cells (ILC3s), by flow-cytometry analysis. Furthermore, when studying the functions of immune cells to tissue repair an important metric to monitor is size of the wound opening. Normal wounds close steadily albeit at non-linear rates, while slow or stalled wound closure can indicate an underlying problem with the repair process. Calliper measurements are difficult and time-consuming to obtain and can require repeated sedation of experimental animals. We provide advanced methods for measuring of wound openness; digital 3D image capture and semi-automated image processing that allows for unbiased, reliable measurements that can be taken repeatedly over time.

An in silico model of cytotoxic T-lymphocyte activation in the lymph node following short peptide vaccination.

Tumour immunotherapy is dependent upon activation and expansion of tumour-targetting immune cells, known as cytotoxic T-lymphocytes (CTLs). Cancer vaccines developed in the past have had limited success and the mechanisms resulting in failure are not well characterized. To elucidate these mechanisms, we developed a human-parametrized, in silico, agent-based model of vaccination-driven CTL activation within a clinical short-peptide vaccination context. The simulations predict a sharp transition in the probability of CTL activation, which occurs with variation in the separation rate (or off-rate) of tumour-specific immune response-inducing peptides (cognate antigen) from the major histocompatibility class I (MHC-I) receptors of dendritic cells (DCs) originally at the vaccination site. For peptides with MHC-I off-rates beyond this transition, it is predicted that no vaccination strategy will lead to successful expansion of CTLs. For slower off-rates, below the transition, the probability of CTL activation becomes sensitive to the numbers of DCs and T cells that interact subsequent to DC migration to the draining lymph node of the vaccination site. Thus, the off-rate is a key determinant of vaccine design.

MicroRNA-155 induction via TNF-α and IFN-γ suppresses expression of programmed death ligand-1 (PD-L1) in human primary cells.

Programmed death ligand-1 (PD-L1) is a critical regulator of T cell function contributing to peripheral immune tolerance. Although it has been shown that posttranscriptional regulatory mechanisms control PD-L1 expression in cancer, it remains unknown whether such regulatory loops operate also in non-transformed cells. Here we studied PD-L1 expression in human dermal lymphatic endothelial cells (HDLECs), which play key roles in immunity and cancer. Treatment of HDLECs with the pro-inflammatory cytokines IFN-γ and TNF-α synergistically up-regulated PD-L1 expression. IFN-γ and TNF-α also affected expression of several microRNAs (miRNAs) that have the potential to suppress PD-L1 expression. The most highly up-regulated miRNA following IFN-γ and TNF-α treatment in HDLECs was miR-155, which has a central role in the immune system and cancer. Induction of miR-155 was driven by TNF-α, the effect of which was significantly enhanced by IFN-γ. The PD-L1 3'-UTR contains two functional miR-155-binding sites. Endogenous miR-155 controlled the kinetics and maximal levels of PD-L1 induction upon IFN-γ and TNF-α treatments. We obtained similar findings in dermal fibroblasts, demonstrating that the IFN-γ/TNF-α/miR-155/PD-L1 pathway is not restricted to HDLECs. These results reveal miR-155 as a critical component of an inflammation-induced regulatory loop controlling PD-L1 expression in primary cells.

Introduction to Homeostatic Migration.

Immune cell development and function occur in specialized immunological tissues, the function of which requires active cell migration and interactions between hematopoietic cells and underlying networks of stromal cells. These cells provide a scaffold on which immune cell migrate, provide microenvironments for efficient antigen presentation, and provide signals required for immune cell recruitment and survival. Technical advances in imaging technologies including multiphoton microscopy and 3D tissue reconstructions are being combined with computational approaches to provide new insights into the process of cell migration and function in immunological tissues.