Project

Improved data-driven bioinformatics tools to greatly extend neo- and xeno-epitope landscapes detected by immunopeptidomics.

Code
3S004321
Duration
01 November 2021 → 31 October 2025
Funding
Research Foundation - Flanders (FWO)
Research disciplines
  • Natural sciences
    • Machine learning and decision making
    • Development of bioinformatics software, tools and databases
  • Medical and health sciences
    • Computational biomodelling and machine learning
    • Bio-informatics and computational biology not elsewhere classified
Keywords
Bioinformatics Clinical proteomics Machine Learning
 
Project description

Vaccination has proven to be very successful, resulting in the eradication of smallpox and the near-eradication of poliovirus, for example. Currently, vaccination is available for over 29 diseases and is estimated to prevent over 3 million deaths a year. However, for some diseases such as cancer and tuberculosis, effective vaccines are not yet available. A major problem in developing vaccines for diseases such as cancer and those caused by intracellular bacteria is that these must rely heavily on T-cell immunity, which requires the identification of efficiently presented MHC-epitopes that will elicit a potent immune response in the body. The identification of such MHC-bound epitopes is pursued most directly through immunopeptidomics, in which the bound epitopes are isolated and analyzed. However, while new mass spectrometry-based protocols are being designed to increase the sensitivity of the experimental identification of these epitopes, including in the lab of my co-promotor Prof. Impens, bioinformatics tools that can efficiently identify the resulting fragmentation mass spectra lag behind. I here therefore will develop novel bioinformatics tools that are specifically tailored to work with such immunopeptidomics data. A key outcome of this effort will be to provide a more comprehensive view on the available epitopes for vaccination efforts, which can help overcome current limitations in searching for applicable epitopes for cancer and intracellular bacterial infections.