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Abstract
Rituximab, a B cell-depleting therapy, is indicated for treating a growing number of autoantibody-mediated autoimmune disorders. However, relapses can occur after treatment and autoantibody-producing B cell subsets may be found during relapses. It is not understood if these autoantibody-producing B cell subsets emerge from the failed depletion of pre-existing B cells or are generated de novo. To further define the mechanisms that cause post-rituximab relapse, we studied patients with autoantibody-mediated muscle-specific kinase (MuSK) myasthenia gravis (MG) who relapsed after treatment. We carried out single-cell transcriptional and B cell receptor (BCR) profiling on longitudinal B cell samples. We identified clones present prior to therapy that continued to persist during relapse. Persistent B cell clones included both antibody-secreting cells and memory B cells characterized by gene expression signatures associated with B cell survival. A subset of persistent antibody-secreting cells and memory B cells were specific for the MuSK autoantigen. These results demonstrate that rituximab is not fully effective at eliminating autoantibody-producing B cells and provide a mechanistic understanding of post-rituximab relapse in MuSK MG.
Authors
Ruoyi Jiang, Miriam L. Fichtner, Kenneth B. Hoehn, Minh C. Pham, Panos Stathopoulos, Richard J. Nowak, Steven H. Kleinstein, Kevin C. O'Connor
Abstract
Pancreatic ductal adenocarcinoma (PDA) is a lethal malignancy that has no effective treatment. The tumor microenvironment (TME) of PDA employs a multitude of immune derangement strategies to protect PDA from immune elimination. Tumor associated macrophages (TAMs) have been implicated in pathogenesis of immune suppression of PDA-TME, however, its underlying mechanisms remained largely unknown. Using primary patient samples, our studies showed that in comparison with macrophages isolated from normal pancreatic tissues, the phagocytosis activity of PDA-TAM is significantly reduced. We found that the expression of homeobox protein VentX, a master regulator of macrophage plasticity, is significantly decreased in the PDA-TAMs. We demonstrated that VentX is required for phagocytosis and that restoration of VentX expression in PDA-TAMs promotes phagocytosis through regulating the signaling cascades involved in the process. Using an ex-vivo culture model of primary human PDA, we showed that VentX-modulated-TAMs transformed PDA-TME from a pro-tumor milieu to an anti-tumor microenvironment by rectifying differentiation, proliferation and activation of PDA-infiltrating immune cells. Using NSG-PDX models of primary human PDAs, we showed that VentX-modulated-TAMs exert strong inhibition on PDA tumorigenesis in vivo. Taken together, our data revealed a central mechanism underlying immune evasion of PDA and a potential novel venue to improve PDA prognosis.
Authors
Yi Le, Hong Gao, William G. Richards, Lei Zhao, Ronald Bleday, Thomas Clancy, Zhenglun Zhu
Abstract
T follicular helper (Tfh) cell migration into germinal centers (GC) is essential for the generation of GC B cells and antibody responses to T dependent (TD) antigens. This process requires interactions between LFA-1 on Tfh cells and ICAMs on B cells. The mechanisms underlying defective antibody responses to TD antigens in DOCK8 deficiency are incompletely understood. We show that mice selectively lacking DOCK8 in T cells have impaired IgG antibody responses to TD antigens, decreased GC size, and reduced numbers of GC B cells. However, they develop normal numbers of Tfh cells with intact capacity for driving B cell differentiation into a GC phenotype in vitro. Notably, migration of DOCK8 deficient T cells into GCs is defective. Following TCR/CD3 ligation, DOCK8 deficient T cells have impaired LFA-1 activation and reduced binding to ICAM-1. DOCK8 is important for LFA1-dependent positioning of Tfh cells in GCs, and thereby the generation of GC B cells and IgG antibody responses to TD antigen.
Authors
Erin Janssen, Mira Tohme, Jordan Butts, Sophie S.B. Giguere, Peter T. Sage, Francisco E. Velázquez, Christy Kam, Elena Milin, Mrinmoy Das, Ali Sobh, Salem Al-Tamemi, Francis W. Luscinskas, Facundo Batista, Raif S. Geha
Abstract
Reprogramming of host metabolism supports viral pathogenesis by fueling viral proliferation, by providing, for example, free amino acids and fatty acids as building blocks. To investigate metabolic effects of SARS-COV-2 infection, we evaluated serum metabolites of COVID-19 patients (n = 33; diagnosed by nucleic acid testing), as compared to COVID-19-negative controls (n = 16). Targeted and untargeted metabolomics analyses identified altered tryptophan metabolism into the kynurenine pathway, which regulates inflammation and immunity. Indeed, these changes in tryptophan metabolism correlated with interleukin-6 (IL-6) levels. Widespread dysregulation of nitrogen metabolism was also seen in infected patients, with altered levels of most amino acids, along with increased markers of oxidant stress (e.g., methionine sulfoxide, cystine), proteolysis, and renal dysfunction (e.g., creatine, creatinine, polyamines). Increased circulating levels of glucose and free fatty acids were also observed, consistent with altered carbon homeostasis. Interestingly, metabolite levels in these pathways correlated with clinical laboratory markers of inflammation (i.e., IL-6 and C-reactive protein) and renal function (i.e., blood urea nitrogen). In conclusion, this initial observational study identified amino acid and fatty acid metabolism as correlates of COVID-19, providing mechanistic insights, potential markers of clinical severity, and potential therapeutic targets.
Authors
Tiffany Thomas, Davide Stefanoni, Julie A. Reisz, Travis Nemkov, Lorenzo Bertolone, Richard O. Francis, Krystalyn E. Hudson, James C. Zimring, Kirk C. Hansen, Eldad A. Hod, Steven L. Spitalnik, Angelo D’Alessandro
Abstract
COVID-19, the disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has resulted in a global pandemic and a disruptive health crisis. COVID-19-related morbidity and mortality has been attributed to an exaggerated immune response. The role of complement activation and its contribution to illness severity is being increasingly recognized. Here, we summarize current knowledge about the interaction of coronaviruses with the complement system. We posit that: (a) coronaviruses activate multiple complement pathways; (b) severe COVID-19 clinical features often resemble complementopathies; (c) the combined effects of complement activation, dysregulated neutrophilia, endothelial injury, and hypercoagulability appear to be intertwined to drive the severe features of COVID-19; (d) a subset of patients with COVID-19 may have a genetic predisposition associated with complement dysregulation; and (e) these observations create a basis for clinical trials of complement inhibitors in life-threatening illness.
Authors
Anuja Java, Anthony J. Apicelli, M. Kathryn Liszewski, Ariella Coler-Reilly, John P. Atkinson, Alfred H.J. Kim, Hrishikesh S. Kulkarni
Abstract
The acute respiratory distress syndrome (ARDS) results from overwhelming pulmonary inflammation. Prior bulk RNA sequencing provided limited insights into ARDS pathogenesis. We used single cell RNA sequencing to probe ARDS at a higher resolution. Peripheral blood mononuclear cells of patients with pneumonia and sepsis with early ARDS were compared to that of sepsis patients who did not develop ARDS. Monocyte clusters from ARDS patients revealed multiple distinguishing characteristics in comparison to monocytes from patients without ARDS including down-regulation of SOCS3 expression accompanied by a pro-inflammatory signature with up-regulation of multiple type I IFN-induced genes, especially in CD16+ cells. To generate an ARDS risk score, we identified up-regulation of 29 genes in the monocytes of these patients, and 17 showed a similar profile in cells of patients in independent cohorts. Monocytes had increased expression of RAB11A, known to inhibit neutrophil efferocytosis, ATP2B1, a calcium pump that exports Ca2+ implicated in endothelial barrier disruption, and SPARC, associated with processing of pro-collagen to collagen. These data show that monocytes of ARDS patients up-regulate expression of genes not just restricted to those associated with inflammation. Together, our findings identify molecules that are likely involved in ARDS pathogenesis that may inform biomarker and therapeutic development.
Authors
Yale Jiang, Brian R. Rosborough, Jie Chen, Sudipta Das, Georgios D. Kitsios, Bryan J. McVerry, Rama K. Mallampalli, Janet S. Lee, Anuradha Ray, Wei Chen, Prabir Ray
Abstract
Background Currently recommended traditional spirometry outputs do not reflect their relative contributions to airflow, and we hypothesized that machine learning algorithms can be trained on spirometry data to identify these structural phenotypes. Methods Participants enrolled in a large multicenter study (COPDGene) were included. The data points from expiratory flow-volume curves were trained using a deep learning model to predict structural phenotypes of COPD on computed tomography (CT), and results were compared with traditional spirometry metrics and an optimized random forest classifier. Area under the receiver operating characteristic curve (AUC) and weighted F-score were used to measure the discriminative accuracy of a fully convolutional neural network, Random Forest, and traditional spirometry metrics to phenotype CT as normal, emphysema-predominant (>5% emphysema), airway-predominant (Pi10>median), and mixed phenotypes. Similar comparisons were made for the detection of functional small airway disease phenotype (fSAD>20% on parametric response mapping). Results Among 8,980 individuals, neural network was more accurate in discriminating predominant emphysema/airway phenotypes (AUC 0.80, 95%CI 0.79-0.81) than traditional measures of spirometry, FEV1/FVC (AUC 0.71, 95%CI 0.69-0.71) and FEV1 %predicted (AUC 0.70, 95%CI 0.68-0.71) ), and random forest classifier (AUC 0.78, 95%CI 0.77-0.79). The neural network was also more accurate in discriminating predominant emphysema/small airway phenotypes (AUC 0.91, 95%CI 0.90-0.92) than FEV1/FVC (AUC 0.80, 95%CI 0.78-0.82), FEV1 %predicted (AUC 0.83, 95%CI 0.80-0.84), and with comparable accuracy with random forest classifier (AUC 0.90, 95%CI 0.88-0.91). Conclusions Structural phenotypes of COPD can be identified from spirometry using deep learning and machine learning approaches, demonstrating their potential to identify individuals for targeted therapies.
Authors
Sandeep Bodduluri, Arie Nakhmani, Joseph M. Reinhardt, Carla G. Wilson, Merry-Lynn N. McDonald, Ramaraju Rudraraju, Byron C Jaeger, Nirav R. Bhakta, Peter J. Castaldi, Frank C. Sciurba, Chengcui Zhang, Purushotham V. Bangalore, Surya P. Bhatt
Abstract
Expression of immune checkpoint ligands (ICLs) is necessary to trigger the inhibitory signal via immune checkpoint receptors (ICRs) in exhausted T cells under tumor immune microenvironment. Nevertheless, ICL expression profile in cancer patients has not been investigated. Using previously reported RNA-seq datasets, we found that expression of ICLs was patient-specific but their co-expression can be patterned in non-small-cell lung cancers (NSCLCs). Since the expressions of PD-L1 and PVR among various ICLs were independently regulated, we could stratify the patients, who were treated with anti-PD-1 later, into four groups according to the expression level of PD-L1 and PVR. Of interest, high PVR and low PVR expressions in PD-L1-expressing patients enriched non-responders and responders to PD-1 blockade, respectively, helping in further selection of responders. Using genetically engineered cancer model, we also found that PVR-deficient and PD-L1-sufficient tumor-bearing mice were highly sensitive to anti-PD-1 therapy, whereas PVR-sufficient and PD-L1-deficient tumor-bearing mice were resistant to anti-PD-1 therapy. Taken together, our study provides a concept that combinatorial expression patterns of PVR and PD-L1 are a key determinant for PD-1 blockade and furthermore suggest a better therapeutic usage of immune checkpoint blockades (ICBs).
Authors
Bo Ryeong Lee, Sehyun Chae, Jihyun Moon, Myeong Joon Kim, Hankyu Lee, Hyuk Wan Ko, Byoung Chul Cho, Hyo Sup Shim, Daehee Hwang, Hye Ryun Kim, Sang-Jun Ha
Abstract
Mycobacterium tuberculosis (Mtb)-specific T cell responses associated with immune control during asymptomatic latent tuberculosis infection (LTBI) remain poorly understood. Using a non-human primate (NHP) aerosol model, we studied the kinetics, phenotypes and functions of Mtb antigen-specific T cells in peripheral and lung compartments of Mtb-infected asymptomatic rhesus macaques by longitudinally sampling blood and bronchoalveolar lavage (BAL), for up to 24 weeks post-infection. We found significantly higher frequencies of Mtb-specific effector and memory CD4 and CD8 T cells producing IFN-γ in the airways compared to peripheral blood, which were maintained throughout the study period. Moreover, Mtb-specific IL-17+ and IL-17/IFN-γ double-positive T cells were present in the airways but were largely absent in the periphery, suggesting that balanced mucosal Th1/Th17 responses are associated with LTBI. The majority of Mtb-specific CD4 T cells that homed to the airways expressed the chemokine receptor CXCR3 and co-expressed CCR6. Notably, CXCR3+CD4+ cells were found in granulomatous and non-granulomatous regions of the lung and inversely correlated with Mtb burden. Our findings provide novel insights into antigen-specific T cell responses associated with asymptomatic Mtb infection that are relevant for developing better strategies to control TB
Authors
Uma Shanmugasundaram, Allison N. Bucsan, Shashank R. Ganatra, Chris Ibegbu, Melanie Quezada, Robert V. Blair, Xavier Alvarez, Vijayakumar Velu, Deepak Kaushal, Jyothi Rengarajan
Abstract
Infective endocarditis is a life-threatening infection of heart valves and adjacent structures characterized by vegetations on valves and other endocardial surfaces, with tissue destruction and risk of embolization. We used high-resolution mass spectrometry to define the proteome of staphylococcal and non-staphylococcal vegetations and Terminal Amine Isotopic Labeling of Substrates (TAILS) to define their proteolytic landscapes. These approaches identified over 2000 human proteins in staphylococcal and non-staphylococcal vegetations. Individual vegetation proteomes demonstrated comparable profiles of quantitatively major constituents that overlapped with serum, platelet and neutrophil proteomes. Staphylococcal vegetation proteomes resembled each other more than the proteomes of non-staphylococcal vegetations. TAILS demonstrated extensive proteolysis within vegetations, with numerous previously undescribed cleavages. Several proteases and pathogen-specific proteins, including virulence factors were identified in most vegetations. Proteolytic peptides in fibronectin and complement C3 were identified as potential infective endocarditis biomarkers. Overlap of staphylococcal and non-staphylococcal vegetation proteomes suggests a convergent thrombotic and immune response to endocardial infection by diverse pathogens. However, the differences between staphylococcal and non-staphylococcal vegetations and internal variance within the non-staphylococcal group indicates that additional pathogen- or patient-specific effects exist. Pervasive proteolysis of vegetation components may arise from vegetation-intrinsic proteases and destabilize vegetations, contributing to embolism.
Authors
Daniel R. Martin, James C. Witten, Carmela D. Tan, E. Rene Rodriguez, Eugene H. Blackstone, Gosta Pettersson, Deborah E. Seifert, Belinda Willard, Suneel Apte
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