Project number 30

Computational modeling of the epigenomic landscape of glioblastoma

During the progression of glioblastoma, cancer cells can undergo epigenomic reprogramming from a proliferative cellular phenotype to an invasive, migratory, and more drug resistant phenotype. Particularly, tumor hypoxia is thought to be a key driver of these reprogramming events. In this PhD project you will use publicly available and in-house generated genomics, epigenomics, and transcriptomics data to model the gene regulatory networks underlying this regulatory heterogeneity. This will involve an integrative analysis of DNA sequence (germ-line variants and somatic mutations from whole-genome sequencing), chromatin activity (e.g, histone modifications and DNA methylation), and gene expression data (RNA-seq). Your predictions of master regulators and gene regulatory networks can be validated in the wet-lab using  CRISPR/Cas9 and massively parallel enhancer-reporter assays. Finally, you will investigate how to modulate the activity of these networks using epigenetic drugs. You have a degree in bioinformatics or computer science. Programming skills (e.g., Python, R, Java) are expected. Wet-lab molecular biology skills are not required but considered as a plus.

This PhD will be a joint effort between the Laboratory of Translational Genetics (headed by Diether Lambrechts), which is focused on cancer (epi)genomics and high-throughput sequencing, and the Laboratory of Computational Biology (headed by Stein Aerts), which is focusing on gene regulatory network prediction, with applications in Drosophila and cancer.

Keywords
glioblastoma, epigenomics, chomatin, gene regulatory networks, drug resistance

Supervisors
Diether Lambrechts, VIB Vesalius Research Center, KU Leuven, Leuven
Stein Aerts, VIB Center for the Biology of Disease, KU Leuven, Leuven