Browsing by Author "Proust, F."

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Open Access
An integrated genomic and metabolomic approach for defining survival time in adult oligodendrogliomas patients
(Springer, 2019) Bund, C.; Guergova‑Kuras, M.; Çiçek, A. Ercüment; Moussallieh, F.-M.; Dali‑Youcef, N.; Piotto, M.; Schneider, P.; Heller, R.; Entz‑Werle, N.; Lhermitte, B.; Chenard, M.-P.; Schott, R.; Proust, F.; Noel, G.; Namer, I. J.
Introduction The identification of frequent acquired mutations shows that patients with oligodendrogliomas have divergent biology with differing prognoses regardless of histological classification. A better understanding of molecular features as well as their metabolic pathways is essential. Objectives The aim of this study was to examine the relationship between the tumor metabolome, six genomic aberrations (isocitrate dehydrogenase1 [IDH1] mutation, 1p/19q codeletion, tumor protein p53 [TP53] mutation, O6-methylguanin-DNA methyltransferase [MGMT] promoter methylation, epidermal growth factor receptor [EGFR] amplification, phosphate and tensin homolog [PTEN] methylation), and the patients’ survival time. Methods We applied 1H high-resolution magic-angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy to 72 resected oligodendrogliomas. Results The presence of IDH1, TP53, 1p19q codeletion, MGMT promoter methylation reduced the relative risk of death, whereas PTEN methylation and EGFR amplification were associated with poor prognosis. Increased concentration of 2-hydroxyglutarate (2HG), N-acetyl-aspartate (NAA), myo-inositol and the glycerophosphocholine/phosphocholine (GPC/ PC) ratio were good prognostic factors. Increasing the concentration of serine, glycine, glutamate and alanine led to an increased relative risk of death. Conclusion HRMAS NMR spectroscopy provides accurate information on the metabolomics of oligodendrogliomas, making it possible to find new biomarkers indicative of survival. It enables rapid characterization of intact tissue and could be used as an intraoperative method.
Open Access
Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy
(Public Library of Science, 2020) Çakmakçı, Doruk; Karakaşlar, Emin Onur; Ruhland, E.; Chenard, M.-P.; Proust, F.; Piotto, M.; Namer, I. J.; Çicek, A. Ercüment
Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) technique can distinguish healthy and malign tissue efficiently using peak intensities of biomarker metabolites. The method is fast, sensitive and can work with small and unprocessed samples, which makes it a good fit for real-time analysis during surgery. However, only a targeted analysis for the existence of known tumor biomarkers can be made and this requires a technician with chemistry background, and a pathologist with knowledge on tumor metabolism to be present during surgery. Here, we show that we can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning. We work on a new and large HRMAS NMR dataset of glioma and control samples (n = 565), which are also labeled with a quantitative pathology analysis. Our results show that a random forest based approach can distinguish samples with tumor cells and controls accurately and effectively with a median AUC of 85.6% and AUPR of 93.4%. We also show that we can further distinguish benign and malignant samples with a median AUC of 87.1% and AUPR of 96.1%. We analyze the feature (peak) importance for classification to interpret the results of the classifier. We validate that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguishing tumor and normal cells and suggest new biomarker regions. The code is released at http://github.com/ciceklab/HRMAS_NC.
Open Access
Metabolomic characterization of human hippocampus from drug-resistant epilepsy with mesial temporal seizure
(Wiley-Blackwell Publishing, 2018-03) Detour, J.; Bund, C.; Behr, C.; Cebula, H.; Çiçek, A. Ercüment; Valenti-Hirsch, Maria-Paola; Lannes, B.; Lhermitte, B.; Nehlig, A.; Kehrli, P.; Proust, F.; Hirsch, E.; Namer, Izzie-Jacques
Within a complex systems biology perspective, we wished to assess whether hippocampi with established neuropathological features have distinct metabolome. Apparently normal hippocampi with no signs of sclerosis (noHS), were compared to hippocampal sclerosis (HS) type 1 (HS1) and/or type 2 (HS2). Hippocampus metabolome from patients with epilepsy-associated neuroepithelial tumors (EANTs), namely, gangliogliomas (GGs) and dysembryoplastic neuroepithelial tumors (DNTs), was also compared to noHS epileptiform tissue. Methods: All patients underwent standardized temporal lobectomy. We applied 1H high-resolution magic angle spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy to 48 resected human hippocampi. NMR spectra allowed quantification of 21 metabolites. Data were analyzed using multivariate analysis based on mutual information. Results: Clear distinct metabolomic profiles were observed between all studied groups. Sixteen and 18 expected metabolite levels out of 21 were significantly different for HS1 and HS2, respectively, when compared to noHS. Distinct concentration variations for glutamine, glutamate, and N-acetylaspartate (NAA) were observed between HS1 and HS2. Hippocampi from GG and DNT patients showed 7 and 11 significant differences in metabolite concentrations when compared to the same group, respectively. GG and DNT had a clear distinct metabolomic profile, notably regarding choline compounds, glutamine, glutamate, aspartate, and taurine. Lactate and acetate underwent similar variations in both groups. Significance: HRMAS NMR metabolomic analysis was able to disentangle metabolic profiles between HS, noHS, and epileptic hippocampi associated with EANT. HRMAS NMR metabolomic analysis may contribute to a better identification of abnormal biochemical processes and neuropathogenic combinations underlying mesial temporal lobe epilepsy.
Open Access
Targeted metabolomics analyses for brain tumor margin assessment during surgery
(Oxford University Press, 2022-06-15) Çakmakçı, D.; Kaynar, Gün; Bund, C.; Piotto, M.; Proust, F.; Namer, I. J.; Çiçek, A. Ercüment
Motivation: Identification and removal of micro-scale residual tumor tissue during brain tumor surgery are key for survival in glioma patients. For this goal, High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy-based assessment of tumor margins during surgery has been an effective method. However, the time required for metabolite quantification and the need for human experts such as a pathologist to be present during surgery are major bottlenecks of this technique. While machine learning techniques that analyze the NMR spectrum in an untargeted manner (i.e. using the full raw signal) have been shown to effectively automate this feedback mechanism, high dimensional and noisy structure of the NMR signal limits the attained performance. Results: In this study, we show that identifying informative regions in the HRMAS NMR spectrum and using them for tumor margin assessment improves the prediction power. We use the spectra normalized with the ERETIC (electronic reference to access in vivo concentrations) method which uses an external reference signal to calibrate the HRMAS NMR spectrum. We train models to predict quantities of metabolites from annotated regions of this spectrum. Using these predictions for tumor margin assessment provides performance improvements up to 4.6% the Area Under the ROC Curve (AUC-ROC) and 2.8% the Area Under the Precision-Recall Curve (AUC-PR). We validate the importance of various tumor biomarkers and identify a novel region between 7.97 ppm and 8.09 ppm as a new candidate for a glioma biomarker. Availability and implementation: The code is released at https://github.com/ciceklab/targeted_brain_tumor_margin_ assessment. The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.5781769.
Open Access
What does reduced FDG uptake mean in high-grade gliomas?
(NLM (Medline), 2019) Bund, C.; Lhermitte, B.; Çiçek, A. Ercüment; Ruhland, E.; Proust, F.; Namer, I. J.
Purpose: As well as in many others cancers, FDG uptake is correlated with the degree of malignancy in gliomas, that is, commonly high FDG uptake in high-grade gliomas. However, in clinical practice, it is not uncommon to observe high-grade gliomas with low FDG uptake. Our aim was to explore the tumor metabolism in 2 populations of high-grade gliomas presenting high or low FDG uptake. Methods: High-resolution magic-angle spinning nuclear magnetic resonance spectroscopy was realized on tissue samples from 7 high-grade glioma patients with high FDG uptake and 5 high-grade glioma patients with low FDG uptake. Tumor metabolomics was evaluated from 42 quantified metabolites and compared by network analysis. Results: Whether originating from astrocytes or oligodendrocytes, the highgrade gliomas with low FDG avidity represent a subgroup of high-grade gliomas presenting common characteristics: low aspartate, glutamate, and creatine levels, which are probably related to the impaired electron transport chain in mitochondria; high serine/glycine metabolism and so one-carbon metabolism; low glycerophosphocholine-phosphocholine ratio in membrane metabolism, which is associated with tumor aggressiveness; and finally negative MGMT methylation status. Conclusions: It seems imperative to identify this subgroup of high-grade gliomas with low FDG avidity, which is especially aggressive. Their identification could be important for early detection for a possible personalized treatment, such as antifolate treatment.