dbDEMC: a database of differentially expressed miRNAs in human cancers

Abstract

BackgroundMicroRNAs (miRNAs) are small noncoding RNAs about 22 nt long that negatively regulate gene expression at the post-transcriptional level. Their key effects on various biological processes, e.g., embryonic development, cell division, differentiation and apoptosis, are widely recognized. Evidence suggests that aberrant expression of miRNAs may contribute to many types of human diseases, including cancer. Here we present a database of differentially expressed miRNAs in human cancers (dbDEMC), to explore aberrantly expressed miRNAs among different cancers.ResultsWe collected the miRNA expression profiles of 14 cancer types, curated from 48 microarray data sets in peer-reviewed publications. The Significance Analysis of Microarrays method was used to retrieve the miRNAs that have dramatically different expression levels in cancers when compared to normal tissues. This database provides statistical results for differentially expressed miRNAs in each data set. A total of 607 differentially expressed miRNAs (590 mature miRNAs and 17 precursor miRNAs) were obtained in the current version of dbDEMC. Furthermore, low-throughput data from the same literature were also included in the database for validation. An easy-to-use web interface was designed for users. Annotations about each miRNA can be queried through miRNA ID or miRBase accession numbers, or can be browsed by different cancer types.ConclusionsThis database is expected to be a valuable source for identification of cancer-related miRNAs, thereby helping with the improvement of classification, diagnosis and treatment of human cancers. All the information is freely available through http://159.226.118.44/dbDEMC/index.html.

The role and clinical implications of microRNAs in hepatocellular carcinoma

“…Deregulation of these two miRNAs has been observed in many cases of B-cell chronic lymphocytic leukemia [126]. Another miRNA gene, the miR-17-92 cluster, was later demonstrated to be upregulated in B-cell lymphoma and accelerated c-Myc-induced tumorigenesis [70,127,128]. Subsequently, involvement of miRNAs in HCC has also been identified [129].…”

“…To evaluate global and dynamic expression of host miRNAs as well as alterations in mRNA levels during acute HCV infection, we have performed a comprehensive microarray analysis [70]. One hundred and forty-two miRNAs were identified as differentially expressed in JFH-1 HCV-infected and UV-inactivated HCV-infected Huh7.5.1 cells.…”

Identifying Comparative Structures in Biomedical Text

“…For example, this approach could be applied to mining reports of differential expression experiments, which are inherently comparisons. In (Yang et al, 2010), the authors defined seven comparative classes of differential expression analyses relevant to the processes of neoplastic transformation and progression, including cancer vs. normal tissue, high grade vs. low grade samples, and metastasis vs. primary cancer. Because comparative statements are often used to summarize the results of a study, these sentences are often of high interest to the reader.…”

miRNA-Disease Association Prediction with Collaborative Matrix Factorization

“…Here, two case studies, Esophageal Neoplasms and Kidney Neoplasms, were proposed to demonstrate the prediction performance of CMFMDA. In addition, we use two important miRNAdisease association databases to validate the prediction results: miR2Disease [57] and dbDEMC [58]. A final note about validation datasets is that only the associations which were absent from the HMDD database would be used.…”