Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer

Abstract

BackgroundMicroRNAs (miRNAs) are a class of non-coding regulatory RNAs approximately 22 nucleotides in length that play a role in a wide range of biological processes. Abnormal miRNA function has been implicated in various human cancers including prostate cancer (PCa). Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. However, limited data are available on the role of cancer-specific miRNAs. Integrative computational bioinformatics approaches are effective for the detection of potential outlier miRNAs in cancer.MethodsThe human miRNA-mRNA target network was reconstructed by integrating multiple miRNA-mRNA interaction datasets. Paired miRNA and mRNA expression profiling data in PCa versus benign prostate tissue samples were used as another source of information. These datasets were analyzed with an integrated bioinformatics framework to identify potential PCa miRNA signatures. In vitro q-PCR experiments and further systematic analysis were used to validate these prediction results.ResultsUsing this bioinformatics framework, we identified 39 miRNAs as potential PCa miRNA signatures. Among these miRNAs, 20 had previously been identified as PCa aberrant miRNAs by low-throughput methods, and 16 were shown to be deregulated in other cancers. In vitro q-PCR experiments verified the accuracy of these predictions. miR-648 was identified as a novel candidate PCa miRNA biomarker. Further functional and pathway enrichment analysis confirmed the association of the identified miRNAs with PCa progression.ConclusionsOur analysis revealed the scale-free features of the human miRNA-mRNA interaction network and showed the distinctive topological features of existing cancer miRNA biomarkers from previously published studies. A novel cancer miRNA biomarker prediction framework was designed based on these observations and applied to prostate cancer study. This method could be applied for miRNA biomarker prediction in other cancers.

Differential Expression of MiR-106b-5p and MiR-200c-3p in Newly Diagnosed Versus Chronic Primary Immune Thrombocytopenia Patients Based on Systematic Analysis

“…In this work, we employed POMA to identify key miRNAs expressed in samples obtained from ITP patients that were newly diagnosed (G1) versus managing a chronic ITP condition (G2). POMA is a framework that has been used to identify candidate miRNA biomarkers for diseases by integrating microarray profiling with experimental and predicted miRNA-mRNA interactions [29, 30]. …”

“…Differentially expressed miRNAs and/or genes were then mapped to the whole network to infer specific miRNA-mRNA subnetworks [12, 20]. According to the framework, stage-specific miRNA-mRNA networks were built, and key miRNAs in the subnetworks were identified on the basis of significant differential expression of miRNAs and genes between each ITP group and the N group using improved POMA [29, 30]. We also constructed a G2’ miRNA–mRNA network based on the identification of DE-miRNAs and DE-mRNAs between G2 and G1.…”

“…Therefore, we initially employed high-throughput microarray technology to measure the expression profiles of miRNAs and genes in peripheral blood cells samples from patients with newly diagnosed ITP, those with chronic ITP, and normal controls. Then, we used the systematic Pipeline of Outlier MicroRNA Analysis (POMA) framework [29, 30] to identify candidate key miRNAs in the two ITP stages based on the miRNA and messenger RNA (mRNA) profiles obtained. Finally, we validated the aberrant expression of key miRNAs in a large sample of patients with ITP.…”

miRNAs as novel biomarkers in the management of prostate cancer

“…Likewise, Zhang et al [81] identified 39 novel miRNAs candidates as PCa biomarkers analyzing Gene Expression Omnibus datasets for PCa and benign prostatic hyperplasia (BPH) using bioinformatics tools, considering the regulatory power of miRNAs. Results were verified by qRT-PCR concluding that miRNA-648 could be a novel biomarker of PCa.…”

Genome-wide analysis of microRNA and mRNA expression signatures in cancer

“…We found that approximately 1.3% of the predicted miRNA targets formed reciprocal "up-down" or "down-up" expression relationships with miRNAs, suggesting that the modulation of miRNA-mRNA interactions could be promising biomarkers for cancers. Integrated expression analysis of miRNAs and mRNAs using microarray technology have revealed signatures implicated in ovarian cancer [165,166] , breast cancer [167][168][169][170][171] , metastatic osteosarcoma [172] , gastric cancer [173,174] , pancreatic cancer [175] , oral squamous cell carcinoma [176] , lung cancer [177][178][179] , prostate cancer [180,181] , follicular thyroid tumors [182] , retinoblastoma [183] , etc. The miRNA/mRNA interactome not only includes the interactions between an miRNA and its targets but also comprises the TF-miRNA network.…”