Literature DB >> 21766834

Is serum or plasma more appropriate for intersubject comparisons in metabolomic studies? An assessment in patients with small-cell lung cancer.

David C Wedge1, J William Allwood, Warwick Dunn, Andrew A Vaughan, Kathryn Simpson, Marie Brown, Lynsey Priest, Fiona H Blackhall, Anthony D Whetton, Caroline Dive, Royston Goodacre.   

Abstract

In clinical analyses, the most appropriate biofluid should be analyzed for optimal assay performance. For biological fluids, the most readily accessible is blood, and metabolomic analyses can be performed either on plasma or serum. To determine the optimal agent for analysis, metabolic profiles of matched human serum and plasma were assessed by gas chromatography/time-of-flight mass spectrometry and ultrahigh-performance liquid chromatography mass spectrometry (in positive and negative electrospray ionization modes). Comparison of the two metabolomes, in terms of reproducibility, discriminative ability and coverage, indicated that they offered similar analytical opportunities. An analysis of the variation between 29 small-cell lung cancer (SCLC) patients revealed that the differences between individuals are markedly similar for the two biofluids. However, significant differences between the levels of some specific metabolites were identified, as were differences in the intersubject variability of some metabolite levels. Glycerophosphocholines, erythritol, creatinine, hexadecanoic acid, and glutamine in plasma, but not in serum, were shown to correlate with life expectancy for SCLC patients, indicating the utility of metabolomic analyses in clinical prognosis and the particular utility of plasma in relation to the clinical management of SCLC.

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Year:  2011        PMID: 21766834     DOI: 10.1021/ac2012224

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  40 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.  Mitochondrial aconitase is a key regulator of energy production for growth and protein expression in Chinese hamster ovary cells.

Authors:  Neha Dhami; Drupad K Trivedi; Royston Goodacre; David Mainwaring; David P Humphreys
Journal:  Metabolomics       Date:  2018-10-01       Impact factor: 4.290

3.  A comparison of human serum and plasma metabolites using untargeted 1H NMR spectroscopy and UPLC-MS.

Authors:  Manuja Kaluarachchi; Claire L Boulangé; Ibrahim Karaman; John C Lindon; Timothy M D Ebbels; Paul Elliott; Russell P Tracy; Nels C Olson
Journal:  Metabolomics       Date:  2018-02-13       Impact factor: 4.290

4.  The Plasma and Serum Metabotyping of Hepatocellular Carcinoma in a Nigerian and Egyptian Cohort using Proton Nuclear Magnetic Resonance Spectroscopy.

Authors:  Mohamed I F Shariff; Jin Un Kim; Nimzing G Ladep; Asmaa I Gomaa; Mary M E Crossey; Edith Okeke; Edmund Banwat; Imam Waked; I Jane Cox; Roger Williams; Elaine Holmes; Simon D Taylor-Robinson
Journal:  J Clin Exp Hepatol       Date:  2017-03-15

5.  Determination of Methylarginines in Infant Plasma by CE-LIF.

Authors:  Thomas H Linz; Susan M Lunte
Journal:  Anal Methods       Date:  2014-06-21       Impact factor: 2.896

6.  Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

Authors:  Howbeer Muhamadali; Yun Xu; David I Ellis; J William Allwood; Nicholas J W Rattray; Elon Correa; Haitham Alrabiah; Jonathan R Lloyd; Royston Goodacre
Journal:  Appl Environ Microbiol       Date:  2015-03-06       Impact factor: 4.792

7.  Antioxidant properties of citric acid interfere with the uricase-based measurement of circulating uric acid.

Authors:  Evan M Ryan; Michael J Duryee; Andrew Hollins; Susan K Dover; Samuel Pirruccello; Harlan Sayles; Kevin D Real; Carlos D Hunter; Geoffrey M Thiele; Ted R Mikuls
Journal:  J Pharm Biomed Anal       Date:  2018-11-09       Impact factor: 3.935

Review 8.  Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science.

Authors:  M Ariel Geer Wallace; Tzipporah M Kormos; Joachim D Pleil
Journal:  J Toxicol Environ Health B Crit Rev       Date:  2016-10-19       Impact factor: 6.393

Review 9.  An overview of renal metabolomics.

Authors:  Sahir Kalim; Eugene P Rhee
Journal:  Kidney Int       Date:  2016-09-28       Impact factor: 10.612

10.  Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer.

Authors:  Johannes F Fahrmann; Kyoungmi Kim; Brian C DeFelice; Sandra L Taylor; David R Gandara; Ken Y Yoneda; David T Cooke; Oliver Fiehn; Karen Kelly; Suzanne Miyamoto
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-08-17       Impact factor: 4.254

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