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

BACKGROUND: 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. METHODS: Metabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by 1H-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. RESULTS: 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 SUVmax and the glutamate concentration, lung cancer is missed in 19% of the cases. CONCLUSION: This study indicates that the 1H-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 SUVmax values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS.

Azithromycin reduces pulmonary fibrosis in a bleomycin mouse model.

Idiopathic pulmonary fibrosis (IPF) is a devastating disease without proper treatment. Despite intensive research, the exact underlying pathogenesis remains elusive. It is regarded as a continuous injury, resulting in inflammation, infiltration, and proliferation of fibroblasts and extracellular matrix deposition, leading to an irreversible restrictive lung function deterioration and death. In this study the effect of azithromycin, a macrolide antibiotic on bleomycin-induced pulmonary fibrosis was investigated. C57BL/6 mice were intratracheally instilled with bleomycin (0.5 mg/kg) or saline. In the bleomycin group, half of the animals received azithromycin every other day from day 1 on. Bronchoalveolar lavage and histology were performed at days 7 and 35, and pulmonary function tests on day 35. At day 35, fibrotic lesions (spindle cell proliferation/collagen I deposition) were paralleled by a restrictive lung function pattern. Alterations were found in neutrophils and macrophages (innate immunity) and in T(H)2, T(H)17, and Treg cytokines (adaptive immunity). Azithromycin significantly reduced both fibrosis and the restrictive lung function pattern. This study demonstrated a beneficial effect of azithromycin on bleomycin-induced pulmonary fibrosis. A possible mechanism could be a modulation of both innate immunity and adaptive immunity. These findings might suggest a potential role for azithromycin in the treatment of IPF.