IDENTIFICAZIONE DI BIOMARCATORI PER LA DIAGNOSI PRECOCE DEL TUMORE POLMONARE

Lung cancer remains the leading cause of cancer-mortality worldwide, mainly due to late diagnosis. Thus, the identification of biomarkers for an early detection would bring great benefit not only for patients but also for high risk subjects. This project was aimed to discover plasma biomarkers potentially useful to enhance our capabilities to identify those individuals at higher risk of lung cancer in heavy smokers population, enrolled in the Multicentric Italian Lung Detection (MILD) program. To this end, we performed multiparametric analysis of proteins and metabolites linked to systemic (Serum Amyloid A, SAA; Paraoxinase 1, PON1; and 50 plasmatic cytokines) and local (proteins and metabolites in exhaled breath condensate, EBC) inflammation and oxidative stress. We also studied the relationships between these parameters and the pulmonary function measured as FEV1 (forced esxpiratory volume in 1 s). Very recently we have demonstrated that increased plasma levels of the acute phase protein SAA and decreased FEV1 levels are associated with an increased risk of lung cancer incidence in heavy smokers. On this basis, for an efficacious detection of the high risk subgroup among the heavy smoking population, we explored the relationship between SAA plasma levels and FEV1. Importantly, we found a significant inverse correlation between these parameters, suggesting that increased levels of SAA are associated to decreased pulmonary function. We then evaluated a group of cytokines by Bio-Plex Suspension Array System, allowing the simultaneous detection of 50 cytokines. According to assessed SAA levels, we evaluated 142 plasma samples by Bio-Plex. By univariate analysis of obtained results we found that SAA levels correlated directly with cytokine levels of IL-12(p40), GRO-α, HGF, MCP-3, M-CSF, SCGF, SDF-1α, IL-6 and IP-10 and that FEV1 values correlated inversely with GRO-α, HGF, MCP-3, β-NGF, SCGF and MIG concentrations. MIG showed the best association with FEV1. Multivariate analysis highlighted an association between SCGF, CTACK, MIF, MIG, IL-16 and Eotaxin. Additionally, we assessed PON1 levels by Western blot and ELISA in the 142 samples. Our data showed an inverse correlation between PON1 and the major acute phase protein CRP (C reactive protein) as well as between PON1 and SAA together with a direct correlation between PON1 and FEV1. This supported our hypothesis that the decrease of the anti-oxidant function corresponds to a systemic increase of acute phase inflammatory proteins and a decrease of pulmonary function. Regarding the locally produced proteins and metabolites we evaluated inflammatory and oxidative stress parameters in 18 EBC samples derived from heavy smokers and 18 obtained from lung cancer patients. By mass spectrometry analysis and immunoenzymatic assays (ELISA, EIA, BIO-PLEX) we generated protein profiles and assessed the levels of Surfactant Protein C, Leucotrien B4, 8-Isoprostane and a group of 14 cytokines. Noteworthy, we could detect an interesting increased level of 8-Isoprostane in EBC samples of lung cancer patients with respect to those derived from heavy smokers. Taken together our multiparametric analyses highlighted the existance of interesting relationships between specific plasma or EBC components and the impairment of lung function. This supports the interesting possibility we have identified potential biomarkers useful for the evaluation of lung cancer risk. However, their effective clinical applicability will be investigated in future studies using a higher number of subjects.