27 research outputs found

    Patients with severe COVID-19 do not have elevated autoantibodies against common diagnostic autoantigens

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    Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative pathogen of coronavirus disease 2019 (COVID-19) presents occasionally with an aberrant autoinflammatory response, including the presence of elevated circulating autoantibodies in some individuals. Whether the development of autoantibodies against self-antigens affects COVID-19 outcomes remains unclear. To better understand the prognostic role of autoantibodies in COVID-19, we quantified autoantibodies against 23 markers that are used for diagnosis of autoimmune disease. To this end, we used serum samples from patients with severe [intensive care unit (ICU)] and moderate (ward) COVID-19, across two to six consecutive time points, and compared autoantibody levels to uninfected healthy and ICU controls. Acute and post-acute serum (from 1 to 26 ICU days) was collected from 18 ICU COVID-19-positive patients at three to six time points; 18 ICU COVID-19-negative patients (sampled on ICU day 1 and 3); 21 ward COVID-19-positive patients (sampled on hospital day 1 and 3); and from 59 healthy uninfected controls deriving from two cohorts. Levels of IgG autoantibodies against 23 autoantigens, commonly used for autoimmune disease diagnosis, were measured in serum samples using MSD® U-PLEX electrochemiluminescence technology (MSD division Meso Scale Discovery®), and results were compared between groups. There were no significant elevations of autoantibodies for any of the markers tested in patients with severe COVID-19. Sample collections at longer time points should be considered in future studies, for assessing the possible development of autoantibody responses following infection with SARS-CoV-2

    B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma

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    B cells are known to contribute to the anti-tumor immune response, especially in immunogenic tumors such as melanoma, yet humoral immunity has not been characterized in these cancers to detail. Here we show comprehensive phenotyping in samples of circulating and tumor-resident B cells as well as serum antibodies in melanoma patients. Memory B cells are enriched in tumors compared to blood in paired samples and feature distinct antibody repertoires, linked to specific isotypes. Tumor-associated B cells undergo clonal expansion, class switch recombination, somatic hypermutation and receptor revision. Compared with blood, tumor-associated B cells produce antibodies with proportionally higher levels of unproductive sequences and distinct complementarity determining region 3 properties. The observed features are signs of affinity maturation and polyreactivity and suggest an active and aberrant autoimmune-like reaction in the tumor microenvironment. Consistent with this, tumor-derived antibodies are polyreactive and characterized by autoantigen recognition. Serum antibodies show reactivity to antigens attributed to autoimmune diseases and cancer, and their levels are higher in patients with active disease compared to post-resection state. Our findings thus reveal B cell lineage dysregulation with distinct antibody repertoire and specificity, alongside clonally-expanded tumor-infiltrating B cells with autoimmune-like features, shaping the humoral immune response in melanoma

    Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

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    <p>Abstract</p> <p>Background</p> <p>There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to non-disease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.</p> <p>Methods</p> <p>Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.</p> <p>Results</p> <p>Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissue-specific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty-six candidate biomarkers for these four cancer types are proposed.</p> <p>Conclusions</p> <p>We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted.</p

    Correction to: A proteome-wide immuno-mass spectrometric identification of serum autoantibodies

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    In the original version of the article [1], an error was noticed under the heading “Immunoprecipitation on protein G magnetic beads” in “Methods” section

    A proteome-wide immuno-mass spectrometric identification of serum autoantibodies

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    Abstract Background Autoantibodies are produced when tolerance to self-antigens is broken and they can be mediators of tissue injury and systemic inflammation. They are excellent biomarkers because they are minimally invasive to screen and are highly abundant in serum due to limited proteolysis and slow clearance. Conventionally used methods of identifying autoantibodies in patient sera include indirect immunofluorescence, enzyme-linked immunoabsorbent assays (ELISAs) and protein microarrays. Here we present a novel proteome-wide immuno-mass spectrometric method to identify serum autoantibody targets. Methods Serum samples from patients with inflammatory bowel disease (IBD) were analyzed by ELISA for the presence of autoantibodies to CUB and zona pellucida-like domain-containing protein 1 (CUZD1). Protein was extracted from the human pancreas as well as 16 other human tissues to make a complex tissue lysate protein mixture. Antibodies in patient sera were immobilized and purified on protein G magnetic beads and subsequently incubated with pancreatic lysate containing CUZD1 or the aforementioned complex tissue lysate. After extensive washing, antibody-bound protein antigens were trypsin-digested and identified using shotgun mass spectrometry. Results The protocol was optimized for the immunoaffinity purification of autoantibody targets from tissue lysate, using CUZD1 from pancreatic lysate and anti-CUZD1 autoantibodies present in IBD patient serum as a proof-of-concept. Pancreatic secretory granule membrane major glycoprotein 2, whose autoantibodies are a known biomarker of Crohn’s disease, was also immunoprecipitated from IBD patient serum, as an additional internal positive control. Conclusions This study demonstrates the effectiveness of a proteomic approach to identify serum autoantibody targets, using immunoaffinity purification followed by tandem mass spectrometry. Our methodology is applicable for proteome-wide analysis of autoantibody targets in a wide variety of clinical settings

    Biochemical and functional characterization of the human tissue kallikrein 9

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    Human tissue kallikrein 9 (KLK9) is a member of the kallikrein-related family of proteases. Despite its known expression profile, much less is known about the functional roles of this protease and its implications in normal physiology and disease. We present here the first data on the biochemical characterization of KLK9, investigate parameters that affect its enzymatic activity (such as inhibitors) and provide preliminary insights into its putative substrates. We show that mature KLK9 is a glycosylated chymotrypsin-like enzyme with strong preference for tyrosine over phenylalanine at the P1 cleavage position. The enzyme activity is enhanced by Mg2+ and Ca2+, but is reversibly attenuated by Zn2+. KLK9 is inhibited in vitro by many naturally occurring or synthetic protease inhibitors. Using a combination of degradomic and substrate specificity assays, we identified candidate KLK9 substrates in two different epithelial cell lines [the non-tumorigenic human keratinocyte cells (HaCaT) and the tumorigenic tongue squamous carcinoma cells (SCC9)]. Two potential KLK9 substrates [KLK10 and midkine (MDK)] were subjected to further validation. Taken together, our data delineate some functional and biochemical properties of KLK9 for future elucidation of the role of this enzyme in health and disease.</jats:p

    Identification of psoriatic arthritis mediators in synovial fluid by quantitative mass spectrometry

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    Abstract Background Synovial fluid (SF) is a dynamic reservoir for proteins originating from the synovial membrane, cartilage, and plasma, and may therefore reflect the pathophysiological conditions that give rise to arthritis. Our goal was to identify and quantify protein mediators of psoriatic arthritis (PsA) in SF. Methods Age and gender-matched pooled SF samples from 10 PsA and 10 controls [early osteoarthritis (OA)], were subjected to label-free quantitative proteomics using liquid chromatography coupled to mass spectrometry (LC-MS/MS), to identify differentially expressed proteins based on the ratios of the extracted ion current of each protein between the two groups. Pathway analysis and public database searches were conducted to ensure these proteins held relevance to PsA. Multiplexed selected reaction monitoring (SRM) assays were then utilized to confirm the elevated proteins in the discovery samples and in an independent set of samples from patients with PsA and controls. Results We determined that 137 proteins were differentially expressed between PsA and control SF, and 44 were upregulated. The pathways associated with these proteins were acute-phase response signalling, granulocyte adhesion and diapedesis, and production of nitric oxide and reactive oxygen species in macrophages. The expression of 12 proteins was subsequently quantified using SRM assays. Conclusions Our in-depth proteomic analysis of the PSA SF proteome identified 12 proteins which were significantly elevated in PsA SF compared to early OA SF. These proteins may be linked to the pathogenesis of PsA, as well serve as putative biomarkers and/or therapeutic targets for this disease
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