Prioritization of neoantigens by the combination of in silico search and mass spectrometry.

Project Details

Description

In this project we will integrate liquid chromatography coupled to tandem
mass spectrometry (LC-MS/MS) into the selection and prioritization of target
neoantigens.

A challenge in developing personalized cancer immunotherapies is the
prediction of putative cancer-specific antigens. Currently, in silico
bioinformatics and algorithms are used to identify peptides that can bind to
human leukocyte antigens. However, these algorithms are far from perfect.
The complex rules associated with endogenous processing and presentation
of potential targets are not completely captured in these bioinformatics tools.
We propose to produce short mRNA’s encoding candidate neoantigens
selected by bioinformatics and to electroporate these mRNA’s into the
patient’s antigen presenting cells. Those neoantigens that can be correctly
processed and presented will be identified by immune precipitation of surface
expressed HLA class-I and –II molecules followed by LC-MS/MS. This will
allow us to prioritize those epitopes that are recognizable by T lymphocytes.
AcronymANI216
StatusActive
Effective start/end date1/01/1931/12/22

Keywords

  • Neoantigens
  • Silico search
  • Mass spectrometry

Flemish discipline codes

  • Hematology
  • Cancer therapy
  • Cancer diagnosis