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Metabolomic and lipidomic studies of glioblastoma cell lines: identification of a radioresistance metabolic index
Denis Desoubzdanne
Groupe de RMN Biomédicale, Laboratoire SPCMIB (UMR CNRS 5068), Université Paul Sabatier, 118 route de Narbonne, 31062 TOULOUSE cedex, France
In a previous study, we showed that the gradation of primary brain tumours (gliomas) was possible from the 1H Nuclear Magnetic Resonance (NMR) spectroscopic analysis of biopsies from patients. Among gliomas, glioblastomas are the worst prognosis tumours. We are now focusing our research on this type of tumour. The standard treatment associates surgery and radiotherapy. However, most glioblastomas recur, and patients usually die within a year. Identification of the cellular mechanism(s) leading to radioresistance is required to find new therapeutic targets. In this study, we have chosen a metabolomic then a lipidomic approach for a better knowledge of radioresistance factors.
The metabolomes of 4 human glioblastoma cell lines, 2 radioresistant (RR: SF763 and U87) and 2 radiosensitive (RS: SF767 and U251), were determined by 1H NMR spectroscopy. The spectra analyses were performed on the aqueous fractions of cell extracts. A multivariate analysis by Principal Component Analysis (PCA) was carried out on raw data from 40 metabolic profiling experiments with specific software (KnowItAll®, BioRad). PCA results revealed a strong discrimination between RR and RS cell lines due to the sum of Phosphorylcholine (PC) and Glycerophosphorylcholine (GPC) signals. A quantitative analysis of PC and GPC confirmed these statistical results with a significant higher proportion of PC+GPC signals in RR cell lines (p<<10-6). Thus, we can propose PC+GPC as a good radioresistance metabolic index. A lipidomic study was then carried out on the 4 cell lines to quantify lipids such as phospholipids, ceramides, sphingomyelines and neutral lipids by GC-MS and/or HPLC. No significant differences could be observed between RR and RS cell lines. Our present investigations are focusing on metabolic disorders which underlie this phenotype at the enzymatic and transcriptomic levels.