Serum metabolic signatures for Alzheimer's Disease reveal alterations in amino acid composition: a validation study.

INTRODUCTION: Alzheimer's Disease (AD) is complex and novel approaches are urgently needed to aid in diagnosis. Blood is frequently used as a source for biomarkers; however, its complexity prevents proper detection. The analytical power of metabolomics, coupled with statistical tools, can assist in reducing this complexity. OBJECTIVES: Thus, we sought to validate a previously proposed panel of metabolic blood-based biomarkers for AD and expand our understanding of the pathological mechanisms involved in AD that are reflected in the blood. METHODS: In the validation cohort serum and plasma were collected from 25 AD patients and 25 healthy controls. Serum was analysed for metabolites using nuclear magnetic resonance (NMR) spectroscopy, while plasma was tested for markers of neuronal damage and AD hallmark proteins using single molecule array (SIMOA). RESULTS: The diagnostic performance of the metabolite biomarker panel was confirmed using sparse-partial least squares discriminant analysis (sPLS-DA) with an area under the curve (AUC) of 0.73 (95% confidence interval: 0.59-0.87). Pyruvic acid and valine were consistently reduced in the discovery and validation cohorts. Pathway analysis of significantly altered metabolites in the validation set revealed that they are involved in branched-chain amino acids (BCAAs) and energy metabolism (glycolysis and gluconeogenesis). Additionally, strong positive correlations were observed for valine and isoleucine between cerebrospinal fluid p-tau and t-tau. CONCLUSIONS: Our proposed panel of metabolites was successfully validated using a combined approach of NMR and sPLS-DA. It was discovered that cognitive-impairment-related metabolites belong to BCAAs and are involved in energy metabolism.

Identifying possible biomarkers of lower urinary tract symptoms using metabolomics and partial least square regression.

INTRODUCTION: The objective of this study was to explore potential novel biomarkers for moderate to severe lower urinary tract symptoms (LUTS) using a metabolomics-based approach, and statistical methods with significant different features than previous reported. MATERIALS AND METHODS: The patients and the controls were selected to participate in the study according to inclusion/exclusion criteria (n = 82). We recorded the following variables: International prostatic symptom score (IPSS), prostate volume, comorbidities, PSA, height, weight, triglycerides, glycemia, HDL cholesterol, and blood pressure. The study of 41 plasma metabolites was done using the nuclear magnetic resonance spectroscopy technique. First, the correlations between the metabolites and the IPSS were done using Pearson. Second, significant biomarkers of LUTS from metabolites were further analysed using a multiple linear regression model. Finally, we validated the findings using partial least square regression (PLS). RESULTS: Small to moderate correlations were found between IPSS and methionine (-0.301), threonine (-0.320), lactic acid (0.294), pyruvic acid (0.207) and 2-aminobutyric-acid (0.229). The multiple linear regression model revealed that only threonine (p = 0.022) was significantly associated with IPSS, whereas methionine (p = 0.103), lactic acid (p = 0.093), pyruvic acid (p = 0.847) and 2-aminobutyric-acid (p = 0.244) lost their significance. However, all metabolites lost their significance in the PLS model. CONCLUSION: When using the robust PLS-regression method, none of the metabolites in our analysis had a significant association with lower urinary tract symptoms. This highlights the importance of using appropriate statistical methods when exploring new biomarkers in urology.

Serum NMR-Based Metabolomics Profiling Identifies Lipoprotein Subfraction Variables and Amino Acid Reshuffling in Myeloma Development and Progression.

Multiple myeloma (MM) is an incurable hematological cancer. It is preceded by monoclonal gammopathy of uncertain significance (MGUS)-an asymptomatic phase. It has been demonstrated that early detection increases the 5-year survival rate. However, blood-based biomarkers that enable early disease detection are lacking. Metabolomic and lipoprotein subfraction variable profiling is gaining traction to expand our understanding of disease states and, more specifically, for identifying diagnostic markers in patients with hematological cancers. This study aims to enhance our understanding of multiple myeloma (MM) and identify candidate metabolites, allowing for a more effective preventative treatment. Serum was collected from 25 healthy controls, 20 patients with MGUS, and 30 patients with MM. 1H-NMR (Nuclear Magnetic Resonance) spectroscopy was utilized to evaluate serum samples. The metabolite concentrations were examined using multivariate, univariate, and pathway analysis. Metabolic profiles of the MGUS patients revealed lower levels of alanine, lysine, leucine but higher levels of formic acid when compared to controls. However, metabolic profiling of MM patients, compared to controls, exhibited decreased levels of total Apolipoprotein-A1, HDL-4 Apolipoprotein-A1, HDL-4 Apolipoprotein-A2, HDL Free Cholesterol, HDL-3 Cholesterol and HDL-4 Cholesterol. Lastly, metabolic comparison between MGUS to MM patients primarily indicated alterations in lipoproteins levels: Total Cholesterol, HDL Cholesterol, HDL Free Cholesterol, Total Apolipoprotein-A1, HDL Apolipoprotein-A1, HDL-4 Apolipoprotein-A1 and HDL-4 Phospholipids. This study provides novel insights into the serum metabolic and lipoprotein subfraction changes in patients as they progress from a healthy state to MGUS to MM, which may allow for earlier clinical detection and treatment.

Perfusion system for studying dynamic metabolomics in rat brain slices exposed to oxygen-glucose deprivation using proton and phosphorus nuclear magnetic resonance.

The aim of the current study was to establish a controlled and reproducible model to study metabolic changes during oxygen-glucose deprivation (OGD) in rat brain using a nuclear magnetic resonance (NMR)-compatible perfusion system. Rat brains were cut into 400-µm thick slices and perfused with artificial cerebrospinal fluid (aCSF) in a 10-mm NMR tube inside a 600-MHz NMR spectrometer. Four experimental conditions were tested: (1) continuous perfusion with aCSF with glucose and normoxia, and (2) 30-, (3) 60-, or (4) 120-min periods of OGD followed by reperfusion of aCSF containing glucose and normoxia. The energetic state of perfused brain slices was measured using phosphorus (31 P) NMR and metabolite changes were measured using proton (1 H) NMR. aCSF samples were collected every 30 min and analyzed using 1 H NMR. The sample temperature was maintained at 36.7 ± 0.1°C and was checked periodically throughout the experiments. Brain slice histology was compared before and after OGD in the perfusion system using hematoxylin-eosin-saffron staining. NMR data clearly distinguished three severity groups (mild, moderate, and severe) after 30, 60, and 120 min of OGD, respectively, compared with the control group. 31 P NMR spectra obtained from controls showed that phosphocreatine levels were stable for 5 h inside the perfusion system. Control 1 H NMR spectra showed that lactate, N-acetylaspartic acid, glutamate, γ-aminobutyric acid, and creatine metabolite levels were stable over time, with lactate levels having a tendency to gradually increase due to the recirculation of the aCSF in the perfusion system. A controlled and reproducible perfusion system was established to study the energetic and metabolic changes in rat brain slices during and after OGD of varying severity.

Lipoprotein and metabolite associations to breast cancer risk in the HUNT2 study.

BACKGROUND: The aim of this study was to gain an increased understanding of the aetiology of breast cancer, by investigating possible associations between serum lipoprotein subfractions and metabolites and the long-term risk of developing the disease. METHODS: From a cohort of 65,200 participants within the Trøndelag Health Study (HUNT study), we identified all women who developed breast cancer within a 22-year follow-up period. Using nuclear magnetic resonance (NMR) spectroscopy, 28 metabolites and 89 lipoprotein subfractions were quantified from prediagnostic serum samples of future breast cancer patients and matching controls (n = 1199 case-control pairs). RESULTS: Among premenopausal women (554 cases) 14 lipoprotein subfractions were associated with long-term breast cancer risk. In specific, different subfractions of VLDL particles (in particular VLDL-2, VLDL-3 and VLDL-4) were inversely associated with breast cancer. In addition, inverse associations were detected for total serum triglyceride levels and HDL-4 triglycerides. No significant association was found in postmenopausal women. CONCLUSIONS: We identified several associations between lipoprotein subfractions and long-term risk of breast cancer in premenopausal women. Inverse associations between several VLDL subfractions and breast cancer risk were found, revealing an altered metabolism in the endogenous lipid pathway many years prior to a breast cancer diagnosis.

Longitudinal Changes in Circulating Metabolites and Lipoproteins After Breast Cancer Treatment.

The multimodal treatment of breast cancer may induce long term effects on the metabolic profile and increase the risk of future cardiovascular disease. In this study, we characterized longitudinal changes in serum lipoprotein subfractions and metabolites after breast cancer treatment, aiming to determine the long-term effect of different treatment modalities. Further, we investigated the prognostic value of treatment-induced changes in breast cancer-specific and overall 10-year survival. In this study, serum samples from breast cancer patients (n = 250) were collected repeatedly before and after radiotherapy, and serum metabolites and lipoprotein subfractions were quantified by NMR spectroscopy. Longitudinal changes were assessed by univariate and multivariate data analysis methods applicable for repeated measures. Distinct changes were detectable in levels of lipoprotein subfractions and circulating metabolites during the first year, with similar changes despite large differences in treatment regimens. We detect increased free cholesterol and decreased esterified cholesterol levels of HDL subfractions, a switch towards larger LDL particles and higher total LDL-cholesterol, in addition to a switch in the glutamine-glutamate ratio. Non-survivors had different lipid profiles from survivors already at baseline. To conclude, our results show development towards an atherogenic lipid profile in breast cancer patients with different treatment regimens.

Associations of lipoprotein particle profile and objectively measured physical activity and sedentary time in schoolchildren: a prospective cohort study.

BACKGROUND: Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile. METHODS: Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables-modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)-and each lipoprotein measure at follow-up. RESULTS: Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak. CONCLUSION: We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort. TRIAL REGISTRATION: ClinicalTrials.gov , # NCT02132494 . Registered 7th April 2014.

Classification and biomarker identification of prostate tissue from TRAMP mice with hyperpolarized 13C-SIRA.

Hyperpolarized 13C isotope resolved spectroscopy boosts NMR signal intensity, which improves signal detection and allows metabolic fluxes to be analyzed. Such hyperpolarized flux data may offer new approaches to tissue classification and biomarker identification that could be translated in vivo. Here we used hyperpolarized stable isotope resolved analysis (SIRA) to measure metabolite specific 13C isotopic enrichments in the central carbon metabolism of mouse prostate. Prostate and tumor tissue samples were acquired from transgenic adenocarcinomas of the mouse prostate (TRAMP) mice. Before euthanasia, mice were injected with [U-13C]glucose intraperitoneally (i.p.). Polar metabolite extracts were prepared, and hyperpolarized 1D-13C NMR spectra were obtained from normal prostate (n = 19) and cancer tissue (n = 19) samples. Binary classification and feature analysis was performed to make a separation model and to investigate differences between samples originating from normal and cancerous prostate tissue, respectively. Hyperpolarized experiments were carried out according to a standardized protocol, which showed a high repeatability (CV = 15%) and an average linewidth in the 1D-13C NMR spectra of 2 ± 0.5 Hz. The resolution of the hyperpolarized 1D-13C spectra was high with little signal overlap in the carbonyl region and metabolite identification was easily accomplished. A discrimination with 95% success rate could be made between samples originating from TRAMP mice prostate and tumor tissue based on isotopomers from uniquely identified metabolites. Hyperpolarized 13C-SIRA allowed detailed metabolic information to be obtained from tissue specimens. The positional information of 13C isotopic enrichments lead to easily interpreted features responsible for high predictive classification of tissue types. This analytical approach has matured, and the robust experimental protocols currently available allow systematic tracking of metabolite flux ex vivo.

Identifying metabolic alterations in newly diagnosed small cell lung cancer patients.

BACKGROUND: Small cell lung cancer (SCLC) is a malignant disease with poor prognosis. At the time of diagnosis most patients are already in a metastatic stage. Current diagnosis is based on imaging, histopathology, and immunohistochemistry, but no blood-based biomarkers have yet proven to be clinically successful for diagnosis and screening. The precise mechanisms of SCLC are not fully understood, however, several genetic mutations, protein and metabolic aberrations have been described. We aim at identifying metabolite alterations related to SCLC and to expand our knowledge relating to this aggressive cancer. METHODS: A total of 30 serum samples of patients with SCLC, collected at the time of diagnosis, and 25 samples of healthy controls were included in this study. The samples were analyzed with nuclear magnetic resonance spectroscopy. Multivariate, univariate and pathways analyses were performed. RESULTS: Several metabolites were identified to be altered in the pre-treatment serum samples of small-cell lung cancer patients compared to healthy individuals. Metabolites involved in tricarboxylic acid cycle (succinate: fold change (FC) = 2.4, p = 0.068), lipid metabolism (LDL triglyceride: FC = 1.3, p = 0.001; LDL-1 triglyceride: FC = 1.3, p = 0.012; LDL-2 triglyceride: FC = 1.4, p = 0.009; LDL-6 triglyceride: FC = 1.5, p < 0.001; LDL-4 cholesterol: FC = 0.5, p = 0.007; HDL-3 free cholesterol: FC = 0.7, p = 0.002; HDL-4 cholesterol FC = 0.8, p < 0.001; HDL-4 apolipoprotein-A1: FC = 0.8, p = 0.005; HDL-4 apolipoprotein-A2: FC ≥ 0.7, p ≤ 0.001), amino acids (glutamic acid: FC = 1.7, p < 0.001; glutamine: FC = 0.9, p = 0.007, leucine: FC = 0.8, p < 0.001; isoleucine: FC = 0.8, p = 0.016; valine: FC = 0.9, p = 0.032; lysine: FC = 0.8, p = 0.004; methionine: FC = 0.8, p < 0.001; tyrosine: FC = 0.7, p = 0.002; creatine: FC = 0.9, p = 0.030), and ketone body metabolism (3-hydroxybutyric acid FC = 2.5, p < 0.001; acetone FC = 1.6, p < 0.001), among other, were found deranged in SCLC. CONCLUSIONS: This study provides novel insight into the metabolic disturbances in pre-treatment SCLC patients, expanding our molecular understanding of this malignant disease.

Cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile in a cohort of Norwegian schoolchildren.

BACKGROUND AND AIMS: The associations between aerobic fitness and traditional measures of lipid metabolism in children are uncertain. We investigated whether higher levels of aerobic fitness benefit lipoprotein metabolism by exploring associations with a comprehensive lipoprotein particle profile. METHODS: In our prospective cohort study, we used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to profile 57 measures of lipoprotein metabolism from fasting serum samples of 858 fifth-grade Norwegian schoolchildren (49.0% girls; mean age 10.0 years). Aerobic fitness was measured using an intermittent shuttle run aerobic fitness test. We used multiple linear regression adjusted for potential confounders to examine cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile. RESULTS: Higher levels of aerobic fitness were associated with a favourable lipoprotein particle profile in the cross-sectional analysis, which included inverse associations with all measures of very low-density lipoprotein (VLDL) particles (e.g., -0.06 mmol·L-1 or -0.23 SD units; 95% CI = -0.31, -0.16 for VLDL cholesterol concentration). In the prospective analysis, the favourable pattern of associations persisted, though the individual associations tended to be more consistent with those of the cross-sectional analysis for the VLDL subclass measures compared to the low-density lipoproteins and high-density lipoproteins. Adjustment for adiposity attenuated the associations in both cross-sectional and prospective models. Nevertheless, an independent effect of aerobic fitness remained for some measures. CONCLUSIONS: Improving children's aerobic fitness levels should benefit lipoprotein metabolism, though a concomitant reduction in adiposity would likely potentiate this effect.

Phosphatase of regenerating liver-3 regulates cancer cell metabolism in multiple myeloma.

Cancer cells often depend on microenvironment signals from molecules such as cytokines for proliferation and metabolic adaptations. PRL-3, a cytokine-induced oncogenic phosphatase, is highly expressed in multiple myeloma cells and associated with poor outcome in this cancer. We studied whether PRL-3 influences metabolism. Cells transduced to express PRL-3 had higher aerobic glycolytic rate, oxidative phosphorylation, and ATP production than the control cells. PRL-3 promoted glucose uptake and lactate excretion, enhanced the levels of proteins regulating glycolysis and enzymes in the serine/glycine synthesis pathway, a side branch of glycolysis. Moreover, mRNAs for these proteins correlated with PRL-3 expression in primary patient myeloma cells. Glycine decarboxylase (GLDC) was the most significantly induced metabolism gene. Forced GLDC downregulation partly counteracted PRL-3-induced aerobic glycolysis, indicating GLDC involvement in a PRL-3-driven Warburg effect. AMPK, HIF-1α, and c-Myc, important metabolic regulators in cancer cells, were not mediators of PRL-3's metabolic effects. A phosphatase-dead PRL-3 mutant, C104S, promoted many of the metabolic changes induced by wild-type PRL-3, arguing that important metabolic effects of PRL-3 are independent of its phosphatase activity. Through this study, PRL-3 emerges as one of the key mediators of metabolic adaptations in multiple myeloma.

Effect of Repeated Freeze-Thaw Cycles on NMR-Measured Lipoproteins and Metabolites in Biofluids.

Metabolic profiling of biofluids by nuclear magnetic resonance (NMR) spectroscopy serves as an important tool in disease characterization, and its accuracy largely depends on the quality of samples. We aimed to explore possible effects of repeated freeze-thaw cycles (FTCs) on concentrations of lipoprotein parameters in serum and metabolite concentrations in serum and urine samples. After one to five FTCs, serum and urine samples (n= 20) were analyzed by NMR spectroscopy, and 112 lipoprotein parameters, 20 serum metabolites, and 35 urine metabolites were quantified by a commercial analytical platform. Principal component analysis showed no systematic changes related to FTCs, and samples from the same donor were closely clustered, showing a higher between-subject variation than within-subject variation. The coefficients of variation were small (medians of 4.3%, 11.0%, and 4.9%  for lipoprotein parameters and serum and urine metabolites, respectively). Minor, but significant accumulated freeze-thaw effects were observed for 32 lipoprotein parameters and one serum metabolite (acetic acid) when comparing FTC1 to further FTCs. Remaining lipoprotein and metabolite concentrations showed no significant change. In conclusion, five FTCs did not significantly alter the concentrations of urine metabolites and introduced only minor changes to serum lipoprotein parameters and metabolites evaluated by the NMR-based platform.

Biomarker Discovery Using NMR-Based Metabolomics of Tissue.

NMR-based metabolomics has shown promise in the diagnosis of diseases as it enables identification and quantification of metabolic biomarkers. Using high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy, metabolic profiles from intact tissue specimens can be obtained with high spectral resolution. In addition, HR-MAS NMR requires minimal sample preparation and the sample is kept intact for subsequent analyses. In this chapter, we describe a typical protocol for NMR-based metabolomics of tissue samples. We cover all major steps ranging from tissue sample collection to determination of biomarkers, including experimental precautions taken to ensure reproducible and reliable reporting of data in the area of clinical application.

The effect of sampling procedures and day-to-day variations in metabolomics studies of biofluids.

Metabolomics analysis of biofluids is a feasible tool for disease characterization and monitoring due to its minimally invasive nature. To reduce unwanted variation in biobanks and clinical studies, it is important to determine the effect of external factors on metabolic profiles of biofluids. In this study we examined the effect of sample collection and sample processing procedures on NMR measured serum lipoproteins and small-molecule metabolites in serum and urine, using a cohort of men diagnosed with either prostate cancer or benign prostatic hyperplasia. We determined day-to-day reliability of metabolites by systematic sample collection at two different days, in both fasting and non-fasting conditions. Study participants received prostate massage the first day to assess the differences between urine with and without prostate secretions. Further, metabolic differences between first-void and mid-stream urine samples, and the effect of centrifugation of urine samples before storage were assessed. Our results show that day-to-day reliability is highly variable between metabolites in both serum and urine, while lipoprotein subfractions possess high reliability. Further, fasting status clearly influenced the metabolite concentrations, demonstrating the importance of keeping this condition constant within a study cohort. Day-to-day reliabilities were however comparable in fasting and non-fasting samples. Urine sampling procedures such as sampling of first-void or mid-stream urine, and centrifugation or not before sample storage, were shown to only have minimal effect on the overall metabolic profile, and is thus unlikely to constitute a confounder in clinical studies utilizing NMR derived metabolomics.

Associations of physical activity and sedentary time with lipoprotein subclasses in Norwegian schoolchildren: The Active Smarter Kids (ASK) study.

BACKGROUND AND AIMS: Physical activity is favourably associated with certain markers of lipid metabolism. The relationship of physical activity with lipoprotein particle profiles in children is not known. Here we examine cross-sectional associations between objectively measured physical activity and sedentary time with serum markers of lipoprotein metabolism. METHODS: Our cohort included 880 children (49.0% girls, mean age 10.2 years). Physical activity intensity and time spent sedentary were measured objectively using accelerometers. 30 measures of lipoprotein metabolism were quantified using nuclear magnetic resonance spectroscopy. Multiple linear regression models adjusted for age, sex, sexual maturity and socioeconomic status were used to determine associations of physical activity and sedentary time with lipoprotein measures. Additional models were adjusted for adiposity. Isotemporal substitution models quantified theoretical associations of replacing 30 min of sedentary time with 30 min of moderate- to vigorous-intensity physical activity (MVPA). RESULTS: Time spent in MVPA was associated with a favourable lipoprotein profile independent of sedentary time. There were inverse associations with a number of lipoprotein measures, including most apolipoprotein B-containing lipoprotein subclasses and triglyceride measures, the ratio of total to high-density lipoprotein (HDL) cholesterol, and non-HDL cholesterol concentration. There were positive associations with larger HDL subclasses, HDL cholesterol concentration and particle size. Reallocating 30 min of sedentary time to MVPA had broadly similar associations. Sedentary time was only partly and weakly associated with an unfavourable lipoprotein profile. CONCLUSIONS: Physical activity of at least moderate-intensity is associated with a favourable lipoprotein profile in schoolchildren, independent of time spent sedentary, adiposity and other confounders.

Hyperoxia affects the lung tissue: A porcine histopathological and metabolite study using five hours of apneic oxygenation.

BACKGROUND: Oxygen is a liberally dosed medicine; however, too much oxygen can be harmful. In certain situations, treatment with high oxygen concentration is necessary, e.g. after cardiopulmonary resuscitation. The amount of oxygen and duration of hyperoxia causing pulmonary damage is not fully elucidated. The aim of this study was to investigate pathophysiological and metabolite changes in lung tissue during hyperoxia while the lungs were kept open under constant low pressure. METHODS: Seven pigs were exposed to 100% oxygen for five hours, using an apneic oxygenation technique with one long uninterrupted inspiration, while carbon dioxide was removed with an interventional lung assist. Arterial blood samples were collected every 30 minutes. Lung biopsies were obtained before and after hyperoxia. Microscopy and high-resolution magic angle spinning nuclear magnetic resonance spectroscopy were used to detect possible pathological and metabolite changes, respectively. Unsupervised multivariate analysis of variance and paired sample tests were performed. A two-tailed p-value ≤ 0.05 was considered significant. RESULTS: No significant changes in arterial pH, and partial pressure of carbon dioxide, and no clear histopathological changes were observed after hyperoxia. While blood glucose and lactate levels changed to a minor degree, their levels dropped significantly in the lung after hyperoxia (p ≤ 0.04). Reduced levels of antioxidants (p ≤ 0.05), tricarboxylic acid cycle and energy (p ≤ 0.04) metabolites and increased levels of several amino acids (p ≤ 0.05) were also detected. CONCLUSION: Despite no histological changes, tissue metabolites were altered, indicating that exposure to hyperoxia affects lung tissue matrix on a molecular basis.

Nanoparticle Ligand-Decoration Procedures Affect in Vivo Interactions with Immune Cells.

Ligand-decorated nanoparticles are extensively studied and applied for in vivo drug delivery and molecular imaging. Generally, two different ligand-decoration procedures are utilized; ligands are either conjugated with nanoparticle ingredients and incorporated during nanoparticle preparation, or they are attached to preformed nanoparticles by utilizing functionalized reactive surface groups (e.g., maleimide). Although the two procedures result in nanoparticles with very similar physicochemical properties, formulations obtained through the latter manufacturing process typically contain nonconjugated reactive surface groups. In the current study, we hypothesized that the different ligand-decoration procedures might affect the extent of interaction between nanoparticles and immune cells (especially phagocytes). In order to investigate our hypothesis, we decorated lipidic nanoparticles with a widely used cyclic Arg-Gly-Asp (cRGD) peptide using the two different procedures. As proven from in vivo experiments in mice, the presence of nonconjugated surface moieties results in increased recognition by the immune system. This is important knowledge considering the emerging focus on understanding and optimizing ways to target and track immune cells and the development of nanomedicine-based strategies in the field of immunotherapy.

Anti-Cancer Potential of Homemade Fresh Garlic Extract Is Related to Increased Endoplasmic Reticulum Stress.

The use of garlic and garlic-based extracts has been linked to decreased incidence of cancer in epidemiological studies. Here we examine the molecular and cellular activities of a simple homemade ethanol-based garlic extract (GE). We show that GE inhibits growth of several different cancer cells in vitro, as well as cancer growth in vivo in a syngeneic orthotopic breast cancer model. Multiple myeloma cells were found to be especially sensitive to GE. The GE was fractionated using solid-phase extractions, and we identified allicin in one GE fraction; however, growth inhibitory activities were found in several additional fractions. These activities were lost during freeze or vacuum drying, suggesting that the main anti-cancer compounds in GE are volatile. The anti-cancer activity was stable for more than six months in −20 °C. We found that GE enhanced the activities of chemotherapeutics, as well as MAPK and PI3K inhibitors. Furthermore, GE affected hundreds of proteins involved in cellular signalling, including changes in vital cell signalling cascades regulating proliferation, apoptosis, and the cellular redox balance. Our data indicate that the reduced proliferation of the cancer cells treated by GE is at least partly mediated by increased endoplasmic reticulum (ER) stress.

Estrogen Receptor α Promotes Breast Cancer by Reprogramming Choline Metabolism.

Estrogen receptor α (ERα) is a key regulator of breast growth and breast cancer development. Here, we report how ERα impacts these processes by reprogramming metabolism in malignant breast cells. We employed an integrated approach, combining genome-wide mapping of chromatin-bound ERα with estrogen-induced transcript and metabolic profiling, to demonstrate that ERα reprograms metabolism upon estrogen stimulation, including changes in aerobic glycolysis, nucleotide and amino acid synthesis, and choline (Cho) metabolism. Cho phosphotransferase CHPT1, identified as a direct ERα-regulated gene, was required for estrogen-induced effects on Cho metabolism, including increased phosphatidylcholine synthesis. CHPT1 silencing inhibited anchorage-independent growth and cell proliferation, also suppressing early-stage metastasis of tamoxifen-resistant breast cancer cells in a zebrafish xenograft model. Our results showed that ERα promotes metabolic alterations in breast cancer cells mediated by its target CHPT1, which this study implicates as a candidate therapeutic target. Cancer Res; 76(19); 5634-46. ©2016 AACR.