Identifying Cancer Specific Functionally Relevant miRNAs from Gene Expression and miRNA-to-Gene Networks Using Regularized Regression

Identifying microRNA signatures for the different types and subtypes of cancer can result in improved detection, characterization and understanding of cancer and move us towards more personalized treatment strategies. However, using microRNA''s differential expression (tumour versus normal) to determine these signatures may lead to inaccurate predictions and low interpretability because of the noisy nature of miRNA expression data. We present a method for the selection of biologically active microRNAs using gene expression data and microRNA-to-gene interaction network. Our method is based on a linear regression with an elastic net regularization. Our simulations show that, with our method, the active miRNAs can be detected with high accuracy and our approach is robust to high levels of noise and missing information. Furthermore, our results on real datasets for glioblastoma and prostate cancer are confirmed by microRNA expression measurements. Our method leads to the selection of potentially functionally important microRNAs. The associations of some of our identified miRNAs with cancer mechanisms are already confirmed in other studies (hypoxia related hsa-mir-210 and apoptosis-related hsa-mir-296-5p). We have also identified additional miRNAs that were not previously studied in the context of cancer but are coherently predicted as active by our method and may warrant further investigation. The code is available in Matlab and R and can be downloaded on http://www.cs.toronto.edu/goldenberg/Anna_Goldenberg/Current_Research.html.     

miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy

Small RNA RNA-seq for microRNAs (miRNAs) is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM). Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA) are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench), miRge was faster (4 to 32-fold) and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.     

Towards computational prediction of microRNA function and activity

While it has been established that microRNAs (miRNAs) play key roles throughout development and are dysregulated in many human pathologies, the specific processes and pathways regulated by individual miRNAs are mostly unknown. Here, we use computational target predictions in order to automatically infer the processes affected by human miRNAs. Our approach improves upon standard statistical tools by addressing specific characteristics of miRNA regulation. Our analysis is based on a novel compendium of experimentally verified miRNA-pathway and miRNA-process associations that we constructed, which can be a useful resource by itself. Our method also predicts novel miRNA-regulated pathways, refines the annotation of miRNAs for which only crude functions are known, and assigns differential functions to miRNAs with closely related sequences. Applying our approach to groups of co-expressed genes allows us to identify miRNAs and genomic miRNA clusters with functional importance in specific stages of early human development. A full list of the predicted mRNA functions is available at http://acgt.cs.tau.ac.il/fame/.     

Hedgehog Signaling Strength Is Orchestrated by the mir-310 Cluster of MicroRNAs in Response to Diet

Since the discovery of microRNAs (miRNAs) only two decades ago, they have emerged as an essential component of the gene regulatory machinery. miRNAs have seemingly paradoxical features: a single miRNA is able to simultaneously target hundreds of genes, while its presence is mostly dispensable for animal viability under normal conditions. It is known that miRNAs act as stress response factors; however, it remains challenging to determine their relevant targets and the conditions under which they function. To address this challenge, we propose a new workflow for miRNA function analysis, by which we found that the evolutionarily young miRNA family, the mir-310s (mir-310/mir-311/mir-312/mir-313), are important regulators of Drosophila metabolic status. mir-310s-deficient animals have an abnormal diet-dependent expression profile for numerous diet-sensitive components, accumulate fats, and show various physiological defects. We found that the mir-310s simultaneously repress the production of several regulatory factors (Rab23, DHR96, and Ttk) of the evolutionarily conserved Hedgehog (Hh) pathway to sharpen dietary response. As the mir-310s expression is highly dynamic and nutrition sensitive, this signal relay model helps to explain the molecular mechanism governing quick and robust Hh signaling responses to nutritional changes. Additionally, we discovered a new component of the Hh signaling pathway in Drosophila, Rab23, which cell autonomously regulates Hh ligand trafficking in the germline stem cell niche. How organisms adjust to dietary fluctuations to sustain healthy homeostasis is an intriguing research topic. These data are the first to report that miRNAs can act as executives that transduce nutritional signals to an essential signaling pathway. This suggests miRNAs as plausible therapeutic agents that can be used in combination with low calorie and cholesterol diets to manage quick and precise tissue-specific responses to nutritional changes.     

Let-7 microRNA family is selectively secreted into the extracellular environment via exosomes in a metastatic gastric cancer cell line

Background

Exosomes play a major role in cell-to-cell communication, targeting cells to transfer exosomal molecules including proteins, mRNAs, and microRNAs (miRNAs) by an endocytosis-like pathway. miRNAs are small noncoding RNA molecules on average 22 nucleotides in length that regulate numerous biological processes including cancer pathogenesis and mediate gene down-regulation by targeting mRNAs to induce RNA degradation and/or interfering with translation. Recent reports imply that miRNAs can be stably detected in circulating plasma and serum since miRNAs are packaged by exosomes to be protected from RNA degradation. Thus, profiling exosomal miRNAs are in need to clarify intercellular signaling and discover a novel disease marker as well.

Methodology/Principal Findings

Exosomes were isolated from cultured cancer cell lines and their quality was validated by analyses of transmission electron microscopy and western blotting. One of the cell lines tested, a metastatic gastric cancer cell line, AZ-P7a, showed the highest RNA yield in the released exosomes and distinctive shape in morphology. In addition, RNAs were isolated from cells and culture media, and profiles of these three miRNA fractions were obtained using microarray analysis. By comparing signal intensities of microarray data and the following validation using RT-PCR analysis, we found that let-7 miRNA family was abundant in both the intracellular and extracellular fractions from AZ-P7a cells, while low metastatic AZ-521, the parental cell line of AZ-P7a, as well as other cancer cell lines showed no such propensity.

Conclusions/Significance

The enrichment of let-7 miRNA family in the extracellular fractions, particularly, in the exosomes from AZ-P7a cells may reflect their oncogenic characteristics including tumorigenesis and metastasis. Since let-7 miRNAs generally play a tumor-suppressive role as targeting oncogenes such as RAS and HMGA2, our results suggest that AZ-P7a cells release let-7 miRNAs via exosomes into the extracellular environment to maintain their oncogenesis.     

Investigation of Content,Stoichiometry and Transfer of miRNA from Human Neural Stem Cell Line Derived Exosomes

Exosomes are small (30–100 nm) membrane vesicles secreted by a variety of cell types and only recently have emerged as a new avenue for cell-to-cell communication. They are natural shuttles of RNA and protein cargo, making them attractive as potential therapeutic delivery vehicles. MicroRNAs (miRNAs) are short non-coding RNAs which regulate biological processes and can be found in exosomes. Here we characterized the miRNA contents of exosomes derived from human neural stem cells (hNSCs). Our investigated hNSC line is a clonal, conditionally immortalized cell line, compliant with good manufacturing practice (GMP), and in clinical trials for stroke and critical limb ischemia in the UK (clinicaltrials.gov: {"type":"clinical-trial","attrs":{"text":"NCT01151124","term_id":"NCT01151124"}}NCT01151124, {"type":"clinical-trial","attrs":{"text":"NCT02117635","term_id":"NCT02117635"}}NCT02117635, and {"type":"clinical-trial","attrs":{"text":"NCT01916369","term_id":"NCT01916369"}}NCT01916369). By using next generation sequencing (NGS) technology we identified the presence of a variety of miRNAs in both exosomal and cellular preparations. Many of these miRNAs were enriched in exosomes indicating that cells specifically sort them for extracellular release. Although exosomes have been proven to contain miRNAs, the copy number quantification per exosome of a given miRNA remains unclear. Herein we quantified by real-time PCR a highly shuttled exosomal miRNA subtype (hsa-miR-1246) in order to assess its stoichiometry per exosome. Furthermore, we utilized an in vitro system to confirm its functional transfer by measuring the reduction in luciferase expression using a 3’ untranslated region dual luciferase reporter assay. In summary, NGS analysis allowed the identification of a unique set of hNSC derived exosomal miRNAs. Stoichiometry and functional transfer analysis of one of the most abundant identified miRNA, hsa-miR-1246, were measured to support biological relevance of exosomal miRNA delivery.     

SPOROS: A pipeline to analyze DISE/6mer seed toxicity

microRNAs (miRNAs) are (18-22nt long) noncoding short (s)RNAs that suppress gene expression by targeting the 3’ untranslated region of target mRNAs. This occurs through the seed sequence located in position 2-7/8 of the miRNA guide strand, once it is loaded into the RNA induced silencing complex (RISC). G-rich 6mer seed sequences can kill cells by targeting C-rich 6mer seed matches located in genes that are critical for cell survival. This results in induction of Death Induced by Survival gene Elimination (DISE), through a mechanism we have called 6mer seed toxicity. miRNAs are often quantified in cells by aligning the reads from small (sm)RNA sequencing to the genome. However, the analysis of any smRNA Seq data set for predicted 6mer seed toxicity requires an alternative workflow, solely based on the exact position 2–7 of any short (s)RNA that can enter the RISC. Therefore, we developed SPOROS, a semi-automated pipeline that produces multiple useful outputs to predict and compare 6mer seed toxicity of cellular sRNAs, regardless of their nature, between different samples. We provide two examples to illustrate the capabilities of SPOROS: Example one involves the analysis of RISC-bound sRNAs in a cancer cell line (either wild-type or two mutant lines unable to produce most miRNAs). Example two is based on a publicly available smRNA Seq data set from postmortem brains (either from normal or Alzheimer’s patients). Our methods (found at https://github.com/ebartom/SPOROS and at Code Ocean: https://doi.org/10.24433/CO.1732496.v1) are designed to be used to analyze a variety of smRNA Seq data in various normal and disease settings.     

Prioritizing and selecting likely novel miRNAs from NGS data

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at: www.ccb.uni-saarland.de/novomirank.     

TargetCompare: A web interface to compare simultaneous miRNAs targets

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs. We cross validated the tool in eight most highly expressed miRNAs in the antrum region of stomach. This helped to identify 43 potential genes that are target of at least six of the referred miRNAs. The developed tool aims to reduce the randomness and increase the chance of selecting strong candidate target genes and miRNAs responsible for playing important roles in the studied tissue.

Availability

http://lghm.ufpa.br/targetcompare     

Genome-Wide and Species-Wide In Silico Screening for Intragenic MicroRNAs in Human,Mouse and Chicken

MicroRNAs (miRNAs) are non-coding RNAs (ncRNAs) involved in regulation of gene expression. Intragenic miRNAs, especially those exhibiting a high degree of evolutionary conservation, have been shown to be coordinately regulated and/or expressed with their host genes, either with synergistic or antagonistic correlation patterns. However, the degree of cross-species conservation of miRNA/host gene co-location is not known and co-expression information is incomplete and fragmented among several studies. Using the genomic resources (miRBase and Ensembl) we performed a genome-wide in silico screening (GWISS) for miRNA/host gene pairs in three well-annotated vertebrate species: human, mouse, and chicken. Approximately half of currently annotated miRNA genes resided within host genes: 53.0% (849/1,600) in human, 48.8% (418/855) in mouse, and 42.0% (210/499) in chicken, which we present in a central publicly available Catalog of intragenic miRNAs (http://www.integratomics-time.com/miR-host/catalog). The miRNA genes resided within either protein-coding or ncRNA genes, which include long intergenic ncRNAs (lincRNAs) and small nucleolar RNAs (snoRNAs). Twenty-seven miRNA genes were found to be located within the same host genes in all three species and the data integration from literature and databases showed that most (26/27) have been found to be co-expressed. Particularly interesting are miRNA genes located within genes encoding for miRNA silencing machinery (DGCR8, DICER1, and SND1 in human and Cnot3, Gdcr8, Eif4e, Tnrc6b, and Xpo5 in mouse). We furthermore discuss a potential for phenotype misattribution of miRNA host gene polymorphism or gene modification studies due to possible collateral effects on miRNAs hosted within them. In conclusion, the catalog of intragenic miRNAs and identified 27 miRNA/host gene pairs with cross-species conserved co-location, co-expression, and potential co-regulation, provide excellent candidates for further functional annotation of intragenic miRNAs in health and disease.