Identification of lncRNA-associated competing triplets reveals global patterns and prognostic markers for cancer

Abstract

Recent studies have suggested that long non-coding RNAs (lncRNAs) can interact with microRNAs (miRNAs) and indirectly regulate miRNA targets though competing interactions. However, the molecular mechanisms underlying these interactions are still largely unknown. In this study, these lncRNA–miRNA–gene interactions were defined as lncRNA-associated competing triplets (LncACTs), and an integrated pipeline was developed to identify lncACTs that are active in cancer. Competing lncRNAs had sponge features distinct from non-competing lncRNAs. In the lncACT cross-talk network, disease-associated lncRNAs, miRNAs and coding-genes showed specific topological patterns indicative of their competence and control of communication within the network. The construction of global competing activity profiles revealed that lncACTs had high activity specific to cancers. Analyses of clustered lncACTs revealed that they were enriched in various cancer-related biological processes. Based on the global cross-talk network and cluster analyses, nine cancer-specific sub-networks were constructed. H19- and BRCA1/2-associated lncACTs were able to discriminate between two groups of patients with different clinical outcomes. Disease-associated lncACTs also showed variable competing patterns across normal and cancer patient samples. In summary, this study uncovered and systematically characterized global properties of human lncACTs that may have prognostic value for predicting clinical outcome in cancer patients.

Double‐negative feedback loop between long non‐coding RNA TUG1 and miR‐145 promotes epithelial to mesenchymal transition and radioresistance in human bladder cancer cells

“…Emerging evidence suggests that lncRNAs act as endogenous miRNA sponges to bind to miRNAs and regulate their function [26,27]. To find out whether TUG1 serves as a miRNA sponge, we performed the bioinformatics analysis and found that TUG1 contained binding sites for several miRNAs.…”

Inferences of individual drug responses across diverse cancer types using a novel competing endogenous RNA network

“…A positive regression coefficient indicated that increased expression was associated with poor survival, and a negative regression coefficient indicated that increased expression was associated with good survival. The DRS for each patient was calculated taking into account both the strength and positive or negative association of lncRNA, miRNA, and genes of all DRCEs with survival.$\text{DRS}=-\sum _{i=1}^n{\beta }_i\ast {\text{Exp}}_i$where n was the number of nonredundant nodes in all DRCEs in the given cancer, β i was the univariate Cox regression coefficient of node i in the DRCE (Wang et al ., 2015, 2017), and Exp i was the expression level of node i of the given patient. Patients were stratified into high or low‐DRS groups using the median as the cutoff.…”

“…Different species of RNA transcripts can communicate with each other, which have been symbolically referred to as letters of a new language. The competing regulation of lncRNA, miRNA, and gene is not only of fundamental importance in physiological conditions (Cesana et al ., 2011), but also relevant in various cancers (Wang et al ., 2015) and may also influence genes associated with drug responses and the development of resistance to cancer therapy (Ling et al ., 2013). For example, Cao et al .…”

Identification of prognostic biomarkers in glioblastoma using a long non-coding RNA-mediated, competitive endogenous RNA network

“…Typically, a ‘guilt by association’ strategy has been used to characterize lncRNA function [13–15]. Recent studies have demonstrated that lncRNAs compete with endogenous RNAs (ceRNAs) by acting as miRNA sponges to regulate expression level of other transcripts [16–19]. For example, the lncRNA HULC plays an important regulatory role in lung cancer by acting as an endogenous ceRNA [20].…”

“…In addition, the muscle-specific lncRNA linc-MD1 regulates the timing of muscle differentiation by sequestering miR-133 to modulate the expression of MAML1 and MEF2C [21]. A recent study identified a lncRNA-associated ceRNA network across 12 different cancers and identified prognostic lncRNAs using network analysis [19]. Another study proposed that the ceRNA interaction network of GBM could reveal canonical oncogenic pathways [22].…”