Literature DB >> 19140133

Development and validation of a gas chromatography/mass spectrometry method for the metabolic profiling of human colon tissue.

Mainak Mal1, Poh Koon Koh, Peh Yean Cheah, Eric Chun Yong Chan.   

Abstract

In this study, a gas chromatography/mass spectrometry (GC/MS) method was developed and validated for the metabolic profiling of human colon tissue. Each colon tissue sample (20 mg) was ultra-sonicated with 1 mL of a mixture of chloroform/methanol/water in the ratio of 20:50:20 (v/v/v), followed by centrifugation, collection of supernatant, drying, removal of moisture using anhydrous toluene and finally derivatization using N-methyl-N-trifluoroacetamide (MSTFA) with 1% trimethylchlorosilane (TMCS). A volume of 1 microL of the derivatized mixture was injected into the GC/MS system. A total of 53 endogenous metabolites were separated and identified in the GC/MS chromatogram, all of which were selected to evaluate the sample stability and precision of the method. Of the identified endogenous metabolites 19 belonging to diverse chemical classes and covering a wide range of the GC retention times (Rt) were selected to investigate the quantitative linearity of the method. The developed GC/MS method demonstrated good reproducibility with intra- and inter-day precision within relative standard deviation (RSD) of +/-15%. The metabolic profiles of the intact tissue were determined to be stable (100 +/- 15%) for up to 90 days at -80 degrees C. Satisfactory results were also obtained in the case of other stability-indicating studies such as freeze/thaw cycle stability, bench-top stability and autosampler stability. The developed method showed a good linear response for each of the 19 analytes tested (r(2) > 0.99). Our GC/MS metabolic profiling method was successfully applied to discriminate biopsied colorectal cancer (CRC) tissue from their matched normal tissue obtained from six CRC patients using orthogonal partial least-squares discriminant analysis [two latent variables, R(2)Y = 0.977 and Q(2) (cumulative) = 0.877]. Copyright 2009 John Wiley & Sons, Ltd.

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Year:  2009        PMID: 19140133     DOI: 10.1002/rcm.3898

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  12 in total

Review 1.  Review of mass spectrometry-based metabolomics in cancer research.

Authors:  David B Liesenfeld; Nina Habermann; Robert W Owen; Augustin Scalbert; Cornelia M Ulrich
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-10-04       Impact factor: 4.254

2.  Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare).

Authors:  David B Liesenfeld; Nina Habermann; Reka Toth; Robert W Owen; Eva Frei; Jürgen Staffa; Petra Schrotz-King; Karel D Klika; Cornelia M Ulrich
Journal:  Metabolomics       Date:  2014-12-20       Impact factor: 4.290

3.  Prediction of gastric cancer metastasis through urinary metabolomic investigation using GC/MS.

Authors:  Jun-Duo Hu; Hui-Qing Tang; Qiang Zhang; Jing Fan; Jing Hong; Jian-Zhong Gu; Jin-Lian Chen
Journal:  World J Gastroenterol       Date:  2011-02-14       Impact factor: 5.742

4.  Metabolomic profiling of cellular responses to carvedilol enantiomers in vascular smooth muscle cells.

Authors:  Mingxuan Wang; Jing Bai; Wei Ning Chen; Chi Bun Ching
Journal:  PLoS One       Date:  2010-11-24       Impact factor: 3.240

5.  Non-invasive fecal metabonomic detection of colorectal cancer.

Authors:  Lee Cheng Phua; Xiu Ping Chue; Poh Koon Koh; Peh Yean Cheah; Han Kiat Ho; Eric Chun Yong Chan
Journal:  Cancer Biol Ther       Date:  2014-01-14       Impact factor: 4.742

Review 6.  Metabolomic studies of human gastric cancer: review.

Authors:  Naresh Doni Jayavelu; Nadav S Bar
Journal:  World J Gastroenterol       Date:  2014-07-07       Impact factor: 5.742

7.  Identification of cancer mechanisms through computational systems modeling.

Authors:  Zhen Qi; Eberhard O Voit
Journal:  Transl Cancer Res       Date:  2014-06-01       Impact factor: 1.241

8.  Metabolic profiling of HepG2 cells incubated with S(-) and R(+) enantiomers of anti-coagulating drug warfarin.

Authors:  Jing Bai; Ming Xuan Wang; Balram Chowbay; Chi Bun Ching; Wei Ning Chen
Journal:  Metabolomics       Date:  2010-11-25       Impact factor: 4.290

9.  MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data.

Authors:  Y M Tikunov; S Laptenok; R D Hall; A Bovy; R C H de Vos
Journal:  Metabolomics       Date:  2011-10-15       Impact factor: 4.290

10.  Engineering the Saccharomyces cerevisiae β-oxidation pathway to increase medium chain fatty acid production as potential biofuel.

Authors:  Liwei Chen; Jianhua Zhang; Wei Ning Chen
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

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