miRNA‐mediated ‘tug‐of‐war’ model reveals ceRNA propensity of genes in cancers

Abstract

Competing endogenous RNA (ceRNA) are transcripts that cross‐regulate each other at the post‐transcriptional level by competing for shared microRNA response elements (MREs). These have been implicated in various biological processes impacting cell‐fate decisions and diseases including cancer. There are several studies that predict possible ceRNA pairs by adopting various machine‐learning and mathematical approaches; however, there is no method that enables us to gauge as well as compare the propensity of the ceRNA of a gene and precisely envisages which among a pair exerts a stronger pull on the shared miRNA pool. In this study, we developed a method that uses the ‘tug of war of genes’ concept to predict and quantify ceRNA potential of a gene for the shared miRNA pool in cancers based on a score represented by SoCeR (score of competing endogenous RNA). The method was executed on the RNA‐Seq transcriptional profiles of genes and miRNA available at TCGA along with CLIP‐supported miRNA‐target sites to predict ceRNA in 32 cancer types which were validated with already reported cases. The proposed method can be used to determine the sequestering capability of the gene of interest as well as in ranking the probable ceRNA candidates of a gene. Finally, we developed standalone applications (SoCeR tool) to aid researchers in easier implementation of the method in analysing different data sets or diseases.

Analysis of circular RNA‑associated competing endogenous RNA network in breast cancer

“…Previous studies have demonstrated that circRNAs sponge miRNAs via MREs in numerous diseases. This mechanism has also been reported in cancer initiation and progression (19). Accumulating evidence has demonstrated that circRNAs regulate the growth, development and metastasis of BC by acting as miRNA sponges.…”

LncRNA NNT-AS1 contributes to the cisplatin resistance of cervical cancer through NNT-AS1/miR-186/HMGB1 axis

“…It has been reported that lncRNA could act as competing endogenous RNA (ceRNA) of miRNAs to indirectly regulate gene expression implicated in various biological processes, including cancer [33]. MiR-186 was found to be a target of NNT-AS1 using bioinformatics prediction program and then NNT-AS1 directly binding to miR-186 was verified by luciferase reporter assay and RNA pull down assay.…”

LncRNA‐associated competing endogenous RNA network analysis uncovered key lncRNAs involved in temozolomide resistance and tumor recurrence of glioblastoma

“…After obtaining significantly positively correlated lncRNA-mRNA pairs, we adopted a comprehensive computational approach to identify significant ceRNA candidates. 31 Several methods have been used to predict the ceRNA network, such as the hypergeometric test, which predicts the ceRNAs based on the number of common miRNAs binding to mRNA or lncRNA. [32][33][34] These studies considered only a single parameter.…”

“…T A B L E 1 Sample details of five mRNAs, long non-coding RNAs (lncRNAs), and microRNAs (miRNAs) expression data of temozolomideresistant glioblastoma multiforme tissues and cells. 31 we first computed the binding affinity of each mRNA and lncRNA targeted by miRNA with slight modifications without considering the conservation score. We used both miRanda and Targetscan for target prediction, but one of them (miRanda) does not provide a conservation score of target sites.…”