Doctoral fellow – Lab for functional cancer genomics and applied bioinformatics, Center for Medical Genetics (Faculty of Medicine and Health Sciences, UGent)
Principal investigator: prof. Jo Vandesompele (PhD)
My research aims at the development of novel functional genomics technologies to study cancer cells and liquid biopsies from cancer patients.
The majority of RNA sequencing methods are based on short reads. Unfortunately, these methods are not well suited or provide very limited information on the sequence integrity and fragmentation status of liquid biopsy derived RNA and on the full sequence composition of circular RNAs, a growing class of non-coding RNA biomarkers. For those reasons, long read sequencing methods have become an attractive option for tackling the challenges mentioned above. In addition to single cDNA molecule sequencing, the Oxford Nanopore Technology can be used for native RNA sequencing, eliminating reverse-transcriptase bias and supplying valuable information on RNA nucleotide modifications.
Although steady-state levels of extracellular RNA in liquid biopsies are becoming recognized of a valuable source of biomarkers, virtually nothing is known about their in vivo kinetics. As such, it is unknown at what rate new extracellular RNA molecules are entering the circulation and how long they remain there. SLAM-seq and other recently developed methods will enable me to quantify nascent RNA to obtain insights in in vivo kinetics of extracellular RNA. This information is crucial to determine the frequency and waiting time in collecting liquid biopsies from cancer patients under active treatment.
In a 3rd research line, I will study the transcriptional heterogeneity of single cancer cells, amongst others upon exposure to precision medicine drugs. However, bulk tissue transcriptome profiling methods do not provide the required resolutions to study differences at the single cell level. While various methods exist for single cell RNA sequencing, their costs are high and analytical sensitivities are low. Here, I will introduce single cell digital RT-PCR for cost-effective targeted measurements of a dozen of genes in tens of thousands of individual cells.