Doctoral student – Lab of Translational Onco-genomics and Bio-informatics (TOBI), Center for Medical Biotechnology (VIB)
Department of Biomolecular Medicine, faculty of Medicine and Health Sciences (UGent)
Principal investigator: prof. Katleen De Preter (PhD)
Immune checkpoint inhibitors (ICIs) are a type of immunotherapy to kill cancer cells by blocking immune checkpoint proteins. While there is an increase in the number of treated cancer patients via immune checkpoint inhibitors, accurate minimal-invasive response prediction tests is still difficult. The development of single-cell technologies has accelerated research in oncology by identifying heterogeneous cell (sub-)populations based on the gene expression, open chromatin, or histone mark profiles. These allow us to evaluate the performance of computational deconvolution, the process of reconstructing the proportions of different cell types from a bulk sample. To date, transcriptomics has been widely used, but it is unclear which data level is the best to infer immune cell type proportions. Besides transcriptome profiling with scRNA-seq, chromatin accessibility can be assessed using scATAC-seq and histone mark profiling can be performed using scCUT&TAG-seq.
In this project, I aim to evaluate different levels of omics data to give better insights of the systemic immunity associated with ICI therapy response. I believe that a better biological understanding of the immunological differences in responder versus non-responder cancer patients will aid in the identification of more accurate non-invasive predictive biomarkers for ICI response.