Metabolic signatures of galactosemia in magnetic resonance

INTRODUCTION. Cancer cells quickly adapt to their microenvironment by reprogramming their metabolism. Specific metabolic responses to defined stress conditions, mimicking tumor microenvironmental changes, may therefore unveil signatures of cancer phenotype, not detected in standard tissue culture. PURPOSE. To identify distinct metabolic signatures associated with metastatic ability, we investigated in the two isogenic breast cancer cell lines, 4T1 (highly metastatic) and 67NR (non-metastatic), how glutamine supply/deprivation affects cellular glucose metabolism, and vice-versa, in aerobic or hypoxic conditions, and the effects on cell growth. METHODS. 4T1 and 67NR cells were cultured in medium A, i.e. DME containing 1% P/S, 10% FBS, 25 mM glucose (Glc), and 6 mM glutamine (Gln). Cell growth was determined in tissue culture from cells cultured for 48 h in various media A-D: A, all nutrients available; B: A but no Gln; C: A but 2 mM Gln; D: A but no Glc. Cellular mitochondrial function was also assessed in both 4T1 and 67NR cells using an XF96 Analyzer (Sea Horse Bioscience, Billerica, MA) and the specific inhibitors: oligomycin, FCCP, antimycin and rotenone. Metabolism was studied in cells grown on microcarriers in the various media A-D under aerobic (∼21% O2) and hypoxic conditions (∼1% O2), using our magnetic resonance (MR)-compatible cell perfusion system on a 500 MHz spectrometer. For the cell perfusion studies, Glc or Gln were exchanged for 1–13C-Glc or 3–13C-Gln respectively. The metabolic fate of 13C-labeled nutrients was followed under the various environmental conditions by 13C MR spectroscopy (MRS), while energy metabolism was observed by 31P MRS. RESULTS. Deprivation of either Glc or Gln for 48 h reduced significantly the cell growth of 4T1 and 67NR cells, resulting in a similar growth rate for the nutrient-deprived 4T1 and 67NR cells. As determined from the MR experiments, each cell line adopted different metabolic strategies to cope when exposed to specific metabolite stress conditions, including on the level of oxygen availability. Unlike in 67NR cells, glycolysis is glutamine-dependent in the more aggressive 4T1 cell line (∼2-fold higher glucose-derived lactate synthesis rate was observed in the presence of glutamine), which decreases when oxygen becomes available to fuel TCA cycle activity, as monitored by glucose-derived glutamate synthesis. The studies further indicate an impaired TCA cycle activity in 67NR cells, reflected in a high accumulation rate of glucose- or glutamine-derived succinate (significantly higher compared to 4T1 cells). This is consistent with the mitochondrial functional analysis, showing higher mitochondrial TCA activity in 4T1 cells than in 67NR, most likely due to impairment of succinate dehydrogenase (SDH, respiratory Complex II) in the latter. CONCLUSIONS. Our results support the association between increased mitochondrial metabolism and metastatic potential, observed recently. We are investigating the SDH status in these cells lines and in additional metastatic and non-metastatic breast cancer cell lines, to establish whether SDH, and glutamine metabolism, could be potential targets for therapy. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P6-01-01.

Where are we in the search for noninvasive nonalcoholic steatohepatitis biomarkers?

Despite the improving imaging techniques, it remains challenging to produce magnetic resonance (MR) imaging fingerprints depicting severity of acute ischemia. The aim of this study was to evaluate the potential of the overall high-field 1 H MR Spectroscopy (1 H-MRS) neurochemical profile as a metabolic signature for acute ischemia severity in rodent brains. We modeled global ischemia with one-stage 4-vessel-occlusion (4VO) in rats. Vascular structures were assessed immediately by magnetic resonance angiography. The neurochemical responses in the bilateral cortex were measured 1h after stroke onset by 1 H-MRS. Then we used Partial-Least-Squares discriminant analysis on the overall neurochemical profiles to seek metabolic signatures for ischemic severity subgroups. This approach was further tested on neurochemical profiles of mouse striatum 1h after permanent middle cerebral artery occlusion, where vascular blood flow was monitored by laser Doppler. Magnetic resonance angiography identified successful 4VO from controls and incomplete global ischemia (e.g., 3VO). 1 H-MR spectra of rat cortex after 4VO showed a specific metabolic pattern, distinct from that of respective controls and rats with 3VO. Partial-Least-Squares discriminant analysis on the overall neurochemical profiles revealed metabolic signatures of acute ischemia that may be extended to mice after permanent middle cerebral artery occlusion. Fingerprinting severity of acute ischemia using neurochemical information may improve MR diagnosis in stroke patients.

Purpose:
\n Proton magnetic resonance spectroscopy (1 H-MRS) has been proposed as a tool to assess male
\ninfertility providing metabolic signatures related to the spermatogenesis in the testis. This study sought to identify the
\nrole of 1 H-MRS in the diagnosis of infertility in patients with semen analysis altered.
\nMaterials and Methods:
\n 14 patients (27 testicles) with fertility problems and with an altered semen analysis (5
\noligospermia, 3 asthenospermia, 6 oligoasthenospermia) and 9 controls (18 testicles) with normal spermatogenesis
\nassessed (men with prior paternity and normal semen analysis) and normal testicles at magnetic resonance (MR)
\nand ultrasonography (US) with colour Doppler (CD) examination were included. All patients underwent testis US and
\nCD investigation, conventional MR examination at 1.5T including T1 and T2 weighted images in three orthogonal
\nplanes and proton magnetic resonance spectroscopy (1 H-MRS) with single-voxel PRESS (TR 2000 ms / TE 31
\nms). Major metabolites peaks (choline, creatine, lipids, lactate) were calculated and compared between the patients
\nand controls.
\nResults:
\n Mean choline peak in the semen analysis altered group was statistically significantly lower than the
\nnormal group (0.69 vs 1.34, 95% CI: 0.52 - 0.85; p < 0.001). 18 testicles within semen analysis altered group
\n(66,7%) had both MR and US examination negative but mean choline peak lower then controls (1.09 vs 1.34, p <
\n0.001). 7 testicles of those presented also varicocele at CD investigation.
\nConclusion:
\n 1 H-MRS revealed a significant shift towards lower choline peak in patients with semen analysis
\naltered compared to controls with normal spermatogenesis. Moreover 1 HMRS provided to find out spermatogenesis
\ndisorder in patients with normal testis at MR and US examination.

Proton magnetic resonance spectroscopy (HMRS) is the only way to study noninvasively the metabolic and biochemical signature of the human tissues and organs.It can also quantify the metabolites within the volume of interest.The metabolic information about the lesions provided by the HMRS can greatly improve the diagnostic,grading accuracy,treatment planning such as target delineation and posttreatment follow-up of the glioma. Key words: Magnetic resonance spectroscopy; Glioma; Target delineation

Ambient air pollution is associated with heart failure (HF), but underlying biological mechanisms remain unclear. We aimed to elucidate metabolic pathways linking air pollution exposure with HF. This prospective cohort study analysed 229 812 UK Biobank participants with nuclear magnetic resonance metabolomics data. Air pollution score was constructed by fine particulate matter, coarse particulate matter, nitrogen dioxide and nitrogen oxides. Air pollution-associated metabolic signatures were identified using elastic net regression among 251 circulating metabolites. Cox regression evaluated associations between metabolic signatures and incident HF risk. Mediation analysis quantified metabolic signatures' role in air pollution-HF relationships. During median 13.1-year follow-up, 8986 participants (3.9%) developed HF. We identified 53 metabolic metabolites reflecting air pollution exposure, comprising lipoprotein metabolism markers (22.6%), fatty acids (17.0%) and amino acids (13.2%), which were used to construct the air pollution-related metabolic signatures score. After adjustment for confounding factors, each SD increase in the metabolic signatures was associated with 8% elevated HF risk (HR 1.08, 95% CI 1.06 to 1.11). Participants in the highest quantile showed a 24% increased HF risk compared with those in the lowest quantile (HR 1.24, 95% CI 1.16 to 1.3). The metabolic signatures mediated 13.08% (95% CI 12.15% to 15.71%) of air pollution-HF associations, with lipoprotein metabolism and fatty acid signatures as primary mediators. Air pollution was associated with increased HF risk, with metabolic perturbations appearing to play a mediating role. These metabolic signatures provide insights into potential mechanisms linking air pollution to cardiovascular outcomes.

BackgroundDistinguishing between some benign lipomas (BLs), atypical lipomatous tumors (ALTs), and dedifferentiated liposarcomas (DDLs) can be challenging due to overlapping magnetic resonance imaging characteristics, and poorly understood molecular mechanisms underlying the malignant transformation of liposarcomas.PurposeTo identify metabolic biomarkers of the lipomatous tumor spectrum by examining human tissue specimens using high-resolution 1H magnetic resonance spectroscopy (MRS).Materials and methodsIn this prospective study, human tissue specimens were obtained from participants who underwent surgical resection for radiologically-indeterminate lipomatous tumors between November 2016 and May 2019. Tissue specimens were obtained from normal subcutaneous fat (n=9), BLs (n=10), ALTs (n=7) and DDLs (n=8). Extracts from specimens were examined with high-resolution MRS at 17.6T. Computational modeling of pattern recognition-based cluster analysis was utilized to identify significant differences in metabolic signatures between the lipomatous tumor types.ResultsSignificant differences between BLs and ALTs were observed for multiple metabolites, including leucine, valine, branched chain amino acids, alanine, acetate, glutamine, and formate. DDLs were distinguished from ALTs by increased glucose and lactate, and increased phosphatidylcholine. Multivariate principal component analysis showed clear clustering identifying distinct metabolic signatures of the tissue types.ConclusionMetabolic signatures identified in 1H MR spectra of lipomatous tumors provide new insights into malignant progression and metabolic targeting. The metabolic patterns identified provide the foundation of developing noninvasive MRS or PET imaging biomarkers to distinguish between BLs, ALTs, and DDLs.

AIMS Magnetic resonance imaging (MRI) is routinely used to diagnose and monitor brain tumours. Magnetic resonance spectroscopy (MRS) allows us to record the metabolic profile of tumours in situ. This provides a non-invasive method to monitor the response of tumours to metabolic therapies. We aimed to characterise the response of pre-clinical models of glioma to metabolic therapies such as arginine deprivation and the ketogenic diet (KD) by MRS, to better understand what metabolic changes are occurring in the tumour. METHOD We performed orthotopic injection of three different cell lines, including the syngeneic models GL261 and CT2A, as well as a primary GBM cell line, into the striatum of C57BL/6 and athymic nude mice respectively. Mice were randomised to either arginine deprivation treatment using pegylated arginine deiminase (ADI), or KD, plus controls. In each animal, we collected single voxel MRS data using STEAM on both the tumour itself, and healthy brain. MRS data was exported in jMRUI format and analysed in R using the spant package, followed by PCA and OPLS-DA. RESULTS PCA showed that there is clear distinction between healthy and tumour spectra across all models. OPLS-DA indicated that the lipid and choline spectral regions were significantly associated with tumour, whereas the NAA and glutamine/glutamate regions were significantly associated with healthy brain. Integration of specific peaks associated with these metabolites confirmed these results. Subset analysis indicated distinct metabolic signatures between the syngeneic models and the primary GBM model. Furthermore, there is evidence to suggest that tumours in animals treated with arginine deprivation have a unique metabolic signature. CONCLUSION This data indicates that the tumour specific response to metabolic therapies can be measured by routine MRS screening. This would allow a non-invasive method by which clinicians could monitor the effectiveness of metabolic therapies in patients with gliomas.

Cancer-induced cachexia is a complex and poorly understood life-threatening syndrome that is characterized by progressive weight loss due to metabolic alterations, depletion of lipid stores, and severe loss of skeletal muscle protein. Gaining the ability to noninvasively image the presence or onset of cachexia is important to better treat this condition, to improve the design and optimization of therapeutic strategies, and to detect the responses to such treatments. In this study, we employed noninvasive magnetic resonance spectroscopic imaging (MRSI) and [(18)F]fluoro-2-deoxy-D-glucose ((18)FDG) positron emission tomography (PET) to identify metabolic signatures typical of cachectic tumors, using this information to analyze the types and extents of metabolic changes induced by the onset of cachexia in normal tissues. Cachexia was confirmed by weight loss as well as analyses of muscle tissue and serum. In vivo, cachexia-inducing murine adenocarcinoma (MAC)16 tumors were characterized by higher total choline (tCho) and higher (18)FDG uptake than histologically similar noncachectic MAC13 tumors. A profound depletion of the lipid signal was observed in normal tissue of MAC16 tumor-bearing mice but not within the tumor tissue itself. High-resolution (1)H magnetic resonance spectroscopy (MRS) confirmed the high tCho level observed in cachectic tumors that occurred because of an increase of free choline and phosphocholine. Higher succinate and lower creatine levels were also detected in cachectic tumors. Taken together, these findings enhance our understanding of the effect of cancer on host organs and tissues as well as promote the development of noninvasive biomarkers for the presence of cachexia and identification of new therapeutic targets.

Simple SummaryPreviously, our group demonstrated high FABP4 circulating levels in breast cancer (BC) patients. Moreover, increased cholesterol and triglycerides (TG) were found. To deeply analyse the lipid metabolism in our BC cohort, lipid and low molecular weight metabolomics processes are performed in 240 women (171 BC and 69 control women). This paper provides original data related to a novel link between TG-enriched particles and BC. The main result of this study is that TG-enriched particles and some branched amino acids, as well as tyrosine and alanine, are positively associated with BC. This suggests that BC patients have a different metabolic signature that could be used for better stratification and treatment. To our knowledge, this is the first time that advanced NMR profiling has been used to identify relevant and specifically altered lipid and amino acid metabolites in BC serum samples, which could be used for early and reliable diagnosis and prognosis.Background: Altered lipid metabolism has been described in some types of cancer. To analyse in depth the metabolic modifications in breast cancer patients, advanced 1H-nuclear magnetic resonance was performed in these patients. The main objective of this paper was to define a specific lipidomic signature for these cancer patients. Materials and methods: Serum from 240 women (171 breast cancer patients and 69 control women) were studied and analysed by nuclear magnetic resonance. Results: Triglyceride-enriched particles, specifically very low-density lipoprotein triglycerides, intermediate-density lipoprotein triglycerides, low-density lipoprotein triglycerides, and high-density lipoprotein triglycerides, were positively associated with breast cancer. Moreover, alanine, tyrosine, and branched amino acids were also associated with increased risk of breast cancer. Conclusions: Breast cancer patients showed a modified metabolome, giving a very interesting tool to draw different radar charts between control women and breast cancer patients. To our knowledge, this is the first time that advanced nuclear magnetic resonance profiling has been used to identify relevant and specifically altered lipid or amino acid metabolites in BC serum samples. The altered metabolic signature could be analysed for early and reliable BC patient diagnosis and prognosis.

The use of magnetic resonance spectroscopy (MRS) for the detection of in-vivo metabolic perturbations is increasing in popularity in Prostate Cancer (PCa) research on both humans and rodent models. However, there are distinct metabolic differences between species and prostate areas; a fact making general conclusions about PCa difficult. Here, we use High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy to provide tissue specific identification of metabolites and their relative ratios; information useful in providing insight into the biochemical pathways of the prostate. As our NMR-based approach reveals, human and rat prostate tissues have different metabolic signatures as reflected in numerous key metabolites, including citrate and choline compounds, but also aspartate, lysine, taurine, glutamate, glutamine, creatine and inositol. In general, distribution of these metabolites is not only highly dependent on the species (human versus rat), but also on the location (lobe/zone) in the prostate tissue and the sample pathology; an observation making HRMAS NMR of intact tissue samples a promising method for extracting differences and common features in various experimental prostate cancer models.

For cancers such as glioblastoma multiforme, there is an increasing interest in defining "biological target volumes" (BTV), high tumour-burden regions which may be targeted with dose boosts in radiotherapy. The definition of a BTV requires insight into tumour characteristics going beyond conventionally defined radiological abnormalities and anatomical features. Molecular and biochemical imaging techniques, like positron emission tomography, the use of Magnetic Resonance (MR) Imaging contrast agents or MR Spectroscopy deliver this information and support BTV delineation. MR Spectroscopy Imaging (MRSI) is the only non-invasive technique in this list. Studies with MRSI have shown that voxels with certain metabolic signatures are more susceptible to predict the site of relapse. Nevertheless, the discovery of complex relationships between a high number of different metabolites, anatomical, molecular and functional features is an ongoing topic of research - still lacking appropriate tools supporting a smooth workflow by providing data integration and fusion of MRSI data with other imaging modalities. We present a solution bridging this gap which gives fast and flexible access to all data at once. By integrating a customized visualization of the multi-modal and multi-variate image data with a highly flexible visual analytics (VA) framework, it is for the first time possible to interactively fuse, visualize and explore user defined metabolite relations derived from MRSI in combination with markers delivered by other imaging modalities. Real-world medical cases demonstrate the utility of our solution. By making MRSI data available both in a VA tool and in a multi-modal visualization renderer we can combine insights from each side to arrive at a superior BTV delineation. We also report feedback from domain experts indicating significant positive impact in how this work can improve the understanding of MRSI data and its integration into radiotherapy planning.

BackgroundExposure to famine in the prenatal period is associated with an increased risk of metabolic disease, including obesity and type 2 diabetes. We employed nuclear magnetic resonance (NMR) metabolomic profiling to identify the metabolic changes that are associated with survival of prenatal famine exposure during the Dutch Famine at the end of World War II and subsequently assess their link to disease.MethodsNMR metabolomics data were generated from serum in 480 individuals prenatally exposed to famine (mean 58.8 years, 0.5 SD) and 464 controls (mean 57.9 years, 5.4 SD). We tested associations of prenatal famine exposure with levels of 168 individual metabolic biomarkers and compared the metabolic biomarker signature of famine exposure with those of 154 common diseases.ResultsPrenatal famine exposure was associated with higher concentrations of branched-chain amino acids ((iso)-leucine), aromatic amino acid (tyrosine), and glucose in later life (0.2–0.3 SD, p < 3 × 10−3). The metabolic biomarker signature of prenatal famine exposure was positively correlated to that of incident type 2 diabetes from the UK Biobank (r = 0.77, p = 3 × 10−27), also when re-estimating the signature of prenatal famine exposure among individuals without diabetes (r = 0.67, p = 1 × 10−18). Remarkably, this association extended to 115 common diseases for which signatures were available (0.3 ≤ r ≤ 0.9, p < 3.2 × 10−4). Correlations among metabolic signatures of famine exposure and disease outcomes were attenuated when the famine signature was adjusted for body mass index.ConclusionsPrenatal famine exposure is associated with a metabolic biomarker signature that strongly resembles signatures of a diverse set of diseases, an observation that can in part be attributed to a shared involvement of obesity.

Localized Hypoxia Results in Spatially Heterogeneous Metabolic Signatures in Breast Tumor Models

In vitro and in vivo NMR based metabolomics in Parkinson's disease