Antigen presentation and the boundary between self and non-self: applications in computational immunology

Uzun, Nazmiye (2023) Antigen presentation and the boundary between self and non-self: applications in computational immunology. PhD thesis, Birkbeck, University of London.

Abstract

This thesis focuses on the applications of computational prediction methods in the areas of antigen presentation and recognition close to the boundary between self and non-self. Publicly available MHC binding prediction tools are combined with data about the frequencies of different HLA alleles within global and regional populations. Additionally, a new in silico method called proteome scanning is presented that assesses whether, in the light of central tolerance mechanisms that remove self-reactive T cells, an individual is likely to have T cells capable of binding to a given peptide-MHC surface. These methods are applied in three main application areas. Firstly, predictions are made concerning individuals with missense mutation haemophilia A and their risk of developing inhibitors against the replacement Factor VIII used to treat the condition. Inhibitor formation is known to be a CD4+ T cell-dependent process; the analysis presented here demonstrates that understanding the risk of inhibitor formation generally requires knowledge of an individual’s HLA types. Secondly, predictions are made concerning the risk of transplant rejection and suggest that the proteome scanning approach can be used to predict whether a given HLA mismatch between donor and recipient is likely to increase rejection risk. Thirdly, predictions are made concerning candidate peptide biomarkers (derived from known tumour antigens) for hepatocellular carcinoma, with the selection of peptide pools optimised in terms of MHC binding affinity and global population coverage. These are currently undergoing laboratory evaluation at the Institute of Hepatology, with promising early results. Taken together, these applications illustrate the breadth of potential contributions to clinical practice afforded by the computational prediction of antigen presentation and recognition close to the self/non-self boundary, including the novel proteome scanning methodology.

Metadata

Statistics

DownloadsShow export options

Export as XMLJSONCSV

Activity Overview

6 month trend

109Downloads

6 month trend

110Hits

Additional statistics are available via IRStats2.

Archive Staff Only (login required)

Edit/View Item