Bioinformatic tools for microRNA dissection

Exosomal ncRNAs in liquid biopsies for lung cancer

Exosomal non-coding RNAs (ncRNAs) have become essential contributors to advancing and treating lung cancers (LCs). The development of liquid biopsies that utilize exosomal ncRNAs (exo-ncRNAs) offers an encouraging method for diagnosing, predicting, and treating LC. This thorough overview examines the dual function of exo-ncRNAs as both indicators for early diagnosis and avenues for LC treatment. Exosomes are tiny vesicles secreted by various cells, including cancerous cells, enabling connection between cells by delivering ncRNAs. These ncRNAs, which encompass circular RNAs, long ncRNAs, and microRNAs, participate in the modulation of gene expression and cellular functions. In LC, certain exo-ncRNAs are linked to tumour advancement, spread, and treatment resistance, positioning them as promising non-invasive indicators in liquid biopsies. Additionally, targeting these ncRNAs offers potential for innovative treatment approaches, whether by suppressing harmful ncRNAs or reinstating the activity of tumour-suppressing ones. This review emphasizes recent developments in the extraction and analysis of exo-ncRNAs, their practical applications in LC treatment, and the challenges and prospects for translating these discoveries into clinical usage. Through this detailed examination of the current state of the art, we aim to highlight the significant potential of exo-ncRNAs for LC diagnostics and treatments.

Determination of key hub genes in Leishmaniasis as potential factors in diagnosis and treatment based on a bioinformatics study

Leishmaniasis is an infectious disease caused by protozoan parasites from different species of leishmania. The disease is transmitted by female sandflies that carry these parasites. In this study, datasets on leishmaniasis published in the GEO database were analyzed and summarized. The analysis in all three datasets (GSE43880, GSE55664, and GSE63931) used in this study has been performed on the skin wounds of patients infected with a clinical form of leishmania (Leishmania braziliensis), and biopsies have been taken from them. To identify differentially expressed genes (DEGs) between leishmaniasis patients and controls, the robust rank aggregation (RRA) procedure was applied. We performed gene functional annotation and protein-protein interaction (PPI) network analysis to demonstrate the putative functionalities of the DEGs. The study utilized Molecular Complex Detection (MCODE), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to detect molecular complexes within the protein-protein interaction (PPI) network and conduct analyses on the identified functional modules. The CytoHubba plugin's results were paired with RRA analysis to determine the hub genes. Finally, the interaction between miRNAs and hub genes was predicted. Based on the RRA integrated analysis, 407 DEGs were identified (263 up-regulated genes and 144 down-regulated genes). The top three modules were listed after creating the PPI network via the MCODE plug. Seven hub genes were found using the CytoHubba app and RRA: CXCL10, GBP1, GNLY, GZMA, GZMB, NKG7, and UBD. According to our enrichment analysis, these functional modules were primarily associated with immune pathways, cytokine activity/signaling pathways, and inflammation pathways. However, a UBD hub gene is interestingly involved in the ubiquitination pathways of pathogenesis. The mirNet database predicted the hub gene's interaction with miRNAs, and results revealed that several miRNAs, including mir-146a-5p, crucial in fighting pathogenesis. The key hub genes discovered in this work may be considered as potential biomarkers in diagnosis, development of agonists/antagonist, novel vaccine design, and will greatly contribute to clinical studies in the future.

HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations

Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation. To this end, we developed a HyperGraph Contrastive Learning with view-aware Attention Mechanism and Integrated multi-view Representation (HGCLAMIR) model to discover potential miRNA-disease associations. First, hypergraph convolutional network (HGCN) was utilized to capture high-order complex relations from hypergraphs related to miRNAs and diseases. Then, we combined HGCN with contrastive learning to improve and enhance the embedded representation learning ability of HGCN. Moreover, we introduced view-aware attention mechanism to adaptively weight the embedded representations of different views, thereby obtaining the importance of multi-view latent representations. Next, we innovatively proposed integrated representation learning to integrate the embedded representation information of multiple views for obtaining more reasonable embedding information. Finally, the integrated representation information was fed into a neural network-based matrix completion method to perform miRNA-disease association prediction. Experimental results on the cross-validation set and independent test set indicated that HGCLAMIR can achieve better prediction performance than other baseline models. Furthermore, the results of case studies and enrichment analysis further demonstrated the accuracy of HGCLAMIR and unconfirmed potential associations had biological significance.

Targeting MicroRNAs with Small Molecules

MicroRNAs (miRs) have been implicated in numerous diseases, presenting an attractive target for the development of novel therapeutics. The various regulatory roles of miRs in cellular processes underscore the need for precise strategies. Recent advances in RNA research offer hope by enabling the identification of small molecules capable of selectively targeting specific disease-associated miRs. This understanding paves the way for developing small molecules that can modulate the activity of disease-associated miRs. Herein, we discuss the progress made in the field of drug discovery processes, transforming the landscape of miR-targeted therapeutics by small molecules. By leveraging various approaches, researchers can systematically identify compounds to modulate miR function, providing a more potent intervention either by inhibiting or degrading miRs. The implementation of these multidisciplinary approaches bears the potential to revolutionize treatments for diverse diseases, signifying a significant stride towards the targeting of miRs by precision medicine.

Computational tools supporting known miRNA identification

The study of small RNAs is a field that is expanding quickly. Other functional short RNA molecules other than microRNAs, and gene expression regulators, have been found in animals and plants. MicroRNAs play a significant role in host-microbe interactions, and parasite microRNAs may affect the host's innate immunity. Furthermore, short RNAs are intriguing non-invasive biomarker possibilities because they can be found in physiological fluids. These trends suggest that for many researchers, quick and simple techniques for expression profiling and subsequent downstream analysis of miRNA-seq data are crucial. We selected sRNAtoolbox to make integrated sRNA research easier. Each tool can be used separately or to explore and analyze sRNAbench results in further depth. A special focus was placed on the tools' usability. We review available miRNA research tools to have an overview of the evaluation of the tools. Mainly we evaluate the tool sRNAtoolbox.

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.

MicroRNAs in infectious diseases: potential diagnostic biomarkers and therapeutic targets

MicroRNAs (miRNAs) are conserved, short, non-coding RNAs that play a crucial role in the post-transcriptional regulation of gene expression. They have been implicated in the pathogenesis of cancer and neurological, cardiovascular, and autoimmune diseases. Several recent studies have suggested that miRNAs are key players in regulating the differentiation, maturation, and activation of immune cells, thereby influencing the host immune response to infection. The resultant upregulation or downregulation of miRNAs from infection influences the protein expression of genes responsible for the immune response and can determine the risk of disease progression. Recently, miRNAs have been explored as diagnostic biomarkers and therapeutic targets in various infectious diseases. This review summarizes our current understanding of the role of miRNAs during viral, fungal, bacterial, and parasitic infections from a clinical perspective, including critical functional mechanisms and implications for their potential use as biomarkers and therapeutic targets.

MicroRNA-183 cluster: a promising biomarker and therapeutic target in gastrointestinal malignancies

Small non-coding RNAs (microRNA, miR), powerful epigenetic regulators, were found involved in the regulation of most biological functions via post-translational inhibition of protein expression. Increased expression of pro-oncogenic miRs (known as miR cancer biomarkers) and inhibition of pro-apoptotic miR expression have been demonstrated in different tumors. The recently identified miR-183 was found implicated in gastrointestinal tumor metabolism regulation. Elevated miR-183 expression and cancer-promoting effects were reported in esophageal and colorectal cancers, which was partially contradicted by controversial data observed in gastric cancers. Anti-cancer effect of miR-183 in gastric cancer cells was associated with the Bim-1 and Ezrin genes regulation. Many studies indicated that miR-183 can inhibit tumor suppressor genes in most cell lines, promoting tumor cell proliferation and migration. Increased miR-183 level results in the downregulation of FOXO1, PDCD4, and other tumor suppressor genes in gastrointestinal tumor cells. MiR-183 also influences the signaling of PI3K/AKT/mTOR, Wnt/β-catenin, and Bcl-2/p53 signaling pathways. Mir-183 inhibits apoptosis and autophagy, and promotes epithelial-to-mesenchymal transition, cancer cell proliferation, and migration. Accordingly, gastrointestinal cancer occurrence, development of chemoradiotherapy resistance, recurrence/metastasis, and prognosis were associated with miR-183 expression. The current study assessed reported miR-183 functions and signaling, providing new insights for the diagnosis and treatment of gastrointestinal malignancies.

Biomarkers of obesity-mediated insulin resistance: focus on microRNAs

Obesity and metabolic syndromes are becoming increasingly prevalent worldwide. Insulin resistance (IR) is a common complication of obesity. However, IR occurrence varies across individuals with obesity and may involve epigenetic factors. To rationalize the allocation of healthcare resources, biomarkers for the early risk stratification of individuals with obesity should be identified. MicroRNAs (miRNAs) are closely associated with metabolic diseases and involved in epigenetic regulation. In this review, we have summarized the changes in miRNA expression in the peripheral circulation and tissues of patients and animals with obesity-associated IR over the last 5 years and identified several candidate biomarkers that predict obesity-related IR. There are areas for improvement in existing studies. First, more than the predictive validity of a single biomarker is required, and a biomarker panel needs to be formed. Second, miRNAs are often studied in isolation and do not form a network of signaling pathways. We believe that early biomarkers can help clinicians accurately predict individuals prone to obesity-related IR at an early stage. Epigenetic regulation may be one of the underlying causes of different clinical outcomes in individuals with obesity. Future studies should focus on objectively reflecting the differences in miRNA profile expression in individuals with obesity-related IR, which may help identify more reliable biomarkers. Understanding the metabolic pathways of these miRNAs can help design new metabolic risk prevention and management strategies, and support the development of drugs to treat obesity and metabolic disorders.

microRNA-dependent regulation of gene expression in GABAergic interneurons

Information processing within neuronal circuits relies on their proper development and a balanced interplay between principal and local inhibitory interneurons within those circuits. Gamma-aminobutyric acid (GABA)ergic inhibitory interneurons are a remarkably heterogeneous population, comprising subclasses based on their morphological, electrophysiological, and molecular features, with differential connectivity and activity patterns. microRNA (miRNA)-dependent post-transcriptional control of gene expression represents an important regulatory mechanism for neuronal development and plasticity. miRNAs are a large group of small non-coding RNAs (21-24 nucleotides) acting as negative regulators of mRNA translation and stability. However, while miRNA-dependent gene regulation in principal neurons has been described heretofore in several studies, an understanding of the role of miRNAs in inhibitory interneurons is only beginning to emerge. Recent research demonstrated that miRNAs are differentially expressed in interneuron subclasses, are vitally important for migration, maturation, and survival of interneurons during embryonic development and are crucial for cognitive function and memory formation. In this review, we discuss recent progress in understanding miRNA-dependent regulation of gene expression in interneuron development and function. We aim to shed light onto mechanisms by which miRNAs in GABAergic interneurons contribute to sculpting neuronal circuits, and how their dysregulation may underlie the emergence of numerous neurodevelopmental and neuropsychiatric disorders.

New Insight into Mechanisms of Cardiovascular Diseases: An Integrative Analysis Approach to Identify TheranoMiRNAs

MiRNAs regulate both physiological and pathological heart functions. Altered expression of miRNAs is associated with cardiovascular diseases (CVDs), making miRNAs attractive therapeutic strategies for the diagnosis and treatment of heart diseases. A recent publication defined, for the first time, the term theranoMiRNA, meaning the miRNAs that may be used both for diagnosis and treatment. The use of in silico tools may be considered fundamental for these purposes, clarifying several molecular aspects, suggesting future directions for in vivo studies. This study aims to explore different bioinformatic tools in order to clarify miRNA interactions with candidate genes, demonstrating the need to use a computational approach when establishing the most probable associations between miRNAs and target genes. This study focused on the functions of miR-133a-3p, miR-21-5p, miR-499a-5p, miR-1-3p, and miR-126-3p, providing an up-to-date overview, and suggests future lines of research in the identification of theranoMiRNAs related to CVDs. Based on the results of the present study, we elucidated the molecular mechanisms that could be linked between miRNAs and CVDs, confirming that these miRNAs play an active role in the genesis and development of heart damage. Given that CVDs are the leading cause of death in the world, the identification of theranoMiRNAs is crucial, hence the need for a definition of in vivo studies in order to obtain further evidence in this challenging field of research.

Recent findings on miR‑370 expression, regulation and functions in cancer (Review)

MicroRNAs (miRNAs/miRs) are a group of small non‑coding RNAs that serve as post‑transcriptional gene modulators. miRNAs have been demonstrated to serve a pivotal role in carcinogenesis and the dysregulated expression of miRNAs is a well‑understood characteristic of cancer. In recent years, miR‑370 has been established as a key miRNA in various cancers. The expression of miR‑370 is dysregulated in various types of cancer and varies markedly across different tumor types. miR‑370 can regulate multiple biological processes, including cell proliferation, apoptosis, migration, invasion, as well as cell cycle progression and cell stemness. Moreover, it has been reported that miR‑370 affects the response of tumor cells to anticancer treatments. Additionally, the expression of miR‑370 is modulated by multiple factors. The present review summarizes the role and mechanism of miR‑370 in tumors, and demonstrates its potential as a molecular marker for cancer diagnosis and prognosis.

A Data-Mining Approach to Identify NF-kB-Responsive microRNAs in Tissues Involved in Inflammatory Processes: Potential Relevance in Age-Related Diseases

The nuclear factor NF-kB is the master transcription factor in the inflammatory process by modulating the expression of pro-inflammatory genes. However, an additional level of complexity is the ability to promote the transcriptional activation of post-transcriptional modulators of gene expression as non-coding RNA (i.e., miRNAs). While NF-kB’s role in inflammation-associated gene expression has been extensively investigated, the interplay between NF-kB and genes coding for miRNAs still deserves investigation. To identify miRNAs with potential NF-kB binding sites in their transcription start site, we predicted miRNA promoters by an in silico analysis using the PROmiRNA software, which allowed us to score the genomic region’s propensity to be miRNA cis-regulatory elements. A list of 722 human miRNAs was generated, of which 399 were expressed in at least one tissue involved in the inflammatory processes. The selection of “high-confidence” hairpins in miRbase identified 68 mature miRNAs, most of them previously identified as inflammamiRs. The identification of targeted pathways/diseases highlighted their involvement in the most common age-related diseases. Overall, our results reinforce the hypothesis that persistent activation of NF-kB could unbalance the transcription of specific inflammamiRNAs. The identification of such miRNAs could be of diagnostic/prognostic/therapeutic relevance for the most common inflammatory-related and age-related diseases.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

miR-344d-3p regulates osteogenic and adipogenic differentiation of mouse mandibular bone marrow mesenchymal stem cells

Postmenopausal osteoporosis (POP) is a chronic disease of bone metabolism that occurs in middle-aged and elderly women. POP can cause abnormalities of the skeletal system in the whole body, and the jaw bone is also impacted, affecting the function of the oral and maxillofacial regions. Mandibular bone marrow mesenchymal stem cells (MBMSCs) play an important role in mandibular bone metabolism, and abnormal differentiation of MBMSCs can affect the metabolic balance between new and old bone. MicroRNAs (miRNAs) can induce the differentiation of MBMSCs. In this study, the changes in biological characteristics of mandible and MBMSCs in the bone microenvironment of postmenopausal osteoporosis were firstly analyzed, and then the key miRNAs screened from miRNAs gene chips were sorted out for verification and functional exploration. It was found that miR-344d-3p promoted the osteogenic differentiation of MC3T3-E1 and MBMSCs. It inhibited the adipogenic differentiation of 3T3-L1 and MBMSCs. In addition, Dnmt3a may be the target gene of miR-344d-3p. In conclusion, this study found new biological indicators related to bone metabolism, which are of great significance in the field of bone reconstruction.

MicroRNAs in Ruminants and Their Potential Role in Nutrition and Physiology

The knowledge of how diet choices, dietary supplements, and feed intake influence molecular mechanisms in ruminant nutrition and physiology to maintain ruminant health, is essential to attain. In the present review, we focus on the role of microRNAs in ruminant health and disease; additionally, we discuss the potential of circulating microRNAs as biomarkers of disease in ruminants and the state of technology for their detection, also considering the major difficulties in the transition of biomarker development from bench to clinical practice. MicroRNAs are an inexhaustible class of endogenous non-protein coding small RNAs of 18 to 25 nucleotides that target either the 3' untranslated (UTR) or coding region of genes, ensuring a tight post-transcriptionally controlled regulation of gene expression. The development of new "omics" technologies facilitated a fresh perspective on the nutrition-to-gene relationship, incorporating more extensive data from molecular genetics, animal nutrition, and veterinary sciences. MicroRNAs might serve as important regulators of metabolic processes and may present the inter-phase between nutrition and gene regulation, controlled by the diet. The development of biomarkers holds the potential to revolutionize veterinary practice through faster disease detection, more accurate ruminant health monitoring, enhanced welfare, and increased productivity. Finally, we summarize the latest findings on how microRNAs function as biomarkers, how technological paradigms are reshaping this field of research, and how platforms are being used to identify novel biomarkers. Numerous studies have demonstrated a connection between circulating microRNAs and ruminant diseases such as mastitis, tuberculosis, foot-and-mouth disease, fasciolosis, and metabolic disorders. Therefore, the identification and analysis of a small number of microRNAs can provide crucial information about the stage of a disease, etiology, and prognosis.

miR-31-5p as a Potential Circulating Biomarker and Tracer of Clinical Improvement for Chronic Inflammatory Demyelinating Polyneuropathy

Background

MicroRNAs are endogenous, small noncoding RNA molecules that play a pivotal role in the regulation of gene expression. MicroRNAs are involved in many biological processes such as proliferation, cell differentiation, neovascularization, and apoptosis. Studies on microRNA expression may contribute to a better understanding of the pathomechanism of chronic inflammatory demyelinating polyneuropathy (CIDP) and consequently enable the development of new therapeutic measures using antisense miRNAs (antagomirs). In this study, we evaluated the level of miR-31-5p in the serum of patients with CIDP and its correlation with the miR-31-5p level and clinical presentation and electrophysiological and biochemical parameters.

Methods

The study group consisted of 48 patients, mean age 61.60 ± 11.76, who fulfilled the diagnostic criteria of a typical variant of CIDP. The expression of miR-31-5p in patient serum probes was investigated by droplet digital PCR. The results were correlated with neurophysiological findings and the patient's clinical and biochemical parameters.

Results

The mean copy number of miRNA-31 in 100 μl serum was 1288.64 ± 2001.02 in the CIDP group of patients, while in the control group, it was 3743.09 ± 4026.90. There was a significant positive correlation (0.426) between IgIV treatment duration and miR-31-5p expression. Patients without IgIV treatment showed significantly lower levels of miR-31 compared to the treated group (259.44 ± 304.02 vs. 1559.48 ± 2168.45; p = 0.002). The group of patients with body weight > 80 kg showed statistically significantly lower levels of miRNA-31-5p than the patients with lower body weight (934.37 ± 1739.66 vs. 1784.62 ± 2271.62, respectively; p = 0.014). Similarly, the patients with elevated cerebrospinal fluid (CSF) protein levels had significantly higher miRNA-31-5p expression than those with normal protein levels (1393.93 ± 1932.27 vs. 987.38 ± 2364.10, respectively; p = 0.044).

Conclusion

The results may support the hypothesis that miR-31-5p is strongly involved in the autoimmune process in CIDP. The positive correlation between higher miR-31-5p levels and duration of IVIg treatment may be an additional factor explaining the efficacy of prolonged IVIg therapy in CIDP.

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.

Recent progress in epigenetics of obesity

Nowadays, obesity is one of the largest public health problems worldwide. In the last few decades, there has been a marked increase in the obesity epidemic and its related comorbidities. Worldwide, more than 2.2 billion people (33%) are affected by overweight or obesity (712 million, 10%) and its associated metabolic complications. Although a high heritability of obesity has been estimated, the genetic variants conducted from genetic association studies only partially explain the variation of body mass index. This has led to a growing interest in understanding the potential role of epigenetics as a key regulator of gene-environment interactions on the development of obesity and its associated complications. Rapid advances in epigenetic research methods and reduced costs of epigenome-wide association studies have led to a great expansion of population-based studies. The field of epigenetics and metabolic diseases such as obesity has advanced rapidly in a short period of time. The main epigenetic mechanisms include DNA methylation, histone modifications, microRNA (miRNA)-mediated regulation and so on. DNA methylation is the most investigated epigenetic mechanism. Preliminary evidence from animal and human studies supports the effect of epigenetics on obesity. Studies of epigenome-wide association studies and genome-wide histone modifications from different biological specimens such as blood samples (newborn, children, adolescent, youth, woman, man, twin, race, and meta-analysis), adipose tissues, skeletal muscle cells, placenta, and saliva have reported the differential expression status of multiple genes before and after obesity interventions and have identified multiple candidate genes and biological markers. These findings may improve the understanding of the complex etiology of obesity and its related comorbidities, and help to predict an individual's risk of obesity at a young age and open possibilities for introducing targeted prevention and treatment strategies.

miRNA-Mediated Epigenetic Regulation of Treatment Response in RA Patients—A Systematic Review

This study aimed to evaluate the role of microRNAs (miRNA) as biomarkers of treatment response in rheumatoid arthritis (RA) patients through a systematic review of the literature. The MEDLINE and Embase databases were searched for studies including RA-diagnosed patients treated with disease-modifying antirheumatic drugs (DMARDs) that identify miRNAs as response predictors. Review inclusion criteria were met by 10 studies. The main outcome of the study was the response to treatment, defined according to EULAR criteria. A total of 839 RA patients and 67 healthy donors were included in the selected studies. RA patients presented seropositivity for the rheumatoid factor of 74.7% and anti-citrullinated C-peptide antibodies of 63.6%. After revision, 15 miRNAs were described as treatment response biomarkers for methotrexate, anti-tumour necrosis factor (TNF), and rituximab. Among treatments, methotrexate presented the highest number of predictor miRNAs: miR-16, miR-22, miR-132, miR-146a and miR-155. The most polyvalent miRNAs were miR-146a, predicting response to methotrexate and anti-TNF, and miR-125b, which predicts response to infliximab and rituximab. Our data support the role of miRNAs as biomarkers of treatment response in RA and point to DMARDs modifying the miRNAs expression. Nevertheless, further studies are needed since a meta-analysis that allows definitive conclusions is not possible due to the lack of studies in this field.

Screening of miRNAs in White Blood Cell as a Radiation Biomarkers for Rapid Assessment of Acute Radiation Injury

Accidental radiation exposure is a threat to human health that necessitates effective clinical diagnosis. Suitable biomarkers are urgently needed for early assessment of exposure dose. Existing technologies being used to assess the extent of radiation have notable limitations. As a radiation biomarker, miRNA has the advantages of simple detection and high throughput. In this study, we screened for miRNAs with dose and time dependent responses in peripheral blood leukocytes via miRNA sequencing in establishing the animal model of acute radiation injury. Four radiation-sensitive and stably expressed miRNAs were selected out in the 24 h group of leukocyte miRNAs: mmu-miR-130b-5p, mmu-miR-148b-5p, mmu-miR-184-3p, mmu-miR-26a-2-3p, and five were screened in the 48 h group of leukocyte miRNAs: mmu-miR-130b-5p, mmu-miR-423-5p, mmu-miR-676-3p, mmu-miR-150-5p, mmu-miR-342-3p.The correlation curves between their expression and irradiation dose were plotted. Then, the results were validated by RT-qPCR in mouse peripheral blood. As a result, mmu-miR-150-5p and mmu-miR-342-3p showed the highest correlation at 48h after irradiation, and mmu-miR-130b-5p showed good correlation at both 24 h and 48 h after irradiation. In a conclusion, the miRNAs that are sensitive to ionizing radiation with dose dependent effects were selected out, which have the potential of forming a rapid assessment scheme for acute radiation injury.

Regulatory Non-Coding RNAs in Familial Hypercholesterolemia, Theranostic Applications

Familial hypercholesterolemia (FH) is a common monogenic disease which is associated with high serum levels of low-density lipoprotein cholesterol (LDL-C) and leads to atherosclerosis and cardiovascular disease (CVD). Early diagnosis and effective treatment strategy can significantly improve prognosis. Recently, non-coding RNAs (ncRNAs) have emerged as novel biomarkers for the diagnosis and innovative targets for therapeutics. Non-coding RNAs have essential roles in the regulation of LDL-C homeostasis, suggesting that manipulation and regulating ncRNAs could be a promising theranostic approach to ameliorate clinical complications of FH, particularly cardiovascular disease. In this review, we briefly discussed the mechanisms and pathophysiology of FH and novel therapeutic strategies for the treatment of FH. Moreover, the theranostic effects of different non-coding RNAs for the treatment and diagnosis of FH were highlighted. Finally, the advantages and disadvantages of ncRNA-based therapies vs. conventional therapies were discussed.

Weight Change Alters the Small RNA Profile of Urinary Extracellular Vesicles in Obesity

INTRODUCTION

Various kidney diseases reportedly show different urinary extracellular vesicle (EV) RNA profiles. Although obesity is one of the main causes of chronic kidney disease, the expression pattern of urinary EV RNA in obesity is uncertain. Our aim was to sequence the small RNA profiles of urinary EVs in obese patients before and after weight reduction and compare them to those of healthy volunteers (HVs).

METHODS

We recruited age-sex-matched obese patients and HVs. The small RNA profiles of urinary EVs were analyzed using RNA sequencing. To evaluate the effect of weight reduction, small RNA profiles of urinary EVs 6 months after bariatric surgery were also analyzed.

RESULTS

The proportion of urinary EVs transfer RNA and microRNA of obese patients differed from that of HVs. Obese patients showed differential expression of 1,343 small RNAs in urinary EVs compared to HVs (fold change ≥2 and p value <0.05). Among those, 61 small RNAs were upregulated in obese patients and downregulated after weight reduction, whereas 167 small RNAs were downregulated in obese patients and upregulated after weight reduction. RNA sequencing revealed the correlation between the specific urinary EV small RNAs and clinical parameters including body weight, low-density lipoprotein cholesterol, triglyceride, high-density lipoprotein cholesterol, serum glucose, estimated glomerular filtration rate, and albuminuria.

CONCLUSION

Obese patients showed distinct urinary EV small RNA profiles compared to HVs. Weight reduction altered urinary EV small-RNA profiles in obese patients.

Deletion of pancreas-specific miR-216a reduces beta-cell mass and inhibits pancreatic cancer progression in mice

miRNAs have crucial functions in many biological processes and are candidate biomarkers of disease. Here, we show that miR-216a is a conserved, pancreas-specific miRNA with important roles in pancreatic islet and acinar cells. Deletion of miR-216a in mice leads to a reduction in islet size, β-cell mass, and insulin levels. Single-cell RNA sequencing reveals a subpopulation of β-cells with upregulated acinar cell markers under a high-fat diet. miR-216a is induced by TGF-β signaling, and inhibition of miR-216a increases apoptosis and decreases cell proliferation in pancreatic cells. Deletion of miR-216a in the pancreatic cancer-prone mouse line KrasG12D;Ptf1aCreER reduces the propensity of pancreatic cancer precursor lesions. Notably, circulating miR-216a levels are elevated in both mice and humans with pancreatic cancer. Collectively, our study gives insights into how β-cell mass and acinar cell growth are modulated by a pancreas-specific miRNA and also suggests miR-216a as a potential biomarker for diagnosis of pancreatic diseases.

MicroRNA of N-region from SARS-CoV-2: Potential sensing components for biosensor development

An oligonucleotide DNA probe has been developed for the application in the DNA electrochemical biosensor for the early diagnosis of coronavirus disease (COVID-19). Here, the virus microRNA from the N-gene of severe acute respiratory syndrome-2 (SARS-CoV-2) was used for the first time as a specific target for detecting the virus and became a framework for developing the complementary DNA probe. The sequence analysis of the virus microRNA was carried out using bioinformatics tools including basic local alignment search tools, multiple sequence alignment from CLUSTLW, microRNA database (miRbase), microRNA target database, and gene analysis. Cross-validation of distinct strains of coronavirus and human microRNA sequences was completed to validate the percentage of identical and consent regions. The percent identity parameter from the bioinformatics tools revealed the virus microRNAs' sequence has a 100% match with the genome of SARS-CoV-2 compared with other coronavirus strains, hence improving the selectivity of the complementary DNA probe. The 30 mer with 53.0% GC content of complementary DNA probe 5' GCC TGA GTT GAG TCA GCA CTG CTC ATG GAT 3' was designed and could be used as a bioreceptor for the biosensor development in the clinical and environmental diagnosis of COVID-19.

MicroRNAs Regulating Mitochondrial Function in Cardiac Diseases

Mitochondria are the key organelles that supply cellular energy. As the most active organ in the body, the energy required to maintain the mechanical function of the heart requires a high quantity of high-quality mitochondria in cardiomyocytes. MicroRNAs (miRNAs) are single-stranded noncoding RNAs, approximately 22 nt in length, which play key roles in mediating post-transcriptional gene silencing. Numerous studies have confirmed that miRNAs can participate in the occurrence and development of cardiac diseases by regulating mitochondrial function-related genes and signaling pathways. Therefore, elucidating the crosstalk that occurs between miRNAs and mitochondria is important for the prevention and treatment of cardiac diseases. In this review, we discuss the biogenesis of miRNAs, the miRNA-mediated regulation of major genes involved in the maintenance of mitochondrial function, and the effects of miRNAs on mitochondrial function in cardiac diseases in order to provide a theoretical basis for the clinical prevention and treatment of cardiac disease and the development of new drugs.

A combinatorial in silico approach for microRNA-target identification: Order out of chaos

Contemporary computational microRNA(miRNA)-target prediction tools have been playing a vital role in pursuing putative targets for a solitary miRNA or a group of miRNAs. These tools utilise a set of probabilistic algorithms, machine learning techniques and analyse experimentally validated miRNA targets to identify the potential miRNA-target pairs. Unfortunately, current tools generate a huge number of false-positive predictions. A standardized approach with a single tool or a combination of tools is still lacking. Moreover, sensitivity, specificity and overall efficiency of any single tool are yet to be satisfactory. Therefore, a systematic combination of selective online tools combining the factors regarding miRNA-target identification would be valuable as an miRNA-target prediction scheme. The focus of this study was to develop a theoretical framework by combining six available online tools to facilitate the current understanding of miRNA-target identification.

Epigenetics, microRNA and Metabolic Syndrome: A Comprehensive Review

Epigenetics refers to the DNA chemistry changes that result in the modification of gene transcription and translation independently of the underlying DNA coding sequence. Epigenetic modifications are reported to involve various molecular mechanisms, including classical epigenetic changes affecting DNA methylation and histone modifications and small RNA-mediated processes, particularly that of microRNAs. Epigenetic changes are reversible and are closely interconnected. They are recognised to play a critical role as mediators of gene regulation, and any alteration in these mechanisms has been identified to mediate various pathophysiological conditions. Moreover, genetic predisposition and environmental factors, including dietary alterations, lifestyle or metabolic status, are identified to interact with the human epigenome, highlighting the importance of epigenetic factors as underlying processes in the aetiology of various diseases such as MetS. This review will reflect on how both the classical and microRNA-regulated epigenetic changes are associated with the pathophysiology of metabolic syndrome. We will then focus on the various aspects of epigenetic-based strategies used to modify MetS outcomes, including epigenetic diet, epigenetic drugs, epigenome editing tools and miRNA-based therapies.

Mutations in cis that affect mRNA synthesis, processing and translation

Genetic mutations that cause hereditary diseases usually affect the composition of the transcribed mRNA and its encoded protein, leading to instability of the mRNA and/or the protein. Sometimes, however, such mutations affect the synthesis, the processing or the translation of the mRNA, with similar disastrous effects. We here present an overview of mRNA synthesis, its posttranscriptional modification and its translation into protein. We then indicate which elements in these processes are known to be affected by pathogenic mutations, but we restrict our review to mutations in cis, in the DNA of the gene that encodes the affected protein. These mutations can be in enhancer or promoter regions of the gene, which act as binding sites for transcription factors involved in pre-mRNA synthesis. We also describe mutations in polyadenylation sequences and in splice site regions, exonic and intronic, involved in intron removal. Finally, we include mutations in the Kozak sequence in mRNA, which is involved in protein synthesis. We provide examples of genetic diseases caused by mutations in these DNA regions and refer to databases to help identify these regions. The over-all knowledge of mRNA synthesis, processing and translation is essential for improvement of the diagnosis of patients with genetic diseases.

LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations

As is known to all, constructing experiments to predict unknown miRNA-disease association is time-consuming, laborious and costly. Accordingly, new prediction model should be conducted to predict novel miRNA-disease associations. What's more, the performance of this method should be high and reliable. In this paper, a new computation model Logistic Weighted Profile-based Collaborative Matrix Factorization (LWPCMF) is put forward. In this method, weighted profile (WP) is combined with collaborative matrix factorization (CMF) to increase the performance of this model. And, the neighbor information is considered. In addition, logistic function is applied to miRNA functional similarity matrix and disease semantic similarity matrix to extract valuable information. At the same time, by adding WP and logistic function, the known correlation can be protected. And, Gaussian Interaction Profile (GIP) kernels of miRNAs and diseases are added to miRNA functional similarity network and disease semantic similarity network to augment kernel similarities. Then, a five-fold cross validation is implemented to evaluate the predictive ability of this method. Besides, case studies are conducted to view the experimental results. The final result contains not only known associations but also newly predicted ones. And, the result proves that our method is better than other existing methods. This model is able to predict potential miRNA-disease associations.

Peripheral blood microRNAs and the COVID-19 patient: methodological considerations, technical challenges and practice points

The COVID-19 emergency pandemic resulting from infection with SARS-CoV-2 represents a major threat to public health worldwide. There is an urgent clinical demand for easily accessible tools to address weaknesses and gaps in the management of COVID-19 patients. In this context, transcriptomic profiling of liquid biopsies, especially microRNAs (miRNAs), has recently emerged as a robust source of potential clinical indicators for medical decision-making. Nevertheless, the analysis of the circulating miRNA signature and its translation to clinical practice requires strict control of a wide array of methodological details. In this review, we indicate the main methodological aspects that should be addressed when evaluating the circulating miRNA profiles in COVID-19 patients, from preanalytical and analytical variables to the experimental design, impact of confounding, analysis of the data and interpretation of the findings, among others. Additionally, we provide practice points to ensure the rigour and reproducibility of miRNA-based biomarker investigations of this condition.Abbreviations: ACE: angiotensin-converting enzyme; ARDS: acute respiratory distress syndrome; COVID-19: coronavirus disease 2019; ERDN: early Detection Research Network; LMWH: low molecular weight heparin; miRNA: microRNA; ncRNA: noncoding RNA; SARS-CoV-2: severe acute respiratory syndrome coronavirus-2; SOP: standard operating procedure.

Circular RNA expression profile of lung squamous cell carcinoma: identification of potential biomarkers and therapeutic targets

Emerging evidences indicated that exosomal circular RNAs (circRNAs) could serve as diagnostic biomarkers for cancers. However, the expression profiles and clinical significance of circRNAs in lung squamous cell carcinoma (LUSC) remain largely unknown. Herein, we analyzed circRNAs expression profile in six pairs of plasma exosome samples of LUSC patients using high-throughput sequencing. A total of 252 differentially expressed exosomal circRNAs were identified, including 133 up-regulated circRNAs and 119 down-regulated circRNAs. Subsequently, the circRNAs–miRNAs–mRNAs interaction network was built to investigate potential function of circRNAs. Three up-regulated circRNAs (hsa_circ_0014235, hsa_circ_0025580 and hsa_circ_0026403) were implied to participate in cancer-related pathways. QRT-PCR experiment confirmed the up-regulation of hsa_circ_0014235 and hsa_circ_0025580. Finally, clinical studies indicated that hsa_circ_0014235 and hsa_circ_0025580 could serve as novel diagnostic biomarkers for LUSC. Taken together, our study revealed exosomal circRNAs expression profile in LUSC for the first time and showed the important diagnostic potential for circRNAs in LUSC.

Recent Highlights of Research on miRNAs as Early Potential Biomarkers for Cardiovascular Complications of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) and its complications pose a serious threat to the life and health of patients around the world. The most dangerous complications of this disease are vascular complications. Microvascular complications of T2DM include retinopathy, nephropathy, and neuropathy. In turn, macrovascular complications include coronary artery disease, peripheral artery disease, and cerebrovascular disease. The currently used diagnostic methods do not ensure detection of the disease at an early stage, and they also do not predict the risk of developing specific complications. MicroRNAs (miRNAs) are small, endogenous, noncoding molecules that are involved in key processes, such as cell proliferation, differentiation, and apoptosis. Recent research has assigned them an important role as potential biomarkers for detecting complications related to diabetes. We suggest that utilizing miRNAs can be a routine approach for early diagnosis and prognosis of diseases and may enable the development of better therapeutic approaches. In this paper, we conduct a review of the latest reports demonstrating the usefulness of miRNAs as biomarkers in the vascular complications of T2DM.

Cell death pathways and viruses: Role of microRNAs

Viral infections lead to the death of more than a million people each year around the world, both directly and indirectly. Viruses interfere with many cell functions, particularly critical pathways for cell death, by affecting various intracellular mediators. MicroRNAs (miRNAs) are a major example of these mediators because they are involved in many (if not most) cellular mechanisms. Virus-regulated miRNAs have been implicated in three cell death pathways, namely, apoptosis, autophagy, and anoikis. Several molecules (e.g., BECN1 and B cell lymphoma 2 [BCL2] family members) are involved in both apoptosis and autophagy, while activation of anoikis leads to cell death similar to apoptosis. These mechanistic similarities suggest that common regulators, including some miRNAs (e.g., miR-21 and miR-192), are involved in different cell death pathways. Because the balance between cell proliferation and cell death is pivotal to the homeostasis of the human body, miRNAs that regulate cell death pathways have drawn much attention from researchers. miR-21 is regulated by several viruses and can affect both apoptosis and anoikis via modulating various targets, such as PDCD4, PTEN, interleukin (IL)-12, Maspin, and Fas-L. miR-34 can be downregulated by viral infection and has different effects on apoptosis, depending on the type of virus and/or host cell. The present review summarizes the existing knowledge on virus-regulated miRNAs involved in the modulation of cell death pathways. Understanding the mechanisms for virus-mediated regulation of cell death pathways could provide valuable information to improve the diagnosis and treatment of many viral diseases.

miRNA Regulatory Functions in Farm Animal Diseases, and Biomarker Potentials for Effective Therapies

MicroRNAs (miRNAs) are small endogenous RNAs that regulate gene expression post-transcriptionally by targeting either the 3′ untranslated or coding regions of genes. They have been reported to play key roles in a wide range of biological processes. The recent remarkable developments of transcriptomics technologies, especially next-generation sequencing technologies and advanced bioinformatics tools, allow more in-depth exploration of messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs), including miRNAs. These technologies have offered great opportunities for a deeper exploration of miRNA involvement in farm animal diseases, as well as livestock productivity and welfare. In this review, we provide an overview of the current knowledge of miRNA roles in major farm animal diseases with a particular focus on diseases of economic importance. In addition, we discuss the steps and future perspectives of using miRNAs as biomarkers and molecular therapy for livestock disease management as well as the challenges and opportunities for understanding the regulatory mechanisms of miRNAs related to disease pathogenesis.

Evaluation and application of tools for the identification of known microRNAs in plants

MicroRNAs (miRNAs), endogenous non-coding RNA regulators, post-transcriptionally inhibit the expression of their target genes. Several tools have been developed for predicting annotated known miRNAs, but there is no consensus about how to select the most suitable method for any given species. In this study, eight miRNA prediction tools (mirnovo, miRPlant, miRDeep-P2, miRExpress, miRkwood, miRDeep2, miR-PREFeR, and sRNAbench) were selected for evaluation. High-throughput small RNA sequencing data from four plant species (including C3 and C4 species, and both monocots and dicots, i.e., Arabidopsis thaliana, Oryza sativa, Triticum aestivum, and Zea mays) were used for the analysis. The sensitivity, accuracy, area under the curve, consistency, duration, and RAM usage of the known miRNA predictions were evaluated for each tool. The miRNA annotations were obtained using miRBase and sRNAanno. Algorithms, such as random forest, BLAST, and receiver operating characteristic curves, were used to evaluate accuracy. Of the tools evaluated, sRNAbench was found to be the most accurate, miRDeep-P2 was the most sensitive, miRDeep-P2 was the fastest, and miRkwood had the highest memory usage. Due to its large genome size, only three tools were able to successfully predict known miRNAs in wheat (Triticum aestivum). Our results enable us to recommend the tool best suited to a variety of researcher needs, which we hope will reduce confusion and enhance future work.

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

•

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

•

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

•

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.

Using exosomal miRNAs extracted from porcine follicular fluid to investigate their role in oocyte development

BACKGROUND

Follicular development is crucial to normal oocyte maturation, with follicular size closely related to oocyte maturation. To better understand the molecular mechanisms behind porcine oocyte maturation, we obtained exosomal miRNA from porcine follicular fluid (PFF). These miRNA samples were then sequenced and analyzed regarding their different follicular sizes, as described in the methods section.

RESULTS

First, these results showed that this process successfully isolated PFF exosomes. Nearly all valid reads from the PFF exosomal sequencing data were successfully mapped to the porcine genome database. Second, we used hierarchical clustering methods to determine that significantly expressed miRNAs were clustered into A, B, C, and D groups in our heatmap according to different follicle sizes. These results allowed for the targeting of potential mRNAs genes related to porcine oocyte development. Third, we chose ten, significantly expressed miRNAs and predicted their target genes for further GO analysis. These results showed that the expression levels of neurotransmitter secretion genes were greatly changed, as were many target genes involved in the regulation of FSH secretion. Notably, these are genes that are very closely related to oocyte maturation in growing follicles. We then used pathway analysis for these targeted genes based on the originally selected ten miRNAs. Results indicated that the pathways were mainly related to the biosynthesis of TGF-beta and its signaling pathway, which are very closely related to reproductive system functions.

CONCLUSIONS

Finally, these exosomal miRNAs obtained from PFF may provide a valuable addition to our understanding of the mechanism of porcine oocyte maturation. It is also likely that these exosomal miRNAs could function as molecular biomarkers to choose high-quality oocytes and allow for in vitro porcine embryo production.

Identification of miRNA Biomarkers for Diverse Cancer Types Using Statistical Learning Methods at the Whole-Genome Scale

Genome-wide analysis of miRNA molecules can reveal important information for understanding the biology of cancer. Typically, miRNAs are used as features in statistical learning methods in order to train learning models to predict cancer. This motivates us to propose a method that integrates clustering and classification techniques for diverse cancer types with survival analysis via regression to identify miRNAs that can potentially play a crucial role in the prediction of different types of tumors. Our method has two parts. The first part is a feature selection procedure, called the stochastic covariance evolutionary strategy with forward selection (SCES-FS), which is developed by integrating stochastic neighbor embedding (SNE), the covariance matrix adaptation evolutionary strategy (CMA-ES), and classifiers, with the primary objective of selecting biomarkers. SNE is used to reorder the features by performing an implicit clustering with highly correlated neighboring features. A subset of features is selected heuristically to perform multi-class classification for diverse cancer types. In the second part of our method, the most important features identified in the first part are used to perform survival analysis via Cox regression, primarily to examine the effectiveness of the selected features. For this purpose, we have analyzed next generation sequencing data from The Cancer Genome Atlas in form of miRNA expression of 1,707 samples of 10 different cancer types and 333 normal samples. The SCES-FS method is compared with well-known feature selection methods and it is found to perform better in multi-class classification for the 17 selected miRNAs, achieving an accuracy of 96%. Moreover, the biological significance of the selected miRNAs is demonstrated with the help of network analysis, expression analysis using hierarchical clustering, KEGG pathway analysis, GO enrichment analysis, and protein-protein interaction analysis. Overall, the results indicate that the 17 selected miRNAs are associated with many key cancer regulators, such as MYC, VEGFA, AKT1, CDKN1A, RHOA, and PTEN, through their targets. Therefore the selected miRNAs can be regarded as putative biomarkers for 10 types of cancer.

MicroRNA-208a-3p promotes osteosarcoma progression via targeting PTEN

Osteosarcoma (OS) is a malignant bone tumor with a poor prognosis. Accumulated evidence has suggested that microRNAs (miRNAs/miRs) may function as either oncogenes or tumor suppressors, which are associated with tumorigenesis and the progression of different types of cancer. In the present study, the role of miR-208a-3p in OS was investigated. The expression levels of miR-208a-3p in OS tissues and cell lines were determined via reverse transcription-quantitative PCR (RT-qPCR). MTT and colony formation assays were performed to verify the proliferation rate of OS cells. In addition, the effects of miR-208a-3p on the migration and invasion of OS cells were revealed using wound-healing and Transwell assays, respectively. Furthermore, the association between miR-208a-3p and phosphatase and tensin homolog (PTEN) 3'-untranslated region was determined via luciferase reporter assays, western blot and RT-qPCR analysis. The results indicated that miR-208a-3p was upregulated in OS tissues and cell lines compared with adjacent normal tissues and human osteoblastic cells, respectively. miR-208a-3p overexpression promoted and miR-208a-3p knockdown inhibited OS cells proliferation and metastatic potential. Additionally, PTEN was validated as a direct target of miR-208a-3p and its expression was negatively associate with that of miR-208a-3p in OS cells. Taken together, these results may suggest that miR-208a-3p promoted OS cells proliferation and metastatic potential via targeting PTEN. Therefore, miR-208a-3p may be considered as a diagnostic biomarker for OS.

Regulatory Mechanisms of Epigenetic miRNA Relationships in Human Cancer and Potential as Therapeutic Targets

Simple Summary

By the virtue of targeting multiple genes, a microRNA (miRNA) can infer variable consequences on tumorigenesis by appearing as both a tumour suppressor and oncogene. miRNAs can regulate gene expression by modulating genome-wide epigenetic status of genes that are involved in various cancers. These miRNAs perform direct inhibition of key mediators of the epigenetic machinery, such as DNA methyltransferases (DNMTs) and histone deacetylases (HDACs) genes. Along with miRNAs gene expression, similar to other protein-coding genes, miRNAs are also controlled by epigenetic mechanisms. Overall, this reciprocal interaction between the miRNAs and the epigenetic architecture is significantly implicated in the aberrant expression of miRNAs detected in various human cancers. Comprehensive knowledge of the miRNA-epigenetic dynamics in cancer is essential for the discovery of novel anticancer therapeutics.

Abstract

Initiation and progression of cancer are under both genetic and epigenetic regulation. Epigenetic modifications including alterations in DNA methylation, RNA and histone modifications can lead to microRNA (miRNA) gene dysregulation and malignant cellular transformation and are hereditary and reversible. miRNAs are small non-coding RNAs which regulate the expression of specific target genes through degradation or inhibition of translation of the target mRNA. miRNAs can target epigenetic modifier enzymes involved in epigenetic modulation, establishing a trilateral regulatory “epi–miR–epi” feedback circuit. The intricate association between miRNAs and the epigenetic architecture is an important feature through which to monitor gene expression profiles in cancer. This review summarises the involvement of epigenetically regulated miRNAs and miRNA-mediated epigenetic modulations in various cancers. In addition, the application of bioinformatics tools to study these networks and the use of therapeutic miRNAs for the treatment of cancer are also reviewed. A comprehensive interpretation of these mechanisms and the interwoven bond between miRNAs and epigenetics is crucial for understanding how the human epigenome is maintained, how aberrant miRNA expression can contribute to tumorigenesis and how knowledge of these factors can be translated into diagnostic and therapeutic tool development.

A Bioinformatic Analysis of MicroRNAs' Role in Human Intervertebral Disc Degeneration

Objectives The aim of our study was to ascertain the underlying role of microRNAs (miRNAs) in human intervertebral disc degeneration (IDD). Design Bioinformatic analysis from multiple databases. Methods Studies of the association of miRNAs and IDD were identified in multiple electronic databases. All potential studies were assessed by the same inclusion and exclusion criteria. We recorded whether miRNA expression was commonly increased or suppressed in the intervertebral disc tissues and cells of IDD subjects. We used String to identify biological process and cellular component pathways of differentially expressed genes. Results We included fifty-seven articles from 1,277 records in this study. This report identified 40 different dysregulated miRNAs in 53 studies, including studies examining cell apoptosis (26 studies, 49.06%), cell proliferation (15 studies, 28.3%), extracellular matrix (ECM) degradation (10 studies, 18.86%), and inflammation (five studies, 9.43%) in IDD patients. Three upregulated miRNAs (miR-19b, miR-32, miR-130b) and three downregulated miRNAs (miR-31, miR-124a, miR-127-5p) were considered common miRNAs in IDD tissues. The top three biological process pathways for upregulated miRNAs were positive regulation of biological process, nervous system development, and negative regulation of biological process, and the top three biological process pathways for downregulated miRNAs were negative regulation of gene expression, intracellular signal transduction, and negative regulation of biological process. Conclusions This study revealed that miRNAs could be novel targets for preventing IDD and treating patients with IDD by regulating their target genes. These results provide valuable information for medical professionals, IDD patients, and health care policy makers.

A Genome-Wide Study of Single-Nucleotide Polymorphisms in MicroRNAs and Further In Silico Analysis Reveals Their Putative Role in Susceptibility to Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (LOAD) is a neurodegenerative disorder of growing relevance in an aging society for which predictive biomarkers are needed. Many genes involved in LOAD are tightly controlled by microRNAs (miRNAs), which can be modulated by single-nucleotide polymorphisms (SNPs). Our aim was to determine the association between SNPs in miRNAs and LOAD. We selected all SNPs in pre-miRNAs with a minor allele frequency (MAF) > 1% and genotyped them in a cohort of 229 individuals diagnosed with LOAD and 237 unrelated healthy controls. In silico analyses were performed to predict the effect of SNPs on miRNA stability and detect downstream pathways. Four SNPs were associated with LOAD risk with a p value < 0.01 (rs74704964 in hsa-miR-518d, rs71363366 in hsa-miR-1283-2, rs11983381 in hsa-miR-4653, and rs10934682 in hsa-miR-544b). In silico analyses support a possible functional effect of those SNPs in miRNA levels and in the regulation of pathways of relevance for the development of LOAD. Although the results are promising, additional studies are needed to validate the association between SNPs in miRNAs and the risk of developing LOAD. Graphical abstract.

MicroRNA-7 targets T-Box 2 to inhibit epithelial-mesenchymal transition and invasiveness in glioblastoma multiforme

The dysregulation of microRNA expression in cancer has been associated with the epithelial-mesenchymal transition (EMT) that triggers invasive ability and increases therapeutic resistance. Here, we determined the microRNA expression profile of seven tumor tissues from patients with glioblastoma multiforme (GBM) by use of microRNA array analysis. We discovered that microRNA-7 (miR-7) is consistently downregulated in all tumor samples. Using the microRNA.org algorithm, the T-box 2 gene (TBX2) was identified as a candidate gene targeted by miR-7. In contrast to miR-7, TBX2 had an increased expression in GBM tumors and was linked to poor prognosis. We confirmed that TBX2 mRNA and protein production are significantly repressed by overexpressing miR-7 in GBM cells in vitro. The reporter assay showed that miR-7 significantly represses the signal from luciferase with the 3' UTR of TBX2. Furthermore, TBX2 overexpression decreased E-cadherin expression and increased Vimentin expression, causing an increasing number of invaded cells in the invasion assay, as well as pulmonary metastasis in vivo. Our findings demonstrated that overexpression of TBX2 in GBM tumors via the downregulation of miR-7 leads to EMT induction and increased cell invasion.