ABSTRACT
In a multicenter study, we determined the expression profiles of 863 microRNAs by array analysis of 454 blood samples from human individuals with different cancers or noncancer diseases, and validated this 'miRNome' by quantitative real-time PCR. We detected consistently deregulated profiles for all tested diseases; pathway analysis confirmed disease association of the respective microRNAs. We observed significant correlations (P = 0.004) between the genomic location of disease-associated genetic variants and deregulated microRNAs.
Subject(s)
Disease/genetics , MicroRNAs/blood , MicroRNAs/genetics , Gene Expression Profiling , Genetic Variation/genetics , Humans , Oligonucleotide Array Sequence Analysis , Reverse Transcriptase Polymerase Chain ReactionABSTRACT
BACKGROUND: 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. METHODS: 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. RESULTS: A hypothesis test based approach 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. CONCLUSIONS: Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.