Abstract
BackgroundMicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts.ResultsTo address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets.ConclusionsOur results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.
Highlights
MicroRNAs play multiple roles in tumor biology [1]
Inference method We used an extended version of the Hermes algorithm, which we had previously introduced to discover and validate glioma-specific competitive endogenous RNA (ceRNA) [5], to systematically discover ceRNA interactions in prostate (PRAD) and breast (BRCA) adenocarcinomas, using matched miRNA and mRNA expression profiles of the corresponding TCGA cohorts
While the ceRNA inference component of the algorithm was unchanged, the new algorithm supports the identification of the specific miRNAs that mediate each interaction; these miRNAs are predicted to target both mRNAs in a ceRNA interaction, and their activity is affected by modulation of target mRNA abundance
Summary
MicroRNAs (miRNAs) play multiple roles in tumor biology [1]. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration [2]. Multiple groups have reported on gene products that modulate miRNA activity [5,6,7, 19,20,21,22,23,24,25,26], including RNA species that can alter the abundance of other RNAs in trans through ceRNA interactions These studies show that targets of the same miRNAs are coupled and that up- or down-regulation of one target may alter the expression of other cognate targets by sequestering or releasing their shared miRNA molecules, respectively (Figure 1A). We propose that the high validation rates of these assays can inform on the accuracy of computational predictions, and will help estimate the number of genes that are modulated by ceRNA in representative tumor contexts
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