Characteristic metabolic profiles revealed by 1H NMR spectroscopy for three types of human brain and nervous system tumours

Demystifying neuroblastoma malignancy through fractal dimension, entropy, and lacunarity

PURPOSE

Neuroblastoma is a pediatric solid tumor with a prognosis associated with histology and age of the patient, which are the parameters of the well-established current classification (Shimada classification). Despite the development of new treatment options, the prognosis of high-risk neuroblastoma patients is still poor. Therefore, there is a continuous need to stratify the children suffering from this tumor. A mathematical and computational approach is proposed to enable automatic and precise cancer diagnosis on the histological slide.

METHODS

We targeted the complexity of neuroblastoma by calculating its image entropy (S), fractal dimension (FD), and lacunarity (λ) in a combined mathematical code. First, we tested the proposed method for patient-derived glioma images. It allowed distinguishing between normal brain tissue, grade II, and grade III glioma, which harbor different outcomes.

RESULTS

In neuroblastoma, our analysis of image's FD, S, and λ combined with a machine learning algorithm automatically predicted tumor malignancy with a receiver operating characteristic curve of 0.82. FD, S, and λ distinguish between neuroblastoma and ganglioneuroma, but they only partially differentiate between the normal samples and the other classes. Ganglioneuroma, the most differentiated form, and poorly-differentiated neuroblastoma display different values of FD, S, and λ.

CONCLUSIONS

FD, S, and λ of imaging recognize groups in neuroblastic tumors. We suggest that future studies including these features may challenge the current Shimada classification of neuroblastoma with categories of favorable and unfavorable histology. It is expected that this methodology could trigger multicenter studies and potentially find practical use in the clinical setting of children's hospitals worldwide.

Hypotaurine evokes a malignant phenotype in glioma through aberrant hypoxic signaling

Metabolomics has shown significant potential in identifying small molecules specific to tumor phenotypes. In this study we analyzed resected tissue metabolites using capillary electrophoresis-mass spectrometry and found that tissue hypotaurine levels strongly and positively correlated with glioma grade. In vitro studies were conducted to show that hypotaurine activates hypoxia signaling through the competitive inhibition of prolyl hydroxylase domain-2. This leads to the activation of hypoxia signaling as well as to the enhancement of glioma cell proliferation and invasion. In contrast, taurine, the oxidation metabolite of hypotaurine, decreased intracellular hypotaurine and resulted in glioma cell growth arrest. Lastly, a glioblastoma xenograft mice model was supplemented with taurine feed and exhibited impaired tumor growth. Taken together, these findings suggest that hypotaurine is an aberrantly produced oncometabolite, mediating tumor molecular pathophysiology and progression. The hypotaurine metabolic pathway may provide a potentially new target for glioblastoma diagnosis and therapy.

Metabolomic signature of brain cancer

Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.

A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer

Disrupted regulation of cellular processes is considered one of the hallmarks of cancer. We analyze metabolomic and transcriptomic profiles jointly collected from breast cancer and hepatocellular carcinoma patients to explore the associations between the expression of metabolic enzymes and the levels of the metabolites participating in the reactions they catalyze. Surprisingly, both breast cancer and hepatocellular tumors exhibit an increase in their gene-metabolites associations compared to noncancerous adjacent tissues. Following, we build predictors of metabolite levels from the expression of the enzyme genes catalyzing them. Applying these predictors to a large cohort of breast cancer samples we find that depleted levels of key cancer-related metabolites including glucose, glycine, serine and acetate are significantly associated with improved patient survival. Thus, we show that the levels of a wide range of metabolites in breast cancer can be successfully predicted from the transcriptome, going beyond the limited set of those measured.

A Pilot Study on the Utility of Serum Metabolomics in Neuroblastoma Patients and Xenograft Models

BACKGROUND

Improved prediction of neuroblastoma (NB) behavior is needed to detect treatment-refractory disease and may allow further reduction in therapy for some patients. In this regard, serum metabolomic analysis has proven utility in several cancer types. We hypothesize that serum metabolomic analysis will correlate with risk-group classification for patients with NB, and sensitively detect NB in murine xenograft models.

PROCEDURE

A pilot study was done on Children's Oncology Group (COG) tumor bank sera from 10 patients (five high-, five low-risk). An institutional pilot study was carried out on five patients comparing sera obtained during active versus minimal disease (complete response/very good partial response; CR/VGPR).

XENOGRAFT

Flank tumors were established in Nu/Nu mice by injection of NB cell lines (IMR-32, SH-EP, SK-N-AS). Serum for comparison was drawn pre-injection, at 1 week after injection when there was no visible tumor, and again once tumors were grossly visible. Comparisons were also made between tumor bearing mouse serum and supernatants from NB cell lines.

METABOLOMIC ANALYSIS

Samples were analyzed by nuclear magnetic resonance and/or gas chromatography-mass spectrometry. Multivariate data analysis was conducted using SIMCA-P (Umetrics).

RESULTS

Serum metabolomic analysis differentiated high- and low-risk patients as well as active disease from CR/VGPR. Differences were in nitrogen, amino acid, and carbohydrate metabolism, as well as ketosis. The serum metabolomic signature in murine xenograft models sensitively detected NB cells and correlated with disease burden. Similar metabolic changes attributable to NB were noted in both human and murine serum.

CONCLUSIONS

Serum metabolomic analysis can distinguish several characteristics of NB. A larger analysis of COG banked sera is warranted.

Modeling cancer metabolism on a genome scale

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field.

Applying metabolomics to understand the aggressive phenotype and identify novel therapeutic targets in glioblastoma

Glioblastoma continues to be an invariably fatal malignancy. The established approach for understanding the biology of these aggressive tumors in an effort to identify novel molecular targets has largely been genotype-based. Unfortunately, clinical gains offered by this level of understanding have been limited, largely based on the complex nature of signaling networks associated with tumorigenesis and the inability to delineate the key “functional” signaling pathways actually driving growth in an individual tumor. Metabolomics is the global quantitative assessment of endogenous metabolites within a biological system, taking into account genetic regulation, altered kinetic activity of enzymes, and changes in metabolic reactions. Thus, compared to genomics and proteomics, metabolomics reflects changes in phenotype and therefore function. In this review, we highlight some of the key advancements that have been made in applying metabolomics to understand the aggressive phenotype of glioblastoma. Collectively, these studies have provided a previously unrecognized window into the underlying biology of these tumors. Current and future efforts are designed to determine how this technology may be applied to improve diagnosis and predict the aggressiveness of glioblastoma, and more importantly, identify novel, therapeutic strategies designed to improve clinical outcomes.

Clinical proton MR spectroscopy in central nervous system disorders

A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units.

Volume localized spin echo correlation spectroscopy with suppression of 'diagonal' peaks

Two dimensional homonuclear (1)H correlation spectroscopy is of considerable interest for volume localized spectral studies, both in vivo and in vitro, of biological as well as material objects. The information principally sought from correlation spectra resides in the cross-peaks, which are often masked however by the presence of diagonal peaks in COSY, or 'pseudo-diagonal' peaks at F1=0 in SECSY. It has therefore been a concern to suppress these diagonal or 'pseudo-diagonal' peaks, in order to ensure that cross-peak information is fully discernible. We present here a report of our work on volume localized DIagonal Suppressed Spin Echo Correlation specTroscopy (LDISSECT) and demonstrate its performance in comparison to the standard volume localized SECSY experiment, employing brain metabolite phantoms in a gel. The sequence works in the inhomogeneous, multi-component environment by exploiting the short acquisition time to suppress undesired information by employing an additional rf pulse. A brief description of the pulse sequence, its theory, and simulations are also included, besides experimental benchmarking on two brain metabolite phantoms in gel phase.

Magnetic resonance spectroscopy in intracranial tumours of glial origin

BACKGROUND AND PURPOSE

To determine in vivo magnetic resonance spectroscopy (MRS) characteristics of intracranial glial tumours and to assess MRS reliability in glioma grading and discrimination between different histopathological types of tumours.

MATERIAL AND METHODS

Analysis of spectra of 26 patients with glioblastomas, 6 with fibrillary astrocytomas, 4 with anaplastic astrocytomas, 2 with pilocytic astrocytoma, 3 with oligodendrogliomas, 3 with anaplastic oligodendrogliomas and 17 control spectra taken from healthy hemispheres.

RESULTS

All tumours' metabolite ratios, except for Cho/Cr in fibrillary astrocytomas (p = 0.06), were statistically significantly different from the control. The tumours showed decreased Naa and Cr contents and a high Cho signal. The Lac-Lip signal was high in grade III astrocytomas and glioblastomas. Reports that Cho/Cr ratio increases with glioma's grade whereas Naa/Cr decreases were not confirmed. Anaplastic astrocytomas compared to grade II astrocytomas had a statistically significantly greater mI/Cr ratio (p = 0.02). In pilocytic astrocytomas the Naa/Cr value (2.58 ± 0.39) was greater, whilst the Cho/Naa ratio was lower (2.14 ± 0.64) than in the other astrocytomas. The specific feature of oligodendrogliomas was the presence of glutamate/glutamine peak Glx. However, this peak was absent in two out of three anaplastic oligodendrogliomas. Characteristically, the latter tumours had a high Lac-Lip signal.

CONCLUSIONS

MRS in vivo cannot be used as a reliable method for glioma grading. The method is useful in discrimination between WHO grade I and WHO grade II astrocytomas as well as oligodendrogliomas from other gliomas.

Profiling metabolite changes in the neuronal differentiation of human striatal neural stem cells using 1H-magnetic resonance spectroscopy

OBJECTIVE

Neural stem cells (NSCs) have been found to play an increasing clinical role in stroke. However, at present, it is not yet possible to noninvasively monitor their differentiation once implanted into the brain.

METHODS

Here, we describe the use of high-resolution H-magnetic resonance spectroscopy (MRS) to define a metabolite profile of undifferentiated human striatal NSCs from the STROC05 cell line and their differentiation after 3-weeks of treatment with purmorphamine.

RESULTS

The undifferentiated conditions were characterized by ~95% of cells expressing nestin and ~77% being Ki67(+)ve, indicating that these were still proliferating. Phosphophocholine+glycerophosphocholine (PC+GPC) as well as myo-Inositol (mI) were increased in these cells. PC+GPC and mI were markedly reduced upon differentiation, potentially serving as markers of the NSC state. Upon differentiation (~45% neurons, ~30% astrocytes, ~13% oligodendrocytes), the concentration of many metabolites decreased in absolute value. The decreasing trend of the N-acetyl-aspartate level was observed in differentiated cells when compared with NSCs. An increase in plasmalogen (enriched in myelin sheets) could potentially serve as a marker of oligodendrocytes.

CONCLUSION

These metabolite characteristics of undifferentiated and differentiated NSCs provide a basis for exploration of their possible use as markers of differentiation after cell transplantation.

The metabolomic signature of malignant glioma reflects accelerated anabolic metabolism

Although considerable progress has been made toward understanding glioblastoma biology through large-scale genetic and protein expression analyses, little is known about the underlying metabolic alterations promoting their aggressive phenotype. We conducted global metabolomic profiling on patient-derived glioma specimens and identified specific metabolic programs differentiating low- and high-grade tumors, with the metabolic signature of glioblastoma reflecting accelerated anabolic metabolism. When coupled with transcriptional profiles, we identified the metabolic phenotype of the mesenchymal subtype to consist of accumulation of the glycolytic intermediate phosphoenolpyruvate and decreased pyruvate kinase activity. Unbiased hierarchical clustering of metabolomic profiles identified three subclasses, which we term energetic, anabolic, and phospholipid catabolism with prognostic relevance. These studies represent the first global metabolomic profiling of glioma, offering a previously undescribed window into their metabolic heterogeneity, and provide the requisite framework for strategies designed to target metabolism in this rapidly fatal malignancy.

1H NMR metabolomics analysis of glioblastoma subtypes: correlation between metabolomics and gene expression characteristics

Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. (1)H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas.

Metabolomics in the fields of oncology: a review of recent research

The study of all endogenously produced metabolites, known as metabolomics, is the youngest of the "omics" sciences. It is becoming increasingly clear that, of all of the "omics" techniques, metabolomic approaches will become increasingly useful in disease diagnosis and have potential power to improve our understanding of the underlying mechanisms of cancer. The primary aim of the review is to discuss the relationship between metabolomics and tumors are elucidated in detail. Then the review is also to introduce the technologies of metabolomics, especially emphasizing the application of metabolomics in the fields of oncology.

Measurement of glycine in the human brain in vivo by 1H-MRS at 3 T: application in brain tumors

Glycine is a key metabolic intermediate required for the synthesis of proteins, nucleic acids, and other molecules, and its detection in cancer could, therefore, provide biologically relevant information about the growth of the tumor. Here, we report measurement of glycine in human brain and gliomas by an optimized point-resolved spectroscopy sequence at 3 T. Echo time dependence of the major obstacle, myo-inositol (mI) multiplet, was investigated with numerical simulations, incorporating the 3D volume localization. The simulations indicated that a subecho pair (TE(1) , TE(2) ) = (60, 100) ms permits detection of both glycine and mI with optimum selectivity. In vivo validation of the optimized point-resolved spectroscopy was conducted on the right parietal cortex of five healthy volunteers. Metabolite signals estimated from LC Model were normalized with respect to the brain water signal, and the concentrations were evaluated assuming the total creatine concentration at 8 mM. The glycine concentration was estimated as 0.6 ± 0.1 mM (mean ± SD, n = 5), with a mean Cramér-Rao lower bound of 9 ± 1%. The point-resolved spectroscopy sequence was applied to measure the glycine levels in patients with glioblastoma multiforme. Metabolite concentrations were obtained using the water signal from the tumor mass. The study revealed that a subset of human gliomas contains glycine levels elevated 1.5-8 fold relative to normal.

Metabolomic pattern of childhood neuroblastoma obtained by ¹H-high-resolution magic angle spinning (HRMAS) NMR spectroscopy

BACKGROUND

The aim of this preliminary study is to characterize by ¹H high-resolution magic angle spinning NMR spectroscopy (HRMAS) the metabolic content of intact biopsy samples obtained from 12 patients suffering from neuroblastoma (NB).

PROCEDURE

The biochemical NB profile was first compared to normal adrenal medulla. In a second step, the relationship between the tumor metabolic profile and the patients' clinical data was investigated.

RESULTS

A higher level of creatine, glutamine/glutamate, acetate and glycine characterized NB biopsies while healthy adrenal medulla tissue contained adrenaline and a larger amount of ascorbic acid. Adrenaline, which was undetectable in NB spectra, represented the metabolic signature of normal adrenal medulla. NB from patients younger than 12 months contained a higher level of acetate and lysine. Conversely, higher amounts of glutathione, glutamate, myo-inositol, glycine, serine and ascorbic acid were detected in NB samples belonging to younger children. Glutamine/glutamate, aspartate, creatine, glycine were characteristic of stage I-II NB. Acetate and creatine were characteristic of stage IV NB. Finally, a relatively higher amount of aspartate, succinate, and glutathione was detected in patients alive without active disease after a mean follow-up of 7 years whereas a higher concentration of acetate and taurine was characteristic of patients with worse prognosis.

CONCLUSIONS

Our preliminary results suggest the existence of a complex metabolic reality in NB, probably representative of tumor behavior. However, the real impact of these promising results should be assessed by long-term prospective studies on a larger cohort of patients.

Metabolomic patterns in glioblastoma and changes during radiotherapy: a clinical microdialysis study

We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers

BACKGROUND

High-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are "NMR visible" will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies.

RESULTS

1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour (astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis.

CONCLUSIONS

A number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours.

Genetical systems biology in livestock: application to gonadotrophin releasing hormone and reproduction

Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology.

Molecular classification of brain tumor biopsies using solid-state magic angle spinning proton magnetic resonance spectroscopy and robust classifiers

Brain tumors are one of the leading causes of death in adults with cancer; however, molecular classification of these tumors with in vivo magnetic resonance spectroscopy (MRS) is limited because of the small number of metabolites detected. In vitro MRS provides highly informative biomarker profiles at higher fields, but also consumes the sample so that it is unavailable for subsequent analysis. In contrast, ex vivo high-resolution magic angle spinning (HRMAS) MRS conserves the sample but requires large samples and can pose technical challenges for producing accurate data, depending on the sample testing temperature. We developed a novel approach that combines a two-dimensional (2D), solid-state, HRMAS proton (1H) NMR method, TOBSY (total through-bond spectroscopy), which maximizes the advantages of HRMAS and a robust classification strategy. We used approximately 2 mg of tissue at -8 degrees C from each of 55 brain biopsies, and reliably detected 16 different biologically relevant molecular species. We compared two classification strategies, the support vector machine (SVM) classifier and a feed-forward neural network using the Levenberg-Marquardt back-propagation algorithm. We used the minimum redundancy/maximum relevance (MRMR) method as a powerful feature-selection scheme along with the SVM classifier. We suggest that molecular characterization of brain tumors based on highly informative 2D MRS should enable us to type and prognose even inoperable patients with high accuracy in vivo.

Metabonomics and its application in oncobiology research

The primary aim of this review is to introduce the research status of metabonomics/metabolomics and the application of metabonomics in oncobiology research. At first, the concept of metabonomics and the relationship between metabonomics and tumors are elucidated in detail. Then the research technologies of metabonomics in oncobiology are introduced. Finally, the latest advances in the application of metabonomics in early diagnosis, treatment and prognosis of tumors are summarized.

Cerebral ependymoma in a patient with multiple sclerosis case report and critical review of the literature

BACKGROUND

The concurrence of multiple sclerosis (MS) and brain tumors is a rare but well-recognized condition. The radiologic evidence of the progressive evolution of a mega-plaque in a tumor has never been described. We report the first case of such an occurrence.

METHODS

A 27-year-old woman with a diagnosis of MS was referred to us for an intense frontal headache. Magnetic resonance imaging showed a mass lesion in correspondence of a black hole lesion previously diagnosed. The patient was operated on, with complete removal of the tumor documented by an intraoperative MRI. The histologic examination evidenced an ependymoma. Postoperative radiotherapy was performed.

RESULTS

The patient is well and recurrence-free at 2 years follow-up.

CONCLUSIONS

The present case, documenting the transformation of a mega-plaque into a tumor, suggests a cause-effect relationship between MS and brain tumors.

1H MRS identifies specific metabolite profiles associated with MYCN-amplified and non-amplified tumour subtypes of neuroblastoma cell lines

Neuroblastoma is the most common extracranial solid malignancy in children. The disease possesses a broad range of clinical phenotypes with widely varying prognoses. Numerous studies have sought to identify the associated genetic abnormalities in the tumour, resulting in the identification of useful prognostic markers. In particular, the presence of multiple copies of the MYCN oncogene (referred to as MYCN amplification) has been found to confer a poor prognosis. However, the molecular pathways involved are as yet poorly defined. Metabolite profiles generated by in vitro (1)H MRS provide a means of investigating the downstream metabolic consequences of genetic alterations and can identify potential targets for new agents. Thirteen neuroblastoma cell lines possessing multiple genetic alterations were investigated; seven were MYCN amplified and six MYCN non-amplified. In vitro magic angle spinning (1)H MRS was performed on cell suspensions, and the spectra analysed to obtain metabolite concentration ratios relative to total choline (tCho). A principal component analysis using these concentration ratios showed that MYCN-amplified and non-amplified cell lines form separate classes according to their metabolite profiles. Phosphocholine/tCho and taurine/tCho were found to be significantly raised (p < 0.05) and glycerophosphocholine/tCho significantly reduced (p < 0.05) in the MYCN-amplified compared with the MYCN non-amplified cell lines (two-tailed t test). (1)H MRS of the SH-EP1 cell line and an isogenic cell line transfected with the MYCN oncogene also showed that MYCN oncogene over-expression causes alterations in phosphocholine, glycerophosphocholine and taurine concentrations. Molecular pathways of choline and taurine metabolism are potential targets for new agents tailored to MYCN-amplified neuroblastoma.

A metabolomics perspective of human brain tumours

During the past decade or so, a wealth of information about metabolites in various human brain tumour preparations (cultured cells, tissue specimens, tumours in vivo) has been accumulated by global profiling tools. Such holistic approaches to cellular biochemistry have been termed metabolomics. Inherent and specific metabolic profiles of major brain tumour cell types, as determined by proton nuclear magnetic resonance spectroscopy ((1)H MRS), have also been used to define metabolite phenotypes in tumours in vivo. This minireview examines the recent advances in the field of human brain tumour metabolomics research, including advances in MRS and mass spectrometry technologies, and data analysis.

Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors

Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. We have used a metabolite profiling approach to test the hypothesis that quantitative signatures of primary metabolites can be used to characterize molecular changes in ovarian tumor tissues. Sixty-six invasive ovarian carcinomas and nine borderline tumors of the ovary were analyzed by gas chromatography/time-of-flight mass spectrometry (GC-TOF MS) using a novel contamination-free injector system. After automated mass spectral deconvolution, 291 metabolites were detected, of which 114 (39.1%) were annotated as known compounds. By t test statistics with P < 0.01, 51 metabolites were significantly different between borderline tumors and carcinomas, with a false discovery rate of 7.8%, estimated with repeated permutation analysis. Principal component analysis (PCA) revealed four principal components that were significantly different between both groups, with the highest significance found for the second component (P = 0.00000009). PCA as well as additional supervised predictive models allowed a separation of 88% of the borderline tumors from the carcinomas. Our study shows for the first time that large-scale metabolic profiling using GC-TOF MS is suitable for analysis of fresh frozen human tumor samples, and that there is a consistent and significant change in primary metabolism of ovarian tumors, which can be detected using multivariate statistical approaches. We conclude that metabolomics is a promising high-throughput, automated approach in addition to functional genomics and proteomics for analyses of molecular changes in malignant tumors.

The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Analysis of the changes in the 1H NMR spectral pattern of perchloric acid extracts of C6 cells with growth

The aim of this work was to identify spectral markers of cell proliferation that could be of use in clinical MRS. Cultured C6 ATCC rat glioma cells were used as models for this purpose and metabolites were extracted with perchloric acid at three different growth curve stages: log, confluence and post-confluence. 1D and 2D in vitro(1)H NMR spectra were recorded at 9.4 T. Statistically significant changes in myo-inositol and glutamine concentrations between log phase and post-confluence were found when normalized to the creatine ratio. The myo-inositol/creatine ratio was 2.76 +/- 0.82 at log phase increasing to 7.43 +/- 1.34 at post-confluence, while the glutamine/creatine ratio decreased from 0.22 +/- 0.03 to 0.10 +/- 0.02. No significant differences were recorded for other metabolites investigated. The fact that both myo-inositol and glutamine are detectable by in vivo MRS at clinical fields makes their changes relevant as potential astrocytic tumour proliferation rate markers in clinical MRS.

Metabolic differences between primary and recurrent human brain tumors: a 1H NMR spectroscopic investigation

High-resolution proton magnetic resonance spectroscopy was performed on tissue specimens from 33 patients with astrocytic tumors (22 astrocytomas, 11 glioblastomas) and 13 patients with meningiomas. For all patients, samples of primary tumors and their first recurrences were examined. Increased anaplasia, with respect to malignant transformation, resulting in a higher malignancy grade, was present in 11 recurrences of 22 astrocytoma patients. Spectroscopic features of tumor types, as determined on samples of the primary occurrences, were in good agreement with previous studies. Compared with the respective primary astrocytomas, characteristic features of glioblastomas were significantly increased concentrations of alanine (Ala) (p = 0.005), increased metabolite ratios of glycine (Gly)/total creatine (tCr) (p = 0.0001) and glutamate (Glu)/glutamine (Gln) (p = 0.004). Meningiomas showed increased Ala (p = 0.02) and metabolite ratios [Gly, total choline (tCho), Ala] over tCr (p = 0.001) relative to astrocytomas, and N-acetylaspartate and myo-inositol were absent. Metabolic changes of an evolving tumor were observed in recurrent astrocytomas: owing to their consecutive assessments, more indicators of malignant degeneration were detected in astrocytoma recurrences (e.g. Gly, p = 0.029; tCho, p = 0.034; Glu, p = 0.015; tCho/tCr, p = 0.001) in contrast to the comparison of primary astrocytomas with primary glioblastomas. The present investigation demonstrated a correlation of the tCho-signal with tumor progression. Significantly elevated concentrations of Ala (p = 0.037) and Glu (p = 0.003) and metabolite ratio tCho/tCr (p = 0.005) were even found in recurrent low-grade astrocytomas with unchanged histopathological grading (n = 11). This may be related to an early stage of malignant transformation, not yet detectable morphologically, and emphasizes the high sensitivity of 1H NMR spectroscopy in elucidating characteristics of brain tumor metabolism.

Proton magnetic resonance spectroscopy in neuroblastoma: Current status, prospects and limitations

Non-invasive biological information about residual neuroblastoma tumour tissue could allow treatment monitoring without the need for repeated biopsies. Magnetic resonance spectroscopy (MRS) can be performed with standard MR-scanners, providing specific biochemical information from selected tumour regions. By proton 1H-MRS, lipids, certain amino acids and lactate can be detected and their relative concentrations estimated in vivo. Using experimental models of neuroblastoma, we have described the potential of 1H-MRS for the prediction of tumour tissue viability and treatment response. Whereas viable neuroblastoma tissue is dominated by the choline 1H-MRS resonance, cell death as a consequence of spontaneous necrosis or successful treatment with chemotherapy, angiogenesis inhibitors, or NSAIDs is associated with decreased choline content. Therapy-induced neuroblastoma cell death is also associated with enhanced 1H-MRS resonances from mobile lipids and polyunsaturated fatty acids. The mobile lipid/choline ratio correlates significantly with cell death and based on the dynamics of this ratio tumour regression or continued growth (drug resistance) after chemotherapy can be predicted in vivo. The implications of these findings are discussed with focus on the potentials and limitations of introducing 1H-MRS for clinical assessment of treatment response in children with neuroblastoma. Biochemical monitoring of neuroblastoma with 1H-MRS could enable tailoring of individual therapy as well as provide early pharmacodynamic evaluation of novel therapeutic modalities.

The development of functional imaging in the diagnosis, management and understanding of childhood brain tumours

Imaging plays a fundamental role in the management of children with brain tumours. A series of new techniques, commonly grouped under the heading functional imaging, promise to give information on the properties and biological characteristics of tissues thereby adding to the structural information available from current imaging. The EPSRC funded a workshop to bring together clinicians from the UK Children's Cancer Study Group and scientific experts in the field to identify clinical problems in childhood brain tumours that may be addressed by functional imaging and to develop a clinical test bed for applying, evaluating and developing this new technology. The presentations and discussion sessions from the workshop are summarised and a review of the current 'state of the art' for this rapidly developing area provided. A key output of the workshop was agreement on a series of hypotheses which can be tested in carefully designed clinical studies.

Metabolic profiles to define the genome: can we hear the phenotypes?

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified by the description of the silent phenotype in genetic manipulations of yeast. High-resolution proton nuclear magnetic resonance ((1)H NMR) spectroscopy provides an ideal mechanism for the profiling of metabolites within biofluids, tissue extracts or, with recent advances, intact tissues. These metabolic datasets can be readily mined using a range of pattern recognition techniques, including hierarchical cluster analysis, principal components analysis, partial least squares and neural networks, with the combined approach being termed metabolomics. This review describes the application of NMR-based metabolomics or metabonomics to genetic and chemical interventions in a number of different species, demonstrating the versatility of such an approach, as well as suggesting how it may be integrated with other "omic" technologies.

1H MR spectroscopy of brain tumours and masses

Accurate diagnosis is essential for optimum management and treatment of patients with brain tumours. Proton magnetic resonance spectroscopy ((1)H MRS) provides information non-invasively on tumour biochemistry and has been shown to provide important additional information to that obtained by conventional radiology. We review the current status of (1)H MRS in classifying brain tumour type and grade, for monitoring response to therapy and progression to higher grade, and as a molecular imaging technique for determining tumour extent for treatment planning.

Noninvasive estimation of tumour viability in a xenograft model of human neuroblastoma with proton magnetic resonance spectroscopy (1H MRS)

The aim of the study was to evaluate proton magnetic resonance spectroscopy ((1)H MRS) for noninvasive biological characterisation of neuroblastoma xenografts in vivo. For designing the experiments, human neuroblastoma xenografts growing subcutaneously in nude rats were analysed in vivo with (1)H MRS and magnetic resonance imaging at 4.7 T. The effects of spontaneous tumour growth and antiangiogenesis treatment, respectively, on spectral characteristics were evaluated. The spectroscopic findings were compared to tumour morphology, proliferation and viable tumour tissue fraction. The results showed that signals from choline (Cho)-containing compounds and mobile lipids (MLs) dominated the spectra. The individual ML/Cho ratios for both treated and untreated tumours were positively correlated with tumour volume (P<0.05). There was an inverse correlation between the ML/Cho ratio and the viable tumour fraction (r=-0.86, P<0.001). Higher ML/Cho ratios concomitant with pronounced histological changes were seen in spectra from tumours treated with the antiangiogenic drug TNP-470, compared to untreated control tumours (P<0.05). In conclusion, the ML/Cho ratio obtained in vivo by (1)H MRS enabled accurate assessment of the viable tumour fraction in a human neuroblastoma xenograft model. (1)H MRS also revealed early metabolic effects of antiangiogenesis treatment. (1)H MRS could prove useful as a tool to monitor experimental therapy in preclinical models of neuroblastoma, and possibly also in children.

Cellular environment of metabolites and a metabonomic study of tamoxifen in endometrial cells using gradient high resolution magic angle spinning 1H NMR spectroscopy

High resolution magic angle spinning (HRMAS) 1H NMR spectroscopy was used to metabolically characterise Ishikawa cells, a human cell line derived from endometrial adenocarcinoma. The spectra obtained had well-resolved resonances from the nucleotide derivatives of uridine and adenosine. Using a combination of diffusion- and relaxation-weighted spectroscopy, the cellular environment of key metabolites previously identified as related to cell growth was also investigated. As Ishikawa cells are hormone-responsive, the metabolic action of tamoxifen, a selective estrogen receptor modulator (SERM), was also investigated. Cells were exposed to 5, 1 and 0.1 microM tamoxifen. Using the statistical regression technique of prediction to latent structures by partial least squares, a predictive model was built modelling the metabolic profile of the cells against exposure to tamoxifen. These spectral changes were characterised by increased resonance intensities from ethanolamine (3.26 ppm), glucose (3.34-3.94 ppm), glutamate (2.14, 2.32 ppm), tyrosine (7.24 ppm), uridine (7.85 ppm) and adenosine (8.20 ppm), and a relative decrease in contributions from myo-inositol resonances (3.30, 3.62, 3.55 ppm). The nucleotide changes suggest that tamoxifen affects RNA transcription, while the changes in ethanolamine and myo-inositol concentrations are indicative of cell membrane turnover.

Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data

OBJECT

In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors.

METHODS

Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors.

CONCLUSIONS

The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.

Biochemical characterization of pediatric brain tumors by using in vivo and ex vivo magnetic resonance spectroscopy

OBJECT

Magnetic resonance (MR) spectroscopy provides biochemical information about tumors. The authors sought to determine the relationship between in vivo and ex vivo biochemical characterization of pediatric brain tumors by using MR spectroscopy. Their hypothesis was that ex vivo MR spectroscopy provides a link between in vivo MR spectroscopy and neuropathological analysis.

METHODS

In vivo proton MR spectroscopy was performed before surgery in 11 patients with neuroepithelial tumors. During resection, a total of 40 tumor biopsy samples were obtained from within the volume of interest identified on in vivo MR spectroscopy and were frozen immediately in liquid nitrogen. High-Resolution Magic Angle Spinning (HRMAS) was used to perform ex vivo MR spectroscopy in these 40 tumor biopsy samples. Neuropathological analysis was performed using the same biopsy samples, and the tumors were classified as ependymoma, choroid plexus carcinoma, pineoblastoma (one each), and pilocytic astrocytoma, medullobastoma, low-grade glioma, and glioblastoma multiforme (two each). Ex vivo HRMAS MR spectroscopy improved line widths and line shapes in the spectra, compared with in vivo MR spectroscopy. Choline (Cho) detected in vivo corresponded to three different peaks ex vivo (glycerophosphocholine, phosphocholine [PCho], and Cho). Metabolite ratios from in vivo spectra correlated with ratios from ex vivo spectra (Pearson correlation coefficient range r = 0.72-0.91; p < or = 0.01). Metabolite ratios from ex vivo spectra, such as PCho/ total creatine (tCr) and lipid/tCr, correlated with the percentage of cancerous tissue and percentage of tumor necrosis, respectively (r = 0.84; p < 0.001).

CONCLUSIONS

Agreement between in vivo and ex vivo MR spectroscopy indicates that ex vivo HRMAS MR spectroscopy can improve resolution of this modality and provide a link between in vivo MR spectroscopy and neuropathological analysis.

1H- and (31)P-MR spectroscopy of primary and recurrent human brain tumors in vitro: malignancy-characteristic profiles of water soluble and lipophilic spectral components

In vitro NMR spectroscopy was performed on specimen of human brain tumors. From all patients, tissue samples of primary tumors and their first recurrences were examined. (31)P- and (1)H-spectra were recorded from samples of meningioma, astrocytoma and glioblastoma. A double extraction procedure of the tissue samples permitted acquisition of information from the membrane fraction and from the cytosolic fraction. (31)P-spectra were used to analyze the lipophilic fraction (phospholipids of the membrane) of the tissue extracts, while the (1)H-spectra reflected information on the metabolic alterations of the hydrophilic, cytosolic fraction of the tissue. The tumor types showed distinctive spectral patterns in both the (31)P- and the (1)H-spectra. Based on the total detectable (31)P signal, the level of phosphatidylcholine was about 34% lower in primary astrocytomas than in primary glioblastomas (p = 0.0003), whereas the level of sphingomyelin was about 45% lower in primary glioblastomas than in primary astrocytomas (p = 0.0061). A similar tendency of these phospholipids was observed when comparing primary and recurrent astrocytoma samples from the same individuals [+15% (p = 0.0103) and -23% (p = 0.0314) change, respectively]. (1)H-spectra of gliomas were characterized by an increase of the ratios of alanine, glycine and choline over creatine as a function of the degree of malignancy. In agreement with findings in the (31)P-spectra, the (1)H-spectra of recurrent astrocytomas showed metabolic profiles of increased malignancy in comparison to their primary occurrence. Since gliomas tend to increase in malignancy upon recurrence, this may reflect evolving tumor metabolism. (1)H-spectra of meningiomas showed the highest ratio of alanine over creatine accompanied by a near absence of myo-inositol. Phospholipid profiles of meningiomas showed higher fractional contents of phosphatidylcholine along with lower phosphatidylserine compared to astrocytomas, while higher phosphatidylethanolamine and sphingomyelin fractional contents distinguished meningiomas from glioblastomas. The extraction method being used in this study combined with high-resolution (1)H- and (31)P-MRS provides a wide range of biochemical information, which enables differentiation not only between tumor types but also between primary and recurrent gliomas, reflecting an evolving tumor metabolism.

MR spectroscopy: a powerful tool for investigating brain function and neurological diseases

Magnetic resonance spectroscopy (MRS) has attracted much attention in recent years and has become an important tool to study in vivo particular biochemical aspects of brain disorders. Since the proton is the most sensitive stable nucleus for MRS, and since almost all metabolites contain hydrogen atoms, investigation by in vivo 1H MRS provides chemical information on tissue metabolites, thus enabling a non-invasive assessment of changes in brain metabolism underlying several brain diseases. In this review a brief description of the basic principles of MRS is given. Moreover, we provide some explanations on the techniques and technical problems related to the use of 1H MRS in vivo including water suppression, localization, editing, quantitation and interpretation of 1H spectra. Finally, we discuss the more recent advancement in three major areas of neurological diseases: brain tumors, multiple sclerosis, and inborn errors of metabolism.

Proton NMR chemical shifts and coupling constants for brain metabolites

Proton NMR chemical shift and J-coupling values are presented for 35 metabolites that can be detected by in vivo or in vitro NMR studies of mammalian brain. Measurements were obtained using high-field NMR spectra of metabolites in solution, under conditions typical for normal physiological temperature and pH. This information is presented with an accuracy that is suitable for computer simulation of metabolite spectra to be used as basis functions of a parametric spectral analysis procedure. This procedure is verified by the analysis of a rat brain extract spectrum, using the measured spectral parameters. In addition, the metabolite structures and example spectra are presented, and clinical applications and MR spectroscopic measurements of these metabolites are reviewed.

High-performance liquid chromatographic analysis of physiological amino acids in human brain tumors by pre-column derivatization with phenylisothiocyanate

A reversed-phase high-performance liquid chromatographic technique for the determination of free amino acids in five biopsies of human brain tumors (two meningiomas, one glioblastoma and two oligodendrogliomas) is described. The frozen tissues were homogenized, deproteinized with perchloric acid and neutralized with potassium hydroxide. Aliquots of the supernatant containing the physiological amino acids are used for pre-column derivatization with phenylisothiocyanate. The derivatized PTC-amino acids (phenylthiocarbamyl derivatives) are stable for a five day period if stored as a powder at -20 degrees C in an inert atmosphere and they can be analyzed on a reversed-phase column (PicoTag) using a gradient of two eluents with absorption detection at a wavelength of 254 nm. Good resolution of several amino acids (>30) is achieved within ca. 60 min. For most amino acids this method is suitable for an accurate measurement over a wide range of physiological concentrations (50-400 pmol) starting from a very small amount of sample.

Comparison of in vivo 1H MRS of human brain tumours with 1H HR-MAS spectroscopy of intact biopsy samples in vitro

High resolution magic angle spinning (MAS) 1H nuclear magnetic resonance (NMR) spectroscopy has been employed to study intact human brain tumour tissue and comparison with the corresponding in vivo spectrum has been made. Two dimensional 1H MAS-NMR measurements, including J-resolved and homonuclear shift correlation spectra, were obtained to aid metabolite signal assignment. MAS gave greatly improved line-shape and reduced line-width in comparison to conventional high resolution in vivo 1H MRS of intact tissue, permitting the simultaneous detection of cellular lipids and metabolites. The technique provides the most direct method for comparison of in vivo spectra with high resolution spectra in vitro and hence allows more reliable peak assignment of in vivo 1H MRS spectra.

Characterization of choline compounds with in vitro 1H magnetic resonance spectroscopy for the discrimination of primary brain tumors

RATIONALE AND OBJECTIVES

The authors sought to compare 1H magnetic resonance spectroscopy (MRS) spectra from extracts of low-grade and high-grade gliomas, especially with respect to the signals of choline-containing compounds.

METHODS

Perchloric acid extracts of six high-grade and six low-grade gliomas were analyzed by 1H MRS at 9.4 Tesla.

RESULTS

The signals of glycerophosphocholine (GPC) at 3.23 ppm, phosphocholine (PC) at 3.22 ppm, and choline (Cho) at 3.21 ppm were identified in both types of tumors. The absolute concentrations of all Cho-containing compounds (GPC + PC + Cho) in high-grade and low-grade gliomas were significantly different. The relative contributions of each of the Cho-containing compounds to the total choline signal were also statistically different. For high-grade gliomas, the choline signal is composed of GPC, PC, and Cho in a well-balanced contribution, whereas in low-grade gliomas, the signal is largely due to GPC with a small involvement of PC and Cho.

CONCLUSIONS

The differences in the concentration and the repartition of Cho-containing compounds seem to be a marker of high-grade gliomas. They could also help to discriminate between high- and low-grade gliomas in some difficult cases, especially if there is histologic uncertainty between anaplastic astrocytomas and low-grade oligodendrogliomas.

Pattern recognition analysis of 1H NMR spectra from perchloric acid extracts of human brain tumor biopsies

Pattern recognition techniques (factor analysis and neural networks) were used to investigate and classify human brain tumors based on the 1H NMR spectra of chemically extracted biopsies (n = 118). After removing information from lactate (because of variable ischemia times), unsupervised learning suggested that the spectra separated naturally into two groups: meningiomas and other tumors. Principal component analysis reduced the dimensionality of the data. A back-propagation neural network using the first 30 principal components gave 85% correct classification of meningiomas and nonmeningiomas. Simplification by vector rotation gave vectors that could be assigned to various metabolites, making it possible to use or to reject their information for neural network classification. Using scores calculated from the four rotated vectors due to creatine and glutamine gave the best classification into meningiomas and nonmeningiomas (89% correct). Classification of gliomas (n = 47) gave 62% correct within one grade. Only inositol showed a significant correlation with glioma grade.

Further assignment of resonances in 1H NMR spectra of cerebrospinal fluid (CSF)

A number of previously unidentified 1H NMR signals detected in CSF spectra of patients with various neurological and metabolic diseases are assigned to metabolites, drugs and drug excipients. Two-dimensional 1H NMR spectroscopy (COSY and J-resolved) is employed to resolve resonances which are hidden by superimposed peaks in one-dimensional spectra. Assignments obtained by making use of 2-D techniques, and of a 1-D 1H NMR data base created for ca. 150 authentic compounds, enable us to clarify the nature of complex signal patterns found in crowded spectral regions of CSF such as the aliphatic methyl region at ca. 1.0 ppm.

Nuclear magnetic resonance spectroscopy of cancer

Nuclear magnetic resonance spectroscopy (MRS) offers a non-invasive approach for studying tumour biochemistry and physiology. This review highlights NMR nuclei (31P, 1H, 19F, 13C, 2H) that have been observed in both pre-clinical and clinical spectroscopic studies of cancer.