To evaluate the role of miRNAs as potential diagnostic and prognostic biomarkers for Asbestos-related interstitial lung diseases (ILD), Non-Small Cell Lung Cancer (NSCLC) and Malignant Pleural Mesothelioma (MPM)

Asbestos is still the leading cause of occupational cancer mortality worldwide. Asbestos-related lung cancer (LC) and malignant pleural mesothelioma (MPM) prognosis is still poor especially at advanced stage, which highlights the need for early diagnosis and effective biomarkers capable of detecting these diseases at early, potentially reversible stages. MicroRNAs have been proposed as potential early diagnostic biomarkers of asbestos-related LC and MPM. miRNAs regulate post-transcriptional gene expression in lung tumorigenesis and serve as promising therapeutic targets and non-invasive biomarkers due to their stability in biological fluids. Changes in miRNAs expression have been associated with diagnosis and prognosis of several chronic diseases and cancers, but the evidence for asbestos-related diseases is still scarce and inconsistent. Therefore, the aim of my thesis is to evaluate the role of miRNAs as diagnostic and prognostic biomarkers of asbestos-related ILD, LC and MPM. To achieve this, I first examined the existing evidence through a systematic review and meta-analysis of the available published literature till 30th June 2023. miR-126, miR-132–3p, and miR-103a-3p were the most promising diagnostic biomarkers for MPM, with a pooled AUC of 85%, 73%, and 50%, respectively. In relation to MPM prognosis, miR-197‑3p resulted associated with increased survival time. miR126, alone and combined with miR-222, was confirmed associated also to LC diagnosis, together with miR-1254 and miR-574–5p; no miRNA was found associated to LC prognosis. This SLR-MA, helps to provide the suggestive evidence that the expression of specific miRNAs in the blood serum or plasma is associated with asbestos-related LC and MPM diagnosis and prognosis. The next aim of this thesis was to check the feasibility of the of the SOPs and evaluate the potential diagnostic role of plasma miRNAs for the detection of asbestos-exposed ILD by conducting a pilot study, before the longitudinal ARRDIA cohort study. 346 miRNAs were detected in the plasma samples of all study subjects. Both, miR-3679-5p and miR-574-5p showed a 89% diagnostic accuracy (95% CI: 0.73-1.00) in discriminating ILD-free asbestos-exposed from unexposed subjects. miR-6516-5p, miR-942-5p, and let-7f-5p showed a 92% diagnostic accuracy (95% CI: 0.76-1.00) in differentiating asbestos-related ILD-cases from ILD-free subjects formerly exposed to asbestos. miR-4714-3p and miR-20a-5p showed a 91% diagnostic accuracy (95% CI: 0.78-1.00) in discriminating asbestos-related ILD cases from unexposed subjects. This pilot study, not only tested the effectiveness of our standard operating procedures in detecting differences in the plasma miRNA expression between subjects formerly exposed to asbestos, with and without interstitial lung disease and unexposed controls, but also suggested that the plasma microRNA profile might be a potential biomarker of asbestos-related lung diseases. The final aim of this thesis was to compare the EBC and plasma miRNA profile between subjects formerly exposed to asbestos, asbestos-related ILD cases, and unexposed controls. Along with plasma sampling, EBC sampling done which is less-invasive, rapid, cost-effective and easily repeatable. A total of 432 miRNAs were detected in plasma samples and 11 miRNAs in EBC samples across all 30 participants. Using plasma samples, miR-548h-5p, demonstrated a 90% diagnostic accuracy (95% CI: 0.75–1.00) in distinguishing ILD-free asbestos-exposed from unexposed subjects, and a 96% diagnostic accuracy (95% CI: 0.88–1.00) in differentiating asbestos-related ILD cases from ILD-free subjects with prior asbestos exposure; also. miR-6127-3p showed a 85% diagnostic accuracy (95% CI: 0.66-1.00) in discriminating asbestos-related ILD cases from unexposed subjects. Using EBC samples let-7a-5p showed a 86% diagnostic accuracy (95% CI: 0.69-1.00) in discriminating ILD-free asbestos exposed from unexposed subjects.