Shin Nishiumi

A Novel Serum Metabolomics-Based Diagnostic Approach for Colorectal Cancer

Background To improve the quality of life of colorectal cancer patients, it is important to establish new screening methods for early diagnosis of colorectal cancer. Methodology/Principal Findings We performed serum metabolome analysis using gas-chromatography/mass-spectrometry (GC/MS). First, the accuracy of our GC/MS-based serum metabolomic analytical method was evaluated by calculating the RSD% values of serum levels of various metabolites. Second, the intra-day (morning, daytime, and night) and inter-day (among 3 days) variances of serum metabolite levels were examined. Then, serum metabolite levels were compared between colorectal cancer patients (N = 60; N = 12 for each stage from 0 to 4) and age- and sex-matched healthy volunteers (N = 60) as a training set. The metabolites whose levels displayed significant changes were subjected to multiple logistic regression analysis using the stepwise variable selection method, and a colorectal cancer prediction model was established. The prediction model was composed of 2-hydroxybutyrate, aspartic acid, kynurenine, and cystamine, and its AUC, sensitivity, specificity, and accuracy were 0.9097, 85.0%, 85.0%, and 85.0%, respectively, according to the training set data. In contrast, the sensitivity, specificity, and accuracy of CEA were 35.0%, 96.7%, and 65.8%, respectively, and those of CA19-9 were 16.7%, 100%, and 58.3%, respectively. The validity of the prediction model was confirmed using colorectal cancer patients (N = 59) and healthy volunteers (N = 63) as a validation set. At the validation set, the sensitivity, specificity, and accuracy of the prediction model were 83.1%, 81.0%, and 82.0%, respectively, and these values were almost the same as those obtained with the training set. In addition, the model displayed high sensitivity for detecting stage 0–2 colorectal cancer (82.8%). Conclusions/Significance Our prediction model established via GC/MS-based serum metabolomic analysis is valuable for early detection of colorectal cancer and has the potential to become a novel screening test for colorectal cancer.

A metabolomic approach to lung cancer

Lung cancer is one of the most common cancers in the world, but no good clinical markers that can be used to diagnose the disease at an early stage and predict its prognosis have been found. Therefore, the discovery of novel clinical markers is required. In this study, metabolomic analysis of lung cancer patients was performed using gas chromatography mass spectrometry. Serum samples from 29 healthy volunteers and 33 lung cancer patients with adenocarcinoma (n=12), squamous cell carcinoma (n=11), or small cell carcinoma (n=10) ranging from stage I to stage IV disease and lung tissue samples from 7 lung cancer patients including the tumor tissue and its surrounding normal tissue were used. A total of 58 metabolites (57 individual metabolites) were detected in serum, and 71 metabolites were detected in the lung tissue. The levels of 23 of the 58 serum metabolites were significantly changed in all lung cancer patients compared with healthy volunteers, and the levels of 48 of the 71 metabolites were significantly changed in the tumor tissue compared with the non-tumor tissue. Partial least squares discriminant analysis, which is a form of multiple classification analysis, was performed using the serum sample data, and metabolites that had characteristic alterations in each histological subtype and disease stage were determined. Our results demonstrate that changes in metabolite pattern are useful for assessing the clinical characteristics of lung cancer. Our results will hopefully lead to the establishment of novel diagnostic tools.

Rapid Preparation of a Plasma Membrane Fraction from Adipocytes and Muscle Cells: Application to Detection of Translocated Glucose Transporter 4 on the Plasma Membrane

The aim of this study was to establish a rapid preparation of plasma membrane from adipocytes and muscle cells to detect translocated glucose transporter (GLUT) 4. A plasma membrane fraction was prepared by sequential centrifugation with buffer containing detergents, and its purity was estimated by detecting insulin receptor β-subunit (IRβ). After insulin stimulus, GLUT4 translocation was observed in 3T3-L1 adipocytes and L6 myotubes. It was found that IRβ and GLUT4 levels on the plasma membrane decreased in adipose and muscle with intake of a 29% lard diet for 14 weeks. Hence, this method should be useful for rapid preparation of the plasma membrane fraction.

Resolvin E1, an endogenous lipid mediator derived from eicosapentaenoic acid, prevents dextran sulfate sodium-induced colitis

Background: Resolvin E1 (RvE1), an endogenous lipid mediator derived from eicosapentaenoic acid, has been identified in local inflammation during the healing stage. RvE1 reduces inflammation in several types of animal models including peritonitis and retinopathy and blocks human neutrophil transendothelial cell migration. The RvE1 receptor ChemR23 is expressed on myeloid cells such as macrophages and dendritic cells. The aim of this study was to determine whether RvE1 regulates colonic inflammation when the innate immune response of macrophages plays a key role in pathogenesis and tissue damage. Methods: The RvE1 receptor ChemR23 was expressed in mouse peritoneal macrophages as defined by flow cytometry. Peritoneal macrophages were pretreated with RvE1, followed by lipopolysaccharide stimulation, whereupon transcriptional levels of proinflammatory cytokines were analyzed. Results: RvE1 treatment led to inhibition of proinflammatory cytokines including TNF‐&agr; and IL‐12p40. In HEK293 cells, pretreatment with RvE1 inhibited TNF‐&agr;‐induced nuclear translocation of NF‐&kgr;B in a ChemR23‐dependent manner. These results suggested that RvE1 could regulate proinflammatory responses of macrophages expressing ChemR23. Therefore, we investigated the beneficial effects of RvE1 in dextran sulfate sodium–induced colitis. RvE1 treatment led to amelioration of colonic inflammation. Conclusions: These results indicate that RvE1 suppresses proinflammatory responses of macrophages. RvE1 and its receptor may therefore be useful as therapeutic targets in the treatment of human inflammatory bowel disease and other inflammatory disorders. Inflamm Bowel Dis 2010

Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer.

Conventional tumor markers are unsuitable for detecting carcinoma at an early stage and lack clinical efficacy and utility. In this study, we attempted to investigate the differences in serum metabolite profiles of gastrointestinal cancers and healthy volunteers using a metabolomic approach and searched for sensitive and specific metabolomic biomarker candidates. Human serum samples were obtained esophageal (n = 15), gastric (n = 11), and colorectal (n = 12) cancer patients and healthy volunteers (n = 12). A model for evaluating metabolomic biomarker candidates was constructed using multiple classification analysis, and the results were assessed with receiver operating characteristic curves. Among the 58 metabolites, the levels of nine, five and 12 metabolites were significantly changed in the esophageal, gastric and colorectal cancer patients, respectively, compared with the healthy volunteers. Multiple classification analysis revealed that the variations in the levels of malonic acid and L-serine largely contributed to the separation of esophageal cancer; gastric cancer was characterized by changes in the levels of 3-hydroxypropionic acid and pyruvic acid; and L-alanine, glucuronoic lactone and L-glutamine contributed to the separation of colorectal cancer. Our approach revealed that some metabolites are more sensitive for detecting gastrointestinal cancer than conventional biomarkers. Our study supports the potential of metabolomics as an early diagnostic tool for cancer.

A Role of the Aryl Hydrocarbon Receptor in Attenuation of Colitis

Background and AimsThe aryl hydrocarbon receptor (AhR), which is a member of the basic helix-loop-helix/Per-Arnt-Sim homology superfamily, plays an important role in multiple biological functions, and AhR knockout (AhR KO) animals suffer from a variety of organ disorders including a decline in the efficacy of their immune system. In addition, AhR activation is known to aid the maintenance of homeostasis in vivo. In this study, we investigated whether AhR is functionally associated with intestinal immunity.Methods and ResultsIn in vivo experiments, it was found that dextran sodium sulfate (DSS)-evoked colitis was more severe in AhR KO mice than in C57BL/6J wild type mice. It was also revealed that the administration of DSS increased the expression levels of AhR and CYP1A1 mRNA in the colon epithelium. In addition, oral administration of β-naphthoflavone (βNF), a non-toxic agonist of AhR, suppressed the pathogenesis of DSS-induced colitis. βNF also attenuated DSS-induced colitis. In cell culture experiments, downregulation of AhR in human colon carcinoma SW480 cells enhanced the inflammatory responses evoked by lipopolysaccharide (LPS), and furthermore, AhR activation attenuated LPS-induced inflammatory responses, suggesting that AhR expressing intestinal epithelial cells are involved in the prevention of colitis.ConclusionsOur findings about the potential role of AhR activators in epithelial immune regulation aid our understanding of mucosal homeostasis and inflammatory bowl disease (IBD) and suggest that AhR activation has therapeutic value for the treatment of IBD.

GCMS‐based metabolomic study in mice with colitis induced by dextran sulfate sodium

Background: Metabolomics provides data about all the metabolic processes of a cell or organism. So far, the changes that occur in the levels of metabolites during the development of colitis have not been fully elucidated. Here we examined the changes of metabolite levels in the serum and colon tissue of colitis mice using gas chromatography mass spectrometry (GC/MS) with the aim of achieving a detailed understanding of the pathogenesis of inflammatory bowel disease (IBD). Methods: To induce colitis, C57BL/6J mice were administered 3.0% dextran sulfate sodium (DSS) in their drinking water for 5 days and were subsequently given drinking water alone. Results: A total of 77 and 92 metabolites were detected in serum and colon tissue, respectively, and among the metabolites the compositions of TCA cycle intermediates and amino acids changed depending on the degree of colitis. Then, partial least square discriminant analysis (PLS‐DA), a multiple classification analysis, showed distinct clustering and clear separation of the groups according to the degree of colitis. Furthermore, PLS‐DA loadings plots revealed that succinic acid, indole‐3‐acetic acid, glutamic acid, and glutamine were the main contributors to the separation of each stage of colitis. In addition, it was revealed that supplementation with glutamine, the level of which was significantly decreased in the acute phase of colonic inflammation, attenuated colitis induced by DSS. Conclusions: Our results suggest that metabolomics is capable of representing the various degrees of colitis, and our findings will aid in the discovery of therapeutic agents for IBD and other inflammatory disorders by metabolomic approaches. (Inflamm Bowel Dis 2011;)

Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis.

Gas chromatography coupled to mass spectrometry (GC/MS) is a core analytical method for metabolomics and has been used as a platform in non-targeted analysis, especially for hydrophilic metabolites. Non-targeted GC/MS-based metabolomics generally requires a high-throughput technology to handle a large volume of samples and an accumulated database (reference library) of the retention times and mass spectra of standard compounds for accurate peak identification. In this study, we provide a practical GC/MS platform and an auto peak identification technique that is not restricted to certain types of mass spectrometers. The platform utilizes a quadrupole mass spectrometer capable of high-speed scanning, resulting in greater output compared with Pegasus GC-time of flight (TOF)/MS, which has been an essential instrument for high-throughput experiments. Moreover, we show that our reference library is broadly applicable to other instruments; peak identification can be readily performed using the library without constructing a reference resource. The usefulness and versatility of our system are demonstrated by the analyses of three experimental metabolomics data sets, including standard mixtures and real biological samples.

Supercritical fluid chromatography/Orbitrap mass spectrometry based lipidomics platform coupled with automated lipid identification software for accurate lipid profiling.

We developed a practical analytical system for high-throughput and comprehensive lipid profiling using a supercritical fluid chromatography (SFC) system coupled to an Orbitrap Fourier transform mass spectrometer (Orbitrap FT-MS). Using our SFC method, polar lipid molecular species were separated based on not only their fatty acyl moieties but also their polar head groups, using a single octadecylsilyl (ODS) column. In addition, because automatic data processing software was used for the identification of lipid molecular species, the analysis time including data processing was about a half an hour per sample. A variety of lipid molecular species were detected in mouse plasma, and isomers which often co-elute in reverse phase separation were identified accurately and quantified individually. To the best of our knowledge, this is the first report describing the chromatographic separation of lipids based on both fatty acyl moieties and polar head groups, using a single ODS column. Our results demonstrate that SFC/MS is a powerful tool for the simultaneous analysis of diverse lipid molecular species.

Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography–mass spectrometry

Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography–mass spectrometry, gas chromatography–mass spectrometry (GC–MS), capillary electrophoresis–mass spectrometry, and matrix assisted laser desorption ionization–mass spectrometry. Then, the findings of studies about GC–MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.