The miR-30 MicroRNA Family Targets smoothened to Regulate Hedgehog Signalling in Zebrafish Early Muscle Development

The importance of microRNAs in development is now widely accepted. However, identifying the specific targets of individual microRNAs and understanding their biological significance remains a major challenge. We have used the zebrafish model system to evaluate the expression and function of microRNAs potentially involved in muscle development and study their interaction with predicted target genes. We altered expression of the miR-30 microRNA family and generated phenotypes that mimicked misregulation of the Hedgehog pathway. Inhibition of the miR-30 family increases activity of the pathway, resulting in elevated ptc1 expression and increased numbers of superficial slow-muscle fibres. We show that the transmembrane receptor smoothened is a target of this microRNA family. Our results indicate that fine coordination of smoothened activity by the miR-30 family allows the correct specification and differentiation of distinct muscle cell types during zebrafish embryonic development.     

MicroRNA 218 Acts as a Tumor Suppressor by Targeting Multiple Cancer Phenotype-associated Genes in Medulloblastoma

Aberrant expression of microRNAs has been implicated in many cancers. We recently demonstrated differential expression of several microRNAs in medulloblastoma. In this study, the regulation and function of microRNA 218 (miR-218), which is significantly underexpressed in medulloblastoma, was evaluated. Re-expression of miR-218 resulted in a significant decrease in medulloblastoma cell growth, cell colony formation, cell migration, invasion, and tumor sphere size. We used C17.2 neural stem cells as a model to show that increased miR-218 expression results in increased cell differentiation and also decreased malignant transformation when transfected with the oncogene REST. These results suggest that miR-218 acts as a tumor suppressor in medulloblastoma. MicroRNAs function by down-regulating translation of target mRNAs. Targets are determined by imperfect base pairing of the microRNA to the 3′-UTR of the mRNA. To comprehensively identify actual miR-218 targets, medulloblastoma cells overexpressing miR-218 and control cells were subjected to high throughput sequencing of RNA isolated by cross-linking immunoprecipitation, a technique that identifies the mRNAs bound to the RNA-induced silencing complex component protein Argonaute 2. High throughput sequencing of mRNAs identified 618 genes as targets of miR-218 and included both previously validated targets and many targets not predicted computationally. Additional work further confirmed CDK6, RICTOR, and CTSB (cathepsin B) as targets of miR-218 and examined the functional role of one of these targets, CDK6, in medulloblastoma.     

Network Modeling Identifies Molecular Functions Targeted by miR-204 to Suppress Head and Neck Tumor Metastasis

Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.     

Differentially expressed miR-20, miR-21, miR-100, miR-125a and miR-146a as a potential biomarker for prostate cancer

Prostate cancer is the leading cause of death among men worldwide. Deregulation of microRNAs has been reported in many cancers. Expression of microRNAs miR-20a-5p, miR-21-5p, miR-100-5p, miR-125a-5p and miR-146a-5p in tissue blocks of histologically confirmed prostate cancer patients compared with BPH patients, to identify potential microRNA biomarker for prostate cancer. MicroRNA was isolated and expression was quantified by qRT-PCR using Taqman Advanced microRNA assay kits. The interactions between the microRNA:target mRNA were predicted by using bioinformatics tools such as miRwalk and miRTargetlink. The experimentally validated targets were analysed using gprofiler to identify their molecular function, biological process and related pathways. The expression analysis revealed that miR-21 and miR-100 were significantly down-regulated whereas miR-125a was up-regulated in prostate cancer patients. Comparative analysis of the expression levels with tumor grading reveal that miR-100 was significantly down-regulated (p?<?0.05) in high grade tumor, indicating that miR-100 associated with prostate cancer. ROC analysis revealed that combined analysis of down-regulated miRNAs (miR-21 and miR-100) shown AUC of 0.72 (95% CI 0.65–0.79). The combined analysis of all five miRNAs showed AUC of 0.87 (95% CI 0.81–0.92). The targets prediction analysis revealed several validated targets including BCL2, ROCK1, EGFR, PTEN, MTOR, NAIF1 and VEGFA. Our results provide evidence that combined analysis of all the five miRNAs as a panel can significantly improve the prediction level of the presence of prostate cancer and may be used as a potential diagnostic biomarker.

     

A probabilistic approach to microRNA-target binding

Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interactions of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set-up a probabilistic model to explain the binding preferences between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new sequence and defines the likelihood of this sequence using a Variable Length Markov Chain. It offers a complementary representation of microRNA–mRNA pairs for microRNA target prediction tools or other probabilistic frameworks of integrative gene regulation analysis. The performance of present model is evaluated by its ability to predict microRNA–target mRNA interaction given a mature microRNA sequence and a putative mRNA binding site. In regard to classification accuracy, it outperforms two recent methods based on thermodynamic stability and sequence complementarity. The experiments can also unveil the effects of base pairing types and non-seed region in duplex formation.     

Deep-sequencing of endothelial cells exposed to hypoxia reveals the complexity of known and novel microRNAs

In order to understand the role of microRNAs (miRNAs) in vascular physiopathology, we took advantage of deep-sequencing techniques to accurately and comprehensively profile the entire miRNA population expressed by endothelial cells exposed to hypoxia. SOLiD sequencing of small RNAs derived from human umbilical vein endothelial cells (HUVECs) exposed to 1% O₂ or normoxia for 24 h yielded more than 22 million reads per library. A customized bioinformatic pipeline identified more than 400 annotated microRNA/microRNA* species with a broad abundance range: miR-21 and miR-126 totaled almost 40% of all miRNAs. A complex repertoire of isomiRs was found, displaying also 5′ variations, potentially affecting target recognition. High-stringency bioinformatic analysis identified microRNA candidates, whose predicted pre-miRNAs folded into a stable hairpin. Validation of a subset by qPCR identified 18 high-confidence novel miRNAs as detectable in independent HUVEC cultures and associated to the RISC complex. The expression of two novel miRNAs was significantly down-modulated by hypoxia, while miR-210 was significantly induced. Gene ontology analysis of their predicted targets revealed a significant association to hypoxia-inducible factor signaling, cardiovascular diseases, and cancer. Overexpression of the novel miRNAs in hypoxic endothelial cells affected cell growth and confirmed the biological relevance of their down-modulation. In conclusion, deep-sequencing accurately profiled known, variant, and novel microRNAs expressed by endothelial cells in normoxia and hypoxia.     

Refining microRNA target predictions: Sorting the wheat from the chaff

microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.     

TargetScreen: An unbiased approach to identify functionally important microRNA targets

We recently identified miR-19 as the critical activity for leukemogenesis within the oncogenic 17~92 cluster of microRNAs.¹ This finding prompted us to test an unbiased method for pinpointing those miR-19 targets may be key to its oncogenic action. Specifically, we used a large-scale short hairpin RNA screen to identify those miR-19 target genes, whose knockdown could reproduce miR-19's effects on lymphocyte transformation. In this way, we found that miR-19 produces a coordinate clampdown on multiple negative regulators of PI3K-related survival signals. These findings have implications for the therapy of miR-19 expressing tumors. They also validate a new strategy for the unbiased identification of functionally important microRNA target genes. Using the example of miR-19 in leukemia, we will discuss some possibilities and limitations of this new approach.     

Comprehensive miRNome and in silico analyses identify the Wnt signaling pathway to be altered in the diabetic liver

Aberrant microRNA expression patterns underlie the pathogenesis of diverse diseases, however in a disease as complex as diabetes where the liver exhibits deregulations of normal metabolic processes, the status and role of microRNAs are not yet completely understood. In a step towards unraveling this correlation, we assessed the global microRNA expression profiles in the control and diabetic (db/db) mice liver. These db/db mice were on a C57BLKS/J background and they exhibit diabetic phenotypes that are remarkably similar to those in humans. microRNA microarray profiling revealed 11 miRNAs to be up-regulated and 2 to be down-regulated in the db/db mice liver. Predicted targets of these differentially expressed microRNAs were retrieved from miRanda and TargetScan and the maximum number of commonly predicted targets mapped onto the Wnt signaling pathway that is otherwise conventionally associated with organogenesis and development. Towards validation of this prediction, we found that major components of the Wnt signaling pathway are inhibited in the db/db mice liver. A significant number of these down-regulated genes of the Wnt signaling pathway are predicted targets to the up-regulated miRNAs and specifically our results show that miR-34a and miR-22 decreased the protein levels of their targets. Overexpression of miR-34a and miR-22 and also inhibition of Wnt signaling using specific inhibitors led to increased lipid accumulation in HepG2 cells. Our data suggest that the Wnt signaling pathway could contribute towards the deregulated hepatic behavior in these animals and an altered hepatic miRNA signature could be playing a regulatory role herein.