Ex vivo tissue perturbations coupled to single-cell RNA-seq reveal multilineage cell circuit dynamics in human lung fibrogenesis.

Pulmonary fibrosis develops as a consequence of failed regeneration after injury. Analyzing mechanisms of regeneration and fibrogenesis directly in human tissue has been hampered by the lack of organotypic models and analytical techniques. In this work, we coupled ex vivo cytokine and drug perturbations of human precision-cut lung slices (hPCLS) with single-cell RNA sequencing and induced a multilineage circuit of fibrogenic cell states in hPCLS. We showed that these cell states were highly similar to the in vivo cell circuit in a multicohort lung cell atlas from patients with pulmonary fibrosis. Using micro-CT-staged patient tissues, we characterized the appearance and interaction of myofibroblasts, an ectopic endothelial cell state, and basaloid epithelial cells in the thickened alveolar septum of early-stage lung fibrosis. Induction of these states in the hPCLS model provided evidence that the basaloid cell state was derived from alveolar type 2 cells, whereas the ectopic endothelial cell state emerged from capillary cell plasticity. Cell-cell communication routes in patients were largely conserved in hPCLS, and antifibrotic drug treatments showed highly cell type-specific effects. Our work provides an experimental framework for perturbational single-cell genomics directly in human lung tissue that enables analysis of tissue homeostasis, regeneration, and pathology. We further demonstrate that hPCLS offer an avenue for scalable, high-resolution drug testing to accelerate antifibrotic drug development and translation.

Multilineage circuits of regenerative cell states.

Regenerating the lungs' architecture after injury requires rebuilding its fibroelastic extracellular matrix scaffold. Konkimalla et al. establish that regenerative cell states (RCSs) of both epithelial and mesenchymal origin are functionally linked and indispensable for this process. Experimental ablation of RCSs causes organ degeneration, whereas their induction causes organ fibrosis.

Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome.

Single-cell proteomics by mass spectrometry is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed mass spectrometry. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a cell slice. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics and spatial omics technologies.

An integrated cell atlas of the lung in health and disease.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Transferability of radiomic signatures from experimental to human interstitial lung disease.

Background: Interstitial lung disease (ILD) defines a group of parenchymal lung disorders, characterized by fibrosis as their common final pathophysiological stage. To improve diagnosis and treatment of ILD, there is a need for repetitive non-invasive characterization of lung tissue by quantitative parameters. In this study, we investigated whether CT image patterns found in mice with bleomycin induced lung fibrosis can be translated as prognostic factors to human patients diagnosed with ILD. Methods: Bleomycin was used to induce lung fibrosis in mice (n_control = 36, n_experimental = 55). The patient cohort consisted of 98 systemic sclerosis (SSc) patients (n_ILD = 65). Radiomic features (n_histogram = 17, n_texture = 137) were extracted from microCT (mice) and HRCT (patients) images. Predictive performance of the models was evaluated with the area under the receiver-operating characteristic curve (AUC). First, predictive performance of individual features was examined and compared between murine and patient data sets. Second, multivariate models predicting ILD were trained on murine data and tested on patient data. Additionally, the models were reoptimized on patient data to reduce the influence of the domain shift on the performance scores. Results: Predictive power of individual features in terms of AUC was highly correlated between mice and patients (r = 0.86). A model based only on mean image intensity in the lung scored AUC = 0.921 ± 0.048 in mice and AUC = 0.774 (CI95% 0.677-0.859) in patients. The best radiomic model based on three radiomic features scored AUC = 0.994 ± 0.013 in mice and validated with AUC = 0.832 (CI95% 0.745-0.907) in patients. However, reoptimization of the model weights in the patient cohort allowed to increase the model's performance to AUC = 0.912 ± 0.058. Conclusion: Radiomic signatures of experimental ILD derived from microCT scans translated to HRCT of humans with SSc-ILD. We showed that the experimental model of BLM-induced ILD is a promising system to test radiomic models for later application and validation in human cohorts.

CellRank for directed single-cell fate mapping.

Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank ( https://cellrank.org ) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.

The discovAIR project: a roadmap towards the Human Lung Cell Atlas.

The Human Cell Atlas (HCA) consortium aims to establish an atlas of all organs in the healthy human body at single-cell resolution to increase our understanding of basic biological processes that govern development, physiology and anatomy, and to accelerate diagnosis and treatment of disease. The Lung Biological Network of the HCA aims to generate the Human Lung Cell Atlas as a reference for the cellular repertoire, molecular cell states and phenotypes, and cell-cell interactions that characterise normal lung homeostasis in healthy lung tissue. Such a reference atlas of the healthy human lung will facilitate mapping the changes in the cellular landscape in disease. The discovAIR project is one of six pilot actions for the HCA funded by the European Commission in the context of the H2020 framework programme. discovAIR aims to establish the first draft of an integrated Human Lung Cell Atlas, combining single-cell transcriptional and epigenetic profiling with spatially resolving techniques on matched tissue samples, as well as including a number of chronic and infectious diseases of the lung. The integrated Human Lung Cell Atlas will be available as a resource for the wider respiratory community, including basic and translational scientists, clinical medicine, and the private sector, as well as for patients with lung disease and the interested lay public. We anticipate that the Human Lung Cell Atlas will be the founding stone for a more detailed understanding of the pathogenesis of lung diseases, guiding the design of novel diagnostics and preventive or curative interventions.

Computed tomography-based radiomics decodes prognostic and molecular differences in interstitial lung disease related to systemic sclerosis.

BACKGROUND: Radiomic features calculated from routine medical images show great potential for personalised medicine in cancer. Patients with systemic sclerosis (SSc), a rare, multiorgan autoimmune disorder, have a similarly poor prognosis due to interstitial lung disease (ILD). Here, our objectives were to explore computed tomography (CT)-based high-dimensional image analysis ("radiomics") for disease characterisation, risk stratification and relaying information on lung pathophysiology in SSc-ILD. METHODS: We investigated two independent, prospectively followed SSc-ILD cohorts (Zurich, derivation cohort, n=90; Oslo, validation cohort, n=66). For every subject, we defined 1355 robust radiomic features from standard-of-care CT images. We performed unsupervised clustering to identify and characterise imaging-based patient clusters. A clinically applicable prognostic quantitative radiomic risk score (qRISSc) for progression-free survival (PFS) was derived from radiomic profiles using supervised analysis. The biological basis of qRISSc was assessed in a cross-species approach by correlation with lung proteomic, histological and gene expression data derived from mice with bleomycin-induced lung fibrosis. RESULTS: Radiomic profiling identified two clinically and prognostically distinct SSc-ILD patient clusters. To evaluate the clinical applicability, we derived and externally validated a binary, quantitative radiomic risk score (qRISSc) composed of 26 features that accurately predicted PFS and significantly improved upon clinical risk stratification parameters in multivariable Cox regression analyses in the pooled cohorts. A high qRISSc score, which identifies patients at risk for progression, was reverse translatable from human to experimental ILD and correlated with fibrotic pathway activation. CONCLUSIONS: Radiomics-based risk stratification using routine CT images provides complementary phenotypic, clinical and prognostic information significantly impacting clinical decision making in SSc-ILD.

Elevated Fibronectin Levels in Profibrotic CD14+ Monocytes and CD14+ Macrophages in Systemic Sclerosis.

Background: Systemic sclerosis (SSc) is an autoimmune disease characterized by overproduction of extracellular matrix (ECM) and multiorgan fibrosis. Animal studies pointed to bone marrow-derived cells as a potential source of pathological ECM-producing cells in immunofibrotic disorders. So far, involvement of monocytes and macrophages in the fibrogenesis of SSc remains poorly understood. Methods and Results: Immunohistochemistry analysis showed accumulation of CD14+ monocytes in the collagen-rich areas, as well as increased amount of alpha smooth muscle actin (αSMA)-positive fibroblasts, CD68+ and mannose-R+ macrophages in the heart and lungs of SSc patients. The full genome transcriptomics analyses of CD14+ blood monocytes revealed dysregulation in cytoskeleton rearrangement, ECM remodeling, including elevated FN1 (gene encoding fibronectin) expression and TGF-ß signalling pathway in SSc patients. In addition, single cell RNA sequencing analysis of tissue-resident CD14+ pulmonary macrophages demonstrated activated profibrotic signature with the elevated FN1 expression in SSc patients with interstitial lung disease. Peripheral blood CD14+ monocytes obtained from either healthy subjects or SSc patients exposed to profibrotic treatment with profibrotic cytokines TGF-ß, IL-4, IL-10, and IL-13 increased production of type I collagen, fibronectin, and αSMA. In addition, CD14+ monocytes co-cultured with dermal fibroblasts obtained from SSc patients or healthy individuals acquired a spindle shape and further enhanced production of profibrotic markers. Pharmacological blockade of the TGF-ß signalling pathway with SD208 (TGF-ß receptor type I inhibitor), SIS3 (Smad3 inhibitor) or (5Z)-7-oxozeaenol (TGF-ß-activated kinase 1 inhibitor) ameliorated fibronectin levels and type I collagen secretion. Conclusions: Our findings identified activated profibrotic signature with elevated production of profibrotic fibronectin in CD14+ monocytes and CD14+ pulmonary macrophages in SSc and highlighted the capability of CD14+ monocytes to acquire a profibrotic phenotype. Taking together, tissue-infiltrating CD14+ monocytes/macrophages can be considered as ECM producers in SSc pathogenesis.

Staphylococcus aureus impairs dermal fibroblast functions with deleterious effects on wound healing.

Chronic wounds are a major disease burden worldwide. The breach of the epithelial barrier facilitates transition of skin commensals to invasive facultative pathogens. Therefore, we investigated the potential effects of Staphylococcus aureus (SA) on dermal fibroblasts as key cells for tissue repair. In co-culture systems combining live or heat-killed SA with dermal fibroblasts derived from the BJ-5ta cell line, healthy individuals, and patients with systemic sclerosis, we assessed tissue repair including pro-inflammatory cytokines, matrix metalloproteases (MMPs), myofibroblast functions, and host defense responses. Only live SA induced the upregulation of IL-1ß/-6/-8 and MMP1/3 as co-factors of tissue degradation. Additionally, the increased cell death reduced collagen production, proliferation, migration, and contractility, prerequisite mechanisms for wound closure. Intracellular SA triggered inflammatory and type I IFN responses via intracellular dsDNA sensor molecules and MyD88 and STING signaling pathways. In conclusion, live SA affected various key tissue repair functions of dermal fibroblasts from different sources to a similar extent. Thus, SA infection of dermal fibroblasts should be taken into account for future wound management strategies.

Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers.

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type-2 epithelial cell health status in lavage fluid and plasma. Using cross-modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.

Impact of CT convolution kernel on robustness of radiomic features for different lung diseases and tissue types.

OBJECTIVES: In this study, we aimed to assess the impact of different CT reconstruction kernels on the stability of radiomic features and the transferability between different diseases and tissue types. Three lung diseases were evaluated, i.e. non-small cell lung cancer (NSCLC), malignant pleural mesothelioma (MPM) and interstitial lung disease related to systemic sclerosis (SSc-ILD) as well as four different tissue types, i.e. primary tumor, largest involved lymph node ipsilateral and contralateral lung. METHODS: Pre-treatment non-contrast enhanced CT scans from 23 NSCLC, 10 MPM and 12 SSc-ILD patients were collected retrospectively. For each patient, CT scans were reconstructed using smooth and sharp kernel in filtered back projection. The regions of interest (ROIs) were contoured on the smooth kernel-based CT and transferred to the sharp kernel-based CT. The voxels were resized to the largest voxel dimension of each cohort. In total, 1386 features were analyzed. Feature stability was assessed using the intraclass correlation coefficient. Features above the stability threshold >0.9 were considered stable. RESULTS: We observed a strong impact of the reconstruction method on stability of the features (at maximum 26% of the 1386 features were stable). Intensity features were the most stable followed by texture and wavelet features. The wavelet features showed a positive correlation between percentage of stable features and size of the ROI (R2 = 0.79, p = 0.005). Lymph node radiomics showed poorest stability (<10%) and lung radiomics the largest stability (26%). Robustness analysis done on the contralateral lung could to a large extent be transferred to the ipsilateral lung, and the overlap of stable lung features between different lung diseases was more than 50%. However, results of robustness studies cannot be transferred between tissue types, which was investigated in NSCLC and MPM patients; the overlap of stable features for lymph node and lung, as well as for primary tumor and lymph node was very small in both disease types. CONCLUSION: The robustness of radiomic features is strongly affected by different reconstruction kernels. The effect is largely influenced by the tissue type and less by the disease type. ADVANCES IN KNOWLEDGE: The study presents to our knowledge the most complete analysis on the impact of convolution kernel on the robustness of CT-based radiomics for four relevant tissue types in three different lung diseases. .

Long noncoding RNA H19X is a key mediator of TGF-ß-driven fibrosis.

TGF-ß is a master regulator of fibrosis, driving the differentiation of fibroblasts into apoptosis-resistant myofibroblasts and sustaining the production of extracellular matrix (ECM) components. Here, we identified the nuclear long noncoding RNA (lncRNA) H19X as a master regulator of TGF-ß-driven tissue fibrosis. H19X was consistently upregulated in a wide variety of human fibrotic tissues and diseases and was strongly induced by TGF-ß, particularly in fibroblasts and fibroblast-related cells. Functional experiments following H19X silencing revealed that H19X was an obligatory factor for TGF-ß-induced ECM synthesis as well as differentiation and survival of ECM-producing myofibroblasts. We showed that H19X regulates DDIT4L gene expression, specifically interacting with a region upstream of the DDIT4L gene and changing the chromatin accessibility of a DDIT4L enhancer. These events resulted in transcriptional repression of DDIT4L and, in turn, in increased collagen expression and fibrosis. Our results shed light on key effectors of TGF-ß-induced ECM remodeling and fibrosis.

18F-AzaFol for Detection of Folate Receptor-ß Positive Macrophages in Experimental Interstitial Lung Disease-A Proof-of-Concept Study.

Background: Interstitial lung disease (ILD) is a common and severe complication in rheumatic diseases. Folate receptor-ß is expressed on activated, but not resting macrophages which play a key role in dysregulated tissue repair including ILD. We therefore aimed to pre-clinically evaluate the potential of 18F-AzaFol-based PET/CT (positron emission computed tomography/computed tomography) for the specific detection of macrophage-driven pathophysiologic processes in experimental ILD. Methods: The pulmonary expression of folate receptor-ß was analyzed in patients with different subtypes of ILD as well as in bleomycin (BLM)-treated mice and respective controls using immunohistochemistry. PET/CT was performed at days 3, 7, and 14 after BLM instillation using the 18F-based folate radiotracer 18F-AzaFol. The specific pulmonary accumulation of the radiotracer was assessed by ex vivo PET/CT scans and quantified by ex vivo biodistribution studies. Results: Folate receptor-ß expression was 3- to 4-fold increased in patients with fibrotic ILD, including idiopathic pulmonary fibrosis and connective tissue disease-related ILD, and significantly correlated with the degree of lung remodeling. A similar increase in the expression of folate receptor-ß was observed in experimental lung fibrosis, where it also correlated with disease extent. In the mouse model of BLM-induced ILD, pulmonary accumulation of 18F-AzaFol reflected macrophage-related disease development with good correlation of folate receptor-ß positivity with radiotracer uptake. In the ex vivo imaging and biodistribution studies, the maximum lung accumulation was observed at day 7 with a mean accumulation of 1.01 ± 0.30% injected activity/lung in BLM-treated vs. control animals (0.31 ± 0.06% % injected activity/lung; p < 0.01). Conclusion: Our preclinical proof-of-concept study demonstrated the potential of 18F-AzaFol as a novel imaging tool for the visualization of macrophage-driven fibrotic lung diseases.

Visualisation of interstitial lung disease by molecular imaging of integrin αvß3 and somatostatin receptor 2.

OBJECTIVE: To evaluate integrin αvß3 (alpha-v-beta-3)-targeted and somatostatin receptor 2 (SSTR2)-targeted nuclear imaging for the visualisation of interstitial lung disease (ILD). METHODS: The pulmonary expression of integrin αvß3 and SSTR2 was analysed in patients with different forms of ILD as well as in bleomycin (BLM)-treated mice and respective controls using immunohistochemistry. Single photon emission CT/CT (SPECT/CT) was performed on days 3, 7 and 14 after BLM instillation using the integrin αvß3-targeting 177Lu-DOTA-RGD and the SSTR2-targeting 177Lu-DOTA-NOC radiotracer. The specific pulmonary accumulation of the radiotracers over time was assessed by in vivo and ex vivo SPECT/CT scans and by biodistribution studies. RESULTS: Expression of integrin αvß3 and SSTR2 was substantially increased in human ILD regardless of the subtype. Similarly, in lungs of BLM-challenged mice, but not of controls, both imaging targets were stage-specifically overexpressed. While integrin αvß3 was most abundantly upregulated on day 7, the inflammatory stage of BLM-induced lung fibrosis, SSTR2 expression peaked on day 14, the established fibrotic stage. In agreement with the findings on tissue level, targeted nuclear imaging using SPECT/CT specifically detected both imaging targets ex vivo and in vivo, and thus visualised different stages of experimental ILD. CONCLUSION: Our preclinical proof-of-concept study suggests that specific visualisation of molecular processes in ILD by targeted nuclear imaging is feasible. If transferred into clinics, where imaging is considered an integral part of patients' management, the additional information derived from specific imaging tools could represent a first step towards precision medicine in ILD.

In Vivo Labeling of Plasma Proteins for Imaging of Enhanced Vascular Permeability in the Lungs.

Increased vascular permeability is an important hallmark of many diseases, including cancer, cerebral ischemia, and severe inflammatory disorders. In this regard, the noninvasive assessment of pathologically increased vascular permeability in vivo is of great interest. In this study, the potential of albumin- and transthyretin-binding radioligands was evaluated for imaging of vascular hyperpermeability. For this purpose, the bleomycin-induced lung injury model was used as a model of inflammation-associated vascular leakage. The plasma protein-binding ligands, which bind to albumin (DOTA-PPB-01) and transthyretin (DOTA-PPB-03), were radiolabeled and used for nuclear imaging and biodistribution studies. In this regard, 177Lu was employed as a surrogate nuclide for detailed preclinical investigations, including single-photon emission computed tomography (SPECT) studies, whereas 44Sc was proposed as a radionuclide for positron emission tomography (PET), which may be relevant for future clinical translation. Mice were administered with these radioligands 6-9 days after intratracheal instillation of bleomycin or saline. Bleomycin-treated mice developed pronounced lung inflammation with enhanced vascular permeability that was reflected in significantly increased lung size and weight due to edema and infiltration with inflammatory cells. Biodistribution studies revealed significantly higher accumulation of 177Lu-DOTA-PPB-01 in injured lungs as compared to lungs of control animals at all investigated time points (4-48 h p.i.). The best contrast was achieved at late time points (16.1 ± 2.91% IA/g vs 2.03 ± 1.22% IA/g, 48 h p.i.) when the blood activity levels were ∼7.5% IA/g. Injection of 177Lu-DOTA-PPB-03 also resulted in increased lung accumulation in bleomycin-treated mice at all investigated time points (2-8 h p.i.). The pharmacokinetics was significantly faster, however, resulting in good contrast already at 8 h p.i. (4.32 ± 0.85% IA/g vs 1.06 ± 0.10% IA/g) when blood activity levels were ∼2% IA/g. The absolute lung accumulation of 177Lu-DOTA-PPB-03 was significantly lower than that of 177Lu-DOTA-PPB-01. PET/CT scans performed with 44Sc-DOTA-PPB-01 distinguished injured from healthy lungs only at late time points (20 h p.i.), whereas 44Sc-DOTA-PPB-03 already allowed the differentiation at 4 h p.i. due to its faster clearance. The investigated radioligands, 44Sc/177Lu-DOTA-PPB-01 and 44Sc/177Lu-DOTA-PPB-03, hold promise for the visualization of vascular leakage in a variety of pathological conditions. 44Sc would be the radionuclide of choice for clinical application as it can be stably coordinated with a DOTA chelator and enables PET imaging over extended periods.

Evaluation of 99mTc-rhAnnexin V-128 SPECT/CT as a diagnostic tool for early stages of interstitial lung disease associated with systemic sclerosis.

BACKGROUND: Given the need for early detection of organ involvement in systemic sclerosis, we evaluated 99mTc-rhAnnexin V-128 for the detection of early stages of interstitial lung disease (ILD) in respective animal models using single photon emission computed tomography (SPECT/CT). METHODS: In bleomycin (BLM)-challenged mice, fos-related antigen 2 (Fra-2) transgenic (tg) mice and respective controls, lung injury was evaluated by analysis of hematoxylin and eosin (HE) and Sirius red staining, with semi-quantification of fibrosis by the Ashcroft score. Apoptotic cells were identified by TUNEL assay, cleaved caspase 3 staining and double staining with specific cell markers. To detect early stages of lung remodeling by visualization of apoptosis, mice were injected intravenously with 99mTc-rhAnnexin V-128 and imaged by small animal SPECT/CT. For confirmation, biodistribution and ex vivo autoradiography studies were performed. RESULTS: In BLM-induced lung fibrosis, inflammatory infiltrates occurred as early as day 3 with peak at day 7, whereas pulmonary fibrosis developed from day 7 and was most pronounced at day 21. In accordance, the number of apoptotic cells was highest at day 3 compared with saline controls and then decreased over time. Epithelial cells (E-cadherin+) and inflammatory cells (CD45+) were the primary cells undergoing apoptosis in the earliest remodeling stages of experimental ILD. This was also true in the pathophysiologically different Fra-2 tg mice, where apoptosis of CD45+ cells occurred in the inflammatory stage. In accordance with the findings on tissue level, at day 3 in the BLM and at week 16 in the Fra-2 tg model, biodistribution and/or ex vivo autoradiography showed increased pulmonary uptake of 99mTc-rhAnnexin V-128 compared with controls. However, accumulation of the radiotracer and thus the signal intensity in lungs was too low to allow the differentiation of healthy and injured lungs in vivo. CONCLUSION: At the tissue level, 99mTc-rhAnnexin V-128 successfully demonstrated early stages of ILD in two animal models by detection of apoptotic epithelial and/or inflammatory cells. In vivo, however, we did not detect early lung injury. It remains to be investigated whether the same applies to human ILD.

Tie2 as a novel key factor of microangiopathy in systemic sclerosis.

BACKGROUND: The angiopoietin(Ang)/Tie2 system is a key regulator of vascular biology. The expression of membrane bound (mb) Tie2 and Ang-1 ensures vessel stability, whereas Ang-2, inducible by vascular endothelial growth factor (VEGF), hypoxia, and inflammation, acts as an antagonist. Tie2 signalling is also attenuated by soluble Tie2 (sTie2), the extracellular domain of the receptor, which is shed upon stimulation with VEGF. Herein, we investigate the role of Ang/Tie2 in the peripheral vasculopathy in systemic sclerosis (SSc) including animal models. METHODS: The expression of Ang-1/-2 and Tie2 in skin/serum of SSc patients was compared with healthy controls by immunohistochemistry (IHC)/ELISA. Expression of Ang/Tie2 was analysed in different animal models: VEGF transgenic (tg) mice, hypoxia model, bleomycin-induced skin fibrosis, and tight skin 1 (TSK1) mice. RESULTS: In SSc, dermal microvessels abundantly expressed Ang-2, but not Ang-1 compared with healthy controls. The percentage of mbTie2+ microvessels was profoundly decreased whereas the levels of sTie2 were increased already in early disease. Both in skin and sera of SSc patients, the Ang1/2 ratio was reduced, being lowest in patients with digital ulcers indicating vessel destabilizing conditions. We next studied potential influencing factors in animal models. The VEGF tg mouse model, the hypoxia, and the inflammation-dependent bleomycin model all showed a similar dysregulation of Ang/Tie2 as in SSc, which did not apply for the non-inflammatory TSK1 model. CONCLUSION: Peripheral microvasculopathy in SSc results from a complex dysregulation of angiogenic signalling networks including the VEGF and the Ang/Tie2 system. The profoundly disturbed Ang-/Tie-2 balance might represent an important target for vascular therapeutic approaches in SSc.

Systemic sclerosis: The need for structured care.

Autoimmune connective tissue diseases (CTDs) have a propensity to affect multiple organ systems as well as physical function, quality of life, and survival. Their clinical heterogeneity, multisystem involvement, and low worldwide prevalence present challenges for researchers to establish a study design to help better understand the course and outcomes of CTDs. Systemic sclerosis (SSc) is a notable example of a CTD, wherein longitudinal cohort studies (LCS) have enabled us to elucidate disease manifestations, disease course, and risk and prognostic factors for clinically important outcomes, by embedding research in clinical practice. Nevertheless, further efforts are needed to better understand SSc especially with regard to recognizing organ involvement early, developing new therapies, optimizing the use of existing therapies, and defining treatment targets. The heterogeneous multi-organ nature of SSc would lend itself well to a structured model of care, wherein step-up treatment algorithms are used with the goal of attaining a prespecified treatment target. In this chapter, we discuss the rationale for a structured treatment approach in SSc and propose possible treatment algorithms for three of the more common disease manifestations, namely skin involvement, digital ulcers and gastrointestinal tract involvement. We discuss possible strategies for evaluating and implementing these algorithms in the setting of LCS. We conclude by presenting a research agenda for the development of structured models of care in SSc.