Analysis of the NCI-60 dataset for cancer-related microRNA and mRNA using expression profiles

• Published in: Computational biology and chemistry 2013-06, Vol.44, p.15-21
• Main Authors: Weng, Chia-Wei, Lee, Shan-Chih, Lee, Yu-Liang, Ng, Ka-Lok
• Format: Article
• Language: English
• Subjects: Cell Line, Tumor; Computation; Confidence intervals; Correlation coefficients; CpG island; Databases, Genetic; Expression profile; Fragile sites; Gene expression; Gene Expression Profiling; Genes; Humans; MicroRNA; MicroRNA cluster; MicroRNAs - genetics; National Cancer Institute (U.S.); Neoplasms - genetics; Oncogene; Pearson correlation; Platforms; Ribonucleic acids; RNA, Messenger - genetics; Spearman rank correlation; Tumor suppressor gene; United States
• ISSN: 1476-9271; 1476-928X
• DOI: 10.1016/j.compbiolchem.2013.02.001

[Display omitted] ► Quantify the miRNA and target gene expression profile by computing the correlation coefficient. ► This work provides a mean of sorting out highly confident cancer-related miRNA–mRNA pairs. ► Statistical test suggests that near CpG island miRNA and fragile site proximal miRNA may be associated with cancer formation. ► The platform is set up by integrating a rather wide range of datasets; such as, human miRNA and target genes data, with the cancerous genes, transcription factor, pathway, CpG island, fragile site and miRNA cluster information. Recent studies have indicated that microRNA (miRNA) may play an oncogenic or tumor suppressor role in human cancer. To study the regulatory role of miRNAs in tumorigenesis, an integrated platform has been set up to provide a user friendly interface for query. The main advantage of the present platform is that all the miRNA target genes’ information and disease records are drawn from experimentally verified or high confidence records. MiRNA target gene results are annotated with reference to the disease gene as well as the pathway database. The correlation strength between miRNA and target gene expression profile is quantified by computing the correlation coefficient using the NCI-60 expression profiling data. Comprehensive analysis of the NCI-60 data found that the cumulative percentage of negative correlation coefficients for cleavage regulation is slightly higher than its positive counterpart; which indicated that the mRNA degradation mechanism is slightly dominant. In addition, the RNAHybrid and TargetScans scores are computed which potentially served as quantitative estimators for miRNA–mRNA binding events. Three scores are defined for each miRNA–mRNA pair, which are based on the disease gene and pathway information. These three scores allow user to sort out high confidence cancer-related miRNA–mRNA pairs. Statistical tests were applied to investigate the relations of three chromosomal features, i.e., CpG island, fragile site, and miRNA cluster, with cancer-related miRNAs. A web-based interface has been set up for query, which can be accessed at: http://ppi.bioinfo.asia.edu.tw/mirna_target/ The main advantage of the present platform on miRNA–mRNA targeting information is that all the target genes’ information and disease records are experimentally verified. Although this may limit the number of miRNA–mRNA relationships, the results provided here are more solid and have fewer false positive events