High-resolution magic angle spinning (HR-MAS) one- and two-dimensional 1H and 13C nuclear magnetic resonance (NMR) spectroscopy has been used to study intact glioblastoma (GBM) brain tumour tissue. The results were compared with in vitro chemical extract and in vivo spectra. The resolution of 1H one-dimensional, 1H TOCSY and 13C HSQC HR-MAS spectra is comparable to that obtained on perchloric extracts. 13C HSQC HR-MAS spectra have been particularly useful for the identification of 37 different metabolites in intact biopsy tumours, excluding water and DSS components. To our knowledge, this is the most detailed assignment of biochemical compounds obtained in intact human tissue, in particular in brain tumour tissue. Tissue degradation during the recording of the NMR experiment was avoided by keeping the sample at a temperature of 4 degrees C. Detailed metabolical compositions of 10 GBM (six primary, two secondary and two unclassified) were obtained. A good correlation between ex vivo and in vivo MRS has been found.

Justification Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently acquired in different centers. The multicenter eTUMOUR project (2004)(2005)(2006)(2007)(2008)(2009), which builds upon previous expertise from the INTERPRET project (2000INTERPRET project ( -2002 has allowed such an evaluation to take place. Materials and Methods A total of 253 pairwise classifiers for glioblastoma, meningioma, metastasis, and low-grade glial diagnosis were inferred based on 211 SV short TE INTERPRET MR spectra obtained at 1.5 T (PRESS or STEAM, 20-32 ms) and automatically pre-processed. Afterwards, the classifiers were tested with 97 spectra, which were subsequently compiled during eTUMOUR. ResultsIn our results based on subsequently acquired spectra, accuracies of around 90% were achieved for most of the pairwise discrimination problems. The exception was for the glioblastoma versus metastasis discrimination, which was below 78%. A more clear definition of metastases may be obtained by other approaches, such as MRSI + MRI. Conclusions The prediction of the tumor type of in-vivo MRS is possible using classifiers developed from previously acquired data, in different hospitals with different instrumentation under the same acquisition protocols. This methodology may find application for assisting in the diagnosis of new brain tumor cases and for the quality control of multicenter MRS databases.

High-resolution magic angle spinning (HR-MAS) 1H NMR spectroscopy of intact human liver needle biopsies has not been previously reported. HR-MAS NMR spectra collected on 17 specimens with tissue amounts between approximately 0.5 and 12 mg showed very good spectral resolution and signal-to-noise ratios. One-dimensional 1H spectra revealed many intense signals corresponding to cellular metabolites. In addition, some high molecular weight metabolites, such as glycogen and mobile fatty acids, could be observed in some spectra. Resonance assignments for 22 metabolites were obtained by combining the analysis of three different types of 1D 1H spectral editing, such as T2 filtering or the nuclear Overhauser effect and 2D TOCSY and 13C-HSQC spectra. Biochemical stability of the liver tissue during up to 16 h of magic angle spinning at 277 K was studied. Biochemical trends corresponding to the different pathologies were observed, involving free fragments of lipids among other metabolites. NMR signal intensity ratios can be useful for discrimination among non-pathological, hepatitis C affected and cirrhotic liver tissues. Overall, this work demonstrates the applicability of HR-MAS NMR spectroscopy to the biochemical characterization of needle biopsies of the human liver.

Non Muscle Invasive Bladder Cancer (NMIBC) is among the most frequent malignant cancers worldwide. NMIBC is treated by transurethral resection of the bladder tumor (TURBT) and intravesical therapies, and has the highest recurrence rate among solid tumors. It requires a lifelong patient monitoring based on repeated cystoscopy and urinary cytology, both having drawbacks that include lack of sensitivity and specificity, invasiveness and care costs. We conducted an investigative clinical study to examine changes in the urinary metabolome of NMBIC patients before and after TURBT, as well during the subsequent surveillance period. Adjusting by prior probability of recurrence per risk, discriminant analysis of UPLC-MS metabolic profiles, displayed negative predictive values for low, low-intermediate, high-intermediate and high risk patient groups of 96.5%, 94.0%, 92.9% and 76.1% respectively. Detailed analysis of the metabolome revealed several candidate metabolites and perturbed phenylalanine, arginine, proline and tryptophan metabolisms as putative biomarkers. A pilot retrospective analysis of longitudinal trajectories of a BC metabolic biomarkers during post TURBT surveillance was carried out and the results give strong support for the clinical use of metabolomic profiling in assessing NMIBC recurrence.

Accurate determination of the concentration of the metabolites contained in intact human biopsies of 10 glioblastoma multiforme samples was achieved using one-dimensional (1)H high-resolution magic angle spinning (HR-MAS) NMR combined with ERETIC (electronic reference to in vivo concentrations) measurements. The amount of sample used ranged from 6.8 to 12.9 mg. Metabolite concentrations were measured in each sample using two methods: with DSS (2,2-dimethyl-2-silapentane-5-sulfonate sodium salt) as an internal reference and with ERETIC as an external electronically generated reference. The ERETIC signal was shown to be highly reproducible and did not affect the spectral quality. The concentrations calculated by the ERETIC method in model solutions were shown to be independent of the salt concentration in the range typically found in biological samples (0-250 mM). The ERETIC method proved to be straightforward to use in tissues and much more robust than the internal standard method. The concentrations calculated using the internal DSS concentration were systematically found to be higher than those determined using the ERETIC technique. These results indicate a possible interaction of the DSS molecules with the biopsy sample. Moreover, variations in the sample preparation process, with possible loss of DSS solution, may hamper the quantification process, as happens in one of the ten samples analysed. In this study, the ERETIC method was validated on model solutions and used in brain tumour tissues. Calculated metabolite concentrations obtained with the ERETIC procedure matched the values determined in the same type of tumours by in vivo, ex vivo and in vitro methodologies.

Metabolism reprogramming is considered a hallmark of cancer. The study of bladder cancer (BC) metabolism could be the key to developing new strategies for diagnosis and therapy. This work aimed to identify tissue and urinary metabolic signatures as biomarkers of BC and get further insight into BC tumor biology through the study of gene-metabolite networks and the integration of metabolomics and transcriptomics data. BC and control tissue samples (n = 44) from the same patients were analyzed by High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance and microarrays techniques. Besides, urinary profiling study (n = 35) was performed in the same patients to identify a metabolomic profile, linked with BC tissue hallmarks, as a potential non-invasive approach for BC diagnosis. The metabolic profile allowed for the classification of BC tissue samples with a sensitivity and specificity of 100%. The most discriminant metabolites for BC tissue samples reflected alterations in amino acids, glutathione, and taurine metabolic pathways. Transcriptomic data supported metabolomic results and revealed a predominant downregulation of metabolic genes belonging to phosphorylative oxidation, tricarboxylic acid cycle, and amino acid metabolism. The urinary profiling study showed a relation with taurine and other amino acids perturbed pathways observed in BC tissue samples, and classified BC from non-tumor urine samples with good sensitivities (91%) and specificities (77%). This urinary profile could be used as a non-invasive tool for BC diagnosis and follow-up.

1H magnetic resonance spectroscopy (MRS) allows accurate and non-invasive in vivo metabolic study, and is a useful tool for the diagnosis of different forms of dementias. Cognitive impairment pathologies have been almost exclusively studied with MRS by comparison with healthy without a global comparison amongst Alzheimer disease (AD), vascular dementia, mild cognitive impairment (MCI) and major depression patients with cognitive impairment. Whereas decrease of N-acetylaspartate (NAA) and increase myo-Inositol (mI) at different brain locations by 1H MRS are common features of AD, Choline (Cho) alterations have been inconclusive. In our study, 64 patients with cognitive impairment were evaluated by 1H MRS using two echo times (31 and 136 ms). There were statistical differences between dementia (AD and vascular dementia) and non-dementia (MCI and depression) spectra at posterior cingulate gyrus. Cho/Cr, mI/Cr and NAA/Cr have been valuables for the differentiation amongst the different cognitive impairment entities. NAA/mI provides the best area under the ROC curve with the highest sensitivity (82.5%) and specificity (72.7%) in diagnosing AD. NAA/mI and mI/Cr ratios differed amongst the four cognitive impairment degenerative pathologies. Metabolic MRS differences found amongst patients with cognitive impairment entities can be useful to differentiate between AD, vascular dementia, MCI and depression.

Wallerian degeneration measured by the NAA concentration at pons and cerebellar peduncles is present early in the disease and correlates with the number of relapses and disease duration.