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This article is part of the supplement: Abstracts of the 16th International Charles Heidelberger Symposium on Cancer Research

Open Access Poster presentation

NMR metabonomic study of lung cancer: metabolic profiling of urine and blood plasma

Joana Carrola1*, Cláudia M Rocha1, António S Barros2, Ana M Gil1, Brian J Goodfellow16, Isabel M Carreira36, João Bernardo46, Ana Gomes46, Vitor Sousa456, Lina Carvalho456 and Iola F Duarte16

Author Affiliations

1 CICECO, Department of Chemistry, University of Aveiro, Aveiro, Portugal

2 QOPNA, Department of Chemistry, University of Aveiro, Aveiro, Portugal

3 Cytogenetics Laboratory and CNC, Faculty of Medicine, University of Coimbra, Coimbra, Portugal

4 University Hospitals of Coimbra, Coimbra, Portugal

5 Institute of Pathological Anatomy, Faculty of Medicine, University of Coimbra, Coimbra, Portugal

6 CIMAGO, Faculty of Medicine, University of Coimbra, Coimbra, Portugal

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BMC Proceedings 2010, 4(Suppl 2):P67  doi:10.1186/1753-6561-4-S2-S67

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1753-6561/4/S2/P67


Published:24 September 2010

© 2010 Carrola et al; licensee BioMed Central Ltd.

Poster presentation

Lung cancer is the leading cause of cancer death, its poor prognosis being related to asymptomatic development and late detection. Hence, there is great need for novel biomarkers that can aid in the early detection of lung cancer. In this study, NMR-metabonomics is applied for investigating lung cancer metabolic signatures in blood plasma and urine. Biofluid samples from lung cancer patients (n = 73) and a control healthy group (n = 56) were analysed by high resolution 1H NMR (500 MHz), and their spectral profiles subjected to multivariate statistics, namely Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Projections to Latent Structures (OPLS)-DA. Multivariate modelling of urinary spectral profiles allowed cancer and control groups to be clearly discriminated with sensitivity and specificity levels of 93 and 94%, respectively. The metabolites giving rise to this separation were mainly creatinine, phenylacetylglycine and N-acetylglutamine/glutamate (elevated in patients), and hippurate and trigonelline (reduced in patients relatively to controls). In the case of blood plasma, good discrimination between the two groups was also achieved, mainly due to increased levels of lactate and LDL+VLDL, and lower levels of HDL, glucose, acetate, histidine, glutamine and valine in cancer compared to healthy subjects. These results show the promising potential of NMR metabonomics for finding putative biomarkers of lung cancer in biofluids, collected in a minimally invasive way, which may have important diagnostic/prognostic impact.