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Arthritis Research UK has approved a 5-year renewal of the OA Centre.
Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming.
OBJECTIVES: An interferon (IFN) gene signature (IGS) is present in approximately 50% of early, treatment naive rheumatoid arthritis (eRA) patients where it has been shown to negatively impact initial response to treatment. We wished to validate this effect and explore potential mechanisms of action. METHODS: In a multicentre inception cohort of eRA patients (n=191), we examined the whole blood IGS (MxA, IFI44L, OAS1, IFI6, ISG15) with reference to circulating IFN proteins, clinical outcomes and epigenetic influences on circulating CD19+ B and CD4+ T lymphocytes. RESULTS: We reproduced our previous findings demonstrating a raised baseline IGS. We additionally showed, for the first time, that the IGS in eRA reflects circulating IFN-α protein. Paired longitudinal analysis demonstrated a significant reduction between baseline and 6-month IGS and IFN-α levels (p<0.0001 for both). Despite this fall, a raised baseline IGS predicted worse 6-month clinical outcomes such as increased disease activity score (DAS-28, p=0.025) and lower likelihood of a good EULAR clinical response (p=0.034), which was independent of other conventional predictors of disease activity and clinical response. Molecular analysis of CD4+ T cells and CD19+ B cells demonstrated differentially methylated CPG sites and dysregulated expression of disease relevant genes, including PARP9, STAT1, and EPSTI1, associated with baseline IGS/IFNα levels. Differentially methylated CPG sites implicated altered transcription factor binding in B cells (GATA3, ETSI, NFATC2, EZH2) and T cells (p300, HIF1α). CONCLUSIONS: Our data suggest that, in eRA, IFN-α can cause a sustained, epigenetically mediated, pathogenic increase in lymphocyte activation and proliferation, and that the IGS is, therefore, a robust prognostic biomarker. Its persistent harmful effects provide a rationale for the initial therapeutic targeting of IFN-α in selected patients with eRA.
Three-dimensional, in-vitro approaches for modelling soft-tissue joint diseases
Diseases affecting the soft tissues of the joint represent a considerable global health burden, causing pain and disability and increasing the likelihood of developing metabolic comorbidities. Current approaches to investigating the cellular basis of joint diseases, including osteoarthritis, rheumatoid arthritis, tendinopathy, and arthrofibrosis, involve well phenotyped human tissues, animal disease models, and in-vitro tissue culture models. Inherent challenges in preclinical drug discovery have driven the development of state-of-the-art, in-vitro human tissue models to rapidly advance therapeutic target discovery. The clinical potential of such models has been substantiated through successful recapitulation of the pathobiology of cancers, generating accurate predictions of patient responses to therapeutics and providing a basis for equivalent musculoskeletal models. In this Review, we discuss the requirement to develop physiologically relevant three-dimensional (3D) culture systems that could advance understanding of the cellular and molecular basis of diseases that affect the soft tissues of the joint. We discuss the practicalities and challenges associated with modelling the complex extracellular matrix of joint tissues—including cartilage, synovium, tendon, and ligament—highlighting the importance of considering the joint as a whole organ to encompass crosstalk across tissues and between diverse cell types. The design of bespoke in-vitro models for soft-tissue joint diseases has the potential to inform functional studies of the cellular and molecular mechanisms underlying disease onset, progression, and resolution. Use of these models could inform precision therapeutic targeting and advance the field towards personalised medicine for patients with common musculoskeletal diseases.
In vivo human keyhole limpet hemocyanin challenge in early phase drug development: A systematic review.
Experimental exposure of healthy volunteers to the T-cell dependent neoantigen keyhole limpet hemocyanin (KLH) permits the evaluation of immunomodulatory investigational medicinal product (IMP) pharmacology prior to the recruitment of patient populations. Despite widespread use, no standardized approach to the design and conduct of such studies has been agreed. The objective of this systematic review was to survey the published literature where KLH was used as a challenge agent, describing methodology, therapeutic targets addressed, and pharmacodynamic outcome measures. We searched MEDLINE, EMBASE, clinicaltrials.gov, and Cochrane CENTRAL for studies using KLH challenge in humans between January 1, 1994, and April 1, 2022. We described key study features, including KLH formulation, dose, use of adjuvants, route of administration, co-administered IMPs, and end points. Of 2421 titles and abstracts screened, 46 met the inclusion criteria, including 14 (31%) early phase trials of IMP, of which 10 (71%) targeted T-cell co-stimulation. IMPs with diverse mechanisms demonstrated modulation of the humoral response to KLH, suggesting limited specificity of this end point. Two early phase IMP studies (14%) described the response to intradermal re-challenge (delayed type hypersensitivity). Challenge regimens for IMP assessment were often incompletely described, and exhibited marked heterogeneity, including primary KLH dose (25-fold variation: 100-2500 mcg), KLH formulation, and co-administration with adjuvants. Methodological heterogeneity and failure to exploit the access to tissue-level mechanism-relevant end points afforded by KLH challenge has impaired the translational utility of this paradigm to date. Future standardization, characterization, and methodological development is required to permit tailored, appropriately powered, mechanism-dependent study design to optimize drug development decisions.
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.
In vivo human keyhole limpet haemocyanin challenge in early phase drug development: A systematic review
Experimental exposure of healthy volunteers to the T-cell dependent neoantigen Keyhole Limpet Haemocyanin (KLH) permits the evaluation of immunomodulatory investigational medicinal product (IMP) pharmacology prior to the recruitment of patient populations. Despite widespread use, no standardized approach to the design and conduct of such studies has been agreed. The objective of this systematic review was to review the published literature where KLH was employed as a challenge agent, describing methodology, therapeutic targets addressed, and pharmacodynamic outcome measures. We searched MEDLINE, EMBASE, clinicaltrials.gov, and Cochrane CENTRAL for studies employing KLH challenge in humans between 1 January 1994 and 1 April 2022. We described key study features, including KLH formulation, dose, use of adjuvants, route of administration, co-administered IMPs and endpoints. Of 2421 titles and abstracts screened, 46 met the inclusion criteria including 14 (31%) early phase trials of IMP, of which 10 (71%) targeted T-cell co-stimulation. IMPs with diverse mechanisms demonstrated modulation of the humoral response to KLH, suggesting limited specificity of this endpoint. Two early phase IMP studies (14%) described the response to intradermal re-challenge (delayed type hypersensitivity). Challenge regimens for IMP assessment were often incompletely described, and exhibited marked heterogeneity, including primary KLH dose (25-fold variation: 100-2500mcg), KLH formulation, and co-administration with adjuvants. Methodological heterogeneity and failure to exploit the access to tissue-level mechanism-relevant endpoints afforded by KLH challenge has impaired the translational utility of this paradigm to-date. Future standardisation, characterisation and methodological development is required to permit tailored, appropriately powered, mechanism-dependent study design to optimise drug development decisions.
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.
Namilumab or infliximab compared with standard of care in hospitalised patients with COVID-19 (CATALYST): a randomised, multicentre, multi-arm, multistage, open-label, adaptive, phase 2, proof-of-concept trial.
BACKGROUND: Dysregulated inflammation is associated with poor outcomes in COVID-19. We aimed to assess the efficacy of namilumab (a granulocyte-macrophage colony stimulating factor inhibitor) and infliximab (a tumour necrosis factor inhibitor) in hospitalised patients with COVID-19, to prioritise agents for phase 3 trials. METHODS: In this randomised, multicentre, multi-arm, multistage, parallel-group, open-label, adaptive, phase 2, proof-of-concept trial (CATALYST), we recruited patients (aged ≥16 years) admitted to hospital with COVID-19 pneumonia and C-reactive protein (CRP) concentrations of 40 mg/L or greater, at nine hospitals in the UK. Participants were randomly assigned with equal probability to usual care or usual care plus a single intravenous dose of namilumab (150 mg) or infliximab (5 mg/kg). Randomisation was stratified by care location within the hospital (ward vs intensive care unit [ICU]). Patients and investigators were not masked to treatment allocation. The primary endpoint was improvement in inflammation, measured by CRP concentration over time, analysed using Bayesian multilevel models. This trial is now complete and is registered with ISRCTN, 40580903. FINDINGS: Between June 15, 2020, and Feb 18, 2021, we screened 299 patients and 146 were enrolled and randomly assigned to usual care (n=54), namilumab (n=57), or infliximab (n=35). For the primary outcome, 45 patients in the usual care group were compared with 52 in the namilumab group, and 29 in the usual care group were compared with 28 in the infliximab group. The probabilities that the interventions were superior to usual care alone in reducing CRP concentration over time were 97% for namilumab and 15% for infliximab; the point estimates for treatment-time interactions were -0·09 (95% CI -0·19 to 0·00) for namilumab and 0·06 (-0·05 to 0·17) for infliximab. 134 adverse events occurred in 30 (55%) of 55 patients in the namilumab group compared with 145 in 29 (54%) of 54 in the usual care group. 102 adverse events occurred in 20 (69%) of 29 patients in the infliximab group compared with 112 in 17 (50%) of 34 in the usual care group. Death occurred in six (11%) patients in the namilumab group compared with ten (19%) in the usual care group, and in four (14%) in the infliximab group compared with five (15%) in the usual care group. INTERPRETATION: Namilumab, but not infliximab, showed proof-of-concept evidence for reduction in inflammation-as measured by CRP concentration-in hospitalised patients with COVID-19 pneumonia. Namilumab should be prioritised for further investigation in COVID-19. FUNDING: Medical Research Council.
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.
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.
Checkpoint-blocker-induced autoimmunity is associated with favourable outcome in metastatic melanoma and distinct T-cell expression profiles.
BACKGROUND: Immune checkpoint blockers (ICBs) activate CD8+ T cells, eliciting both anti-cancer activity and immune-related adverse events (irAEs). The relationship of irAEs with baseline parameters and clinical outcome is unclear. METHODS: Retrospective evaluation of irAEs on survival was performed across primary (N = 144) and secondary (N = 211) independent cohorts of patients with metastatic melanoma receiving single agent (pembrolizumab/nivolumab-sICB) or combination (nivolumab and ipilimumab-cICB) checkpoint blockade. RNA from pre-treatment and post-treatment CD8+ T cells was sequenced and differential gene expression according to irAE development assessed. RESULTS: 58.3% of patients developed early irAEs and this was associated with longer progression-free (PFS) and overall survival (OS) across both cohorts (log-rank test, OS: P
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.
Two distinct clinical patterns of checkpoint inhibitor-induced thyroid dysfunction.
INTRODUCTION: Immune checkpoint inhibitors can lead to thyroid dysfunction. However, the understanding of the clinical phenotype of ICI-induced thyroid dysfunction in the real-world population is limited. The purpose of this study was to characterise the clinical patterns of dysfunction and evaluate the demographic, biochemical and immunological features associated with this patient cohort. MATERIALS AND METHODS: To characterise the longitudinal clinical course of thyroid dysfunction in patients from a single, UK regional cancer centre, a retrospective review of patients was conducted. Inclusion criteria included all patients treated with antiPD-1 checkpoint inhibitors (ICI), either as monotherapy (pembrolizumab/nivolumab) or in combination with a CTLA-4 inhibitor (ipilimumab). Patterns of toxicity were evaluated together with assessment of antibody titres. RESULTS: Over 16 months, thyroid dysfunction was seen in 13/90 and 3/13 patients treated with anti-PD1 monotherapy and in combination with ipilimumab, respectively. Patients either developed hyperthyroidism followed by hypothyroidism (12/16) or de novo hypothyroidism (4/16). Most patients were female (n = 11). All patients required thyroid replacement therapy. There was no relationship between clinical pattern of dysfunction and the presence of thyroid autoantibodies. CONCLUSIONS: There are two distinct patterns of thyroid dysfunction in ICI-treated patients. Patients with thyroiditis develop subsequent hypothyroidism in the vast majority of cases. The potential benefit from steroids or other therapy to manage the hyperthyroid phase remains unclear. Early detection of these patients through appropriate monitoring will improve clinical management and early hormone replacement, reducing the symptomatic burden of hypothyroidism.
Novel methodology to discern predictors of remission and patterns of disease activity over time using rheumatoid arthritis clinical trials data.
OBJECTIVES: To identify predictors of remission and disease activity patterns in patients with rheumatoid arthritis (RA) using individual participant data (IPD) from clinical trials. METHODS: Phase II and III clinical trials completed between 2002 and 2012 were identified by systematic literature review and contact with UK market authorisation holders. Anonymised baseline and follow-up IPD from non-biological arms were amalgamated. Multiple imputation was used to handle missing outcome and covariate information. Random effects logistic regression was used to identify predictors of remission, measured by the Disease Activity Score 28 (DAS28) at 6 months. Novel latent class mixed models characterised DAS28 over time. RESULTS: IPD of 3290 participants from 18 trials were included. Of these participants, 92% received methotrexate (MTX). Remission rates were estimated at 8.4%(95%CI 7.4%to9.5%) overall, 17%(95%CI 14.8%to19.4%) for MTX-naïve patients with early RA and 3.2% (95% CI 2.4% to 4.3%) for those with prior MTX exposure at entry. In prior MTX-exposed patients, lower baseline DAS28 and MTX reinitiation were associated with remission. In MTX-naïve patients, being young, white, male, with better functional and mental health, lower baseline DAS28 and receiving concomitant glucocorticoids were associated with remission. Three DAS28 trajectory subpopulations were identified in MTX-naïve and MTX-exposed patients. A number of variables were associated with subpopulation membership and DAS28 levels within subpopulations. CONCLUSIONS: Predictors of remission differed between MTX-naïve and prior MTX-exposed patients at entry. Latent class mixed models supported differential non-biological therapy response, with three distinct trajectories observed in both MTX-naïve and MTX-exposed patients. Findings should be useful when designing future RA trials and interpreting results of biomarker studies.
Ultra-fast super-resolution imaging of biomolecular mobility in tissues
Super-resolution techniques have addressed many biological questions, yet molecular quantification at rapid timescales in live tissues remains challenging. We developed a light microscopy system capable of sub-millisecond sampling to characterize molecular diffusion in heterogeneous aqueous environments comparable to interstitial regions between cells in tissues. We demonstrate our technique with super-resolution tracking of fluorescently labelled chemokine molecules in a collagen matrix and ex vivo lymph node tissue sections, outperforming competing methods.
Molecular and spatial analysis of tertiary lymphoid structures in Sjogren's syndrome.
Tertiary lymphoid structures play important roles in autoimmune and non-autoimmune conditions. While many of the molecular mechanisms involved in tertiary lymphoid structure formation have been identified, the cellular sources and temporal and spatial relationship remain unknown. Here we use combine single-cell RNA-sequencing, spatial transcriptomics and proteomics of minor salivary glands of patients with Sjogren's disease and Sicca Syndrome, with ex-vivo functional studies to construct a cellular and spatial map of key components involved in the formation and function of tertiary lymphoid structures. We confirm the presence of a fibroblast cell state and identify a pericyte/mural cell state with potential immunological functions. The identification of cellular properties associated with these structures and the molecular and functional interactions identified by this analysis may provide key therapeutic cues for tertiary lymphoid structures associated conditions in autoimmunity and cancer.
Why does understanding the biology of fibroblasts in immunity really matter?
Fibroblasts are known for their ability to make and modify the extracellular matrix. However, there is more to them than meets the eye. It is now clear that they help define tissue microenvironments and support immune responses in organs. As technology advances, we have started to uncover the secrets of fibroblasts. In this Essay, we present fibroblasts as not only the builders and renovators of tissue environments but also the rheostat cells for immune circuits. Although they perform location-specific functions, they do not have badges of fixed identity. Instead, they display a spectrum of functional states and can swing between these states depending on the needs of the organ. As fibroblasts participate in a range of activities both in health and disease, finding the key factors that alter their development and functional states will be an important goal to restore homeostasis in maladapted tissues.
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19.
BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49-7·33], p=0·0033; and 2·58 [1·10-6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16-31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69-7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. INTERPRETATION: Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. FUNDING: Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.
A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19.
The future of traction force microscopy
Animal cells continuously sense and respond to mechanical force. Quantifying these forces remains a major challenge in bioengineering; yet such measurements are essential for the understanding of cellular function. Traction force microscopy is one of the most successful and broadly-used force probing technologies, chosen for the simplicity of its implementation, flexibility to mimic cellular conditions, and well-established analysis pipe-line. Here, we review the accomplishments, and discuss the applicability and limitations of traction force microscopy. We explain fundamental shortcomings of the method, summarise latest improvements, and outline future pathways towards the impact of the method, especially considering latest developments in state-of-the-art super-resolution fluorescence imaging. In light of the increasing discovery of the importance of mechanobiology in cell physiology, we envisage traction force microscopy to remain a major player for quantifying mechanical forces in living cells.
Quantifying Immune Cell Force Generation Using Traction Force Microscopy.
Immune cells rely on the generation of mechanical force to carry out their function. Consequently, there is a pressing need for quantitative methodologies that permit the probing of the spatio-temporal distribution of mechanical forces generated by immune cells. In this chapter, we provide a guide to quantify immune cell force generation using traction force microscopy (TFM), with a specific focus on its application to the study of the T-cell immunological synapse.