Metabonomic classification and detection of small molecule biomarkers of malignant pleural effusions

To date, most research has been focused on the benign molecules in pleural effusions, and diagnosis of malignant ones still remains challenging. In the present study, targeting the small molecules as potential biomarkers to predict the malignancy of the effusions, the metabolic profiles of 81 clinical pleural effusions (41 malignant effusions from lung cancer and 40 benign ones) were investigated through a NMR-based metabonomic approach. In (1)H NMR analysis, a total of ten small molecules in the effusions were simultaneously determined. Significantly higher mean values of valine, lactate, and alanine and markedly lower signal intensities of acetoacetate, trimethylamine-N-oxide, and α- and β-glucose were observed in malignant pleural effusions compared with those in benign ones. DFA modeling of NMR spectra subjected to a validation allowed the malignant effusions to be discriminated from benign ones in both training and validation groups. Currently, the conventional clinical analyses on chemical constituents in effusions could not provide a reliable prediction of malignancy of the effusions; the present results revealed that the small molecules might serve as useful biomarkers for diagnosis of the effusions, and the present NMR-based metabonomic approach provided a valuable potential to rapidly and sensitively predict the malignancy of the pleural effusions.