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Plasmatic extracellular vesicle microRNAs in malignant pleural mesothelioma and asbestos-exposed subjects suggest a 2-miRNA signature as potential biomarker of disease

August 31, 2017 By Law Offices of Thomas J. Lamb, P.A.

Background:  Malignant Pleural Mesothelioma (MPM) is an aggressive cancer mainly caused by asbestos exposure and refractory to current therapies. Specific diagnostic markers for early MPM diagnosis are needed. Changes in miRNA expression have been implicated in several diseases and cancers, including MPM. We examined if a specific miRNA signature in plasmatic extracellular vesicles (EV) may help to discriminate between malignant pleural mesothelioma patients (MPM) and subjects with Past Asbestos Exposure (PAE).

Methodology/Principal findings:  We investigated 23 MPM patients and 19 cancer-free subjects with past asbestos exposure (PAE). We screened 754 miRNAs in plasmatic EVs by OpenArray and found 55 differential miRNAs using logistic regression models adjusted for age, sex, BMI, and smoking. Among the top-20 differential miRNAs chosen for validation by Real time PCR, 16 were confirmed. Using receiver operating characteristic (ROC) curve analysis, the most discriminating miRNA combination was given by miR-103a-3p + miR-30e-3p, which generated an AUC of 0.942 (95% CI 0.87–1.00), with a sensitivity of 95.5% and a specificity of 80.0%. Using multivariate Cox regression analysis including gender, age, BMI and smoking we found a Hazard Ratio for miR-103a-3p above the median of 0.37 (95%CI 0.13–1.13) and of 0.51 (95%CI 0.17–1.52) for miR-30e-3p.

Conclusions:  This study suggests EV-associated miR-103a-3p and miR-30e-3p are able to discriminate MPM from PAE subjects. Larger and prospective studies are needed to confirm these two-miRNA signature alone or in combination with other biomarkers as diagnostic tools for MPM.

[Article continues at original source]

Source: Plasmatic extracellular vesicle microRNAs in malignant pleural mesothelioma and asbestos-exposed subjects suggest a 2-miRNA signature as potential biomarker of disease


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