Identification of epigenetically regulated pathways in cancer is possible using the expression methylation quantitative trait loci (emQTL) approach published in Fleischer, Tekpli et al. 2017. Using an improved version of this method, we have now identified epigenetic dysregulation associated with increased activity of the cell cycle, showing that epigenetic dysregulation in triple negative breast cancer may provide a growth advantage in these tumors.
To assess the functional and causal effects of the identified epigenetic alterations, we are using CRISPR epigenetic editing. In breast cancer cell lines with stable and inducible expression of deactivated Cas9 fused with the catalytic domain of DNMT3A, we can induce DNA methylation at specific loci. The effects of induced DNA methylation is assessed by measuring transcription factor occupancy, target gene expression, and cell proliferation and migration.
Using diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) it is possible to assess parameters such as cellular density, blood flow, and growth patterns of tumors. In this project we are using MRI in combination with 'omics data to create "portraits" of tumors that can help predict treatment response. This project is part of the PerCaThe convergence environment funded by UiO Life Science. These data has already been used as part of a pharmacokinetic and pharmacodynamic N-of-1 in silico model showing proof-of-concept that we can predict and improve treatment response (Lai et al. 2019)
miR-34a is a tumor supressor lowly expressed in triple negative breast cancer, and miR-34a replacement therapy has been suggested for patients with this disease. In this project we confirm that miR-34a is highly associated with regulation of the cell cycle, and we show that miR-34a expression is also associated with altered production of amino acids.