12 research outputs found

    Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response

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    Abstract Background The HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize “non-self” antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer. Methods RNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles. Results The genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls. Conclusions The integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient’s tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade

    Bioinformatic, Biochemical, and Immunological Mining of MHC Class I Restricted T Cell Epitopes for a Marburg Nucleoprotein Microparticle Vaccine

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    The Marburg virus (MARV), the virus responsible for Marburg hemorrhagic fever (MHF), is considered a top-priority pathogen for vaccine development. Recent outbreaks in Equatorial Africa have highlighted the urgency of MARV because of its high fatality rate and historical concerns about potential weaponization. Currently, there are no licensed vaccines for MARV. Existing vaccine candidates rely on attenuated recombinant vesicular stomatitis virus carrying MARV glycoprotein (VSVΔG) or the chimpanzee replication-defective adenovirus 3 vector ChAd3-MARV. Although these platforms provide significant protection in animal models, they face challenges because of their limited thermal stability and the need for cold storage during deployment in resource-poor areas. An alternative approach involves using adjuvanted poly (lactic-co-glycolic acid) (PLGA) microparticles loaded with synthetic peptides representing MHC class I—restricted T cell epitopes. This vaccine platform has demonstrated effectiveness in protecting against SARS-CoV-2 and EBoV disease in animal models and has the advantage of not requiring cold storage and remaining stable at room temperature for over six months. This report outlines the design, manufacturing, and in vivo immunogenicity testing of PLGA microparticle human vaccines designed to prevent Marburg hemorrhagic fever

    Leichtmetalle

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    Toxic metal emissions from incineration: Mechanisms and control

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    Remote Laser Spectroscopy and Interferometry

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