miRGate: a curated database of human, mouse and rat miRNA-mRNA targets

DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation

BACKGROUND

MicroRNA (miRNA) has been shown to play a key role in the occurrence and progression of diseases, making uncovering miRNA-disease associations vital for disease prevention and therapy. However, traditional laboratory methods for detecting these associations are slow, strenuous, expensive, and uncertain. Although numerous advanced algorithms have emerged, it is still a challenge to develop more effective methods to explore underlying miRNA-disease associations.

RESULTS

In the study, we designed a novel approach on the basis of deep autoencoder and combined feature representation (DAE-CFR) to predict possible miRNA-disease associations. We began by creating integrated similarity matrices of miRNAs and diseases, performing a logistic function transformation, balancing positive and negative samples with k-means clustering, and constructing training samples. Then, deep autoencoder was used to extract low-dimensional feature from two kinds of feature representations for miRNAs and diseases, namely, original association information-based and similarity information-based. Next, we combined the resulting features for each miRNA-disease pair and used a logistic regression (LR) classifier to infer all unknown miRNA-disease interactions. Under five and tenfold cross-validation (CV) frameworks, DAE-CFR not only outperformed six popular algorithms and nine classifiers, but also demonstrated superior performance on an additional dataset. Furthermore, case studies on three diseases (myocardial infarction, hypertension and stroke) confirmed the validity of DAE-CFR in practice.

CONCLUSIONS

DAE-CFR achieved outstanding performance in predicting miRNA-disease associations and can provide evidence to inform biological experiments and clinical therapy.

Circular RNA circ0001955 promotes cervical cancer tumorigenesis and metastasis via the miR-188-3p/NCAPG2 axis

BACKGROUND

Circular RNAs (circRNAs) are known to play a crucial role in a variety of malignancies. However, the precise role of circRNAs in cervical squamous cell carcinoma (CSCC) remains largely unknown.

METHODS

The expression of circ0001955 was determined by real-time quantitative PCR and fluorescence in situ hybridization. To examine the effects of circ0001955 on CSCC metastasis and growth, functional experiments were conducted in vitro and in vivo. Mechanistically, nucleocytoplasmic separation, dual luciferase reporter assay, RNA antisense purification experiments, and rescue experiments were performed to confirm the interaction between circ0001955, miR-188-3p, and NCAPG2 in CSCC.

RESULTS

Here, we demonstrated that a circRNA derived from the CSNK1G1 gene (circ0001955) is significantly upregulated in CSCC. The overexpression of circ0001955 promotes tumor proliferation and metastasis, whereas the knockdown of circ0001955 exerts the opposite effects. Mechanistically, circ0001955 competitively binds miR-188-3p and prevents miR-188-3p from reducing the levels of NCAPG2, activating the AKT/mTOR signaling pathway to induce epithelial mesenchymal transformation. Notably, the application of an inhibitor of mTOR significantly antagonized circ0001955-mediated CSCC tumorigenesis.

CONCLUSION

circ0001955 promotes CSCC tumorigenesis and metastasis via the miR-188-3p/NCAPG2 axis which would provide an opportunity to search new therapeutic targets for CSCC.

Major regulators of the multi-step metastatic process are potential therapeutic targets for breast cancer management

Metastasis is a multi-step process that leads to the dissemination of tumor cells to new sites and, consequently, to multi-organ neoplasia. Although most lethal breast cancer cases are related to metastasis occurrence, little is known about the dysregulation of each step, and clinicians still lack reliable therapeutic targets for metastasis impairment. To fill these gaps, we constructed and analyzed gene regulatory networks for each metastasis step (cell adhesion loss, epithelial-to-mesenchymal transition, and angiogenesis). Through topological analysis, we identified E2F1, EGR1, EZH2, JUN, TP63, and miR-200c-3p as general hub-regulators, FLI1 for cell-adhesion loss specifically, and TRIM28, TCF3, and miR-429 for angiogenesis. Applying the FANMOD algorithm, we identified 60 coherent feed-forward loops regulating metastasis-related genes associated with distant metastasis-free survival prediction. miR-139-5p, miR-200c-3p, miR-454-3p, and miR-1301-3p, among others, were the FFL's mediators. The expression of the regulators and mediators was observed to impact overall survival and to go along with metastasis occurrence. Lastly, we selected 12 key regulators and observed that they are potential therapeutic targets for canonical and candidate antineoplastics and immunomodulatory drugs, like trastuzumab, goserelin, and calcitriol. Our results highlight the relevance of miRNAs in mediating feed-forward loops and regulating the expression of metastasis-related genes. Altogether, our results contribute to understanding the multi-step metastasis complexity and identifying novel therapeutic targets and drugs for breast cancer management.

GKLOMLI: a link prediction model for inferring miRNA-lncRNA interactions by using Gaussian kernel-based method on network profile and linear optimization algorithm

BACKGROUND

The limited knowledge of miRNA-lncRNA interactions is considered as an obstruction of revealing the regulatory mechanism. Accumulating evidence on Human diseases indicates that the modulation of gene expression has a great relationship with the interactions between miRNAs and lncRNAs. However, such interaction validation via crosslinking-immunoprecipitation and high-throughput sequencing (CLIP-seq) experiments that inevitably costs too much money and time but with unsatisfactory results. Therefore, more and more computational prediction tools have been developed to offer many reliable candidates for a better design of further bio-experiments.

METHODS

In this work, we proposed a novel link prediction model based on Gaussian kernel-based method and linear optimization algorithm for inferring miRNA-lncRNA interactions (GKLOMLI). Given an observed miRNA-lncRNA interaction network, the Gaussian kernel-based method was employed to output two similarity matrixes of miRNAs and lncRNAs. Based on the integrated matrix combined with similarity matrixes and the observed interaction network, a linear optimization-based link prediction model was trained for inferring miRNA-lncRNA interactions.

RESULTS

To evaluate the performance of our proposed method, k-fold cross-validation (CV) and leave-one-out CV were implemented, in which each CV experiment was carried out 100 times on a training set generated randomly. The high area under the curves (AUCs) at 0.8623 ± 0.0027 (2-fold CV), 0.9053 ± 0.0017 (5-fold CV), 0.9151 ± 0.0013 (10-fold CV), and 0.9236 (LOO-CV), illustrated the precision and reliability of our proposed method.

CONCLUSION

GKLOMLI with high performance is anticipated to be used to reveal underlying interactions between miRNA and their target lncRNAs, and deciphers the potential mechanisms of the complex diseases.

2022 updates to the Rat Genome Database: a Findable, Accessible, Interoperable, and Reusable (FAIR) resource

The Rat Genome Database (RGD, https://rgd.mcw.edu) has evolved from simply a resource for rat genetic markers, maps, and genes, by adding multiple genomic data types and extensive disease and phenotype annotations and developing tools to effectively mine, analyze, and visualize the available data, to empower investigators in their hypothesis-driven research. Leveraging its robust and flexible infrastructure, RGD has added data for human and eight other model organisms (mouse, 13-lined ground squirrel, chinchilla, naked mole-rat, dog, pig, African green monkey/vervet, and bonobo) besides rat to enhance its translational aspect. This article presents an overview of the database with the most recent additions to RGD's genome, variant, and quantitative phenotype data. We also briefly introduce Virtual Comparative Map (VCMap), an updated tool that explores synteny between species as an improvement to RGD's suite of tools, followed by a discussion regarding the refinements to the existing PhenoMiner tool that assists researchers in finding and comparing quantitative data across rat strains. Collectively, RGD focuses on providing a continuously improving, consistent, and high-quality data resource for researchers while advancing data reproducibility and fulfilling Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.

Review of databases for experimentally validated human microRNA-mRNA interactions

MicroRNAs (miRs) may contribute to disease etiology by influencing gene expression. Numerous databases are available for miR target prediction and validation, but their functionality is varied, and outputs are not standardized. The purpose of this review is to identify and describe databases for cataloging validated miR targets. Using Tools4miRs and PubMed, we identified databases with experimentally validated targets, human data, and a focus on miR-messenger RNA (mRNA) interactions. Data were extracted about the number of times each database was cited, the number of miRs, the target genes, the interactions per database, experimental methodology and key features of each database. The search yielded 10 databases, which in order of most cited to least were: miRTarBase, starBase/The Encyclopedia of RNA Interactomes, DIANA-TarBase, miRWalk, miRecords, miRGator, miRSystem, miRGate, miRSel and targetHub. Findings from this review suggest that the information presented within miR target validation databases can be enhanced by adding features such as flexibility in performing queries in multiple ways, downloadable data, ongoing updates and integrating tools for further miR-mRNA target interaction analysis. This review is designed to aid researchers, especially those new to miR bioinformatics tools, in database selection and to offer considerations for future development and upkeep of validation tools. Database URL http://mirtarbase.cuhk.edu.cn/.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

Folic Acid and Vitamin B12 Prevent Deleterious Effects of Rotenone on Object Novelty Recognition Memory and Kynu Expression in an Animal Model of Parkinson's Disease

Parkinson's disease (PD) is characterized by a range of motor signs, but cognitive dysfunction is also observed. Supplementation with folic acid and vitamin B12 is expected to prevent cognitive impairment. To test this in PD, we promoted a lesion within the substantia nigra pars compacta of rats using the neurotoxin rotenone. In the sequence, the animals were supplemented with folic acid and vitamin B12 for 14 consecutive days and subjected to the object recognition test. We observed an impairment in object recognition memory after rotenone administration, which was prevented by supplementation (p < 0.01). Supplementation may adjust gene expression through efficient DNA methylation. To verify this, we measured the expression and methylation of the kynureninase gene (Kynu), whose product metabolizes neurotoxic metabolites often accumulated in PD as kynurenine. Supplementation prevented the decrease in Kynu expression induced by rotenone in the substantia nigra (p < 0.05), corroborating the behavioral data. No differences were observed concerning the methylation analysis of two CpG sites in the Kynu promoter. Instead, we suggest that folic acid and vitamin B12 increased global DNA methylation, reduced the expression of Kynu inhibitors, maintained Kynu-dependent pathway homeostasis, and prevented the memory impairment induced by rotenone. Our study raises the possibility of adjuvant therapy for PD with folic acid and vitamin B12.

Circulating microRNA203 and its target genes' role in psoriasis pathogenesis

Numerous microRNAs (miRNAs) have been found to have an aberrant expression in the peripheral blood or psoriasis patients' lesions. Psoriasis was shown to have the abnormal expression of microRNA-203 (miR-203). It is a skin-specific signal that governs cellular proliferation in a protein kinase C-dependent manner and is mostly generated by keratinocytes. This work evaluated the expression levels of the circulating miR-203 target genes SOCS3, SOCS6, TP63, TNF-, IL8, and IL24 in psoriasis patients. Using a relative quantitation PCR technique, we determined the expression levels of miR-203 and its target genes (SOCS3, SOCS6, TP63, TNF-, IL8, and IL24) in the plasma of 120 psoriatic patients and matched healthy controls. The disease characteristics of the patients were then correlated with the expression results. We also conducted numerous enrichment analyses for the diseases, functions, and pathways connected to the under-researched biomarkers. Compared to healthy controls, psoriatic patients had significantly increased levels of miR-203 expression; 7.1 (4.4–9.9). In contrast, psoriatic patients had significantly lower expression of all the examined genes compared to healthy controls. Regarding all the study biomarkers, the receiver operating characteristic (ROC) curve analysis demonstrated significant sensitivity and specificity for differentiating between psoriatic patients and healthy controls. According to the results of the disease matching score generated by miR-203 and its target genes, psoriasis was ranked first with a score of 4.45. The third-place finisher with a value of 3.98, it also demonstrated that miR-203 and its target genes are connected to various skin disorders. Our results show that miR-203 contributes to psoriasis pathogenesis not only locally in skin lesions but also in circulation, indicating that it may contribute to the systemic symptoms of the illness. MiR-203 overexpression in psoriasis suggests that miR-203 may be involved in an anti-inflammatory response because it targets both SOCS gene family members and pro-inflammatory cytokines.

miRNA therapeutics in precision oncology: a natural premium to nurture

The dynamic spectrum of microRNA (miRNA) has grown significantly over the years with its identification and exploration in cancer therapeutics and is currently identified as an important resource for innovative strategies due to its functional behavior for gene regulation and modulation of complex biological networks. The progression of cancer is the consequence of uncontrolled, nonsynchronous procedural faults in the biological system. Diversified and variable cellular response of cancerous cells has always raised challenges in effective cancer therapy. miRNAs, a class of non-coding RNAs (ncRNAs), are the natural genetic gift, responsible to preserve the homeostasis of cell to nurture. The unprecedented significance of endogenous miRNAs has exhibited promising therapeutic potential in cancer therapeutics. Currently, miRNA mimic miR-34, and an antimiR aimed against miR-122 has entered the clinical trials for cancer treatments. This review, highlights the recent breakthroughs, challenges, clinical trials, and advanced delivery vehicles in the administration of miRNA therapies for precision oncology.

miR-200a/b/-429 downregulation is a candidate biomarker of tumor radioresistance and independent of hypoxia in locally advanced cervical cancer

Many patients with locally advanced cervical cancer experience recurrence within the radiation field after chemoradiotherapy. Biomarkers of tumor radioresistance are required to identify patients in need of intensified treatment. Here, the biomarker potential of miR-200 family members was investigated in this disease. Also, involvement of tumor hypoxia in the radioresistance mechanism was determined, using a previously defined 6-gene hypoxia classifier. miR-200 expression was measured in pre-treatment tumor biopsies of an explorative cohort (n=90) and validation cohort 1 (n=110) by RNA sequencing. Publicly available miR-200 data of 79 patients were included for validation of prognostic significance. A score based on expression of the miR-200a/b/-429 (miR-200a, miR-200b and miR-429) cluster showed prognostic significance in all cohorts. The score was significant in multivariate analysis of central pelvic recurrence. No association with distant recurrence or hypoxia status was found. Potential miRNA target genes were identified from gene expression profiles and showed enrichment of genes in extracellular matrix organization and cell adhesion. miR-200a/b/-429 overexpression had a pronounced radiosensitizing effect in tumor xenografts, whereas the effect was minor in vitro. In conclusion, miR-200a/b/-429 downregulation is a candidate biomarker of central pelvic recurrence and seems to predict cell-adhesion-mediated tumor radioresistance independent of clinical markers and hypoxia.

PRKCE non-coding variants influence on transcription as well as translation of its gene

Untranslated regions of the gene play a crucial role in gene expression regulation at mRNA and protein levels. Mutations at UTRs impact expression by altering transcription factor binding, transcriptional/translational efficacy, miRNA-mediated gene regulation, mRNA secondary structure, ribosomal translocation, and stability. PKCε, a serine/threonine kinase, is aberrantly expressed in numerous diseases such as cardiovascular disorders, neurological disorders, and cancers; its probable cause is unknown. Therefore, in the current study, the influence of PRKCE 5'-and 3'UTR variants was explored for their potential impact on its transcription and translation through several bioinformatics approaches. UTR variants data was obtained through different databases and initially evaluated for their regulatory function. Variants with regulatory function were then studied for their effect on PRKCE binding with transcription factors (TF) and miRNAs, as well as their impact on mRNA secondary structure. Study outcomes indicated the regulatory function of 73 5'UTR and 17 3'UTR variants out of 376. 5'UTR variants introduced AP1 binding sites and promoted the PRKCE transcription. Four 3'UTR variants introduced a circular secondary structure, increasing PRKCE translational efficacy. A region in 5'UTR position 45,651,564 to 45,651,644 was found where variants readily influenced the miRNA-PRKCE mRNA binding. The study further highlighted a PKCε-regulated feedback loop mechanism that induces the activity of TFs, promoting its gene transcription. The study provides foundations for experimentation to understand these variants' role in diseases. These variants can also serve as the genetic markers for different diseases' diagnoses after validation at the cell and population levels.

The Connection between MicroRNAs and Oral Cancer Pathogenesis: Emerging Biomarkers in Oral Cancer Management

Oral cancer is a common human malignancy that still maintains an elevated mortality rate despite scientific progress. Tumorigenesis is driven by altered gene expression patterns of proto-oncogenes and tumor-suppressor genes. MicroRNAs, a class of short non-coding RNAs involved in gene regulation, seem to play important roles in oral cancer development, progression, and tumor microenvironment modulation. As properties of microRNAs render them stable in diverse liquid biopsies, together with their differential expression signature in cancer cells, these features place microRNAs at the top of promising biomarkers for diagnostic and prognostic values. In this review, we highlight eight expression levels and functions of the most relevant microRNAs involved in oral cancer development, progression, and microenvironment sustainability. Furthermore, we emphasize the potential of using these small RNA species as non-invasive biomarkers for the early detection of oral cancerous lesions. Conclusively, we highlight the perspectives and limitations of microRNAs as novel diagnostic tools, as well as therapeutic models.

The effects of exosomes derived from trabecular meshwork cells on Schlemm's canal endothelial cells

Trabecular meshwork (TM) and Schlemm’s canal (SC) are the main structures within the conventional outflow pathway, and TM cells and SC endothelial (SCE) cells are essential for controlling intraocular pressure. To examine the interaction between TM cells and SCE cells, we investigated whether exosomes contribute to intercellular communication. Additionally, TM cells in glaucoma acquire mesenchymal characteristics in response to transforming growth factor (TGF)-β2 and extracellular matrix proteins such as collagen type 1 (Col-1); these changes result in increased resistance of aqueous outflow. In this study, we stimulated TM cells with TGF-β2 and Col-1 and characterized the exosomal miRNAs (exomiRs) released in response to each stimulus. Isolated exosomes were rich in miRNAs, with downregulated miR-23a-5p and upregulated miR-3942-5p and miR-7515 levels following Col-1 or TGF-β2 stimulation. Next, a miRNA-mRNA network under TGF-β2 stimulation was constructed. There were no connections among the 3 miRNAs and predicted genes under Col-1 stimulation. GO and KEGG analyses revealed that the identified miRNAs were associated with various signaling pathways, including the inflammatory response. Interestingly, SCE cells treated with miR-7515 mimic showed increased VEGFA, VEGFR2, PECAM, and Tie2 expression. Ultrastructures typical of exosomes and positive staining for exosomal markers were observed in human TM cells. Our data showed that TM cells may communicate with SCE cells via exomiRs and that miR-7515 may be important for SCE cell reprogramming.

The Rat Genome Database (RGD) facilitates genomic and phenotypic data integration across multiple species for biomedical research

Model organism research is essential for discovering the mechanisms of human diseases by defining biologically meaningful gene to disease relationships. The Rat Genome Database (RGD, ( https://rgd.mcw.edu )) is a cross-species knowledgebase and the premier online resource for rat genetic and physiologic data. This rich resource is enhanced by the inclusion and integration of comparative data for human and mouse, as well as other human disease models including chinchilla, dog, bonobo, pig, 13-lined ground squirrel, green monkey, and naked mole-rat. Functional information has been added to records via the assignment of annotations based on sequence similarity to human, rat, and mouse genes. RGD has also imported well-supported cross-species data from external resources. To enable use of these data, RGD has developed a robust infrastructure of standardized ontologies, data formats, and disease- and species-centric portals, complemented with a suite of innovative tools for discovery and analysis. Using examples of single-gene and polygenic human diseases, we illustrate how data from multiple species can help to identify or confirm a gene as involved in a disease and to identify model organisms that can be studied to understand the pathophysiology of a gene or pathway. The ultimate aim of this report is to demonstrate the utility of RGD not only as the core resource for the rat research community but also as a source of bioinformatic tools to support a wider audience, empowering the search for appropriate models for human afflictions.

MicroRNA Regulates Early-Life Stress–Induced Depressive Behavior via Serotonin Signaling in a Sex-Dependent Manner in the Prefrontal Cortex of Rats

Background

The underlying neurobiology of early-life stress (ELS)-induced major depressive disorder is not clearly understood.

Methods

In this study, we used maternal separation (MS) as a rodent model of ELS and tested whether microRNAs (miRNAs) target serotonin genes to regulate ELS-induced depression-like behavior and whether this effect is sex dependent. We also examined whether environmental enrichment prevents susceptibility to depression- and anxiety-like behavior following MS and whether enrichment effects are mediated through serotonin genes and their corresponding miRNAs.

Results

MS decreased sucrose preference, which was reversed by enrichment. Males also exhibited greater changes in forced swim climbing and escape latency tests only following enrichment. Slc6a4 and Htr1a were upregulated in the frontal cortex following MS. In male MS rats, enrichment slightly reversed Htr1a expression to levels similar to control rats. miR-200a-3p and miR-322-5p, which target SLC6A4, were decreased by MS, but not significantly. An HTR1A-targeting miRNA, miR-320-5p, was also downregulated by MS and showed slight reversal by enrichment in male animals. miR-320-5p targeting of Htr1a was validated in vitro using SHSY neuroblastoma cell lines.

Conclusions

Altogether, this study implicates miRNA interaction with the serotonin pathway in ELS-induced susceptibility to depression-related reward deficits. Furthermore, because of its recovery by enrichment in males, miR-320 may represent a viable sex-specific target for reward-related deficits in major depressive disorder.

Molecular Profiling of Decompensated Cirrhosis by a Novel MicroRNA Signature

Noninvasive staging of decompensated cirrhosis is an unmet clinical need. The aims of this study were to characterize and validate a novel microRNA (miRNA) signature to stage decompensated cirrhosis and predict the portal pressure and systolic cardiac response to nonselective beta-blockers (NSBBs). Serum samples from patients with decompensated cirrhosis (n = 36) and healthy controls (n = 36) were tested for a novel signature of five miRNAs (miR-452-5p, miR-429, miR-885-5p, miR-181b-5p, and miR-122-5p) identified in the secretome of primary human hepatocytes and for three miRNAs (miR-192-5p, miR-34a-5p, and miR-29a-5p) previously discovered as biomarkers of chronic liver disease. All patients had ascites, which was refractory in 18 (50%), and were placed on NSBBs for variceal bleeding prophylaxis. In all patients, serum miRNAs, hepatic venous pressure gradient, and an echocardiogram study were performed before and 1 month after NSBBs. Patients with cirrhosis had lower serum levels of miR-429, miR-885-5p, miR-181b-5p, miR-122-5p, miR-192-5p, and miR-29a-5p (P < 0.05). Baseline serum miR-452-5p and miR-429 levels were lower in NSBB responders (P = 0.006). miR-181b-5p levels were greater in refractory ascites than in diuretic-sensitive ascites (P = 0.008) and correlated with serum creatinine. miR-452-5p and miR-885-5p were inversely correlated with baseline systemic vascular resistance (ρ = -0.46, P = 0.007; and ρ = -0.41, P = 0.01, respectively) and with diminished systolic contractility (ρ = -0.55, P = 0.02; and ρ = -0.55, P = 0.02, respectively) in patients with refractory ascites after NSBBs. Conclusion: Analysis of a miRNA signature in serum discriminates between patients with decompensated cirrhosis who show more severe systemic circulatory dysfunction and compromised systolic function after beta-blockade and those more likely to benefit from NSBBs.

Integrative approaches for analysis of mRNA and microRNA high-throughput data

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Review on tools and databases linking miRNA and its mRNA targetome.

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Databases show little overlap in miRNA targetome predictions suggesting strong contextual effects.

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Deconvolution and deep learning approaches are promising new approaches to improve miRNA targetome predictions.

Advanced sequencing technologies such as RNASeq provide the means for production of massive amounts of data, including transcriptome-wide expression levels of coding RNAs (mRNAs) and non-coding RNAs such as miRNAs, lncRNAs, piRNAs and many other RNA species. In silico analysis of datasets, representing only one RNA species is well established and a variety of tools and pipelines are available. However, attaining a more systematic view of how different players come together to regulate the expression of a gene or a group of genes requires a more intricate approach to data analysis. To fully understand complex transcriptional networks, datasets representing different RNA species need to be integrated. In this review, we will focus on miRNAs as key post-transcriptional regulators summarizing current computational approaches for miRNA:target gene prediction as well as new data-driven methods to tackle the problem of comprehensively and accurately dissecting miRNome-targetome interactions.

MicroRNAs Regulate Metabolic Phenotypes During Multicellular Tumor Spheroids Progression

During tumor progression, cancer cells rewire their metabolism to face their bioenergetic demands. In recent years, microRNAs (miRNAs) have emerged as regulatory elements that inhibit the translation and stability of crucial mRNAs, some of them causing direct metabolic alterations in cancer. In this study, we investigated the relationship between miRNAs and their targets mRNAs that control metabolism, and how this fine-tuned regulation is diversified depending on the tumor stage. To do so, we implemented a paired analysis of RNA-seq and small RNA-seq in a breast cancer cell line (MCF7). The cell line was cultured in multicellular tumor spheroid (MCTS) and monoculture conditions. For MCTS, we selected two-time points during their development to recapitulate a proliferative and quiescent stage and contrast their miRNA and mRNA expression patterns associated with metabolism. As a result, we identified a set of new direct putative regulatory interactions between miRNAs and metabolic mRNAs representative for proliferative and quiescent stages. Notably, our study allows us to suggest that miR-3143 regulates the carbon metabolism by targeting hexokinase-2. Also, we found that the overexpression of several miRNAs could directly overturn the expression of mRNAs that control glycerophospholipid and N-Glycan metabolism. While this set of miRNAs downregulates their expression in the quiescent stage, the same set is upregulated in proliferative stages. This last finding suggests an additional metabolic switch of the above mentioned metabolic pathways between the quiescent and proliferative stages. Our results contribute to a better understanding of how miRNAs modulate the metabolic landscape in breast cancer MCTS, which eventually will help to design new strategies to mitigate cancer phenotype.

Differential expression of microRNA miR-150-5p in IgA nephropathy as a potential mediator and marker of disease progression

Understanding why certain patients with IgA nephropathy progress to kidney failure while others maintain normal kidney function remains a major unanswered question. To help answer this, we performed miRNome profiling by next generation sequencing of kidney biopsies in order to identify microRNAs specifically associated with the risk of IgA nephropathy progression. Following sequencing and validation in independent cohorts, four microRNAs (-150-5p, -155-5p, -146b-5p, -135a-5p) were found to be differentially expressed in IgA nephropathy progressors compared to non-progressors, and patients with thin membrane nephropathy, lupus nephritis and membranous nephropathy, and correlated with estimated glomerular filtration rate, proteinuria, and the Oxford MEST-C scores (five histological features that are independent predictors of clinical outcome). Each individual microRNA increased the discrimination score of the International IgAN Prediction Tool, although due to the small number of samples the results did not reach statistical significance. miR-150-5p exhibited the largest amplitude of expression between cohorts and displayed the best discrimination between IgA nephropathy progressors and non-progressors by receiver operating curve analysis (AUC: 0.8). However, expression was similarly upregulated in kidneys with established fibrosis and low estimated glomerular filtration rates at the time of biopsy. Consistent with a more generic role in kidney fibrosis, in situ hybridization revealed that miR-150-5p was found in lymphoid infiltrates, and areas of proliferation and fibrosis consistent with the known drivers of progression. Thus, miR-150-5p may be a potential functional mediator of kidney fibrosis that may add value in predicting risk of progression in IgA nephropathy and other kidney diseases.

Computational Methods and Software Tools for Functional Analysis of miRNA Data

miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs.

Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical application

Noncoding RNAs (ncRNAs) are a large segment of the transcriptome that do not have apparent protein-coding roles, but they have been verified to play important roles in diverse biological processes, including disease pathogenesis. With the development of innovative technologies, an increasing number of novel ncRNAs have been uncovered; information about their prominent tissue-specific expression patterns, various interaction networks, and subcellular locations will undoubtedly enhance our understanding of their potential functions. Here, we summarized the principles and innovative methods for identifications of novel ncRNAs that have potential functional roles in cancer biology. Moreover, this review also provides alternative ncRNA databases based on high-throughput sequencing or experimental validation, and it briefly describes the current strategy for the clinical translation of cancer-associated ncRNAs to be used in diagnosis.

Prediction of the miRNA interactome - Established methods and upcoming perspectives

MicroRNAs (miRNAs) are well-studied small noncoding RNAs involved in post-transcriptional gene regulation in a wide range of organisms, including mammals. Their function is mediated by base pairing with their target RNAs. Although many features required for miRNA-mediated repression have been described, the identification of functional interactions is still challenging. In the last two decades, numerous Machine Learning (ML) models have been developed to predict their putative targets. In this review, we summarize the biological knowledge and the experimental data used to develop these ML models. Recently, Deep Neural Network-based models have also emerged in miRNA interaction modeling. We thus outline established and emerging models to give a perspective on the future developments needed to improve the identification of genes directly regulated by miRNAs.

Improving Bioinformatics Prediction of microRNA Targets by Ranks Aggregation

microRNAs are noncoding RNAs which downregulate a large number of target mRNAs and modulate cell activity. Despite continued progress, bioinformatics prediction of microRNA targets remains a challenge since available software still suffer from a lack of accuracy and sensitivity. Moreover, these tools show fairly inconsistent results from one another. Thus, in an attempt to circumvent these difficulties, we aggregated all human results of four important prediction algorithms (miRanda, PITA, SVmicrO, and TargetScan) showing additional characteristics in order to rerank them into a single list. Instead of deciding which prediction tool to use, our method clearly helps biologists getting the best microRNA target predictions from all aggregated databases. The resulting database is freely available through a webtool called miRabel¹ which can take either a list of miRNAs, genes, or signaling pathways as search inputs. Receiver operating characteristic curves and precision-recall curves analysis carried out using experimentally validated data and very large data sets show that miRabel significantly improves the prediction of miRNA targets compared to the four algorithms used separately. Moreover, using the same analytical methods, miRabel shows significantly better predictions than other popular algorithms such as MBSTAR, miRWalk, ExprTarget and miRMap. Interestingly, an F-score analysis revealed that miRabel also significantly improves the relevance of the top results. The aggregation of results from different databases is therefore a powerful and generalizable approach to many other species to improve miRNA target predictions. Thus, miRabel is an efficient tool to guide biologists in their search for miRNA targets and integrate them into a biological context.

The Regulatory Roles of Non-coding RNAs in Angiogenesis and Neovascularization From an Epigenetic Perspective

Angiogenesis is a crucial process for organ morphogenesis and growth during development, and it is especially relevant during the repair of wounded tissue in adults. It is coordinated by an equilibrium of pro- and anti-angiogenic factors; nevertheless, when affected, it promotes several diseases. Lately, a growing body of evidence is indicating that non-coding RNAs (ncRNAs), such as miRNAs, circRNAs, and lncRNAs, play critical roles in angiogenesis. These ncRNAs can act in cis or trans and alter gene transcription by several mechanisms including epigenetic processes. In the following pages, we will discuss the functions of ncRNAs in the regulation of angiogenesis and neovascularization, both in normal and disease contexts, from an epigenetic perspective. Additionally, we will describe the contribution of Next-Generation Sequencing (NGS) techniques to the discovery and understanding of the role of ncRNAs in angiogenesis.

Exploratory study on microRNA profiles from plasma-derived extracellular vesicles in Alzheimer's disease and dementia with Lewy bodies

Background

Because of the increasing life expectancy in our society, aging-related neurodegenerative disorders are one of the main issues in global health. Most of these diseases are characterized by the deposition of misfolded proteins and a progressive cognitive decline. Among these diseases, Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) are the most common types of degenerative dementia. Although both show specific features, an important neuropathological and clinical overlap between them hampers their correct diagnosis. In this work, we identified molecular biomarkers aiming to improve the misdiagnosis between both diseases.

Methods

Plasma extracellular vesicles (EVs) -from DLB, AD and healthy controls- were isolated using size-exclusion chromatography (SEC) and characterized by flow cytometry, Nanoparticle Tracking Analysis (NTA) and cryo-electron microscopy. Next Generation Sequencing (NGS) and related bibliographic search was performed and a selected group of EV-associated microRNAs (miRNAs) was analysed by qPCR.

Results

Results uncovered two miRNAs (hsa-miR-451a and hsa-miR-21-5p) significantly down-regulated in AD samples respect to DLB patients, and a set of four miRNAs (hsa-miR-23a-3p, hsa-miR-126-3p, hsa-let-7i-5p, and hsa-miR-151a-3p) significantly decreased in AD respect to controls. The two miRNAs showing decreased expression in AD in comparison to DLB provided area under the curve (AUC) values of 0.9 in ROC curve analysis, thus suggesting their possible use as biomarkers to discriminate between both diseases. Target gene analysis of these miRNAs using prediction online tools showed accumulation of phosphorylation enzymes, presence of proteasome-related proteins and genes involved in cell death among others.

Conclusion

Our data suggest that plasma-EV associated miRNAs may reflect a differential profile for a given dementia-related disorder which, once validated in larger cohorts of patients, could help to improve the differential diagnosis of DLB versus AD.

Electronic supplementary material

The online version of this article (10.1186/s40035-019-0169-5) contains supplementary material, which is available to authorized users.

miR-1, miR-499 and miR-208 are sensitive markers to diagnose sudden death due to early acute myocardial infarction

MicroRNAs (miRNAs) are strongly up-regulated under pathological stress and in a wide range of diseases. In recent years, miRNAs are under investigation for their potential use as biomarkers in cardiovascular diseases. We investigate whether specific cardio-miRNAs are overexpressed in heart samples from subjects deceased for acute myocardial infarction (AMI) or sudden cardiac death (SCD), and whether miRNA could help differentiate between them. Forty four cases of death due to cardiovascular disease were selected, respectively, 19 cases categorized as AMI and 25 as SCD. Eighteen cases of traumatic death without pathological cardiac involvement were selected as control. Immunohistochemical investigation was performed for CD15, IL-15, Cx43, MCP-1, tryptase, troponin C and troponin I. Reverse transcription and quantitative real-time PCR were performed for miR-1, miR-133, miR-208 and miR-499. In AMI group, stronger immunoreaction for the CD15, IL-15 and MCP-1 antibodies was detectable compared with SCD and control. Cx43 showed a negative reaction with respect to the other groups. Real-time PCR results showed a down-regulation of all miRNAs in the AMI group compared with SCD and control. The selected miRNAs presented high accuracy in discriminating SCD from AMI (miR-1 and miR-499) and AMI from control (miR-208) representing a potential aid for both clinicians and pathologists for differential diagnosis.

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/.

Comprehensive Overview and Assessment of microRNA Target Prediction Tools in Homo sapiens and Drosophila melanogaster

Background:

MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression at the post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and blocking translation process. Many dysfunctions of these small regulatory molecules have been linked to the development and progression of several diseases. Therefore, it is necessary to reliably predict potential miRNA targets.

Objective:

A large number of computational prediction tools have been developed which provide a faster way to find putative miRNA targets, but at the same time, their results are often inconsistent. Hence, finding a reliable, functional miRNA target is still a challenging task. Also, each tool is equipped with different algorithms, and it is difficult for the biologists to know which tool is the best choice for their study.

Methods:

We analyzed eleven miRNA target predictors on Drosophila melanogaster and Homo sapiens by applying significant empirical methods to evaluate and assess their accuracy and performance using experimentally validated high confident mature miRNAs and their targets. In addition, this paper also describes miRNA target prediction algorithms, and discusses common features of frequently used target prediction tools.

Results:

The results show that MicroT, microRNA and CoMir are the best performing tool on Drosopihla melanogaster; while TargetScan and miRmap perform well for Homo sapiens. The predicted results of each tool were combined in order to improve the performance in both the datasets, but any significant improvement is not observed in terms of true positives.

Conclusion:

The currently available miRNA target prediction tools greatly suffer from a large number of false positives. Therefore, computational prediction of significant targets with high statistical confidence is still an open challenge.

Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome

microRNAs are evolutionarily conserved, endogenously produced, noncoding RNAs (ncRNAs) of approximately 19-24 nucleotides (nts) in length known to exhibit gene silencing of complementary target sequence. Their deregulated expression is reported in various disease conditions and thus has therapeutic implications. In the last decade, various computational resources are published in this field. In this chapter, we have reviewed bioinformatics resources, i.e., miRNA-centered databases, algorithms, and tools to predict miRNA targets. First section has enlisted more than 75 databases, which mainly covers information regarding miRNA registries, targets, disease associations, differential expression, interactions with other noncoding RNAs, and all-in-one resources. In the algorithms section, we have compiled about 140 algorithms from eight subcategories, viz. for the prediction of precursor (pre-) and mature miRNAs. These algorithms are developed on various sequence, structure, and thermodynamic based features incorporated into different machine learning techniques (MLTs). In addition, computational identification of miRNAs from high-throughput next generation sequencing (NGS) data and their variants, viz. isomiRs, differential expression, miR-SNPs, and functional annotation, are discussed. Prediction and analysis of miRNAs and their associated targets are also evaluated under miR-targets section providing knowledge regarding novel miRNA targets and complex host-pathogen interactions. In conclusion, we have provided comprehensive review of in silico resources published in miRNA research to help scientific community be updated and choose the appropriate tool according to their needs.

A panel of noncoding RNAs in non-small-cell lung cancer

Non-small-lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC could pave the way for effective therapies. Analysis of molecular genetic biomarkers in biological fluids has been proposed as a useful tool for cancer diagnosis. Here, we aimed to develop a panel of noncoding RNAs (ncRNAs) in sputum for NSCLC early detection. Expression of 11 ncRNAs were analyzed by real-time polymerase chain reaction in sputum samples of 30 NSCLC patients and 30 sex- and age-matched cancer-free controls. Stability of endogenous microRNAs (miRNAs) in sputum was evaluated after 3 and 6 days at 4°C, 6 months, and 1 year at -80°C. Nine ncRNAs showed significant differences of their expression in sputum between NSCLC patients and controls. A logistic regression model with the best prediction was built based on miR-145, miR-126, and miR-7. The composite of the three miRNAs produced 90% sensitivity and specificity in distinguishing NSCLC patients from the controls. Results indicate that miRNAs could be useful biomarkers based on their stability under various storage conditions and maintain differential changes between cancer and control groups. Moreover, measurement of miRNAs in sputum could be a noninvasive approach for detection of lung cancer.

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.

Integrated analysis of microRNA and mRNA expression profiles in splenomegaly induced by non-cirrhotic portal hypertension in rats

The spleen plays an important role in the immune and hematopoietic systems. Splenomegaly is a frequent consequence of portal hypertension, but the underlying molecular and cellular mechanisms remain to be fully elucidated. In this study, we have performed a whole-genome microarray analysis combined with histological examination in enlarged spleens isolated from rats with partial portal vein ligation (PPVL) surgery to provide comprehensive profiles of microRNAs and their target mRNAs with a focus on their potential biological functions. A total of 964 mRNAs and 30 microRNAs showed significant differential expression in the spleens of PPVL rats compared to rats undergoing a sham procedure. Twenty-two down-regulated microRNAs were associated with significantly increased genes highly involved in fibrogenic activity and cell proliferation/migration (e.g., Ctgf, Serpine1, Col1a1). Consistently, histological analyses demonstrated increased splenic fibrosis and cell proliferation in the spleens of PPVL rats. Eight up-regulated microRNAs were associated with suppression of genes that are related to interferon-mediated antiviral activity in innate immune responses (e.g., Irf7, Dhx58). In conclusion, we determined a specific microRNA-mRNA network potentially implicated in the tissue fibrosis and cell proliferation in portal hypertension-induced splenomegaly. Our findings provide new insight into the mechanisms for regulation of spleen structure and function.

Motif scraper: a cross-platform, open-source tool for identifying degenerate nucleotide motif matches in FASTA files

Summary

Many genomic features are defined not by exact sequence matches, but by degenerate nucleotide motifs that represent multiple compatible matches. While there are databases cataloging genomic features, such as the location of transcription factor motifs, for commonly used model species, identifying the locations of novel motifs, known motifs in non-model genomes, or known motifs in personal whole-genomes is difficult. I designed motif scraper to overcome this limitation, allowing for efficient, multiprocessor motif searches in any FASTA file.

Availability and implementation

The motif scraper package (MIT license) is available via PyPI, and the Python source is available on GitHub at https://github.com/RobersonLab/motif_scraper.

NACC1, as a Target of MicroRNA-331-3p, Regulates Cell Proliferation in Urothelial Carcinoma Cells

The nucleus accumbens-associated protein 1 (NACC1) is a transcription factor constitutively expressed in the urothelium, where it regulates cell growth, senescence, autophagy, and epithelial-mesenchymal transition. microRNA (miRNA) constitutes a class of small non-coding RNAs which are involved in cell proliferation, differentiation, and progression of tumors. miRNAs and their target molecules are utilized for molecular diagnosis of urothelial carcinoma. NACC1 is one of several putative target molecules of miR-331-3p, and is associated with cell proliferation in cancers such as prostate and cervical cancer. Functional experiments involving miR-331-3p and its target molecule NACC1 were conducted using the urothelial carcinoma (UC) cell lines, T24, UMUC6, and KU7. Furthermore, quantitative reverse transcription polymerase chain reaction and immunostaining were performed to evaluate the expression of NACC1 in UC derived from transurethral resection of bladder tumor (TUR-Bt) specimens. The methane thiosulfonate (MTS) assay revealed that cell proliferation was significantly reduced after transient transfection of miR-331-3p precursor and/or NACC1 siRNA in UC cells. Cell senescence via cell cycle arrest at the G1 phase was induced by NACC1 inhibition. On the other hand, suppression of NACC1 induced cell migration and invasion abilities. Immunohistochemical analysis of TUR-Bt specimens revealed that over 70% of UC cells presented strongly positive results for NACC1. In contrast, normal urothelial cells were weakly positive for NACC1. It was also found that NACC1 expression was lower in invasive UC cells than in non-invasive UC cells. Loss of NACC1 induced vessel invasion in invasive UC tissues. The present results indicate that NACC1 regulated by miR-331-3p contributes to cell proliferation, and is involved in cell migration and invasion. This suggests that NACC1 can serve as a potential target molecule for the prediction and prognosis of UC, and can contribute to effective treatment strategies.

Estradiol-mediated regulation of hepatic iNOS in obese rats: Impact of Src, ERK1/2, AMPKα, and miR-221

PURPOSE

This study aimed to investigate in vivo effects of estradiol on the regulation of hepatic inducible nitric oxide synthase (iNOS) expression in the high fat (HF) diet-induced obesity. Also, we aimed to investigate whether activation of the extracellular signal-regulated kinase (ERK1/2), adenosine monophosphate-activated protein kinase (AMPK), Src kinase, and miR-221 is involved in estradiol-mediated regulation of iNOS in the liver of obese male Wistar rats. Male Wistar rats were fed a standard laboratory diet or a HF diet for 10 weeks. Half of HF rats were treated with estradiol intraperitoneally (40 μg/kg), whereas the other half were placebo-treated 24 H before euthanasia. Results show that estradiol treatment of HF rats decreased hepatic iNOS mRNA (P < 0.05) and protein expression (P < 0.01), the protein levels of p65 subunit of nuclear factor κB (P < 0.05) and ERα (P < 0.05), ERK1/2 phosphorylation (P < 0.001), and ERα/Src kinase association (P < 0.05). By contrast, hepatic Src protein level (P < 0.05), AMPKα phosphorylation (P < 0.05), and miR-221 expression (P < 0.05) were increased in HF rats after estradiol treatment. Our results indicate that estradiol in vivo regulates hepatic iNOS expression in obese rats via molecular mechanisms involving ERK1/2, AMPK, Src, and miR-221 signaling.

RNA-Seq reveals the existence of a CDKN1C-E2F1-TP53 axis that is altered in human T-cell lymphoblastic lymphomas

Background

Precursor T-cell lymphoblastic lymphomas (T-LBL) are rare aggressive hematological malignancies that mainly develop in children. As in other cancers, the loss of cell cycle control plays a prominent role in the pathogenesis in these malignancies that is primarily attributed to loss of CDKN2A (encoding protein p16INK4A). However, the impact of the deregulation of other genes such as CDKN1C, E2F1, and TP53 remains to be clarified. Interestingly, experiments in mouse models have proven that conditional T-cell specific deletion of Cdkn1c gene may induce a differentiation block at the DN3 to DN4 transition, and that the loss of this gene in the absence of Tp53 led to aggressive thymic lymphomas.

Results

In this manuscript, we demonstrated that the simultaneous deregulation of CDKN1C, E2F1, and TP53 genes by epigenetic mechanisms and/or the deregulation of specific microRNAs, together with additional impairing of TP53 function by the expression of dominant-negative isoforms are common features in primary human T-LBLs.

Conclusions

Previous experimental work in mice revealed that T-cell specific deletion of Cdkn1c accelerates lymphomagenesis in the absence of Tp53. If, as expected, the consequences of the deregulation of the CDKN1C-E2F1-TP53 axis were the same as those experimentally demonstrated in mouse models, the disruption of this axis might be useful to predict tumor aggressiveness, and to provide the basis towards the development of potential therapeutic strategiesin human T-LBL.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4304-y) contains supplementary material, which is available to authorized users.

Understanding Neurodevelopmental Disorders: The Promise of Regulatory Variation in the 3'UTRome

Neurodevelopmental disorders have a strong genetic component, but despite widespread efforts, the specific genetic factors underlying these disorders remain undefined for a large proportion of affected individuals. Given the accessibility of exome sequencing, this problem has thus far been addressed from a protein-centric standpoint; however, protein-coding regions only make up ∼1% to 2% of the human genome. With the advent of whole genome sequencing we are in the midst of a paradigm shift as it is now possible to interrogate the entire sequence of the human genome (coding and noncoding) to fill in the missing heritability of complex disorders. These new technologies bring new challenges, as the number of noncoding variants identified per individual can be overwhelming, making it prudent to focus on noncoding regions of known function, for which the effects of variation can be predicted and directly tested to assess pathogenicity. The 3'UTRome is a region of the noncoding genome that perfectly fulfills these criteria and is of high interest when searching for pathogenic variation related to complex neurodevelopmental disorders. Herein, we review the regulatory roles of the 3'UTRome as binding sites for microRNAs or RNA binding proteins, or during alternative polyadenylation. We detail existing evidence that these regions contribute to neurodevelopmental disorders and outline strategies for identification and validation of novel putatively pathogenic variation in these regions. This evidence suggests that studying the 3'UTRome will lead to the identification of new risk factors, new candidate disease genes, and a better understanding of the molecular mechanisms contributing to neurodevelopmental disorders.

Transcriptome analysis reveals non-identical microRNA profiles between arterial and venous plasma

Circulating microRNAs presented in venous plasma have been demonstrated as powerful biomarkers for the complex diseases like cancer. Nevertheless, those presented in arterial plasma remained largely unexplored. Here, using microarray technique, we compared microRNA expression profiles of the matched arterial and venous plasma samples from the same male rats. Though the microRNA profiles were largely similar, we identified 24 differentially expressed microRNAs, including 10 arterial highly expressed microRNAs and 14 venous highly expressed microRNAs. The differentially expressed microRNAs were validated by qRT-PCR. Computational analysis of these microRNAs and their targets indicated that arterial highly expressed microRNAs were overrepresented for functional terms like hematopoiesis and diseases like Crohn's Disease and leukemia; while venous highly expressed microRNAs were enriched for cell differentiation function, and diseases like distal myopathies and heart failure. Our analysis also suggested significant correlations between plasma microRNA expression and tissue microRNA expression. Four arterial highly expressed microRNAs also showed enriched expression in specific tissues and would be novel biomarker candidates.

MicroRNA deregulation in triple negative breast cancer reveals a role of miR-498 in regulating BRCA1 expression

Emerging evidence suggests that BRCA1 pathway contributes to the behavior of sporadic triple negative breast cancer (TNBC), but little is known about the mechanisms underlying this association. Considering the central role that microRNAs (miRNAs) play in gene expression regulation, the aim of this study was to identify miRNAs specifically deregulated in TNBC and investigate their involvement in BRCA1 regulation. Using locked nucleic acid (LNA)-based microarrays, expression levels of 1919 miRNAs were measured in paraffin-embedded tissues from 122 breast tumors and 11 healthy breast tissue samples. Differential miRNA expression was explored among the main subtypes of breast cancer, and 105 miRNAs were identified as specific for triple negative tumors. In silico prediction revealed that miR-498 and miR-187-5p target BRCA1, and these results were confirmed by luciferase reporter assay. While miR-187-5p was found overexpressed in a luminal B cell line, miR-498 was highly expressed in a triple negative cell line, Hs578T, and its expression was negatively correlated with the levels of BRCA1. We functionally demonstrated that miR-498 inhibits BRCA1 in breast cancer cell lines, and showed that inhibition of miR-498 led to reduced proliferation in the triple negative cell line Hs578T. Our results indicate that miR-498 regulates BRCA1 expression in breast cancer and its overexpression could contribute to the pathogenesis of sporadic TNBC via BRCA1 downregulation.

MicroRNA-target cross-talks: Key players in glioblastoma multiforme

The role of microRNAs in brain cancer is still naive. Some act as oncogene and others as tumor suppressors. Discovery of efficient biomarkers is mandatory to debate that aggressive disease. Bioinformatically selected microRNAs and their targets were investigated to evaluate their putative signature as diagnostic and prognostic biomarkers in primary glioblastoma multiforme. Expression of a panel of seven microRNAs (hsa-miR-34a, hsa-miR-16, hsa-miR-17, hsa-miR-21, hsa-miR-221, hsa-miR-326, and hsa-miR-375) and seven target genes ( E2F3, PI3KCA, TOM34, WNT5A, PDCD4, DFFA, and EGFR) in 43 glioblastoma multiforme specimens were profiled compared to non-cancer tissues via quantitative reverse transcription-polymerase chain reaction. Immunohistochemistry staining for three proteins (VEGFA, BAX, and BCL2) was performed. Gene enrichment analysis identified the biological regulatory functions of the gene panel in glioma pathway. MGMT ( O-6-methylguanine-DNA methyltransferase) promoter methylation was analyzed for molecular subtyping of tumor specimens. Our data demonstrated a significant upregulation of five microRNAs (hsa-miR-16, hsa-miR-17, hsa-miR-21, hsa-miR-221, and hsa-miR-375), three genes ( E2F3, PI3KCA, and Wnt5a), two proteins (VEGFA and BCL2), and downregulation of hsa-miR-34a and three other genes ( DFFA, PDCD4, and EGFR) in brain cancer tissues. Receiver operating characteristic analysis revealed that miR-34a (area under the curve = 0.927) and miR-17 (area under the curve = 0.900) had the highest diagnostic performance, followed by miR-221 (area under the curve = 0.845), miR-21 (area under the curve = 0.836), WNT5A (area under the curve = 0.809), PDCD4 (area under the curve = 0.809), and PI3KCA (area under the curve = 0.800). MGMT promoter methylation status was associated with high miR-221 levels. Moreover, patients with VEGFA overexpression and downregulation of TOM34 and BAX had poor overall survival. Nevertheless, miR-17, miR-221, and miR-326 downregulation were significantly associated with high recurrence rate. Multivariate analysis by hierarchical clustering classified patients into four distinct groups based on gene panel signature. In conclusion, the explored microRNA-target dysregulation could pave the road toward developing potential therapeutic strategies for glioblastoma multiforme. Future translational and functional studies are highly recommended to better understand the complex bio-molecular signature of this difficult-to-treat tumor.

Coordination of Myeloid Differentiation with Reduced Cell Cycle Progression by PU.1 Induction of MicroRNAs Targeting Cell Cycle Regulators and Lipid Anabolism

During macrophage development, myeloid progenitor cells undergo terminal differentiation coordinated with reduced cell cycle progression. Differentiation of macrophages from myeloid progenitors is accompanied by increased expression of the E26 transformation-specific transcription factor PU.1. Reduced PU.1 expression leads to increased proliferation and impaired differentiation of myeloid progenitor cells. It is not understood how PU.1 coordinates macrophage differentiation with reduced cell cycle progression. In this study, we utilized cultured PU.1-inducible myeloid cells to perform genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) analysis coupled with gene expression analysis to determine targets of PU.1 that may be involved in regulating cell cycle progression. We found that genes encoding cell cycle regulators and enzymes involved in lipid anabolism were directly and inducibly bound by PU.1 although their steady-state mRNA transcript levels were reduced. Inhibition of lipid anabolism was sufficient to reduce cell cycle progression in these cells. Induction of PU.1 reduced expression of E2f1, an important activator of genes involved in cell cycle and lipid anabolism, indirectly through microRNA 223. Next-generation sequencing identified microRNAs validated as targeting cell cycle and lipid anabolism for downregulation. These results suggest that PU.1 coordinates cell cycle progression with differentiation through induction of microRNAs targeting cell cycle regulators and lipid anabolism.

Novel miRNA-mRNA interactions conserved in essential cancer pathways

Cancer is a complex disease in which unrestrained cell proliferation results in tumour development. Extensive research into the molecular mechanisms underlying tumorigenesis has led to the characterization of oncogenes and tumour suppressors that are key elements in cancer growth and progression, as well as that of other important elements like microRNAs. These genes and miRNAs appear to be constitutively deregulated in cancer. To identify signatures of miRNA-mRNA interactions potentially conserved in essential cancer pathways, we have conducted an integrative analysis of transcriptomic data, also taking into account methylation and copy number alterations. We analysed 18,605 raw transcriptome samples from The Cancer Genome Atlas covering 15 of the most common types of human tumours. From this global transcriptome study, we recovered known cancer-associated miRNA-targets and importantly, we identified new potential targets from miRNA families, also analysing the phenotypic outcomes of these genes/mRNAs in terms of survival. Further analyses could lead to novel approaches in cancer therapy.

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.

Prediction of miRNA-mRNA Interactions Using miRGate

miRGate ( http://mirgate.bioinfo.cnio.es /) is a freely available database that contains predicted and experimentally validated microRNA-messenger RNA (miRNA-mRNA) target pairs. This resource includes novel predictions from five well-established algorithms, but recalculated from a common and comprehensive sequence dataset. It includes all 3'-UTR sequences of all known genes of the three more widely employed genomes (human, mouse, and rat), and all annotated miRNA sequences from those genomes. Besides, it also contains predictions for all genes in human targeted by miRNA viruses such as Epstein-Barr and Kaposi sarcoma-associated herpes virus.The approach intends to circumvent one of the main drawbacks in this area, as diverse sequences and gene database versions cause poor overlap among different target prediction methods even with experimentally confirmed targets. As a result, miRGate predictions have been successfully validated using functional assays in several laboratories.This chapter describes how a user can access target information via miRGate's web interface. It also shows how automatically access the database through the programmatic interface based on representational state transfer services (REST), using the application programming interface (API) available at http://mirgate.bioinfo.cnio.es/API .

ARN: Analysis and Visualization System for Adipogenic Regulation Network Information

Adipogenesis is the process of cell differentiation through which preadipocytes become adipocytes. Lots of research is currently ongoing to identify genes, including their gene products and microRNAs, that correlate with fat cell development. However, information fragmentation hampers the identification of key regulatory genes and pathways. Here, we present a database of literature-curated adipogenesis-related regulatory interactions, designated the Adipogenesis Regulation Network (ARN, http://210.27.80.93/arn/), which currently contains 3101 nodes (genes and microRNAs), 1863 regulatory interactions, and 33,969 expression records associated with adipogenesis, based on 1619 papers. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 37,000 PubMed abstracts. Additionally, we further determined 13,103 possible node relationships by searching miRGate, BioGRID, PAZAR and TRRUST. ARN also has several useful features: i) regulatory map information; ii) tests to examine the impact of a query node on adipogenesis; iii) tests for the interactions and modes of a query node; iv) prediction of interactions of a query node; and v) analysis of experimental data or the construction of hypotheses related to adipogenesis. In summary, ARN can store, retrieve and analyze adipogenesis-related information as well as support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.