Background: The interaction of allergens and allergen-specific IgE initiates the allergic cascade after crosslinking of receptors on effector cells. Antibodies of other isotypes may modulate such a reaction. Receptor crosslinking requires binding of antibodies to multiple epitopes on the allergen. Limited information is available on the complexity of the epitope structure of most allergens.
Objectives: We sought to allow description of the complexity of IgE, IgG, and IgG epitope recognition at a global, allergome-wide level during allergen-specific immunotherapy (AIT).
Methods: We generated an allergome-wide microarray comprising 731 allergens in the form of more than 172,000 overlapping 16-mer peptides. Allergen recognition by IgE, IgG, and IgG was examined in serum samples collected from subjects undergoing AIT against pollen allergy.
Results: Extensive induction of linear peptide-specific Phl p 1- and Bet v 1-specific humoral immunity was demonstrated in subjects undergoing a 3-year-long AIT against grass and birch pollen allergy, respectively. Epitope profiles differed between subjects but were largely established already after 1 year of AIT, suggesting that dominant allergen-specific antibody clones remained as important contributors to humoral immunity following their initial establishment during the early phase of AIT. Complex, subject-specific patterns of allergen isoform and group cross-reactivities in the repertoires were observed, patterns that may indicate different levels of protection against different allergen sources.
Conclusions: The study highlights the complexity and subject-specific nature of allergen epitopes recognized following AIT. We envisage that epitope deconvolution will be an important aspect of future efforts to describe and analyze the outcomes of AIT in a personalized manner.
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http://dx.doi.org/10.1016/j.jaci.2020.08.002 | DOI Listing |
Cancer Lett
December 2024
Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China; CNRS-LIA Hematology and Cancer, Sino-French Research Center for Life Sciences and Genomics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address:
Acute myeloid leukemia (AML) has lagged in benefiting from immunotherapies, primarily due to the scarcity of actionable AML-specific antigens. Driver mutations represent promising immunogenic targets, but a comprehensive characterization of the AML neoantigen landscape and their impact on patient outcomes and the AML immune microenvironment remain unclear. Herein, we conducted matched DNA and RNA sequencing on 304 AML patients and extensively integrated data from additional ∼2500 AML cases, identifying 49 driver genes, notably characterized by a significant proportion of insertions and deletions (indels).
View Article and Find Full Text PDFNat Commun
October 2024
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Advances in mass spectrometry accelerates the characterization of HLA ligandome, necessitating the development of efficient methods for immunopeptidomics analysis and (neo)antigen prediction. We develop ImmuneApp, an interpretable deep learning framework trained on extensive HLA ligand datasets, which improves the prediction of HLA-I epitopes, prioritizes neoepitopes, and enhances immunopeptidomics deconvolution. ImmuneApp extracts informative embeddings and identifies key residues for pHLA binding.
View Article and Find Full Text PDFJ Lipid Res
September 2024
Department of Cytokinetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic; Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic. Electronic address:
Glycosylated sphingolipids (GSLs) are a diverse group of cellular lipids typically reported as being rare in normal mammary tissue. In breast cancer (BCa), GSLs have emerged as noteworthy markers associated with breast cancer stem cells, mediators of phenotypic plasticity, and contributors to cancer cell chemoresistance. GSLs are potential surface markers that can uniquely characterize the heterogeneity of the tumor microenvironment, including cancer cell subpopulations and epithelial-mesenchymal plasticity (EMP).
View Article and Find Full Text PDFNat Biotechnol
July 2024
Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Antigen discovery technologies have largely focused on major histocompatibility complex (MHC) class I-restricted human T cell receptors (TCRs), leaving methods for MHC class II-restricted and mouse TCR reactivities relatively undeveloped. Here we present TCR mapping of antigenic peptides (TCR-MAP), an antigen discovery method that uses a synthetic TCR-stimulated circuit in immortalized T cells to activate sortase-mediated tagging of engineered antigen-presenting cells (APCs) expressing processed peptides on MHCs. Live, tagged APCs can be directly purified for deconvolution by sequencing, enabling TCRs with unknown specificity to be queried against barcoded peptide libraries in a pooled screening context.
View Article and Find Full Text PDFSci Data
June 2024
Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.
Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow that was applied to unveil high-performing protein markers for high-grade serous ovarian carcinoma (HGSOC) from publicly available ovarian cancer tissue and serum proteomics datasets. Diagnosis of HGSOC, an aggressive form of ovarian cancer, currently relies on diagnostic methods based on tissue biopsy and/or non-specific biomarkers such as the cancer antigen 125 (CA125) and human epididymis protein 4 (HE4).
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