Computational methods for identifying miRNA sponge interactions

Le, Thuc Duy; Zhang, Junpeng; Liu, Lin; Li, Jiuyong

doi:10.1093/bib/bbw042

Cited by 75 publications

(83 citation statements)

References 73 publications

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“…For the ground truth of validation, we combine the experimentally validated miRNA sponge interactions from [8] with miRSponge [57]. In total, we have obtained 99 experimentally validated miRNA sponge interactions (details in Additional file 6).…”

Section: Resultsmentioning

confidence: 99%

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Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

Zhang

Liu

et al. 2017

BMC Bioinformatics

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BackgroundRecent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown.ResultsIn this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of PPIs. We focus on investigating breast cancer (BRCA) related miRNA sponge co-regulation, by integrating heterogeneous data, including miRNA, long non-coding RNA (lncRNA) and messenger RNA (mRNA) expression data, experimentally validated miRNA-target interactions, PPIs and lncRNA-target interactions, and the list of breast cancer genes. We find that the inferred BRCA-related miRSCoPPI network is highly connected and scale free. The top 10% hub genes in the BRCA-related miRSCoPPI network have potential biological implications in breast cancer. By utilizing a graph clustering method, we discover 17 BRCA-related miRSCoPPI modules. Through pathway enrichment analysis of the modules, we find that several modules are significantly enriched in pathways associated with breast cancer. Moreover, 10 modules have good performance in classifying breast tumor and normal samples, and can act as module signatures for prognostication. By using putative computationally predicted miRNA-target interactions, we have consistent results with those obtained using experimentally validated miRNA-target interactions, indicating that miRSCoPPI is robust in inferring miRNA sponge co-regulation of PPIs in human breast cancer.ConclusionsTaken together, the results demonstrate that miRSCoPPI is a promising tool for inferring BRCA-related miRNA sponge co-regulation of PPIs and it can help with the understanding of the co-regulation roles of miRNA sponges on the PPIs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1672-2) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

“…Based on the hypothesis, a pool of RNAs acting as ceRNAs (also called miRNA sponges), such as lncRNAs, pseudogenes, mRNAs and circular RNAs (circRNAs), compete with each other by sponging miRNAs for interactions. Previous studies have shown that miRNA sponges play important roles in the physiology and development of human cancers [7, 8]. …”

Section: Introductionmentioning

confidence: 99%

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

Zhang

Liu

et al. 2017

BMC Bioinformatics

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“…Liu et al (2015) showed that miR-146b-5p functioned as a tumor suppressor by targeting TRAF6 and predicted the prognosis of human gliomas. Recent studies showed that lncRNA could function as a miRNA sponge to regulate mRNA expression levels (Le, Zhang, Liu, & Li, 2017). CeRNA was proved to be an effective posttranscriptional regulation mechanism of lncRNAs on downstream target transcripts (Yang et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

HOXA11‐AS promotes the growth and invasion of renal cancer by sponging miR‐146b‐5p to upregulate MMP16 expression

Yang

Zhang

Jin

et al. 2018

Journal Cellular Physiology

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Recently, increasing studies showed that long noncoding RNAs (lncRNAs) play critical roles in tumor progression. However, the function and underlying mechanism of HOMEOBOX A11 antisense RNA (HOXA11-AS) on renal cancer remain unclear. In the current study, our data showed that the expression of HOXA11-AS was significantly upregulated in clear cell renal cell carcinoma (ccRCC) tissues and cell lines. High HOXA11-AS expression was associated with the advanced clinical stage, tumor stage, and lymph node metastasis. Function assays showed that HOXA11-AS inhibition significantly suppressed renal cancer cells growth, invasion, and ETM phenotype. In addition, underlying mechanism revealed that HOXA11-AS could act as a competing endogenous RNA (ceRNA) that repressed miR-146b-5p expression, which regulated its downstream target MMP16 in renal cancer. Taken together, our findings suggested that HOXA11-AS could promote renal cancer cells growth and invasion by modulating miR-146b-5p-MMP16 axis. Thus, our findings suggested that HOXA11-AS could serve as potential therapeutic target for the treatment of renal cancer.

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“…Previous studies had shown that functionally similar miRNAs always appear in similar diseases; therefore many computational models were proposed to identify novel miRNA-disease associations [13,[41][42][43][44][45][46]. For example, Jiang et al [31] analyzed and improved disease-gene prediction model, introduced the principle of hypergeometric distribution and how to use it, and discussed its application in prediction model and its actual effect.…”

Section: Introductionmentioning

confidence: 99%

miRNA-Disease Association Prediction with Collaborative Matrix Factorization

et al. 2017

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As one of the factors in the noncoding RNA family, microRNAs (miRNAs) are involved in the development and progression of various complex diseases. Experimental identification of miRNA-disease association is expensive and time-consuming. Therefore, it is necessary to design efficient algorithms to identify novel miRNA-disease association. In this paper, we developed the computational method of Collaborative Matrix Factorization for miRNA-Disease Association prediction (CMFMDA) to identify potential miRNA-disease associations by integrating miRNA functional similarity, disease semantic similarity, and experimentally verified miRNA-disease associations. Experiments verified that CMFMDA achieves intended purpose and application values with its short consuming-time and high prediction accuracy. In addition, we used CMFMDA on Esophageal Neoplasms and Kidney Neoplasms to reveal their potential related miRNAs. As a result, 84% and 82% of top 50 predicted miRNA-disease pairs for these two diseases were confirmed by experiment. Not only this, but also CMFMDA could be applied to new diseases and new miRNAs without any known associations, which overcome the defects of many previous computational methods.

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Computational methods for identifying miRNA sponge interactions

Cited by 75 publications

References 73 publications

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

HOXA11‐AS promotes the growth and invasion of renal cancer by sponging miR‐146b‐5p to upregulate MMP16 expression

miRNA-Disease Association Prediction with Collaborative Matrix Factorization

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