Can nuclear magnetic resonance (NMR) spectroscopy reveal different metabolic signatures for lung tumours?
authors Duarte, IF; Rocha, CM; Barros, AS; Gil, AM; Goodfellow, BJ; Carreira, IM; Bernardo, J; Gomes, A; Sousa, V; Carvalho, L
nationality International
journal VIRCHOWS ARCHIV
author keywords Lung tumour; NMR spectroscopy; HRMAS; Metabolic profile; Multivariate statistics
keywords INVASIVE CERVICAL-CANCER; HR-MAS SPECTROSCOPY; BREAST-CANCER; IN-VIVO; PROSTATE-CANCER; H-1; TISSUE; MRS; LACTATE; CHOLINE
abstract This study aims to evaluate the potential of H-1 NMR spectroscopy, combined with multivariate statistics, for discriminating between tumour and non-involved (control) pulmonary parenchyma and for providing biochemical information on different histological types. Paired tissue samples from 24 primary lung tumours were directly analysed by high-resolution magic angle spinning (HRMAS) H-1 NMR spectroscopy (500 MHz), and their spectral profiles subjected to principal component analysis (PCA) and partial least squares regression discriminant analysis (PLS-DA). Tumour and adjacent control parenchyma were clearly discriminated in the PLS-DA model with a high level of sensitivity (95% of tumour samples correctly classified) and 100% specificity (no false positives). The metabolites giving rise to this separation were mainly lactate, glycerophosphocholine, phosphocholine, taurine, reduced glutathione and uridine di-phosphate (elevated in tumours) and glucose, phosphoethanolamine, acetate, lysine, methionine, glycine, myo- and scyllo-inositol (reduced in tumours compared to control tissues). Furthermore, PLS-DA of a sub-set of tumour samples allowed adenocarcinomas to be discriminated from carcinoid tumours and epidermoid carcinomas, highlighting differences in metabolite levels between these histological types, and therefore revealing valuable knowledge on the biochemistry of different types of bronchial-pulmonary carcinomas.
publisher SPRINGER
issn 0945-6317
year published 2010
volume 457
issue 6
beginning page 715
ending page 725
digital object identifier (doi) 10.1007/s00428-010-0993-6
web of science category Pathology
subject category Pathology
unique article identifier WOS:000284371200010
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journal impact factor 2.936
5 year journal impact factor 2.717
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