Most cells in the human body secrete extracellular vesicles that encapsulate biomolecules from their
source cells. Consequently, these vesicles serve as indicators of the physiological state of their source
cells, including pathological conditions such as cancer. However, isolating and purifying these vesicles
for diagnostic purposes in clinical settings is challenging, amongst others due to the complex and
time-consuming procedures involved. Recently, my promoter's laboratory developed a filtrationbased
method, termed FAEVEr, for isolating extracellular vesicles followed by downstream proteomics
on their cargo. In this proposal, I aim to adapt the FAEVEr method to efficiently isolate extracellular
vesicles from complex biomatrices, such as blood plasma. Given that these vesicles also contain
nucleic acids, I will further modify the FAEVEr method to enable the parallel isolation and analysis of
both nucleic acids and proteins, thereby enhancing our view on their biomolecular content. As a
clinical case study, brain tumors have been chosen due to the significant challenges in accurately
stratifying and monitoring these tumours in a minimally-invasive way using liquid biopsies. Prior to
analysing patient samples, I will validate my method using rat models of patient-derived
glioblastoma xenografts. Ultimately, my PhD research will result in a novel technique that facilitates
multi-modal analysis of extracellular vesicles in liquid biopsies.