Melanoma is a devastating disease with few therapeutic options in the advanced stage and with the urgent need of reliable biomarkers for early detection. In this context, circulating microRNAs are raising great interest as diagnostic biomarkers. We analyzed the expression profiles of 21 selected microRNAs in plasma samples from melanoma patients and healthy donors to identify potential diagnostic biomarkers. Data analysis was performed using global mean normalization and NormFinder algorithm. Linear regression followed by receiver operating characteristic analyses was carried out to evaluate whether selected plasma miRNAs were able to discriminate between cases and controls. We found five microRNAs that were differently expressed among cases and controls after Bonferroni correction for multiple testing. Specifically, miR-15b-5p, miR-149-3p, and miR-150-5p were up-regulated in plasma of melanoma patients compared with healthy controls, while miR-193a-3p and miR-524-5p were down-regulated. Receiver operating characteristic analyses of these selected microRNAs provided area under the receiver operating characteristic curve values ranging from 0.80 to 0.95. Diagnostic value of microRNAs is improved when considering the combination of miR-149-3p, miR-150-5p, and miR-193a-3p. The triple classifier had a high capacity to discriminate between melanoma patients and healthy controls, making it suitable to be used in early melanoma diagnosis.

MicroRNAs (miRNAs) are a class of short non-coding RNAs involved in the regulation of gene expression and the control of several cellular processes at physiological and pathological levels. Furthermore, extracellular vesicles (EV), which are small membrane-bound vesicles secreted by cells in the extracellular environment, contain functional miRNAs. The remarkable deregulation of many miRNAs has been demonstrated in respiratory diseases. Among them, miR-206, miR-133a-5p, and miR-133a-3p are striated muscle-specific miRNAs (myo-miRNA), related to skeletal muscle dysfunction, one of the commonest systemic manifestations in patients with chronic obstructive pulmonary disease (COPD). Nevertheless, their circulating expression in COPD patients is not demonstrated. For these reasons, we performed a pilot study to analyze the expression profiles of myo-miRNAs in plasma-derived EV from patients with COPD. We analyzed the expression profiles of selected myo-miRNAs in plasma-derived EV from COPD. Receiver operating characteristic analyses were carried out to evaluate whether selected plasma miRNAs were able to discriminate between different groups of COPD patients. We found EV-embedded myo-miRNAs in the bloodstream of COPD patients. Specifically, miR-206, miR-133a-5p and miR-133a-3p were significantly upregulated in group B patients. Receiver operating characteristic analyses of the combination of these selected miRNAs showed their high capacity to discriminate group B from other COPD patients. Our data provide evidence that myo-miRNA are present in EV in the plasma of COPD patients and their expression (miR-206, miR-133a-5p, and miR-133a-3p) can discriminate group B from group C patients. The future analysis of a larger number of patients should allow us to obtain more refined correlations.

Background: Guidelines recommend limiting melanoma screening in a population with known risk factors, but none indicates methods for efficient recruitment. The purpose of this study is to compare three different methods of recruiting subjects to be screened for melanoma to detect which, if any, is the most efficient. Methods: From 2010 to 2019, subjects were recruited as follows: (1) regular skin examinations (RS), mainly conducted through the Associazione Contro il Melanoma network; (2) occasional melanoma screening (OS), during annual public campaigns; (3) and selective screening (SS), where people were invited to undergo a skin check after filling in a risk evaluation questionnaire, in cases where the assigned outcome was intermediate/high risk. Melanoma risk factors were compared across different screening methods. Generalized Linear Mixed Models were used for multivariable analysis. Results: A total of 2238 subjects (62.7% women) were recruited, median age 44 years (2–85), and 1094 (48.9 %) records were collected through RS, 826 (36.9 %) through OS, and 318 (14.2 %) through SS. A total of 131 suspicious non-melanoma skin cancers were clinically diagnosed, 20 pathologically confirmed, and 2 melanomas detected. SS performed significantly better at selecting subjects with a family history of melanoma and I-II phototypes compared to OS. Conclusions: Prior evaluation of melanoma known risk factors allowed for effective selection of a population to screen at higher risk of developing a melanoma.

No abstract