PubMed

Related Articles A dried blood spot mass spectrometry metabolomic approach for rapid breast cancer detection. Onco Targets Ther. 2016;9:1389-98 Authors: Wang Q, Sun T, Cao Y, Gao P, Dong J, Fang Y, Fang Z, Sun X, Zhu Z Abstract OBJECTIVE: Breast cancer (BC) is still a lethal threat to women worldwide. An accurate screening and diagnosis strategy performed in an easy-to-operate manner is highly warranted in clinical perspective. Besides the routinely focused protein markers, blood is full of small molecular metabolites with diverse structures and properties. This study aimed to screen metabolite markers with BC diagnosis potentials. METHODS: A dried blood spot-based direct infusion mass spectrometry (MS) metabolomic analysis was conducted for BC and non-BC differentiation. The targeted analytes included 23 amino acids and 26 acylcarnitines. RESULTS: Multivariate analysis screened out 21 BC-related metabolites in the blood. Regression analysis generated a diagnosis model consisting of parameters Pip, Asn, Pro, C14:1/C16, Phe/Tyr, and Gly/Ala. Tested with another set of BC and non-BC samples, this model showed a sensitivity of 92.2% and a specificity of 84.4%. Compared to the routinely used protein markers, this model exhibited distinct advantage with its higher sensitivity. CONCLUSION: Blood metabolites screening is a more plausible approach for BC detection. Furthermore, this direct MS analysis could be finished within few minutes, which means that its throughput is higher than the currently used imaging techniques. PMID: 27042107 [PubMed]

Related Articles Combining systems pharmacology, transcriptomics, proteomics, and metabolomics to dissect the therapeutic mechanism of Chinese herbal Bufei Jianpi formula for application to COPD. Int J Chron Obstruct Pulmon Dis. 2016;11:553-66 Authors: Zhao P, Yang L, Li J, Li Y, Tian Y, Li S Abstract Bufei Jianpi formula (BJF) has long been used as a therapeutic agent in the treatment of COPD. Systems pharmacology identified 145 active compounds and 175 potential targets of BJF in a previous study. Additionally, BJF was previously shown to effectively prevent COPD and its comorbidities, such as ventricular hypertrophy, by inhibition of inflammatory cytokine production, matrix metalloproteinases expression, and other cytokine production, in vivo. However, the system-level mechanism of BJF for the treatment of COPD is still unclear. The aim of this study was to gain insight into its system-level mechanisms by integrating transcriptomics, proteomics, and metabolomics together with systems pharmacology datasets. Using molecular function, pathway, and network analyses, the genes and proteins regulated in COPD rats and BJF-treated rats could be mainly attributed to oxidoreductase activity, antioxidant activity, focal adhesion, tight junction, or adherens junction. Furthermore, a comprehensive analysis of systems pharmacology, transcript, protein, and metabolite datasets is performed. The results showed that a number of genes, proteins, metabolites regulated in BJF-treated rats and potential target proteins of BJF were involved in lipid metabolism, cell junction, oxidative stress, and inflammatory response, which might be the system-level therapeutic mechanism of BJF treatment. PMID: 27042044 [PubMed - in process]

Related Articles Metabolomic application in toxicity evaluation and toxicological biomarker identification of natural product. Chem Biol Interact. 2016 Mar 31; Authors: Chen DQ, Chen H, Chen L, Tang DD, Miao H, Zhao YY Abstract Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented to toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed. PMID: 27041073 [PubMed - as supplied by publisher]

Related Articles Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism. Mol Biosyst. 2016 Apr 4; Authors: Elsemman IE, Mardinoglu A, Shoaie S, Soliman TH, Nielsen J Abstract Hepatitis C virus (HCV) infection is a worldwide healthcare problem; however, traditional treatment methods have failed to cure all patients, and HCV has developed resistance to new drugs. Systems biology-based analyses could play an important role in the holistic analysis of the impact of HCV on hepatocellular metabolism. Here, we integrated HCV assembly reactions with a genome-scale hepatocyte metabolic model to identify metabolic targets for HCV assembly and metabolic alterations that occur between different HCV progression states (cirrhosis, dysplastic nodule, and early and advanced hepatocellular carcinoma (HCC)) and healthy liver tissue. We found that diacylglycerolipids were essential for HCV assembly. In addition, the metabolism of keratan sulfate and chondroitin sulfate was significantly changed in the cirrhosis stage, whereas the metabolism of acyl-carnitine was significantly changed in the dysplastic nodule and early HCC stages. Our results explained the role of the upregulated expression of BCAT1, PLOD3 and six other methyltransferase genes involved in carnitine biosynthesis and S-adenosylmethionine metabolism in the early and advanced HCC stages. Moreover, GNPAT and BCAP31 expression was upregulated in the early and advanced HCC stages and could lead to increased acyl-CoA consumption. By integrating our results with copy number variation analyses, we observed that GNPAT, PPOX and five of the methyltransferase genes (ASH1L, METTL13, SMYD2, TARBP1 and SMYD3), which are all located on chromosome 1q, had increased copy numbers in the cancer samples relative to the normal samples. Finally, we confirmed our predictions with the results of metabolomics studies and proposed that inhibiting the identified targets has the potential to provide an effective treatment strategy for HCV-associated liver disorders. PMID: 27040643 [PubMed - as supplied by publisher]

Related Articles Implications of genotypic differences in the generation of a urinary metabolomics radiation signature. Mutat Res. 2016 Mar 25; Authors: Laiakis EC, Pannkuk EL, Diaz-Rubio ME, Wang YW, Mak TD, Simbulan-Rosenthal CM, Brenner DJ, Fornace AJ Abstract The increased threat of radiological terrorism and accidental nuclear exposures, together with increased usage of radiation-based medical procedures, has made necessary the development of minimally invasive methods for rapid identification of exposed individuals. Genetically predisposed radiosensitive individuals comprise a significant number of the population and require specialized attention and treatments after such events. Metabolomics, the assessment of the collective small molecule content in a given biofluid or tissue, has proven effective in the rapid identification of radiation biomarkers and metabolic perturbations. To investigate how the genotypic background may alter the ionizing radiation (IR) signature, we analyzed urine from Parp1(-/-) mice, as a model radiosensitive genotype, exposed to IR by utilizing the analytical power of liquid chromatography coupled with mass spectrometry (LC-MS), as urine has been thoroughly investigated in wild type (WT) mice in previous studies from our laboratory. Samples were collected at days one and three after irradiation, time points that are important for the early and efficient triage of exposed individuals. Time-dependent perturbations in metabolites were observed in the tricarboxylic acid pathway (TCA). Other differentially excreted metabolites included amino acids and metabolites associated with dysregulation of energy metabolism pathways. Time-dependent apoptotic pathway activation between WT and mutant mice following IR exposure may explain the altered excretion patterns, although the origin of the metabolites remains to be determined. This first metabolomics study in urine from radiation exposed genetic mutant animal models provides evidence that this technology can be used to dissect the effects of genotoxic agents on metabolism by assessing easily accessible biofluids and identify biomarkers of radiation exposure. Applications of metabolomics could be incorporated in the future to further elucidate the effects of IR on the metabolism of Parp1(-/-) genotype by assessing individual tissues. PMID: 27040378 [PubMed - as supplied by publisher]

Related Articles Dynamic Metabolic Profiles and Tissue-Specific Source Effects on the Metabolome of Developing Seeds of Brassica napus. PLoS One. 2015;10(4):e0124794 Authors: Tan H, Xie Q, Xiang X, Li J, Zheng S, Xu X, Guo H, Ye W Abstract Canola (Brassica napus) is one of several important oil-producing crops, and the physiological processes, enzymes, and genes involved in oil synthesis in canola seeds have been well characterized. However, relatively little is known about the dynamic metabolic changes that occur during oil accumulation in seeds, as well as the mechanistic origins of metabolic changes. To explore the metabolic changes that occur during oil accumulation, we isolated metabolites from both seed and silique wall and identified and characterized them by using gas chromatography coupled with mass spectrometry (GC-MS). The results showed that a total of 443 metabolites were identified from four developmental stages. Dozens of these metabolites were differentially expressed during seed ripening, including 20 known to be involved in seed development. To investigate the contribution of tissue-specific carbon sources to the biosynthesis of these metabolites, we examined the metabolic changes of silique walls and seeds under three treatments: leaf-detachment (Ld), phloem-peeling (Pe), and selective silique darkening (Sd). Our study demonstrated that the oil content was independent of leaf photosynthesis and phloem transport during oil accumulation, but required the metabolic influx from the silique wall. Notably, Sd treatment resulted in seed senescence, which eventually led to a severe reduction of the oil content. Sd treatment also caused a significant accumulation of fatty acids (FA), organic acids and amino acids. Furthermore, an unexpected accumulation of sugar derivatives and organic acid was observed in the Pe- and Sd-treated seeds. Consistent with this, the expression of a subset of genes involved in FA metabolism, sugar and oil storage was significantly altered in Pe and Sd treated seeds. Taken together, our studies suggest the metabolite profiles of canola seeds dynamically varied during the course of oil accumulation, which may provide a new insight into the mechanisms of the oil accumulation at the metabolite level. PMID: 25919591 [PubMed - indexed for MEDLINE]

Related Articles High-throughput concentration-response analysis for omics datasets. Environ Toxicol Chem. 2015 Sep;34(9):2167-80 Authors: Smetanová S, Riedl J, Zitzkat D, Altenburger R, Busch W Abstract Omics-based methods are increasingly used in current ecotoxicology. Therefore, a large number of observations for various toxic substances and organisms are available and may be used for identifying modes of action, adverse outcome pathways, or novel biomarkers. For these purposes, good statistical analysis of toxicogenomic data is vital. In contrast to established ecotoxicological techniques, concentration-response modeling is rarely used for large datasets. Instead, statistical hypothesis testing is prevalent, which provides only a limited scope for inference. The present study therefore applied automated concentration-response modeling for 3 different ecotoxicotranscriptomic and ecotoxicometabolomic datasets. The modeling process was performed by simultaneously applying 9 different regression models, representing distinct mechanistic, toxicological, and statistical ideas that result in different curve shapes. The best-fitting models were selected by using Akaike's information criterion. The linear and exponential models represented the best data description for more than 50% of responses. Models generating U-shaped curves were frequently selected for transcriptomic signals (30%), and sigmoid models were identified as best fit for many metabolomic signals (21%). Thus, selecting the models from an array of different types seems appropriate, because concentration-response functions may vary because of the observed response type, and they also depend on the compound, the organism, and the investigated concentration and exposure duration range. The application of concentration-response models can help to further tap the potential of omics data and is a necessary step for quantitative mixture effect assessment at the molecular response level. PMID: 25900799 [PubMed - indexed for MEDLINE]

Related Articles The intracellular parasite Toxoplasma gondii depends on the synthesis of long-chain and very long-chain unsaturated fatty acids not supplied by the host cell. Mol Microbiol. 2015 Jul;97(1):64-76 Authors: Ramakrishnan S, Docampo MD, MacRae JI, Ralton JE, Rupasinghe T, McConville MJ, Striepen B Abstract Apicomplexa are parasitic protozoa that cause important human diseases including malaria, cryptosporidiosis and toxoplasmosis. The replication of these parasites within their target host cell is dependent on both salvage as well as de novo synthesis of fatty acids. In Toxoplasma gondii, fatty acid synthesis via the apicoplast-localized FASII is essential for pathogenesis, while the role of two other fatty acid biosynthetic complexes remains unclear. Here, we demonstrate that the ER-localized fatty acid elongation (ELO) complexes are essential for parasite growth. Conditional knockdown of the nonredundant hydroxyacyl-CoA dehydratase and enoyl-CoA reductase enzymes in the ELO pathway severely repressed intracellular parasite growth. (13) C-glucose and (13) C-acetate labeling and comprehensive lipidomic analyses of these mutants showed a selective defect in synthesis of unsaturated long and very long-chain fatty acids (LCFAs and VLCFAs) and depletion of phosphatidylinositol and phosphatidylethanolamine species containing unsaturated LCFAs and VLCFAs. This requirement for ELO pathway was bypassed by supplementing the media with specific fatty acids, indicating active but inefficient import of host fatty acids. Our experiments highlight a gap between the fatty acid needs of the parasite and availability of specific fatty acids in the host cell that the parasite has to close using a dedicated synthesis and modification pathway. PMID: 25825226 [PubMed - indexed for MEDLINE]

Related Articles Metabolite profiling to discriminate different species and genus from thistles in Korea using liquid chromatography with quadrupole time-of-flight mass spectrometry. J Sep Sci. 2015 Feb;38(3):502-10 Authors: Ha IJ, Lee MY, Kwon YK, Jung Y, Kim HK, Hwang GS Abstract This study was designed to classify and identify closely related thistle species in the genus Cirsium, as well as Carduus and Cephalonoplos species, which are also thistles. The comprehensive and untargeted metabolite profiles of nine Korean thistles were determined using ultra high performance liquid chromatography combined with hybrid quadrupole time-of-flight mass spectrometry. The difference in metabolite profiles among species was explored using principal component analysis and hierarchical clustering analysis. The significantly different metabolites (Bonferroni-corrected P-value < 0.001) were used to construct a partial least squares discriminant analysis model to predict the species of thistle. Nine species were successfully classified using a partial least squares discriminant analysis model and confirmed using a cross-validation method. Species with similar features were grouped based on unique patterns in variable clusters. The present study suggests that liquid chromatography with quadrupole time-of-flight mass spectrometry untargeted metabolomic profiling with chemometric analysis is an efficient and powerful tool for discriminating between different species of medicinal herbs. PMID: 25413645 [PubMed - indexed for MEDLINE]

Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas. Radiat Oncol. 2016;11(1):51 Authors: Mörén L, Wibom C, Bergström P, Johansson M, Antti H, Bergenheim AT Abstract BACKGROUND: Glioblastomas progress rapidly making response evaluation using MRI insufficient since treatment effects are not detectable until months after initiation of treatment. Thus, there is a strong need for supplementary biomarkers that could provide reliable and early assessment of treatment efficacy. Analysis of alterations in the metabolome may be a source for identification of new biomarker patterns harboring predictive information. Ideally, the biomarkers should be found within an easily accessible compartment such as the blood. METHOD: Using gas-chromatographic- time-of-flight-mass spectroscopy we have analyzed serum samples from 11 patients with glioblastoma during the initial phase of radiotherapy. Fasting serum samples were collected at admittance, on the same day as, but before first treatment and in the morning after the second and fifth dose of radiation. The acquired data was analyzed and evaluated by chemometrics based bioinformatics methods. Our findings were compared and discussed in relation to previous data from microdialysis in tumor tissue, i.e. the extracellular compartment, from the same patients. RESULTS: We found a significant change in metabolite pattern in serum comparing samples taken before radiotherapy to samples taken during early radiotherapy. In all, 68 metabolites were lowered in concentration following treatment while 16 metabolites were elevated in concentration. All detected and identified amino acids and fatty acids together with myo-inositol, creatinine, and urea were among the metabolites that decreased in concentration during treatment, while citric acid was among the metabolites that increased in concentration. Furthermore, when comparing results from the serum analysis with findings in tumor extracellular fluid we found a common change in metabolite patterns in both compartments on an individual patient level. On an individual metabolite level similar changes in ornithine, tyrosine and urea were detected. However, in serum, glutamine and glutamate were lowered after treatment while being elevated in the tumor extracellular fluid. CONCLUSION: Cross-validated multivariate statistical models verified that the serum metabolome was significantly changed in relation to radiation in a similar pattern to earlier findings in tumor tissue. However, all individual changes in tissue did not translate into changes in serum. Our study indicates that serum metabolomics could be of value to investigate as a potential marker for assessing early response to radiotherapy in malignant glioma. PMID: 27039175 [PubMed - as supplied by publisher]

Metabolomic network analysis of estrogen-stimulated MCF-7 cells: a comparison of overrepresentation analysis, quantitative enrichment analysis and pathway analysis versus metabolite network analysis. Arch Toxicol. 2016 Apr 2; Authors: Maertens A, Bouhifd M, Zhao L, Odwin-DaCosta S, Kleensang A, Yager JD, Hartung T Abstract In the context of the Human Toxome project, mass spectroscopy-based metabolomics characterization of estrogen-stimulated MCF-7 cells was studied in order to support the untargeted deduction of pathways of toxicity. A targeted and untargeted approach using overrepresentation analysis (ORA), quantitative enrichment analysis (QEA) and pathway analysis (PA) and a metabolite network approach were compared. Any untargeted approach necessarily has some noise in the data owing to artifacts, outliers and misidentified metabolites. Depending on the chemical analytical choices (sample extraction, chromatography, instrument and settings, etc.), only a partial representation of all metabolites will be achieved, biased by both the analytical methods and the database used to identify the metabolites. Here, we show on the one hand that using a data analysis approach based exclusively on pathway annotations has the potential to miss much that is of interest and, in the case of misidentified metabolites, can produce perturbed pathways that are statistically significant yet uninformative for the biological sample at hand. On the other hand, a targeted approach, by narrowing its focus and minimizing (but not eliminating) misidentifications, renders the likelihood of a spurious pathway much smaller, but the limited number of metabolites also makes statistical significance harder to achieve. To avoid an analysis dependent on pathways, we built a de novo network using all metabolites that were different at 24 h with and without estrogen with a p value <0.01 (53) in the STITCH database, which links metabolites based on known reactions in the main metabolic network pathways but also based on experimental evidence and text mining. The resulting network contained a "connected component" of 43 metabolites and helped identify non-endogenous metabolites as well as pathways not visible by annotation-based approaches. Moreover, the most highly connected metabolites (energy metabolites such as pyruvate and alpha-ketoglutarate, as well as amino acids) showed only a modest change between proliferation with and without estrogen. Here, we demonstrate that estrogen has subtle but potentially phenotypically important alterations in the acyl-carnitine fatty acids, acetyl-putrescine and succinoadenosine, in addition to likely subtle changes in key energy metabolites that, however, could not be verified consistently given the technical limitations of this approach. Finally, we show that a network-based approach combined with text mining identifies pathways that would otherwise neither be considered statistically significant on their own nor be identified via ORA, QEA, or PA. PMID: 27039105 [PubMed - as supplied by publisher]

Effect of acupuncture and its influence on cerebral activity in functional dyspepsia patients: study protocol for a randomized controlled trial. Trials. 2016;17(1):183 Authors: Ko SJ, Park K, Kim J, Kim M, Kim JH, Lee J, Mohamed AZ, Yeo I, Kim J, Choi SM, Kim H, Park JW, Lee JH Abstract BACKGROUND: Functional dyspepsia (FD) is a prevalent gastric disorder that is difficult to manage due to lack of satisfactory treatments. Acupuncture has been studied with regard to the rising need for treating FD, but the mechanism verifying its efficacy has not yet been fully revealed. The aim of this study is to explore the efficacy and mechanism of acupuncture for FD compared with a sham group. METHODS/DESIGN: We describe a proposal for a randomized, assessor-blind, sham-controlled trial with 70 eligible participants who will be randomly allocated either into an acupuncture or a sham group. Participants in the acupuncture group will receive 10 sessions of real acupuncture treatment and those in the sham group will be treated with identical sessions using a Streitberger needle. Functional magnetic resonance imaging (fMRI) and metabolomics studies will be implemented before and after 4 weeks of treatment to investigate the mechanism of acupuncture. The primary outcome is a proportion of responders with adequate symptom relief and the secondary outcomes include the Nepean Dyspepsia Index - Korean version, Functional Dyspepsia-Related Quality of Life questionnaire, Ways of Coping Questionnaire, Coping Strategies Questionnaire, perception of bodily sensation questionnaire, State-Trait Anxiety Inventory, and the Center for Epidemiological Studies - Depression Scale. The outcomes will be evaluated before and after the treatment. DISCUSSION: This is the first large-scale trial evaluating the efficacy and mechanism of acupuncture with fMRI and metabolomic methods. We will compare real acupuncture with the Streitberger sham needle to verify the specific effect of acupuncture. The results of this trial are expected to be relevant evidences affecting policy and decision-makers associated with routine healthcare. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02358486 . Date of Registration: 21 January 2015. PMID: 27039086 [PubMed - as supplied by publisher]

Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling. Curr Protoc Mol Biol. 2016;114:30.4.1-30.4.32 Authors: Fiehn O Abstract Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small-molecule metabolites (<650 Da), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds sufficiently volatile for gas chromatography. This unit shows how GC-MS-based metabolomics allows integration of targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated standard operating procedures, GC-MS can identify and semiquantify over 200 compounds from human body fluids (e.g., plasma, urine, or stool) per study. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to untargeted profiling using liquid chromatography-mass spectrometry. GC-MS is a mature technology that uses not only classic detectors (quadrupole) but also target mass spectrometers (triple quadrupole) and accurate mass instruments (quadrupole-time of flight). This unit covers sample preparation from mammalian samples, data acquisition, quality control, and data processing. © 2016 by John Wiley & Sons, Inc. PMID: 27038389 [PubMed - as supplied by publisher]

Looking into aqueous humor through metabolomics spectacles - exploring its metabolic characteristics in relation to myopia. J Pharm Biomed Anal. 2016 Mar 18; Authors: Barbas-Bernardos C, Armitage EG, García A, Mérida S, Navea A, Bosch-Morell F, Barbas C Abstract Aqueous humor is the transparent fluid found in the anterior chamber of the eye that provides the metabolic requirements to the avascular tissues surrounding it. Despite the fact that metabolomics could be a powerful tool in the characterization of this biofluid and in revealing metabolic signatures of common ocular diseases such as myopia, it has never to our knowledge previously been applied in humans. In this research a novel method for the analysis of aqueous humor is presented to show its application in the characterization of this biofluid using CE-MS. The method was extended to a dual platform method (CE-MS and LC-MS) in order to compare samples from patients with different severities of myopia in order to explore the disease from the metabolic phenotype point of view. With this method, a profound knowledge of the metabolites present in human aqueous humor has been obtained: over 40 metabolites were reproducibly and simultaneously identified from a low volume of sample by CE-MS, including among others, a vast number of amino acids and derivatives. When this method was extended to study groups of patients with high or low myopia in both CE-MS and LC-MS, it has been possible to identify over 20 significantly different metabolite and lipid signatures that distinguish patients based on the severity of myopia. Among these, the most notable higher abundant metabolites in high myopia were aminooctanoic acid, arginine, citrulline and sphinganine while features of low myopia were aminoundecanoic acid, dihydro-retinoic acid and cysteinylglycine disulfide. This dual platform approach offered complementarity such that different metabolites were detected in each technique. Together the experiments presented provide a whelm of valuable information about human aqueous humor and myopia, proving the utility of non-targeted metabolomics for the first time in analyzing this type of sample and the metabolic phenotype of this disease. PMID: 27036676 [PubMed - as supplied by publisher]

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis. Genome Med. 2016;8(1):34 Authors: Huang S, Chong N, Lewis NE, Jia W, Xie G, Garmire LX Abstract BACKGROUND: More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. METHODS: We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. RESULTS: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. CONCLUSIONS: We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis. PMID: 27036109 [PubMed - as supplied by publisher]

Individual variability in human blood metabolites identifies age-related differences. Proc Natl Acad Sci U S A. 2016 Mar 28; Authors: Chaleckis R, Murakami I, Takada J, Kondoh H, Yanagida M Abstract Metabolites present in human blood document individual physiological states influenced by genetic, epigenetic, and lifestyle factors. Using high-resolution liquid chromatography-mass spectrometry (LC-MS), we performed nontargeted, quantitative metabolomics analysis in blood of 15 young (29 ± 4 y of age) and 15 elderly (81 ± 7 y of age) individuals. Coefficients of variation (CV = SD/mean) were obtained for 126 blood metabolites of all 30 donors. Fifty-five RBC-enriched metabolites, for which metabolomics studies have been scarce, are highlighted here. We found 14 blood compounds that show remarkable age-related increases or decreases; they include 1,5-anhydroglucitol, dimethyl-guanosine, acetyl-carnosine, carnosine, ophthalmic acid, UDP-acetyl-glucosamine,N-acetyl-arginine,N6-acetyl-lysine, pantothenate, citrulline, leucine, isoleucine, NAD(+), and NADP(+) Six of them are RBC-enriched, suggesting that RBC metabolomics is highly valuable for human aging research. Age differences are partly explained by a decrease in antioxidant production or increasing inefficiency of urea metabolism among the elderly. Pearson's coefficients demonstrated that some age-related compounds are correlated, suggesting that aging affects them concomitantly. Although our CV values are mostly consistent with those CVs previously published, we here report previously unidentified CVs of 51 blood compounds. Compounds having moderate to high CV values (0.4-2.5) are often modified. Compounds having low CV values, such as ATP and glutathione, may be related to various diseases because their concentrations are strictly controlled, and changes in them would compromise health. Thus, human blood is a rich source of information about individual metabolic differences. PMID: 27036001 [PubMed - as supplied by publisher]

A novel treatment of cystic fibrosis acting on-target: cysteamine plus epigallocatechin gallate for the autophagy-dependent rescue of class II-mutated CFTR. Cell Death Differ. 2016 Apr 1; Authors: Tosco A, De Gregorio F, Esposito S, De Stefano D, Sana I, Ferrari E, Sepe A, Salvadori L, Buonpensiero P, Di Pasqua A, Grassia R, Leone CA, Guido S, De Rosa G, Lusa S, Bona G, Stoll G, Maiuri MC, Mehta A, Kroemer G, Maiuri L, Raia V Abstract We previously reported that the combination of two safe proteostasis regulators, cysteamine and epigallocatechin gallate (EGCG), can be used to improve deficient expression of the cystic fibrosis transmembrane conductance regulator (CFTR) in patients homozygous for the CFTR Phe508del mutation. Here we provide the proof-of-concept that this combination treatment restored CFTR function and reduced lung inflammation (P<0.001) in Phe508del/Phe508del or Phe508del/null-Cftr (but not in Cftr-null mice), provided that such mice were autophagy-competent. Primary nasal cells from patients bearing different class II CFTR mutations, either in homozygous or compound heterozygous form, responded to the treatment in vitro. We assessed individual responses to cysteamine plus EGCG in a single-centre, open-label phase-2 trial. The combination treatment decreased sweat chloride from baseline, increased both CFTR protein and function in nasal cells, restored autophagy in such cells, decreased CXCL8 and TNF-α in the sputum, and tended to improve respiratory function. These positive effects were particularly strong in patients carrying Phe508del CFTR mutations in homozygosity or heterozygosity. However, a fraction of patients bearing other CFTR mutations failed to respond to therapy. Importantly, the same patients whose primary nasal brushed cells did not respond to cysteamine plus EGCG in vitro also exhibited deficient therapeutic responses in vivo. Altogether, these results suggest that the combination treatment of cysteamine plus EGCG acts 'on-target' because it can only rescue CFTR function when autophagy is functional (in mice) and improves CFTR function when a rescuable protein is expressed (in mice and men). These results should spur the further clinical development of the combination treatment.Cell Death and Differentiation advance online publication, 1 April 2016; doi:10.1038/cdd.2016.22. PMID: 27035618 [PubMed - as supplied by publisher]

Altered Mitochondrial Respiration and Other Features of Mitochondrial Function in Parkin-Mutant Fibroblasts from Parkinson's Disease Patients. Parkinsons Dis. 2016;2016:1819209 Authors: Haylett W, Swart C, van der Westhuizen F, van Dyk H, van der Merwe L, van der Merwe C, Loos B, Carr J, Kinnear C, Bardien S Abstract Mutations in the parkin gene are the most common cause of early-onset Parkinson's disease (PD). Parkin, an E3 ubiquitin ligase, is involved in respiratory chain function, mitophagy, and mitochondrial dynamics. Human cellular models with parkin null mutations are particularly valuable for investigating the mitochondrial functions of parkin. However, published results reporting on patient-derived parkin-mutant fibroblasts have been inconsistent. This study aimed to functionally compare parkin-mutant fibroblasts from PD patients with wild-type control fibroblasts using a variety of assays to gain a better understanding of the role of mitochondrial dysfunction in PD. To this end, dermal fibroblasts were obtained from three PD patients with homozygous whole exon deletions in parkin and three unaffected controls. Assays of mitochondrial respiration, mitochondrial network integrity, mitochondrial membrane potential, and cell growth were performed as informative markers of mitochondrial function. Surprisingly, it was found that mitochondrial respiratory rates were markedly higher in the parkin-mutant fibroblasts compared to control fibroblasts (p = 0.0093), while exhibiting more fragmented mitochondrial networks (p = 0.0304). Moreover, cell growth of the parkin-mutant fibroblasts was significantly higher than that of controls (p = 0.0001). These unanticipated findings are suggestive of a compensatory mechanism to preserve mitochondrial function and quality control in the absence of parkin in fibroblasts, which warrants further investigation. PMID: 27034887 [PubMed]

Improving the Sensitivity, Resolution, and Peak Capacity of Gradient Elution in Capillary Liquid Chromatography With Large-Volume Injections by Using Temperature-Assisted On-column Solute Focusing. Anal Chem. 2016 Apr 1; Authors: Wilson RE, Groskreutz SR, Weber SG Abstract Capillary HPLC (cLC) with gradient elution is the separation method of choice for the fields of proteomics and metabolomics. This is due to the complementary nature of cLC flow rates and electrospray or nanospray ionization mass spectrometry (ESI-MS). The small column diameters result in good mass sensitivity. Good concentration sensitivity is also possible by injection of relatively large volumes of solution and relying on solvent-based solute focusing. However, if the injection volume is too large or solutes are poorly retained during injection, volume overload occurs which leads to altered peak shapes, decreased sensitivity and lower peak capacity. Solutes that elute early even with the use of a solvent gradient are especially vulnerable to this problem. In this paper we describe a simple, automated instrumental method, Temperature-Assisted On-column Solute Focusing (TASF), that is capable of focusing large volume injections of small molecules and peptides under gradient conditions. By injecting a large sample volume while cooling a short segment of the column inlet at sub-ambient temperatures, solutes are concentrated into narrow bands at the head of the column. Rapidly raising the temperature of this segment of the column leads to separations with less peak broadening in comparison to solvent focusing alone. For large volume injections of both mixtures of small molecules and a bovine serum albumin tryptic digest, TASF improved the peak shape and resolution in chromatograms. TASF showed the most dramatic improvements with shallow gradients, which is particularly useful for biological applications. Results demonstrate the ability of TASF with gradient elution to improve the sensitivity, resolution, and peak capacity of volume overloaded samples beyond gradient compression alone. Additionally, we have developed and validated a double extrapolation method for predicting retention factors at extremes of temperature and mobile phase composition. Using this method, the effects of TASF can be predicted, allowing determination of the usefulness of this technique for a particular application. PMID: 27033165 [PubMed - as supplied by publisher]

Amino acid profiling as a method of discovering biomarkers for early diagnosis of cancer. Amino Acids. 2016 Mar 31; Authors: Simińska E, Koba M Abstract Cancer is one of the main causes of mortality in the world and its early detection significantly increases chances of patients' survival. High cancer mortality rate is caused mainly by late-stage diagnosis and lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of cancers in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. Several recent researchers indicate amino acids as a potential marker for cancer detection. An ideal cancer biomarker should be characterized by high specificity and sensitivity, reliability, ease of measurement and, what is important, ability to detect disease in its early stage. This study is focused on indicating metabolic amino acid profiling as a method of identifying biomarkers for cancer early detection and screening. Presented results are derived from the most recent studies where patients in early, often asymptomatic stages of disease constituted a large percentage of all the patients and, what is important, where researchers have observed alterations in these patients' amino acid profiles. This review is concentrated on analyzing studies on the most common cancers with high mortality rate. Inventing effective methods of early diagnosis is particularly important in case of such diseases. Research presented in this publication is focused on patients with lung, breast and colon cancer. In all analyzed cases, significant changes in the amino acid profile in cancer patients comparing to healthy controls were observed. This study indicates potential of amino acid profiling as method for early cancer detection. PMID: 27033065 [PubMed - as supplied by publisher]