The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer

Pulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer. Metabolic profiles of...

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Published in:	BMC cancer Vol. 18; no. 1; p. 868
Main Authors:	Vanhove, K, Giesen, P, Owokotomo, O E, Mesotten, L, Louis, E, Shkedy, Z, Thomeer, M, Adriaensens, P
Format:	Journal Article
Language:	English
Published:	England BioMed Central Ltd 03-09-2018 BioMed Central BMC
Subjects:	1H-NMR Amino acids Biomarkers Computed tomography Diagnosis Discriminant analysis Glutamate High-performance liquid chromatography Inflammation Lung cancer Lung inflammation Magnetic resonance spectroscopy Medical imaging Medical screening Metabolic phenotype Metabolism Metabolites NMR Nuclear magnetic resonance Nuclear magnetic resonance spectroscopy Plasma Positron emission tomography ROC Tomography Lung inflammation Metabolic phenotype 1H-NMR Glutamate Lung cancer ROC
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Summary:	Pulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer. Metabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by H-NMR spectroscopy. Models to discriminate between groups were trained by PLS-LDA. A test set was used for independent validation. A ROC curve was built to evaluate the diagnostic performance of potential biomarkers. Sensitivity, specificity, PPV and NPV of PET-CT to diagnose cancer are 96, 23, 76 and 71%. Metabolic profiles differentiate between cancer and inflammation with a sensitivity of 89%, a specificity of 87% and a MCE of 12%. Removal of the glutamate metabolite results in an increase of MCE (38%) and a decrease of both sensitivity and specificity (62%), demonstrating the importance of glutamate for discrimination. At the cut-off point 0.31 on the ROC curve, the relative glutamate concentration discriminates between cancer and inflammation with a sensitivity of 85%, a specificity of 81%, and an AUC of 0.88. PPV and NPV are 92 and 69%. In PET-positive patients with a relative glutamate level ≤ 0.31 the sensitivity to diagnose cancer reaches 100% with a PPV of 94%. In PET-negative patients, a relative glutamate level > 0.31 increases the specificity of PET from 23% to 58% and results in a high NPV of 100%. In case of discrepancy between SUV and the glutamate concentration, lung cancer is missed in 19% of the cases. This study indicates that the H-NMR-derived relative plasma concentration of glutamate allows discrimination between lung cancer and lung inflammation. A glutamate level ≤ 0.31 in PET-positive patients corresponds to the diagnosis of lung cancer with a higher specificity and PPV than PET-CT. Glutamate levels > 0.31 in patients with PET negative lung lesions is likely to correspond with inflammation. Caution is needed for patients with conflicting SUV values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1471-2407 1471-2407
DOI:	10.1186/s12885-018-4755-1