Angle Spinning Magnetic Resonance Spectroscopy Research Articles

Molecular Profiling of Peanut under Raw, Roasting, and Autoclaving Conditions Using High-Resolution Magic Angle Spinning and Solution 1H NMR Spectroscopy.

Higher rates of peanut allergy have been observed in countries that commonly roast peanuts prior to consumption. Despite the importance of understanding the role of thermal processing in allergy and on peanut composition, studies toward generating signatures that identify molecular contents following processing are scant. Here, we identified spectral signatures to track changes and differences in the molecular composition of peanuts under raw, roasted, and high-pressure and high-temperature autoclaved conditions. We analyzed both the solid flesh of the seed and solutions derived from soaking peanuts using High-Resolution Magic Angle Spinning (HR-MAS) and solution 1H Nuclear Magnetic Resonance (NMR) spectroscopy, respectively. The NMR spectra of intact peanuts revealed triglycerides as the dominant species, assigned on the basis of multiplets at 4.1 and 4.3 ppm, and corresponding defatted flours revealed the presence of sugars. Sucrose assigned based on a doublet at 5.4 ppm (anomeric proton), and triglycerides were the most abundant small molecules observed, with little variation between conditions. Soaked peanut solutions were devoid of lipids, and their resulting spectra matched the profiles of defatted peanuts. Spectral signatures resulting from autoclaving differed strikingly between those from raw and roasted peanuts, with considerable line-broadening in regions corresponding to proteins and amino-acid side chains, from 0.5 to 2.0 ppm and 6.5 to 8.5 ppm. Taken together, by using complementary NMR methods to obtain a fingerprint of the molecular components in peanuts, we demonstrated that autoclaving led to a distinct composition, likely resulting from the hydrolytic cleavage of proteins, the most important molecule of the allergic reaction.

Metabolic profiling of colorectal cancer organoids: A comparison between high-resolution magic angle spinning magnetic resonance spectroscopy and solution nuclear magnetic resonance spectroscopy of polar extracts.

Patient-derived cancer cells cultured in vitro are a cornerstone of cancer metabolism research. More recently, the introduction of organoids has provided the research community with a more versatile model system. Physiological structure and organization of the cell source tissue are maintained in organoids, representing a closer link to in vivo tumor models. High-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) is a commonly applied analytical approach for metabolic profiling of intact tissue, but its use has not been reported for organoids. The aim of the current work was to compare the performance of HR MAS MRS and extraction-based nuclear magnetic resonance (NMR) in metabolic profiling of wild-type and tumor progression organoids (TPOs) from human colon cancer, and further to investigate how the sequentially increased genetic alterations of the TPOs affect the metabolic profile. Sixteen metabolites were reliably identified and quantified both in spectra based on NMR of extracts and HR MAS MRS of intact organoids. The metabolite concentrations from the two approaches were highly correlated (r = 0.94), and both approaches were able to capture the systematic changes in metabolic features introduced by the genetic alterations characteristic of colorectal cancer progression (e.g., increased levels of lactate and decreased levels of myo-inositol and phosphocholine with an increasing number of mutations). The current work highlights that HR MAS MRS is a well-suited method for metabolic profiling of intact organoids, with the additional benefit that the nondestructive nature of HR MAS enables subsequent recovery of the organoids for further analyses based on nucleic acids or proteins.

Maternal exposure to polystyrene microplastics alters placental metabolism in mice.

The rapid growth in the worldwide use of plastics has resulted in a vast accumulation of microplastics in the air, soil and water. The impact of these microplastics on pregnancy and fetal development remains largely unknown. In pregnant mice, we recently demonstrated that exposure to micro- and nanoplastics throughout gestation resulted in significant fetal growth restriction. One possible explanation for reduced fetal growth is abnormal placental metabolism. To evaluate the effect of maternal exposure to microplastics on placental metabolism. In the present study, CD-1 pregnant mice were exposed to 5 μm polystyrene microplastics in filtered drinking water at one of four concentrations (0 ng/L (controls), 102 ng/L, 104 ng/L, 106 ng/L) throughout gestation (n = 7-11/group). At embryonic day 17.5, placental tissue samples were collected (n = 28-44/group). Metabolite profiles were determined using 1H high-resolution magic angle spinning magnetic resonance spectroscopy. The relative concentration of lysine (p = 0.003) and glucose (p < 0.0001) in the placenta were found to decrease with increasing microplastic concentrations, with a significant reduction at the highest exposure concentration. Multivariate analysis identified shifts in the metabolic profile with MP exposure and pathway analysis identified perturbations in the biotin metabolism, lysine degradation, and glycolysis/gluconeogenesis pathways. Maternal exposure to microplastics resulted in significant alterations in placental metabolism. This study highlights the potential impact of microplastic exposure on pregnancy outcomes and that efforts should be made to minimize exposure to plastics, particularly during pregnancy.

Endothelial nitric oxide deficiency results in abnormal placental metabolism

Placental metabolism determines the amount of nutrients available to the fetus and may be altered in pregnancies complicated by fetal growth restriction (FGR). To study which metabolites are associated with FGR, we performed 1H high-resolution magic angle spinning magnetic resonance spectroscopy of placental tissue from endothelial nitric oxide synthase knockout (eNOS KO) mice, a model of FGR, and C57BL/6J controls at embryonic day 17.5 (n = 24/genotype). The relative concentration of glucose was increased in the placentas of eNOS KO mice compared to controls (p = 0.006). This study highlights the potential for glucose as a biomarker of abnormal placental metabolism that leads to FGR.

High resolution magic angle spinning MRS in prostate cancer.

Prostate cancer (PCa) is one of the leading causes of death among men worldwide. The current methods utilized to screen for prostate cancer may not have sufficient sensitivity in distinguishing aggressive from indolent diseases, which affect the quality of life of patients in the short and long term. The overdiagnosis of cases and overtreatment are prevalent due to the heterogeneity of the disease in terms of latent and progressive variants, as well as in the tissue types present in biopsy samples. The purpose of this review is to discuss the potential clinical benefits of incorporating high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) modalities to overcome the current challenges in the diagnosis, prognostication, and monitoring of PCa.

Impact of intratumoral heterogeneity on the metabolic profiling of breast cancer tissue using high-resolution magic angle spinning magnetic resonance spectroscopy.

High-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) is a useful metabolic profiling technique for human tissue. However, the impact of intratumoral heterogeneity on the metabolite levels of breast cancers is not yet established. The purpose of this prospective study was to investigate whether the tumor cell fraction of core needle biopsy (CNB) specimens of breast cancers affect metabolic profiles assessed with HR-MAS MRS. From June 2015 to December 2016, 46 patients with 47 breast cancers were enrolled. HR-MAS MRS was used for the metabolic profiling of 285 CNB specimens from the 47 cancers. Multiple CNB samples (range 2-8) for the HR-MAS MRS experiment were obtained from surgical specimens under ultrasound guidance following surgical removal of the tumor. Tumor cell fraction was expressed as a percentage of the tumor cell volume relative to the total tumor volume contained in each CNB sample. Metabolite quantification levels were compared according to primary tumor characteristics using the t-test. Multivariate analyses were performed including primary tumor characteristics and tumor cell percentages as variables. Correlations between tumor cell percentage and metabolite levels in the CNB specimens were assessed according to the immunohistochemical status of the primary tumor. In univariate analysis, levels of choline-containing compounds, glutamate, glutamine, glycine, serine, and taurine were correlated with primary tumor characteristics. In multivariate analysis, most metabolite levels were not affected by tumor cell percentage. Tumor cell percentage showed poor correlation with metabolite levels in hormone receptor-positive cancer and triple-negative cancer, and poor to fair correlation with metabolite levels in HER2-positive cancer. This study showed that differences in the tumor cell fraction of CNB samples do not affect predictions on the primary cancer from which the samples are obtained.

Screening human lung cancer with predictive models of serum magnetic resonance spectroscopy metabolomics

The current high mortality of human lung cancer stems largely from the lack of feasible, early disease detection tools. An effective test with serum metabolomics predictive models able to suggest patients harboring disease could expedite triage patient to specialized imaging assessment. Here, using a training-validation-testing-cohort design, we establish our high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS)-based metabolomics predictive models to indicate lung cancer presence and patient survival using serum samples collected prior to their disease diagnoses. Studied serum samples were collected from 79 patients before (within 5.0 y) and at lung cancer diagnosis. Disease predictive models were established by comparing serum metabolomic patterns between our training cohorts: patients with lung cancer at time of diagnosis, and matched healthy controls. These predictive models were then applied to evaluate serum samples of our validation and testing cohorts, all collected from patients before their lung cancer diagnosis. Our study found that the predictive model yielded values for prior-to-detection serum samples to be intermediate between values for patients at time of diagnosis and for healthy controls; these intermediate values significantly differed from both groups, with an F1 score = 0.628 for cancer prediction. Furthermore, values from metabolomics predictive model measured from prior-to-diagnosis sera could significantly predict 5-y survival for patients with localized disease.

Biodistribution of Poly(alkyl cyanoacrylate) Nanoparticles in Mice and Effect on Tumor Infiltration of Macrophages into a Patient-Derived Breast Cancer Xenograft

We have investigated the biodistribution and tumor macrophage infiltration after intravenous injection of the poly(alkyl cyanoacrylate) nanoparticles (NPs): PEBCA (poly(2-ethyl-butyl cyanoacrylate), PBCA (poly(n-butyl cyanoacrylate), and POCA (poly(octyl cyanoacrylate), in mice. These NPs are structurally similar, have similar PEGylation, and have previously been shown to give large variations in cellular responses in vitro. The PEBCA NPs had the highest uptake both in the patient-derived breast cancer xenograft MAS98.12 and in lymph nodes, and therefore, they are the most promising of these NPs for delivery of cancer drugs. High-resolution magic angle spinning magnetic resonance (HR MAS MR) spectroscopy did not reveal any differences in the metabolic profiles of tumors following injection of the NPs, but the PEBCA NPs resulted in higher tumor infiltration of the anti-tumorigenic M1 macrophages than obtained with the two other NPs. The PEBCA NPs also increased the ratio of M1/M2 (anti-tumorigenic/pro-tumorigenic) macrophages in the tumors, suggesting that these NPs might be used both as a vehicle for drug delivery and to modulate the immune response in favor of enhanced therapeutic effects.

In vivo γ-aminobutyric acid increase as a biomarker of the epileptogenic zone: An unbiased metabolomics approach.

Following surgery, focal seizures relapse in 20% to 50% of cases due to the difficulty of delimiting the epileptogenic zone (EZ) by current imaging or electrophysiological techniques. Here, we evaluate an unbiased metabolomics approach based on ex vivo and in vivo nuclear magnetic resonance spectroscopy (MRS) methods to discriminate the EZ in a mouse model of mesiotemporal lobe epilepsy (MTLE). Four weeks after unilateral injection of kainic acid (KA) into the dorsal hippocampus of mice (KA-MTLE model), we analyzed hippocampal and cortical samples with high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Using advanced multivariate statistics, we identified the metabolites that best discriminate the injected dorsal hippocampus (EZ) and developed an in vivo MEGAPRESS MRS method to focus on the detection of these metabolites in the same mouse model. Multivariate analysis of HRMAS data provided evidence that γ-aminobutyric acid (GABA) is largely increased in the EZ of KA-MTLE mice and is the metabolite that best discriminates the EZ when compared to sham and, more importantly, when compared to adjacent brain regions. These results were confirmed by capillary electrophoresis analysis and were not reversed by a chronic exposition to an antiepileptic drug (carbamazepine). Then, using in vivo noninvasive GABA-edited MRS, we confirmed that a high GABA increase is specific to the injected hippocampus of KA-MTLE mice. Our strategy using ex vivo MRS-based untargeted metabolomics to select the most discriminant metabolite(s), followed by in vivo MRS-based targeted metabolomics, is an unbiased approach to accurately define the EZ in a mouse model of focal epilepsy. Results suggest that GABA is a specific biomarker of the EZ in MTLE.

MP08-15 CHARACTERIZATION OF THE METABOLOMIC PROFILE OF FAT-POOR ANGIOMYOLIPOMA AND CLEAR CELL CARCINOMA BY HIGH RESOLUTION MAGIC ANGLE SPINNING MAGNETIC RESONANCE SPECTROSCOPY

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP08)1 Apr 2020MP08-15 CHARACTERIZATION OF THE METABOLOMIC PROFILE OF FAT-POOR ANGIOMYOLIPOMA AND CLEAR CELL CARCINOMA BY HIGH RESOLUTION MAGIC ANGLE SPINNING MAGNETIC RESONANCE SPECTROSCOPY Melissa Huynh*, Andrew Gusev, Francesco Palmas, Lindsey Vandergrift, Chin-Lee Wu, Leo Cheng, and Adam Feldman Melissa Huynh* Melissa Huynh* More articles by this author , Andrew GusevAndrew Gusev More articles by this author , Francesco PalmasFrancesco Palmas More articles by this author , Lindsey VandergriftLindsey Vandergrift More articles by this author , Chin-Lee WuChin-Lee Wu More articles by this author , Leo ChengLeo Cheng More articles by this author , and Adam FeldmanAdam Feldman More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000828.015AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Fat-poor angiomyolipoma (AML) can be difficult to differentiate from renal cell carcinoma (RCC) radiographically and may lead to biopsy or unnecessary intervention. In vivoplatforms with the ability to identify tumor histology based on metabolic profiles may avoid unnecessary procedures & their complications. The metabolomics of AML have not been characterized, & research into this area may provide targetable molecules for large AMLs. In this study, we investigate the metabolomic profile of AMLs compared to clear cell RCC (ccRCC) using high resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). METHODS: Tissue samples were obtained from radical or partial nephrectomy specimens that were fresh frozen & stored at -80°C. Tissue HRMAS MRS was performed by a Bruker AVANCE spectrometer. Metabolomic profiles of RCC & adjacent benign renal tissue were compared, and false discovery rates (FDR) accounted for multiple testing. Regions of interest (ROI) with FDR <0.05 were considered potential predictors of ccRCC rather than AML. The Wilcoxon rank sum test was used to compare median MRS relative intensities for candidate predictors. Logistic regression was used to determine odds ratios for risk of malignancy based on abundance of each metabolite. RESULTS: There were 16 ccRCC samples & 7 AML specimens. Candidate predictors of malignancy rather than AML based on FDR p-values include histidine, phenylalanine, phosphocholine, serine, alanine, glutamate, glutathione, glycerophosphocholine, & glutamine. While an abundance of these metabolites is associated with higher risk of malignancy, the odds ratio was particularly high in the 3.5-3.49 ppm spectral region (OR 2.99x106, 95% CI 3.27, 2.73x1012, p=0.033) in ccRCC samples (Table 1). CONCLUSIONS: HRMAS MRS identified metabolites that may help differentiate fat-poor AML from ccRCC. In particular, metabolites in the 3.5-3.49 ppm spectral region increased the risk of harboring RCC. Our findings may contribute to future in vivostudies to help identify which patients require intervention for malignancy & which may be observed for benign AML without requiring biopsy. Source of Funding: NIH Grant #CA115746 © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e111-e112 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Melissa Huynh* More articles by this author Andrew Gusev More articles by this author Francesco Palmas More articles by this author Lindsey Vandergrift More articles by this author Chin-Lee Wu More articles by this author Leo Cheng More articles by this author Adam Feldman More articles by this author Expand All Advertisement PDF downloadLoading ...

Using high-resolution magic angle spinning magnetic resonance spectroscopy to characterize the metabolomic profile of renal cell carcinoma.

710 Background: Renal cell carcinoma (RCC) is a metabolic disease, with the various subtypes exhibiting aberrations in different metabolic pathways. Metabolomics may offer greater sensitivity for revealing disease biology than evaluation of tissue morphology. In this study, we investigate the metabolomic profile of RCC using high resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Methods: Tissue samples were obtained from radical or partial nephrectomy specimens that were fresh frozen &amp; stored at -80ºC. Tissue HRMAS MRS was performed by a Bruker AVANCE spectrometer. Metabolomic profiles of RCC &amp; adjacent benign renal tissue were compared, and false discovery rates (FDR) were used to account for multiple testing. Regions of interest (ROI) with FDR &lt; 0.05 were selected as potential predictors of malignancy. The Wilcoxon rank sum test was used to compare median MRS relative intensities for the candidate predictors. Logistic regression was used to determine odds ratios for risk of malignancy based on abundance of each metabolite. Results: There were 38 RCC (16 clear cell, 11 papillary, 11 chromophobe) &amp; 13 adjacent normal tissue specimens (matched pairs). Metabolic predictors of malignancy based on FDR include histidine, phenylalanine, phosphocholine, serine, phosphocreatine, creatine, glycerophosphocholine, valine, glycine, myo-inositol, scylla-inositol, taurine, glutamine, spermine, acetoacetate &amp; lactate. Higher levels of spermine, histidine &amp; phenylalanine at 3.15-3.13 ppm were associated with a decreased risk of RCC (OR 4x10−5, 95% CI 7.42x10−8, 0.02), while 2.84-2.82 ppm increased the risk of malignant pathology (OR 7158.67, 95% CI 6.3, 8.3x106), and the specific metabolites characterizing this region remain to be identified. Tumor stage did not appear to affect the metabolomics of malignant tumors, suggesting that metabolites are more dependent on histologic subtype. Conclusions: HRMAS-MRS identified many metabolites that may predict RCC. We demonstrated that those in the 3.14-3.13 ppm ROI were present in lower levels in RCC, while higher levels of metabolites in the 2.84-2.82 ppm ROI substantially increased the risk of RCC.

Using high-resolution magic angle spinning magnetic resonance spectroscopy to characterize the metabolomic profile of fat-poor angiomyolipoma and renal cell carcinoma.

711 Background: Fat-poor angiomyolipoma (AML) can be difficult to differentiate from renal cell carcinoma (RCC) radiographically and may lead to biopsy or unnecessary intervention. In vivoplatforms with the ability to identify tumor histology based on metabolic profiles may avoid unnecessary procedures &amp; their complications. The metabolomics of AML have not been characterized, &amp; research into this area may provide targetable molecules for large AMLs. In this study, we investigate the metabolomic profile of AMLs compared to clear cell RCC (ccRCC) using high resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Methods: Tissue samples were obtained from radical or partial nephrectomy specimens that were fresh frozen &amp; stored at -80ºC. Tissue HRMAS MRS was performed by a Bruker AVANCE spectrometer. Metabolomic profiles of RCC &amp; adjacent benign renal tissue were compared, and false discovery rates (FDR) accounted for multiple testing. Regions of interest (ROI) with FDR &lt;0.05 were considered potential predictors of ccRCC rather than AML. The Wilcoxon rank sum test was used to compare median MRS relative intensities for candidate predictors. Logistic regression was used to determine odds ratios for risk of malignancy based on abundance of each metabolite. Results: There were 16 ccRCC samples &amp; 7 AML specimens. Candidate predictors of malignancy rather than AML based on FDR p-values include histidine, phenylalanine, phosphocholine, serine, alanine, glutamate, glutathione, glycerophosphocholine, &amp; glutamine. While an abundance of these metabolites is associated with higher risk of malignancy, the odds ratio was particularly high in the 3.5-3.49 ppm spectral region (OR 2.99x106, 95% CI 3.27, 2.73x1012, p=0.033)in ccRCC samples. Conclusions: HRMAS MRS identified metabolites that may help differentiate fat-poor AML from ccRCC. In particular, metabolites in the 3.5-3.49 ppm spectral region increased the risk of harboring RCC. Our findings may contribute to future in vivostudies to help identify which patients require intervention for malignancy &amp; which may be observed for benign AML without requiring biopsy.

Historical Biobanks in Breast Cancer Metabolomics- Challenges and Opportunities.

Background: Metabolomic characterization of tumours can potentially improve prediction of cancer prognosis and treatment response. Here, we describe efforts to validate previous metabolomic findings using a historical cohort of breast cancer patients and discuss challenges with using older biobanks collected with non-standardized sampling procedures. Methods: In total, 100 primary breast cancer samples were analysed by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and subsequently examined by histology. Metabolomic profiles were related to the presence of cancer tissue, hormone receptor status, T-stage, N-stage, and survival. RNA integrity number (RIN) and metabolomic profiles were compared with an ongoing breast cancer biobank. Results: The 100 samples had a median RIN of 4.3, while the ongoing biobank had a significantly higher median RIN of 6.3 (p = 5.86 × 10−7). A low RIN was associated with changes in choline-containing metabolites and creatine, and the samples in the older biobank showed metabolic differences previously associated with tissue degradation. The association between metabolomic profile and oestrogen receptor status was in accordance with previous findings, however, with a lower classification accuracy. Conclusions: Our findings highlight the importance of standardized biobanking procedures in breast cancer metabolomics studies.

Integrative metabolic and transcriptomic profiling of prostate cancer tissue containing reactive stroma

Reactive stroma is a tissue feature commonly observed in the tumor microenvironment of prostate cancer and has previously been associated with more aggressive tumors. The aim of this study was to detect differentially expressed genes and metabolites according to reactive stroma content measured on the exact same prostate cancer tissue sample. Reactive stroma was evaluated using histopathology from 108 fresh frozen prostate cancer samples gathered from 43 patients after prostatectomy (Biobank1). A subset of the samples was analyzed both for metabolic (n = 85) and transcriptomic alterations (n = 78) using high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) and RNA microarray, respectively. Recurrence-free survival was assessed in patients with clinical follow-up of minimum five years (n = 38) using biochemical recurrence (BCR) as endpoint. Multivariate metabolomics and gene expression analysis compared low (≤15%) against high reactive stroma content (≥16%). High reactive stroma content was associated with BCR in prostate cancer patients even when accounting for the influence of Grade Group (Cox hazard proportional analysis, p = 0.013). In samples with high reactive stroma content, metabolites and genes linked to immune functions and extracellular matrix (ECM) remodeling were significantly upregulated. Future validation of these findings is important to reveal novel biomarkers and drug targets connected to immune mechanisms and ECM in prostate cancer. The fact that high reactive stroma grading is connected to BCR adds further support for the clinical integration of this histopathological evaluation.

Anti-Bacterial Adhesion Activity of Tropical Microalgae Extracts.

The evolution of regulations concerning biocidal products aimed towards an increased protection of the environment (e.g., EU Regulation No 528/2012) requires the development of new non-toxic anti-fouling (AF) systems. As the marine environment is an important source of inspiration, such AF systems inhibiting the adhesion of organisms without any toxicity could be based on molecules of natural origin. In this context, the antibiofilm potential of tropical microalgal extracts was investigated. The tropics are particularly interesting in terms of solar energy and temperatures which provide a wide marine diversity and a high production of microalgae. Twenty microalgal strains isolated from the Indian Ocean were studied. Their extracts were characterized in terms of global chemical composition by high resolution magic angle spinning (HR-MAS) and nuclear magnetic resonance (NMR) spectroscopy, toxicity against marine bacteria (viability and growth) and anti-adhesion effect. The different observations made by confocal laser scanning microscopy (CLSM) showed a significant activity of three extracts from Dinoflagellate strains against the settlement of selected marine bacteria without any toxicity at a concentration of 50 μg/mL. The Symbiodinium sp. (P-78) extract inhibited the adhesion of Bacillus sp. 4J6 (Atlantic Ocean), Shewanella sp. MVV1 (Indian Ocean) and Pseudoalteromonas lipolytica TC8 (Mediterranean Ocean) at 60, 76 and 52%, respectively. These results underlined the potential of using microalgal extracts to repel fouling organisms.

Metabolic profiling of the three neural derived embryonal pediatric tumors retinoblastoma, neuroblastoma and medulloblastoma, identifies distinct metabolic profiles.

The rare pediatric embryonal tumors retinoblastoma, medulloblastoma and neuroblastoma derive from neuroectodermal tissue and share similar histopathological features despite different anatomical locations and diverse clinical outcomes. As metabolism can reflect genetic and histological features, we investigated whether the metabolism of embryonal tumors reflects their similar histology, shared developmental and neural origins, or tumor location. We undertook metabolic profiling on 50 retinoblastoma, 39 medulloblastoma and 70 neuroblastoma using high resolution magic angle spinning magnetic resonance spectroscopy (1H-MRS). Mean metabolite concentrations identified several metabolites that were significantly different between the tumor groups including taurine, hypotaurine, glutamate, glutamine, GABA, phosphocholine, N-acetylaspartate, creatine, glycine and myoinositol, p < 0.0017. Unsupervised multivariate analysis found that each tumor group clustered separately, with a unique metabolic profile, influenced by their underlying clinical diversity. Taurine was notably high in all tumors consistent with prior evidence from embryonal tumors. Retinoblastoma and medulloblastoma were more metabolically similar, sharing features associated with the central nervous system (CNS). Neuroblastoma had features consistent with neural tissue, but also contained significantly higher myoinositol and altered glutamate-glutamine ratio, suggestive of differences in the underlying metabolism of embryonal tumors located outside of the CNS. Despite the histological similarities and shared neural metabolic features, we show that individual neuroectodermal derived embryonal tumors can be distinguished by tissue metabolic profile. Pathway analysis suggests the alanine-aspartate-glutamate and taurine-hypotaurine metabolic pathways may be the most pertinent pathways to investigate for novel therapeutic strategies. This work strengthens our understanding of the biology and metabolic pathways underlying neuroectodermal derived embryonal tumors of childhood.

Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy

Background:Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy.Methods:We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan–Meier survival analyses and concordance index (C-index).Results:High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively).Conclusions:Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

Magnetic resonance metabolic profiling of estrogen receptor-positive breast cancer: correlation with currently used molecular markers.

Estrogen receptor (ER)-positive breast cancers overall have a good prognosis, however, some patients suffer relapses and do not respond to endocrine therapy. The purpose of this study was to determine whether there are any correlations between high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) metabolic profiles of core needle biopsy (CNB) specimens and the molecular markers currently used in patients with ER-positive breast cancers. The metabolic profiling of CNB samples from 62 ER-positive cancers was performed by HR-MAS MRS. Metabolic profiles were compared according to human epidermal growth factor receptor 2 (HER2) and Ki-67 status, and luminal type, using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA). In univariate analysis, the HER2-positive group was shown to have higher levels of glycine and glutamate, compared to the HER2-negative group (P<0.01, and P <0.01, respectively). The high Ki-67 group showed higher levels of glutamate than the low Ki-67 group without statistical significance. Luminal B cancers showed higher levels of glycine (P=0.01) than luminal A cancers. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the subgroups according to HER2 and Ki-67 status, and luminal type. This study showed that the metabolic profiles of CNB samples assessed by HR-MAS MRS can be used to detect potential prognostic biomarkers as well as to understand the difference in metabolic mechanism among subtypes of ER-positive breast cancer.

Metabolic Response to Everolimus in Patient-Derived Triple-Negative Breast Cancer Xenografts.

Patients with triple-negative breast cancer (TNBC) are unresponsive to endocrine and anti-HER2 pharmacotherapy, limiting their therapeutic options to chemotherapy. TNBC is frequently associated with abnormalities in the PI3K/AKT/mTOR signaling pathway; drugs targeting this pathway are currently being evaluated in these patients. However, the response is variable, partly due to heterogeneity within TNBC, conferring a need to identify biomarkers predicting response and resistance to targeted therapy. In this study, we used a metabolomics approach to assess response to the mTOR inhibitor everolimus in a panel of TNBC patient-derived xenografts (PDX) (n = 103 animals). Tumor metabolic profiles were acquired using high-resolution magic angle spinning magnetic resonance spectroscopy. Partial least-squares-discriminant analysis on relative metabolite concentrations discriminated treated xenografts from untreated controls with an accuracy of 67% (p = 0.003). Multilevel linear mixed-effects models (LMM) indicated reduced glycolytic lactate production and glutaminolysis after treatment, consistent with PI3K/AKT/mTOR pathway inhibition. Although inherent metabolic heterogeneity between different PDX models seemed to hinder prediction of treatment response, the metabolic effects following treatment were more pronounced in responding xenografts compared to nonresponders. Additionally, the metabolic information predicted p53 mutation status, which may provide complementary insight into the interplay between PI3K signaling and other drivers of disease progression.

Mild and Short-Term Caloric Restriction Prevents Obesity-Induced Cardiomyopathy in Young Zucker Rats without Changing in Metabolites and Fatty Acids Cardiac Profile.

Caloric restriction (CR) ameliorates cardiac dysfunction associated with obesity. However, most of the studies have been performed under severe CR (30–65% caloric intake decrease) for several months or even years in aged animals. Here, we investigated whether mild (20% food intake reduction) and short-term (2-weeks) CR prevented the obese cardiomyopathy phenotype and improved the metabolic profile of young (14 weeks of age) genetically obese Zucker fa/fa rats. Heart weight (HW) and HW/tibia length ratio was significantly lower in fa/fa rats after 2 weeks of CR than in counterparts fed ad libitum. Invasive pressure measurements showed that systolic blood pressure, maximal rate of positive left ventricle (LV) pressure, LV systolic pressure and LV end-diastolic pressure were all significantly higher in obese fa/fa rats than in lean counterparts, which were prevented by CR. Magnetic resonance imaging revealed that the increase in LV end-systolic volume, stroke volume and LV wall thickness observed in fa/fa rats was significantly lower in animals on CR diet. Histological analysis also revealed that CR blocked the significant increase in cardiomyocyte diameter in obese fa/fa rats. High resolution magic angle spinning magnetic resonance spectroscopy analysis of the LV revealed a global decrease in metabolites such as taurine, creatine and phosphocreatine, glutamate, glutamine and glutathione, in obese fa/fa rats, whereas lactate concentration was increased. By contrast, fatty acid concentrations in LV tissue were significantly elevated in obese fa/fa rats. CR failed to restore the LV metabolomic profile of obese fa/fa rats. In conclusion, mild and short-term CR prevented an obesity-induced cardiomyopathy phenotype in young obese fa/fa rats independently of the cardiac metabolic profile.