ArticleNucleic acids research2012
Prioritizing cancer-related key miRNA-target interactions by integrative genomics.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
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- Establishing a GRU-GCN coordination-based prediction model for miRNA-disease associations.BMC genomic data · 2025Article
- Microglia secrete miR-146a-5p-containing exosomes to regulate neurogenesis in depression.Molecular therapy : the journal of the American Society of Gene Therapy · 2022Article
- MiR-194 promotes hepatocellular carcinoma through negative regulation of CADM1.International journal of clinical and experimental pathology · 2020Article
- Optimizing prognosis-related key miRNA-target interactions responsible for cancer metastasis.Oncotarget · 2017Article
- Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm.Scientific reports · 2017Article
- The Role of MicroRNAs in Kidney Disease.Non-coding RNA · 2015Review
- Genome-wide DNA methylome reveals the dysfunction of intronic microRNAs in major psychosis.BMC medical genomics · 2015Article
- Systematically Prioritizing Functional Differentially Methylated Regions (fDMRs) by Integrating Multi-omics Data in Colorectal Cancer.Scientific reports · 2015Article
- Chromatin states modify network motifs contributing to cell-specific functions.Scientific reports · 2015Article
- Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data.Nucleic acids research · 2015Article
- Predicting the functions of long noncoding RNAs using RNA-seq based on Bayesian network.BioMed research international · 2015Article
- Semi-supervised learning for potential human microRNA-disease associations inference.Scientific reports · 2014Article
- Protein-driven inference of miRNA-disease associations.Bioinformatics (Oxford, England) · 2014Article
- Integrating multi-omics for uncovering the architecture of cross-talking pathways in breast cancer.PloS one · 2014Article
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Corrections and comments
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Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accumulating evidence indicates that microRNAs (miRNAs) can function as oncogenes or tumor suppressor genes by controlling few key targets, which in turn contribute to the pathogenesis of cancer. The identification of cancer-related key miRNA-target interactions remains a challenge. We performed a systematic analysis of known cancer-related key interactions manually curated from published papers based on different aspects including sequence, expression and function. Known cancer-related key interactions show more miRNA binding sites (especially for 8mer binding sites), more reliable binding of miRNA to the target region, higher expression associations and broader functional coverage when compared to non-disease-related interactions. Through integrating these sequence, expression and function features, we proposed a bioinformatics approach termed PCmtI to prioritize cancer-related key interactions. Ten-fold cross-validation of our approach revealed that it can achieve an area under the receiver operating characteristic curve of 93.9%. Subsequent leave-one-miRNA-out cross-validation also demonstrated the performance of our approach. Using miR-155 as a case, we found that the top ranked interactions can account for most functions of miR-155. In addition, we further demonstrated the power of our approach by 23 recently identified cancer-related key interactions. The approach described here offers a new way for the discovery of novel cancer-related key miRNA-target interactions.
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Registered trials
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