Biom-19. Metabolic Alteration Induced by Selective Knock Down of Gabpb1l in U251 Cells

Abstract

BACKGROUND TERT promoter mutations that result in TERT expression are observed in over 80% of GBM and upstream inhibition of TERT expression by targeting GABPB1L is currently under investigation. In that context, non-invasive reliable biomarkers that can help detect TERT expression are needed. The aim of this research was to assess the value of magnetic resonance spectroscopy (MRS)-detectable metabolic changes as biomarkers of TERT expression in GBM. METHODS GABPB1L knock down clones (GABPB1LKD) were established by introducing Crispr Cas9 plasmid vector targeting GABPB1L into U251 cells. Two representative clones with different knock down efficiency were chosen and compared to control cells. Tumor forming capacity was evaluated by colony formation assay and magnetic resonance imaging of orthotopically implanted tumors in mice. Cells were extracted using the dual phase extraction method and 1H-MRS data of cell extracts acquired using a Bruker 500 scanner. The data was analyzed using Mnova software. Multivariate analysis was performed using the SIMCA software. RESULTS TERT expression was significantly reduced in GABPB1LKD compared to control cells depending on the GABPB1L knock down efficiency. Colony forming capacity was impaired in GABPB1LKD compared to control cells. In vivo MRI data showed significantly smaller tumor volumes in GABPB1LKD compared to control. Unbiased PCA analysis of 1H-MRS data showed separation of GABPB1LKD and control extracts and VIP scores derived from the OPLS-DA analysis, demonstrated that the common metabolites leading to separation of GABPB1LKD and control cells were aspartate, glutathione, glycerophosphocholine, glutamine, NAD(P)+, AXP. This data was confirmed by univariate analysis that revealed that aspartate, glutathione, glutamine, NAD(P)+, AXP level was significantly reduced in GABPB1LKD. CONCLUSIONS GABPB1L knock down cells that show reduced TERT expression demonstrate MRS-detectable metabolic changes. These could be translated into clinical applications, improve the monitoring of GBM patients and advance precision medicine.