In Australia, more money is spent on skin cancer than any other malignancy.,Despite this, the mortality rate of melanoma, the deadliest form, has steadily increased over the past 50 years.,Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress.,Whole-microRNAome profiling was performed on plasma samples from 32 patients with histologically confirmed melanoma and 16 normal controls.,A classification algorithm was trained on these data and independently validated on multiple previously published microRNA data sets, representing (i) melanoma patient- and normal-blood, (ii) melanoma and nevi biopsy tissue, and (iii) cell lines and purified exosomes.,38 circulating microRNAs had biologically and statistically significant differences between melanoma and normal plasma samples (MEL38).,A support vector machine algorithm, trained on these markers, showed strong independent classification accuracy (AUC 0.79-0.94).,A majority of MEL38 genes have been previously associated with melanoma and are known regulators of angiogenesis, metastasis, tumour suppression, and treatment resistance.,MEL38 exhibits disease state specificity and robustness to platform and specimen-type variation.,It has potential to become an objective diagnostic biomarker and improve the precision and accuracy of melanoma detection and monitoring.
MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancer patients.,Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool.,Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanoma patients.,We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanoma patients as test set, and 11 samples of melanoma patients as independent validation set.,A hypothesis test based approch detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanoma patients and 30 miRNAs that were upregulated in blood cells of melanoma patients as compared to blood cells of healthy controls.,The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81).,Applying hierarchical clustering and principal component analysis we found that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on miRNA expression analysis.,Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis.,MiRNA microarray data were validated by qRT-PCR.,Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.