Mining cancer gene expression databases for latent information on intronic microRNAs.

ABSTRACT: Around 50% of all human microRNAs reside within introns of coding genes and are usually co-transcribed. Gene expression datasets, therefore, should contain a wealth of miRNA-relevant latent information, exploitable for many basic and translational research aims. The present study was undertaken to investigate this possibility. We developed an in silico approach to identify intronic-miRNAs relevant to breast cancer, using public gene expression datasets. This led to the identification of a miRNA signature for aggressive breast cancer, and to the characterization of novel roles of selected miRNAs in cancer-related biological phenotypes. Unexpectedly, in a number of cases, expression regulation of the intronic-miRNA was more relevant than the expression of their host gene. These results provi

SUBMITTER: Monterisi S 

PROVIDER: S-EPMC5528658 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature