Literature DB >> 32042743

A gas chromatography-mass spectrometry (GC-MS) metabolomic approach in human colorectal cancer (CRC): the emerging role of monosaccharides and amino acids.

Luigi Barberini1, Angelo Restivo2, Antonio Noto1, Simona Deidda2, Claudia Fattuoni3, Vassilios Fanos4, Luca Saba2, Luigi Zorcolo5, Michele Mussap6.   

Abstract

BACKGROUND: Colorectal cancer (CRC) has been confirmed to be the third most commonly diagnosed cancer in males and the second in females. We investigated the blood plasma metabolome in CRC patients and in healthy adults to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways as prognostic factors in patients with CRC.
METHODS: Fifteen patients with CRC and nine healthy adults were enrolled in the study and their blood plasma samples analyzed by gas chromatography-mass spectrometry (GC-MS). Univariate Student's t-test, multivariate principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were conducted on MetaboAnalyst 4.0. The analysis of metabolic profiles was carried out by the web-based extension Metabolite Sets Enrichment Analysis (MSEA).
RESULTS: Overall, 125 metabolites were identified in plasma samples by GC-MS. In CRC patient samples, nine metabolites, including D-mannose and fructose, were significantly more abundant than in controls; conversely, eleven amino derivatives were less abundant, including methionine, valine, lysine, and proline. Methionine was significantly less abundant in died patients compared with survivors. The most significantly altered metabolic pathways in CRC patients are those involving monosaccharides (primarily the catabolic pathway of fructose and D-mannose), and amino acids (primarily methionine, valine, leucine, and isoleucine).
CONCLUSIONS: The abundance of D-mannose in CRC patient samples contributes to inhibiting the growth of cancer cells, while the abundance of fructose may be consistent either with low consumption of fructose by aerobic glycolysis within cancer cells or with a high bioavailability of fructose from diet. The reduction in methionine concentration may be related to increased activity of the threonine and methionine catabolic pathways, confirmed by high levels of α-hydroxybutyrate. 2019 Annals of Translational Medicine. All rights reserved.

Entities:  

Keywords:  Colorectal cancer (CRC); D-mannose; amino acids; metabolomics; methionine; monosaccharides

Year:  2019        PMID: 32042743      PMCID: PMC6989984          DOI: 10.21037/atm.2019.12.34

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


  48 in total

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Review 3.  Role of S-adenosylmethionine cycle in carcinogenesis.

Authors:  Radovan Murín; Eva Vidomanová; Bhavani S Kowtharapu; Jozef Hatok; Dušan Dobrota
Journal:  Gen Physiol Biophys       Date:  2017-12       Impact factor: 1.512

Review 4.  The Emerging Hallmarks of Cancer Metabolism.

Authors:  Natalya N Pavlova; Craig B Thompson
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5.  A review of applications of metabolomics in cancer.

Authors:  Richard D Beger
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6.  Glycan analysis of colorectal cancer samples reveals stage-dependent changes in CEA glycosylation patterns.

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Journal:  Clin Proteomics       Date:  2018-03-02       Impact factor: 3.988

Review 7.  Biomarkers in colorectal cancer: Current clinical utility and future perspectives.

Authors:  Marco Vacante; Antonio Maria Borzì; Francesco Basile; Antonio Biondi
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Authors:  M Nitter; B Norgård; S de Vogel; S J P M Eussen; K Meyer; A Ulvik; P M Ueland; O Nygård; S E Vollset; T Bjørge; A Tjønneland; L Hansen; M Boutron-Ruault; A Racine; V Cottet; R Kaaks; T Kühn; A Trichopoulou; C Bamia; A Naska; S Grioni; D Palli; S Panico; R Tumino; P Vineis; H B Bueno-de-Mesquita; H van Kranen; P H Peeters; E Weiderpass; M Dorronsoro; P Jakszyn; M Sánchez; M Argüelles; J M Huerta; A Barricarte; M Johansson; I Ljuslinder; K Khaw; N Wareham; H Freisling; T Duarte-Salles; M Stepien; M J Gunter; E Riboli
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10.  Circulating miR-1290 and miR-320d as Novel Diagnostic Biomarkers of Human Colorectal Cancer.

Authors:  Xiangxiang Liu; Xueni Xu; Bei Pan; Bangshun He; Xiaoxiang Chen; Kaixuan Zeng; Mu Xu; Yuqin Pan; Huiling Sun; Tao Xu; Xiuxiu Hu; Shukui Wang
Journal:  J Cancer       Date:  2019-01-01       Impact factor: 4.207

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3.  Blockade of the amino acid transporter SLC6A14 suppresses tumor growth in colorectal Cancer.

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5.  Analysis of the Components in Moxa Smoke by GC-MS and Preliminary Discussion on Its Toxicity and Side Effects.

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Journal:  Evid Based Complement Alternat Med       Date:  2020-10-31       Impact factor: 2.629

6.  Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer.

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7.  Metabolomic analysis of plasma from breast tumour patients. A pilot study.

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