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Default NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma.

NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma.

Related Articles NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma.

Carcinogenesis. 2014 Nov 3;

Authors: Rocha CM, Barros AS, Goodfellow BJ, Carreira IM, Gomes A, Sousa V, Bernardo J, Carvalho L, Gil AM, Duarte IF

Abstract
Lung tumour subtyping, particularly the distinction between adenocarcinoma (AdC) and squamous cell carcinoma (SqCC), is a critical diagnostic requirement. In this work, the metabolic signatures of lung carcinomas were investigated through (1)H NMR metabolomics, with a view to provide additional criteria for improved diagnosis and treatment planning. High Resolution Magic Angle Spinning (HRMAS) NMR spectroscopy was used to analyse matched tumour and adjacent control tissues from 56 patients undergoing surgical excision of primary lung carcinomas. Multivariate modelling allowed tumour and control tissues to be discriminated with high accuracy (97% classification rate), mainly due to significant differences in the levels of 13 metabolites. Notably, the magnitude of those differences were clearly distinct for AdC and SqCC: major alterations in AdC were related to phospholipid metabolism (increased phosphocholine, glycerophosphocholine and phosphoethanolamine, together with decreased acetate) and protein catabolism (increased peptide moieties), whereas SqCC had stronger glycolytic and glutaminolytic profiles (negatively correlated variations in glucose and lactate and positively correlated increases in glutamate and alanine). Other tumour metabolic features were increased creatine, GSH, taurine and uridine nucleotides, the first two being especially prominent in SqCC and the latter in AdC. Furthermore, multivariate analysis of AdC and SqCC profiles allowed their discrimination with a 94% classification rate, thus showing great potential for aiding lung tumours subtyping. Overall, this study has provided new, clear evidence of distinct metabolic signatures for lung AdC and SqCC, which can potentially impact on diagnosis and provide important leads for future research on novel therapeutic targets or imaging tracers.


PMID: 25368033 [PubMed - as supplied by publisher]



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