miRò: a miRNA knowledge base

Machine Learning-Based Ensemble Feature Selection and Nested Cross-Validation for miRNA Biomarker Discovery in Usher Syndrome

Usher syndrome (USH) is a rare genetic disorder affecting vision, hearing, and balance. Identifying reliable biomarkers is crucial for early diagnosis and understanding disease mechanisms. MicroRNAs (miRNAs), key regulators of gene expression, hold promise as biomarkers for USH. This study aimed to identify a minimal subset of miRNAs that could serve as biomarkers to effectively differentiate USH from controls. We employed ensemble feature selection techniques to select the top miRNAs appearing in at least three algorithms. Machine learning models were trained and tested using this subset, followed by validation on an independent 10% sample. Our approach identified 10 key miRNAs as potential biomarkers for USH. To further validate their biological relevance, we conducted pathway analysis, which revealed significant pathways associated with USH. Furthermore, our approach achieved high classification performance, with an accuracy of 97.7%, sensitivity of 98%, specificity of 92.5%, F1 score of 95.8%, and an AUC of 97.5%. These findings demonstrate that combining ensemble feature selection with machine learning provides a robust strategy for miRNA biomarker discovery, advancing USH diagnosis and molecular understanding.

Comparative Analysis of Published Database Predicting MicroRNA Binding in 3'UTR of mRNA in Diverse Species

BACKGROUND

Micro-RNAs are endogenous non-coding RNA moieties of 22-27 nucleotides that play a crucial role in the regulation of various biological processes and make them useful prognostic and diagnostic biomarkers. Discovery and experimental validation of miRNA is a laborious and time-consuming process. For early prediction, multiple bioinformatics databases are available for miRNA target prediction; however, their utility can confuse amateur researchers in selecting the most appropriate tools for their study.

OBJECTIVE

This descriptive review aimed to analyse the usability of the existing database based on the following criteria: accessibility, efficiency, interpretability, updatability, and flexibility for miRNA target prediction of 3'UTR of mRNA in diverse species so that the researchers can utilize the database most appropriate to their research.

METHODS

A systematic literature search was performed in PubMed, Google Scholar and Scopus databases up to November 2022. ≥10,000 articles found online, including ⁓130 miRNA tools, which contain various information on miRNA. Out of them, 31 databases that provide information on validated 3'UTR miRNAs target databases were included and analysed in this review.

RESULTS

These miRNA database tools are being used in varied areas of biological research to select the most suitable miRNA for their experimental validation. These databases, updated until the year 2021, consist of miRNA-related data from humans, animals, mice, plants, viruses etc. They contain 525-29806351 data entries, and information from most databases is freely available on the online platform.

CONCLUSION

Reviewed databases provide significant information, but not all information is accurate or up-to-date. Therefore, Diana-TarBase and miRWalk are the most comprehensive and up-to-date databases.

MicroRNA-Target Identification: A Combinatorial In Silico Approach

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA-target prediction.

miRNA profiling of primate cervicovaginal lavage and extracellular vesicles reveals miR-186-5p as a potential antiretroviral factor in macrophages

Cervicovaginal secretions, or their components collected, are referred to as cervicovaginal lavage (CVL). CVL constituents have utility as biomarkers and play protective roles in wound healing and against HIV-1 infection. However, several components of cervicovaginal fluids are less well understood, such as extracellular RNAs and their carriers, for example, extracellular vesicles (EVs). EVs comprise a wide array of double-leaflet membrane extracellular particles and range in diameter from 30 nm to over one micron. The aim of this study was to determine whether differentially regulated CVL microRNAs (miRNAs) might influence retrovirus replication. To this end, we characterized EVs and miRNAs of primate CVL during the menstrual cycle and simian immunodeficiency virus (SIV) infection of macaques. EVs were enriched by stepped ultracentrifugation, and miRNA profiles were assessed with a medium-throughput stem-loop/hydrolysis probe qPCR platform. Whereas hormone cycling was abnormal in infected subjects, EV concentration correlated with progesterone concentration in uninfected subjects. miRNAs were present predominantly in the EV-depleted CVL supernatant. Only a small number of CVL miRNAs changed during the menstrual cycle or SIV infection, for example, miR-186-5p, which was depleted in retroviral infection. This miRNA inhibited HIV replication in infected macrophages in vitro. In silico target prediction and pathway enrichment analyses shed light on the probable functions of miR-186-5p in hindering HIV infections via immunoregulation, T-cell regulation, disruption of viral pathways, etc. These results provide further evidence for the potential of EVs and small RNAs as biomarkers or effectors of disease processes in the reproductive tract.

HMGA1-Regulating microRNAs Let-7a and miR-26a are Downregulated in Human Seminomas

Background: Recent studies have underlined HMGA protein’s key role in the onset of testicular germ cell tumors, where HMGA1 is differently expressed with respect to the state of differentiation, suggesting its fine regulation as master regulator in testicular tumorigenesis. Several studies have highlighted that the HMGA1 transcript is strictly regulated by a set of inhibitory microRNAs. Thus, the aim of this study is to test whether HMGA1 overexpression in human seminomas may be induced by the deregulation of miR-26a and Let-7a—two HMGA1-targeting microRNAs. Methods: HMGA1 mRNA and Let-7a and miR-26a levels were measured in a seminoma dataset available in the Cancer Genome Atlas database and confirmed in a subset of seminomas by qRT-PCR and western blot. A TCam-2 seminoma cell line was then transfected with Let-7a and miR-26a and tested for proliferation and motility abilities. Results: an inverse correlation was found between the expression of miR-26a and Let-7a and HMGA1 expression levels in seminomas samples, suggesting a critical role of these microRNAs in HMGA1 levels regulation. Accordingly, functional studies showed that miR-26a and Let-7a inhibited the proliferation, migration and invasion capabilities of the human seminoma derived cell line TCam-2. Conclusions: these data strongly support that the upregulation of HMGA1 levels occurring in seminoma is—at least in part—due to the downregulation of HMGA1-targeting microRNAs.

Interaction between miRNAs and signaling cascades of Wnt pathway in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL), a severe problem all over the world and represents around 25% of all total leukemia cases, is generating the need for novel targets against CLL. Wnt signaling cascade regulates cell proliferation, differentiation, and cell death processes. Thus, any alteration of the Wnt signaling pathway protein cascade might develop into various types of cancers, either by upregulation or downregulation of the Wnt signaling pathway protein components. In addition, it is reported that activation of the Wnt signaling pathway is associated with the transcriptional activation of microRNAs (miRNAs) by binding to its promoter region, suggesting feedback regulation. Considering the protein regulatory functions of various miRNAs, they can be approached therapeutically as modulatory targets for protein components of the Wnt signaling pathway. In this article, we have discussed the potential role of miRNAs in the regulation of Wnt signaling pathway proteins related to the pathogenesis of CLL via crosstalk between miRNAs and Wnt signaling pathway proteins. This might provide a clear insight into the Wnt protein regulatory function of various miRNAs and provide a better understanding of developing advanced and promising therapeutic approaches against CLL.

Exosomal lncRNAs and cancer: connecting the missing links

Motivation

Extracellular vesicles (EVs), including exosomes and microvesicles, are potent and clinically valuable tools for early diagnosis, prognosis and potentially the targeted treatment of cancer. The content of EVs is closely related to the type and status of the EV-secreting cell. Circulating exosomes are a source of stable RNAs including mRNAs, microRNAs and long non-coding RNAs (lncRNAs).

Results

This review outlines the links between EVs, lncRNAs and cancer. We highlight communication networks involving the tumor microenvironment, the immune system and metastasis. We show examples supporting the value of exosomal lncRNAs as cancer biomarkers and therapeutic targets. We demonstrate how a system biology approach can be used to model cell-cell communication via exosomal lncRNAs and to simulate effects of therapeutic interventions. In addition, we introduce algorithms and bioinformatics resources for the discovery of tumor-specific lncRNAs and tools that are applied to determine exosome content and lncRNA function. Finally, this review provides a comprehensive collection and guide to databases for exosomal lncRNAs.

Supplementary information

Supplementary data are available at Bioinformatics online.

mirDIP 4.1-integrative database of human microRNA target predictions

MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA-target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA-target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA-target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.

Differential expression of miRNAs related to angiogenesis and adipogenesis in subcutaneous fat of obese and nonobese women

To disclose the mechanisms surrounding obesity, we selected microRNAs (miRNAs) that target genes involved in adipogenesis, angiogenesis, and inflammation and compared their expression levels in the subcutaneous adipose tissue of 40 obese and nonobese women. Mature miRNAs were extracted from subcutaneous adipose tissue samples that were collected during surgery and quantified by real-time polymerase chain reaction. miR-16 was overexpressed in the nonobese group (n-expression ratio = - 151.1; P < 0.001). Furthermore, the expression levels of two other miRNAs were significantly correlated with waist circumference in nonobese women (miR-27b, r = 0.453; P = 0.027 and miR-424-5p, r = 0.502, P = 0.014). Central and total subcutaneous adipose tissue thicknesses were correlated with miR-424-5p levels (r = 0.506, P = 0.034 and r = 0.475, P = 0.046, respectively) in the nonobese group. In the obese group, miR-424-5p expression was correlated with body mass index (r = 0.582, P = 0.018). miR-16 and miR-424 have shown correlations with body-fat-mass-related parameters. Because these miRNAs have vascular endothelial growth factor (VEGF) and its receptors as target genes, they may be involved in the alterations of angiogenesis observed in obesity. In addition, higher levels of miR-27 and miR-424 were correlated with higher fat depot measurements in nonobese women. These results highlight the importance of miRNA expression in subcutaneous adipose tissue and encourage further investigation of miRNAs as prognostic markers.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

miRandb: A Metadatabase of Online Resources of miRNA and miRNA Targets

MicroRNA (miRNA) studies deliver numerous types of information including miRNA identification, sequence of miRNAs, target prediction, roles in diseases, and interactions in signaling pathways. Considering the different types of miRNA data, the number of miRNA databases has been increasing quickly. While resources have been planned to simplify miRNA analysis, scientists are facing the challenging task of choosing the most proper tool to retrieve related information. In this chapter, we introduce the use of miRandb, a resource that we have established to present an outline of different types of miRNA online resources and to simplify finding the right miRNA information that scientists need for their research. miRandb offers a user-friendly platform to find related information about any miRNA data among more than 188 present miRNA databases. miRandb has an easy procedure, and information can be retrieved by miRNA category resources. Each database comprises numerous kinds of information including database activity, description, main and unique features, organism, URL, publication, category, published year, citations per year, last update, and relative popularity. miRandb provides several opportunities and facilitates access to diverse classes of microRNA resources. miRandb is available at http://miRandb.ir .

Improving biocuration of microRNAs in diseases: a case study in idiopathic pulmonary fibrosis

MicroRNAs (miRNAs) are small and non-coding RNA molecules that inhibit gene expression posttranscriptionally. They play important roles in several biological processes, and in recent years there has been an interest in studying how they are related to the pathogenesis of diseases. Although there are already some databases that contain information for miRNAs and their relation with illnesses, their curation represents a significant challenge due to the amount of information that is being generated every day. In particular, respiratory diseases are poorly documented in databases, despite the fact that they are of increasing concern regarding morbidity, mortality and economic impacts. In this work, we present the results that we obtained in the BioCreative Interactive Track (IAT), using a semiautomatic approach for improving biocuration of miRNAs related to diseases. Our procedures will be useful to complement databases that contain this type of information. We adapted the OntoGene text mining pipeline and the ODIN curation system in a full-text corpus of scientific publications concerning one specific respiratory disease: idiopathic pulmonary fibrosis, the most common and aggressive of the idiopathic interstitial cases of pneumonia. We curated 823 miRNA text snippets and found a total of 246 miRNAs related to this disease based on our semiautomatic approach with the system OntoGene/ODIN. The biocuration throughput improved by a factor of 12 compared with traditional manual biocuration. A significant advantage of our semiautomatic pipeline is that it can be applied to obtain the miRNAs of all the respiratory diseases and offers the possibility to be used for other illnesses.

Database URL

http://odin.ccg.unam.mx/ODIN/bc2015-miRNA/.

MicroRNAs in melanoma development and resistance to target therapy

microRNAs constitute a complex class of pleiotropic post-transcriptional regulators of gene expression involved in the control of several physiologic and pathologic processes. Their mechanism of action is primarily based on the imperfect matching of a seed region located at the 5′ end of a 21-23 nt sequence with a partially complementary sequence located in the 3′ untranslated region of target mRNAs. This leads to inhibition of mRNA translation and eventually to its degradation. Individual miRNAs are capable of binding to several mRNAs and several miRNAs are capable of influencing the function of the same mRNAs. In recent years networks of miRNAs are emerging as capable of controlling key signaling pathways responsible for the growth and propagation of cancer cells. Furthermore several examples have been provided which highlight the involvement of miRNAs in the development of resistance to targeted drug therapies. In this review we provide an updated overview of the role of miRNAs in the development of melanoma and the identification of the main downstream pathways controlled by these miRNAs. Furthermore we discuss a group of miRNAs capable to influence through their respective up- or down-modulation the development of resistance to BRAF and MEK inhibitors.

Circulating microRNAs and Bioinformatics Tools to Discover Novel Diagnostic Biomarkers of Pediatric Diseases

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the post-transcriptional level. Current studies have shown that miRNAs are also present in extracellular spaces, packaged into various membrane-bound vesicles, or associated with RNA-binding proteins. Circulating miRNAs are highly stable and can act as intercellular messengers to affect many physiological processes. MicroRNAs circulating in body fluids have generated strong interest in their potential use as clinical biomarkers. In fact, their remarkable stability and the relative ease of detection make circulating miRNAs ideal tools for rapid and non-invasive diagnosis. This review summarizes recent insights about the origin, functions and diagnostic potential of extracellular miRNAs by especially focusing on pediatric diseases in order to explore the feasibility of alternative sampling sources for the development of non-invasive pediatric diagnostics. We will also discuss specific bioinformatics tools and databases for circulating miRNAs focused on the identification and discovery of novel diagnostic biomarkers of pediatric diseases.

Intestinal and Circulating MicroRNAs in Coeliac Disease

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene expression at the post-transcriptional level and play a key role in the pathogenesis of autoimmune and gastrointestinal diseases. Previous studies have revealed that miRNAs are dysregulated in intestinal biopsies of patients affected by coeliac disease (CD). Combined bioinformatics analyses of miRNA expression profiles and mRNA target genes as classified by Gene Ontology, are powerful tools to investigate the functional role of miRNAs in coeliac disease. However, little is still known about the function of circulating miRNAs, their expression level compared to tissue miRNAs, and whether the mechanisms of post-transcriptional regulation are the same of tissue miRNAs. In any case, if we assume that a cell-cell communication process has to occur, and that circulating miRNAs are delivered to recipient cells, we can derive useful information by performing target predictions. Interestingly, all of the mRNA targets of dysregulated miRNAs reported in the literature (i.e., miR-31-5p, miR-192, miR-194, miR-449a and miR-638) belong to several important biological processes, such as Wnt signaling, cell proliferation and differentiation, and adherens junction pathways. Although we think that these predictions have to be necessarily confirmed by “wet-lab” data, the miRNAs dysregulated during the development of CD could be potentially involved in the pathogenesis of coeliac disease and their correlation with circulating miRNAs offers new possibilities to use them as disease biomarkers.

FARNA: knowledgebase of inferred functions of non-coding RNA transcripts

Non-coding RNA (ncRNA) genes play a major role in control of heterogeneous cellular behavior. Yet, their functions are largely uncharacterized. Current available databases lack in-depth information of ncRNA functions across spectrum of various cells/tissues. Here, we present FARNA, a knowledgebase of inferred functions of 10,289 human ncRNA transcripts (2,734 microRNA and 7,555 long ncRNA) in 119 tissues and 177 primary cells of human. Since transcription factors (TFs) and TF co-factors (TcoFs) are crucial components of regulatory machinery for activation of gene transcription, cellular processes and diseases in which TFs and TcoFs are involved suggest functions of the transcripts they regulate. In FARNA, functions of a transcript are inferred from TFs and TcoFs whose genes co-express with the transcript controlled by these TFs and TcoFs in a considered cell/tissue. Transcripts were annotated using statistically enriched GO terms, pathways and diseases across cells/tissues based on guilt-by-association principle. Expression profiles across cells/tissues based on Cap Analysis of Gene Expression (CAGE) are provided. FARNA, having the most comprehensive function annotation of considered ncRNAs across widest spectrum of human cells/tissues, has a potential to greatly contribute to our understanding of ncRNA roles and their regulatory mechanisms in human. FARNA can be accessed at: http://cbrc.kaust.edu.sa/farna

Enhanced Expression of FRA16B using AT-Rich DNA Binding Chemicals in a Woman with Secondary Amenorrhoea

Fragile sites represent regions of chromatin that fail to compact during mitosis. Based on the prevalence and pattern of inheritance they are classified as rare fragile sites or common fragile sites. Rare fragile sites either occur spontaneously or can be induced by certain AT-specific binding chemicals namely distamycin, Hoechst 33258, Berenil and others. The most common of all rare autosomal fragile sites is fra(16)(q22) with a heterozygote frequency of ~5%. FRA16B results from an expansion of a 33 bp AT-rich Minisatellite repeat. These rare forms are usually heritable and segregate in a Mendelian fashion. The proband who was referred for secondary amenorrhoea, revealed 46,XX,fra(16)(q22.1)pat karyotype. Her father and younger sibling were also found to be carriers. This study aimed to delineate the genotypic and phenotypic features exhibited by these carriers and to evaluate FRA16B expression using AT-specific binding chemicals. The additives employed were Berenil, BrdU and Hoechst 33258. Berenil at a concentration of 150 µg/ml showed the highest expression of FRA16B. Although the recent breakthrough in molecular characterization of fragile sites plays a critical role in comprehending their association with various diseases, the physiological link between them and amenorrhoea is not clearly understood.

Polymorphisms in Non-coding RNA Genes and Their Targets Sites as Risk Factors of Sporadic Colorectal Cancer

Colorectal cancer (CRC) is a complex disease that develops as a consequence of both genetic and environmental risk factors in interplay with epigenetic mechanisms, such as microRNAs (miRNAs). CRC cases are predominantly sporadic in which the disease develops with no apparent hereditary syndrome. The last decade has seen the progress of genome-wide association studies (GWAS) that allowed the discovery of several genetic regions and variants associated with weak effects on sporadic CRC. Collectively these variants may enable a more accurate prediction of an individual's risk to the disease and its prognosis. However, the number of variants contributing to CRC is still not fully explored.SNPs in genes encoding the miRNA sequence or in 3'UTR regions of the corresponding binding sites may affect miRNA transcription, miRNA processing, and/or the fidelity of the miRNA-mRNA interaction. These variants could plausibly impact miRNA expression and target mRNA translation into proteins critical for cellular integrity, differentiation, and proliferation.In the present chapter, we describe the different aspects of variations related to miRNAs and other non-coding RNAs (ncRNAs) and evidence from studies investigating these candidate genetic alterations in support to their role in CRC development and progression.

Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm

Identification of the associations between microRNA molecules and human diseases from large-scale heterogeneous biological data is an important step for understanding the pathogenesis of diseases in microRNA level. However, experimental verification of microRNA-disease associations is expensive and time-consuming. To overcome the drawbacks of conventional experimental methods, we presented a combinatorial prioritization algorithm to predict the microRNA-disease associations. Importantly, our method can be used to predict microRNAs (diseases) associated with the diseases (microRNAs) without the known associated microRNAs (diseases). The predictive performance of our proposed approach was evaluated and verified by the internal cross-validations and external independent validations based on standard association datasets. The results demonstrate that our proposed method achieves the impressive performance for predicting the microRNA-disease association with the Area Under receiver operation characteristic Curve (AUC), 86.93%, which is indeed outperform the previous prediction methods. Particularly, we observed that the ensemble-based method by integrating the predictions of multiple algorithms can give more reliable and robust prediction than the single algorithm, with the AUC score improved to 92.26%. We applied our combinatorial prioritization algorithm to lung neoplasms and breast neoplasms, and revealed their top 30 microRNA candidates, which are in consistent with the published literatures and databases.

Single nucleotide polymorphisms within MicroRNAs, MicroRNA targets, and MicroRNA biogenesis genes and their impact on colorectal cancer survival

We have shown that single nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes, miRNA target genes, and miRNA biogenesis genes minimally contribute to colon cancer risk. It is possible that these SNPs alter survival. We analyzed 565 SNPs in or adjacent to microRNAs, target genes, or biogenesis genes, using 1,115 cases and 1,173 controls; 837 cases had survival information. We tested SNPs for associations with colorectal cancer (CRC) survival using a Cox proportional hazard model adjusting for age, study center, gender, AJCC disease stage, and MSI tumor status. Multiple comparison adjustments were made using the step-down Bonferroni correction. SNPs associated with survival (P_raw  < 0.05) also were assessed with messenger RNA (mRNA). Seven of the 565 SNPs analyzed were associated significantly with CRC survival after adjustment for multiple comparisons. Six of these increased risk of dying, and one, rs12140 (ADAMTS1) decreased risk of dying from CRC (HRR = 0.44, 95% CI (0.24, 0.83; P_Holm  = 0.011). Six SNPs altered colon cancer risk and five were associated with altered mRNA expression across genotypes. One SNP, rs2059691 (PRKRA), was associated with increased mRNA expression and worse survival, and one SNP, rs6598964 (LIN28A), decreased risk of developing colon cancer [OR = 0.77 95% CI (0.61, 0.98)] and increased risk of dying from CRC (HRR = 2.26 95% CI (1.52, 3.36). P_Holm  = 0.003). The few SNPs associated with CRC survival, colon cancer risk, or with mRNA expression, resided in genes that influence metastasis and angiogenesis. © 2017 Wiley Periodicals, Inc.

Computational and Experimental Identification of Tissue-Specific MicroRNA Targets

In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.

Targeting BTK through microRNA in chronic lymphocytic leukemia

Bruton's tyrosine kinase (BTK) is a critical mediator of survival in B-cell neoplasms. Although BTK inhibitors have transformed therapy in chronic lymphocytic leukemia (CLL), patients with high-risk genetics are at risk for relapse and have a poor prognosis. Identification of novel therapeutic strategies for this group of patients is an urgent unmet clinical need, and therapies that target BTK via alternative mechanisms may fill this niche. Herein, we identify a set of microRNAs (miRs) that target BTK in primary CLL cells and show that the histone deacetylase (HDAC) repressor complex is recruited to these miR promoters to silence their expression. Targeting the HDACs by using either RNA interference against HDAC1 in CLL or a small molecule inhibitor (HDACi) in CLL and mantle cell lymphoma restored the expression of the BTK-targeting miRs with loss of BTK protein and downstream signaling and consequent cell death. We have also made the novel and clinically relevant discovery that inhibition of HDAC induces the BTK-targeting miRs in ibrutinib-sensitive and resistant CLL to effectively reduce both wild-type and C481S-mutant BTK. This finding identifies a novel strategy that may be promising as a therapeutic modality to eliminate the C481S-mutant BTK clone that drives resistance to ibrutinib and provides the rationale for a combination strategy that includes ibrutinib to dually target BTK to suppress its prosurvival signaling.

miR-579-3p controls melanoma progression and resistance to target therapy

Therapy of melanoma patients harboring activating mutations in the BRAF (V-raf murine sarcoma viral oncogene homolog B1) oncogene with a combination of BRAF and MEK inhibitors is plagued by the development of drug resistance. Mutational events, as well as adaptive mechanisms, contribute to the development of drug resistance. In this context we uncover here the role of a miRNA, miR-579-3p. We first show that low expression of miR-579-3p is a negative prognostic factor correlating with poor survival. Expression levels of miR-579-3p decrease from nevi to stage III/IV melanoma samples and even further in cell lines resistant to BRAF/MEK inhibitors. Mechanistically, we demonstrate that miR-579-3p acts as an oncosuppressor by targeting the 3'UTR of two oncoproteins: BRAF and an E3 ubiquitin protein ligase, MDM2. Moreover miR-579-3p ectopic expression impairs the establishment of drug resistance in human melanoma cells. Finally, miR-579-3p is strongly down-regulated in matched tumor samples from patients before and after the development of resistance to targeted therapies.

'Atherothrombosis-associated microRNAs in Antiphospholipid syndrome and Systemic Lupus Erythematosus patients'

MicroRNAs markedly affect the immune system, and have a relevant role in CVD and autoimmune diseases. Yet, no study has analyzed their involvement in atherothrombosis related to APS and SLE patients. This study intended to: 1) identify and characterize microRNAs linked to CVD in APS and SLE; 2) assess the effects of specific autoantibodies. Six microRNAs, involved in atherothrombosis development, were quantified in purified leukocytes from 23 APS and 64 SLE patients, and 56 healthy donors. Levels of microRNAs in neutrophils were lower in APS and SLE than in healthy donors. Gene and protein expression of miRNA biogenesis-related molecules were also reduced. Accordingly, more than 75% of identified miRNAs by miRNA profiling were underexpressed. In monocytes, miR124a and -125a were low, while miR-146a and miR-155 appeared elevated. Altered microRNAs’ expression was linked to autoimmunity, thrombosis, early atherosclerosis, and oxidative stress in both pathologies. In vitro treatment of neutrophils, monocytes, and ECs with aPL-IgG or anti-dsDNA-IgG antibodies deregulated microRNAs expression, and decreased miRNA biogenesis-related proteins. Monocyte transfections with pre-miR-124a and/or -125a caused reduction in atherothrombosis-related target molecules. In conclusion, microRNA biogenesis, significantly altered in neutrophils of APS and SLE patients, is associated to their atherothrombotic status, further modulated by specific autoantibodies.

Web-based tools for microRNAs involved in human cancer

MicroRNAs (miRNAs/miRs) are a family of small, endogenous and evolutionarily-conserved non-coding RNAs that are involved in the regulation of several cellular and functional processes. miRNAs can act as oncogenes or tumor suppressors in all types of cancer, and could be used as prognostic and diagnostic biomarkers. Databases and computational algorithms are behind the majority of the research performed on miRNAs. These tools assemble and curate the relevant information on miRNAs and present it in a user-friendly manner. The current review presents 14 online databases that address every aspect of miRNA cancer research. Certain databases focus on miRNAs and a particular type of cancer, while others analyze the behavior of miRNAs in different malignancies at the same time. Additional databases allow researchers to search for mutations in miRNAs or their targets, and to review the naming history of a particular miRNA. All these databases are open-access, and are a valuable tool for those researchers working with these molecules, particularly those who lack access to an advanced computational infrastructure.

RNA expression signatures and posttranscriptional regulation in diabetic nephropathy

In the last decade, the integration of molecular approaches including transcriptome and miRNome analyses uncovered pathological mechanisms involved in the progression of diabetic nephropathy (DN). Using these techniques, molecular marker candidates [both messenger RNA (mRNA) and miRNA] have also been identified which may enable the characterization of patients at high risk for progression to end-stage renal disease. The results of such studies are urgently needed for a molecular definition of DN and for targeted treatment to improve patient care. The heterogeneity of kidney tissue and the minute amounts of RNA isolated from renal biopsies remain a challenge for omics-studies. Nevertheless, several studies have succeeded in the identification of RNA expression signatures in patients with diabetes and kidney disease. These studies show a reduced expression of growth factors such as VEGF and EGF, and an increased expression of matrix components and matrix-modulating enzymes, an activation of specific NF-κB modules, inflammatory pathways and the complement system. microRNAs are involved in the fine-tuning of mRNA abundance by binding to the 3' untranslated region of a target mRNA, which leads in most cases to translational repression or mRNA cleavage and a decrease in protein output. Here, we review the platforms used for miRNA expression profiling and ways to predict miRNA targets and functions. Several miRNAs have been shown to be involved in the pathogenesis of DN (e.g. miR-21, miR-192, miR-215, miR-216a, miR-29, let-7, miR-25, miR-93, etc.). Functional studies provide evidence that miRNAs are not only diagnostic tools but also represent potential therapeutic targets in DN.

Urinary microRNAs as potential biomarkers of pesticide exposure

MicroRNAs (miRNAs) are post-transcriptional regulators that silence messenger RNAs. Because miRNAs are stable at room temperature and long-lived, they have been proposed as molecular biomarkers to monitor disease and exposure status. While urinary miRNAs have been used clinically as potential diagnostic markers for kidney and bladder cancers and other diseases, their utility in non-clinical settings has yet to be fully developed. Our goal was to investigate the potential for urinary miRNAs to act as biomarkers of pesticide exposure and early biological response by identifying the miRNAs present in urine from 27 parent/child, farmworker/non-farmworker pairs (16FW/11NFW) collected during two agricultural seasons (thinning and post-harvest) and characterizing the between- and within-individual variability of these miRNA epigenetic regulators. MiRNAs were isolated from archived urine samples and identified using PCR arrays. Comparisons were made between age, households, season, and occupation. Of 384 miRNAs investigated, 297 (77%) were detectable in at least one sample. Seven miRNAs were detected in at least 50% of the samples, and one miRNA was present in 96% of the samples. Principal components and hierarchical clustering analyses indicate significant differences in miRNA profiles between farmworker and non-farmworker adults as well as between seasons. Six miRNAs were observed to be positively associated with farmworkers status during the post-harvest season. Expression of five of these miRNA trended towards a positive dose response relationship with organophosphate pesticide metabolites in farmworkers. These results suggest that miRNAs may be novel biomarkers of pesticide exposure and early biological response.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Bioinformatic tools for microRNA dissection

Recently, microRNAs (miRNAs) have emerged as important elements of gene regulatory networks. MiRNAs are endogenous single-stranded non-coding RNAs (~22-nt long) that regulate gene expression at the post-transcriptional level. Through pairing with mRNA, miRNAs can down-regulate gene expression by inhibiting translation or stimulating mRNA degradation. In some cases they can also up-regulate the expression of a target gene. MiRNAs influence a variety of cellular pathways that range from development to carcinogenesis. The involvement of miRNAs in several human diseases, particularly cancer, makes them potential diagnostic and prognostic biomarkers. Recent technological advances, especially high-throughput sequencing, have led to an exponential growth in the generation of miRNA-related data. A number of bioinformatic tools and databases have been devised to manage this growing body of data. We analyze 129 miRNA tools that are being used in diverse areas of miRNA research, to assist investigators in choosing the most appropriate tools for their needs.

deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data

Small non-coding RNAs (e.g. miRNAs) and long non-coding RNAs (e.g. lincRNAs and circRNAs) are emerging as key regulators of various cellular processes. However, only a very small fraction of these enigmatic RNAs have been well functionally characterized. In this study, we describe deepBase v2.0 (http://biocenter.sysu.edu.cn/deepBase/), an updated platform, to decode evolution, expression patterns and functions of diverse ncRNAs across 19 species. deepBase v2.0 has been updated to provide the most comprehensive collection of ncRNA-derived small RNAs generated from 588 sRNA-Seq datasets. Moreover, we developed a pipeline named lncSeeker to identify 176 680 high-confidence lncRNAs from 14 species. Temporal and spatial expression patterns of various ncRNAs were profiled. We identified approximately 24 280 primate-specific, 5193 rodent-specific lncRNAs, and 55 highly conserved lncRNA orthologs between human and zebrafish. We annotated 14 867 human circRNAs, 1260 of which are orthologous to mouse circRNAs. By combining expression profiles and functional genomic annotations, we developed lncFunction web-server to predict the function of lncRNAs based on protein-lncRNA co-expression networks. This study is expected to provide considerable resources to facilitate future experimental studies and to uncover ncRNA functions.

Effectiveness and Usability of Bioinformatics Tools to Analyze Pathways Associated with miRNA Expression

MiRNAs are small, nonprotein-coding RNA molecules involved in gene regulation. While bioinformatics help guide miRNA research, it is less clear how they perform when studying biological pathways. We used 13 criteria to evaluate effectiveness and usability of existing bioinformatics tools. We evaluated the performance of six bioinformatics tools with a cluster of 12 differentially expressed miRNAs in colorectal tumors and three additional sets of 12 miRNAs that are not part of a known cluster. MiRPath performed the best of all the tools in linking miRNAs, with 92% of all miRNAs linked as well as the highest based on our established criteria followed by Ingenuity (58% linked). Other tools, including Empirical Gene Ontology, miRó, miRMaid, and PhenomiR, were limited by their lack of available tutorials, lack of flexibility and interpretability, and/or difficulty using the tool. In summary, we observed a lack of standardization across bioinformatic tools and a general lack of specificity in terms of pathways identified between groups of miRNAs. Hopefully, this evaluation will help guide the development of new tools.

Circulating micrornas associated with glycemic impairment and progression in Asian Indians

AIMS/HYPOTHESIS

Asian Indians have a high incidence of type 2 diabetes, but factors associated with glycemic progression in this population are not understood. MicroRNAs are emerging as important mediators of glucose homeostasis and have not been previously studied in Asian Indians. We examined microRNA (miR) expression associated with glycemic impairment and progression in Asian Indians from the San Francisco Bay Area. We studied 128 Asian Indians age 45-84 years without known cardiovascular disease and not taking diabetes medications. Oral glucose tolerance tests were performed at baseline and after 2.5 years. We quantified circulating miRs from plasma collected during the enrollment visit using a flow cytometry-based assay.

RESULTS

Glycemic impairment was present in 57 % (n = 73) at baseline. MiR-191 was positively associated with glycemic impairment (odds ratio (OR) 1.7 (95 % CI 1.2, 2.4), p < 0.01). The prevalence of glycemic progression after 2.5 years was 24 % (n = 23). Six miRs were negatively associated with glycemic progression: miR-122 (OR 0.5 (0.2, 0.8), p < 0.01), miR-15a (OR 0.6 (0.4, 0.9), p < 0.01), miR-197 (OR 0.6 (0.4, 0.9), p < 0.01), miR-320a (OR 0.6 (0.4, 0.9), p < 0.01), miR-423 (OR 0.6 (0.4, 0.9), p < 0.01), and miR-486 (OR 0.5 (0.3, 0.8), p < 0.01). Further multivariate adjustment did not attenuate these results.

CONCLUSIONS/INTERPRETATION

This is the first study to investigate circulating miRs associated with glycemic status among this high-risk ethnic group. Individual miRs were significantly associated with both glycemic impairment and glycemic progression. Further studies are needed to determine whether miR (s) might be useful clinical biomarkers for incident T2D in the Asian Indian population.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

Circulating microRNA-320a and microRNA-486 predict thiazolidinedione response: Moving towards precision health for diabetes prevention

INTRODUCTION

The aims of this study were to compare microRNA (miR) expression between individuals with and without insulin resistance and to determine whether miRs predict response to thiazolidinedione treatment.

MATERIALS AND METHODS

In a sample of 93 healthy adults, insulin resistance was defined as steady state plasma glucose (SSPG)≥180 mg/dL and insulin sensitive as <120 mg/dL. Response to thiazolidinedione therapy was defined as ≥10% decrease in SSPG. We selected a panel of microRNAs based on prior evidence for a role in insulin or glucose metabolism. Fold change and Wilcoxon rank sum tests were calculated for the 25 miRs measured.

RESULTS

At baseline, 81% (n=75) of participants were insulin resistant. Five miRs were differentially expressed between the insulin resistant and sensitive groups: miR-193b (1.45 fold change (FC)), miR-22-3p (1.15 FC), miR-320a (1.36 FC), miR-375 (0.59 FC), and miR-486 (1.21 FC) (all p<0.05). In the subset who were insulin resistant at baseline and received thiazolidinediones (n=47), 77% (n=36) showed improved insulin sensitivity. Six miRs were differentially expressed between responders compared to non-responders: miR-20b-5p (1.20 FC), miR-21-5p, (0.92 FC), miR-214-3p (1.13 FC), miR-22-3p (1.14 FC), miR-320a (0.98 FC), and miR-486-5p (1.25 FC) (all p<0.05).

DISCUSSION

This study is the first to report miRs associated with response to a pharmacologic intervention for insulin resistance. MiR-320a and miR-486-5p identified responders to thiazolidinedione therapy among the insulin resistant group.

Principles of miRNA-mRNA interactions: beyond sequence complementarity

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression by altering the translation efficiency and/or stability of targeted mRNAs. In vertebrates, more than 50% of all protein-coding RNAs are assumed to be subject to miRNA-mediated control, but current high-throughput methods that reliably measure miRNA-mRNA interactions either require prior knowledge of target mRNAs or elaborate preparation procedures. Consequently, experimentally validated interactions are relatively rare. Furthermore, in silico prediction based on sequence complementarity of miRNAs and their corresponding target sites suffers from extremely high false positive rates. Apparently, sequence complementarity alone is often insufficient to reflect the complex post-transcriptional regulation of mRNAs by miRNAs, which is especially true for animals. Therefore, combined analysis of small non-coding and protein-coding RNAs is indispensable to better understand and predict the complex dynamics of miRNA-regulated gene expression. Single-nucleotide polymorphisms (SNPs) and alternative polyadenylation (APA) can affect miRNA binding of a given transcript from different individuals and tissues, and especially APA is currently emerging as a major factor that contributes to variations in miRNA-mRNA interplay in animals. In this review, we focus on the influence of APA and SNPs on miRNA-mediated gene regulation and discuss the computational approaches that take these mechanisms into account.

Analysis of Glioblastoma Patients' Plasma Revealed the Presence of MicroRNAs with a Prognostic Impact on Survival and Those of Viral Origin

Background

Glioblastoma multiforme (GBM) is among the most aggressive cancers with a poor prognosis in spite of a plethora of established diagnostic and prognostic biomarkers and treatment modalities. Therefore, the current goal is the detection of novel biomarkers, possibly detectable in the blood of GBM patients that may enable an early diagnosis and are potential therapeutic targets, leading to more efficient interventions.

Experimental Procedures

MicroRNA profiling of 734 human and human-associated viral miRNAs was performed on blood plasma samples from 16 healthy individuals and 16 patients with GBM, using the nCounter miRNA Expression Assay Kits.

Results

We identified 19 miRNAs with significantly different plasma levels in GBM patients, compared to the healthy individuals group with the difference limited by a factor of 2. Additionally, 11 viral miRNAs were found differentially expressed in plasma of GBM patients and 24 miRNA levels significantly correlated with the patients’ survival. Moreover, the overlap between the group of candidate miRNAs for diagnostic biomarkers and the group of miRNAs associated with survival, consisted of ten miRNAs, showing both diagnostic and prognostic potential. Among them, hsa miR 592 and hsa miR 514a 3p have not been previously described in GBM and represent novel candidates for selective biomarkers. The possible signalling, induced by the revealed miRNAs is discussed, including those of viral origin, and in particular those related to the impaired immune response in the progression of GBM.

Conclusion

The GBM burden is reflected in the alteration of the plasma miRNAs pattern, including viral miRNAs, representing the potential for future clinical application. Therefore proposed biomarker candidate miRNAs should be validated in a larger study of an independent cohort of patients.

miR2GO: comparative functional analysis for microRNAs

miR2GO is a web-based platform for comparative analyses of human miRNA functions. It includes two programs: miRmut2GO and miRpair2GO. miRmut2GO implements a knowledge-based method to assess the functional effects of genetic and somatic mutations in microRNA seed regions. The functional effects of a mutation are analysed by semantic comparison of enriched gene ontology (GO) annotations of the target gene sets for the wild-type and mutated alleles. miRpair2GO compares the functions of two different miRNAs based on the enriched functional annotations of their target gene sets.

AVAILABILITY AND IMPLEMENTATION

The miR2GO web server is available at http://compbio.uthsc.edu/miR2GO.

microRNAs and Personalized Medicine: Evaluating Their Potential as Cancer Biomarkers

microRNA deregulations are often, if not invariably, associated with human malignancies, including cancers. Though most of these deregulations may not be functionally implicated in tumorigenesis, the fact that microRNA expression can be monitored in a variety of human specimens, including biological fluids, supports studies aimed at characterizing microRNA signatures able to detect various cancers (diagnosis), predict their outcome (prognosis), monitor their treatment (theranosis), and adapt therapy to a patient (precision medicine). Here, we review and discuss pros and cons of microRNA-based approaches that can support their exploitation as cancer biomarkers.

MicroRNAs associated with exercise and diet: a systematic review

MicroRNAs are posttranscriptional regulators of gene expression. MicroRNAs reflect individual biologic adaptation to exposures in the environment. As such, measurement of circulating microRNAs presents an opportunity to evaluate biologic changes associated with behavioral interventions (i.e., exercise, diet) for weight loss. The aim of this study was to perform a systematic review of the literature to summarize what is known about circulating microRNAs associated with exercise, diet, and weight loss. We performed a systematic review of three scientific databases. We included studies reporting on circulating microRNAs associated with exercise, diet, and weight loss in humans. Of 1,219 studies identified in our comprehensive database search, 14 were selected for inclusion. Twelve reported on microRNAs associated with exercise, and two reported on microRNAs associated with diet and weight loss. The majority of studies used a quasiexperimental, cross-sectional design. There were numerous differences in the type and intensity of exercise and dietary interventions, the biologic source of microRNAs, and the methodological approaches used quantitate microRNAs. Data from several studies support an association between circulating microRNAs and exercise. The evidence for an association between circulating microRNAs and diet is weaker because of a small number of studies. Additional research is needed to validate previous observations using methodologically rigorous approaches to microRNA quantitation to determine the specific circulating microRNA signatures associated with behavioral approaches to weight loss. Future directions include longitudinal studies to determine if circulating microRNAs are predictive of response to behavioral interventions.

Computational Prediction of microRNA Targets

Computational prediction of microRNA (miRNA) targets is a fundamental step towards the characterization of miRNA function and the understanding of their role in disease. A single miRNA can regulate hundreds of different gene transcripts through partial sequence complementarity and a single gene may be regulated by several miRNAs acting cooperatively. The remarkable advances made in recent years have allowed the identification of key features for functional miRNA binding sites. A plethora of prediction tools are now available, but their accuracies remain rather poor, as miRNA target recognition has revealed itself to be a very complex and dynamic mechanism, still only partially understood.In this chapter, the principles of miRNA target prediction in animals are presented, together with the most up-to-date and effective computational approaches and tools available.

ReNE: a cytoscape plugin for regulatory network enhancement

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by ReNE is exportable in multiple formats for further analysis via third party applications. ReNE can be freely installed from the Cytoscape App Store (http://apps.cytoscape.org/apps/rene) and the full source code is freely available for download through a SVN repository accessible at http://www.sysbio.polito.it/tools_svn/BioInformatics/Rene/releases/. ReNE enhances a network by only integrating data from public repositories, without any inference or prediction. The reliability of the introduced interactions only depends on the reliability of the source data, which is out of control of ReNe developers.

Comprehensive reconstruction and visualization of non-coding regulatory networks in human

Research attention has been powered to understand the functional roles of non-coding RNAs (ncRNAs). Many studies have demonstrated their deregulation in cancer and other human disorders. ncRNAs are also present in extracellular human body fluids such as serum and plasma, giving them a great potential as non-invasive biomarkers. However, non-coding RNAs have been relatively recently discovered and a comprehensive database including all of them is still missing. Reconstructing and visualizing the network of ncRNAs interactions are important steps to understand their regulatory mechanism in complex systems. This work presents ncRNA-DB, a NoSQL database that integrates ncRNAs data interactions from a large number of well established on-line repositories. The interactions involve RNA, DNA, proteins, and diseases. ncRNA-DB is available at http://ncrnadb.scienze.univr.it/ncrnadb/. It is equipped with three interfaces: web based, command-line, and a Cytoscape app called ncINetView. By accessing only one resource, users can search for ncRNAs and their interactions, build a network annotated with all known ncRNAs and associated diseases, and use all visual and mining features available in Cytoscape.

The potential of microRNAs in personalized medicine against cancers

MicroRNAs orchestrate the expression of the genome and impact many, if not all, cellular processes. Their deregulation is thus often causative of human malignancies, including cancers. Numerous studies have implicated microRNAs in the different steps of tumorigenesis including initiation, progression, metastasis, and resistance to chemo/radiotherapies. Thus, microRNAs constitute appealing targets for novel anticancer therapeutic strategies aimed at restoring their expression or function. As microRNAs are present in a variety of human cancer types, microRNA profiles can be used as tumor-specific signatures to detect various cancers (diagnosis), to predict their outcome (prognosis), and to monitor their treatment (theranosis). In this review, we present the different aspects of microRNA biology that make them remarkable molecules in the emerging field of personalized medicine against cancers and provide several examples of their industrial exploitation.

MicroRNA-30a suppresses breast tumor growth and metastasis by targeting metadherin

Accumulating data have shown the involvement of microRNAs in cancerous processes as either oncogenes or tumor suppressor genes. Here, we established miR-30a as a tumor suppressor gene in breast cancer development and metastasis. Ectopic expression of miR-30a in breast cancer cell lines resulted in the suppression of cell growth and metastasis in vitro. Consistently, the xenograft mouse model also unveiled the suppressive effects of miR-30a on tumor growth and distal pulmonary metastasis. With dual luciferase reporter assay, we revealed that miR-30a could bind to the 3'-untranslated region of metadherin (MTDH) gene, thus exerting inhibitory effect on MTDH. Furthermore, we demonstrated that silence of MTDH could recapitulate the effects of miR-30a overexpression, while overexpression of MTDH could partially abrogate miR-30a-mediated suppression. Of significance, expression level of miR-30a was found to be significantly lower in primary breast cancer tissues than in the paired normal tissues. Further evaluation verified that miR-30a was negatively correlated with the extent of lymph node and lung metastasis in patients with breast cancer. Taken together, our findings indicated miR-30a inhibits breast cancer proliferation and metastasis by directly targeting MTDH, and miR-30a can serve as a prognostic marker for breast cancer. Manipulation of miR-30a may provide a promising therapeutic strategy for breast cancer treatment.

Common features of microRNA target prediction tools

The human genome encodes for over 1800 microRNAs (miRNAs), which are short non-coding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one miRNA to target multiple gene transcripts, miRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of miRNA targets is a critical initial step in identifying miRNA:mRNA target interactions for experimental validation. The available tools for miRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to miRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all miRNA target prediction tools, four main aspects of the miRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MiRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.