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Title: | Diagnosis of lung cancer: what metabolomics can contribute | Authors: | DERVEAUX, Elien LOUIS, Evelyne VANHOVE, Karolien BERVOETS, Liene MESOTTEN, Liesbet THOMEER, Michiel ADRIAENSENS, Peter |
Issue Date: | 2018 | Publisher: | IntechOpen | Source: | Costa Torres, Alba Fabiola (ed.). Lung Cancer: Latest Strategies for Diagnosis and Treatment, IntechOpen, p. 79-94 | Abstract: | The reprogrammed metabolism of cancer cells reflects itself in an alteration of metabolite concentrations, which in turn can be used to define a specific metabolic phenotype or fingerprint for cancer. In this contribution, a metabolism-based discrimination between lung cancer patients and healthy controls, derived from an analysis of human blood plasma by proton nuclear magnetic resonance (1H-NMR) spectroscopy, is described. This technique is becoming widely used in the field of metabolomics because of its ability to provide a highly informative spectrum, representing the relative metabolite concentrations. Cancer types are characterized by decreased or increased levels of specific plasma metabolites, such as glucose or lactate, compared to controls. Data analysis by multivariate statistics provides a classification model with high levels of sensitivity and specificity. Nuclear magnetic resonance (NMR) metabolomics might not only contribute to the diagnosis of lung cancer but also shows potential for treatment follow-up as well as for paving the way to a better understanding of disease-related diverting biochemical pathways. | Keywords: | Metabolomics; human blood plasma; metabolic phenotype; 1H-NMR spectroscopy; metabolite spiking; multivariate OPLS-DA statistics; lung cancer; cancer cell metabolism; biomarker | Document URI: | http://hdl.handle.net/1942/26044 | ISBN: | 9781789843491 | DOI: | 10.5772/intechopen.79258 | Rights: | © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | Category: | B2 | Type: | Book Section | Validations: | vabb 2020 |
Appears in Collections: | Research publications |
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Bookchapter Manuscript_010618-final.pdf Restricted Access | Peer-reviewed author version | 241.69 kB | Adobe PDF | View/Open Request a copy |
62342.pdf | Published version | 2.33 MB | Adobe PDF | View/Open |
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