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Background: The aberrant expression of microRNAs is closely connected to the occurrence and development of a great deal of human diseases. To study human diseases, numerous effective computational models that are valuable and meaningful have been presented by researchers. Results: Here, we present a computational framework based on graph Laplacian regularized L2, 1-nonnegative matrix factorization (GRL2, 1-NMF) for inferring possible human disease-connected miRNAs. First, manually validated disease-connected microRNAs were integrated, and microRNA functional similarity information along with two kinds of disease semantic similarities were calculated. Next, we measured Gaussian interaction profile (GIP) kernel similarities for both diseases and microRNAs. Then, we adopted a preprocessing step, namely, weighted K nearest known neighbours (WKNKN), to decrease the sparsity of the miRNA-disease association matrix network. Finally, the GRL2,1-NMF framework was used to predict links between microRNAs and diseases. Conclusions: The new method (GRL2, 1-NMF) achieved AUC values of 0.9280 and 0.9276 in global leave-one-out cross validation (global LOOCV) and five-fold cross validation (5-CV), respectively, showing that GRL2, 1-NMF can powerfully discover potential disease-related miRNAs, even if there is no known associated disease. [ABSTRACT FROM AUTHOR]

Background: There is growing evidence supporting a role for microRNAs (miRNA) as targets in aberrant mechanisms of DNA hypermethylation. Epigenetic silencing of tumor suppressor miRNAs, including miR-663, which has recently been reported to be inactivated by hypermethylation in several cancers, may play important roles in pediatric acute myeloid leukemia (AML). However, expression of miR-663 and its promoter methylation remain status unclear in childhood leukemia. Methods: Promoter methylation status of miR-663 was investigated by methylation specific PCR (MSP) and bisulfate genomic sequencing (BGS). Transcriptional expression of miR-663 was evaluated by semi-quantitative and real-time PCR, and the relationship between expression of miR-663 and promoter methylation was confirmed using 5-aza-2'-deoxycytidine (5-Aza) demethylation reagent. Results: MiR-663 was aberrantly methylated in 45.5% (5/11) leukemia cell lines; BGS showed that the promoter was significantly methylated in three AML cell lines; methylation of miR-663 was significantly higher in Chinese pediatric AML patients [41.4% (29/70)] compared to normal bone marrow (NBM) control samples [10.0% (3/30)]. These results were confirmed by both BGS and 5-Aza demethylation analysis. In addition, miR-663 transcript expression was significantly lower in AML patients, both with and without miR-663 methylation, compared to controls; however, there were no significant differences in clinical features or French-American-British (FAB) classification between patients with and without miR-663 methylation. Conclusions: Expression of miR-663 was significantly lower in pediatric AML cells compared to NBM controls; furthermore, a high frequency of miR-663 promoter hypermethylation was observed in both AML cell lines and pediatric AML samples. Inactivation of miR-663 by promoter hypermethylation could be affected by 5-Aza demethylation. These findings suggest that hypermethylation of the miR-663 promoter may be an early event in the development of pediatric AML. [ABSTRACT FROM AUTHOR]