MicroRNA (Shariqah, United Arab Emirates)最新文献

Gastric cancer (GC) is the fourth most frequent disease in the world and the second cause of cancer-related death. In this way, over 80% of diagnoses are made in the middle to advanced degrees of the disease, underscoring the requirement for innovative biomarkers that can be identified quickly. Meaningly, biomarkers that can complement endoscopic diagnosis and be used to detect patients with a high risk of GC are desperately needed. These biomarkers will allow for the accurate prediction of therapy response and prognosis in GC patients, as well as the development of an optimal treatment strategy for each individual. Conspicuously, microRNAs (miRNAs) and small noncoding RNA regulate the expression of target mRNA, thereby modifying critical biological mechanisms. According to the data, abnormally miRNAs expression in GC is linked to tumor growth, carcinogenesis, aggression, and distant metastasis. Importantly, miRNA expression patterns and nextgeneration sequencing (NGS) can also be applied to analyze different kinds of tissues and cancers. Given the high death rates and poor prognosis of GC, and the absence of a clinical diagnostic factor that is adequately sensitive to GC, research on novel sensitive and specific markers for GC diagnosis is critical. In this review, we examine the latest research findings that suggest the feasibility and clinical utility of miRNAs in GC.

Background: Small non-coding micro RNAs (miRNAs) are indicated in various metabolic processes and play a critical role in disease pathology, including gestational diabetes mellitus (GDM).

Objective: The purpose of this study was to examine the altered expression of miRNAs and their target genes in placental tissue (PL), cord blood (CB), and maternal blood (MB) of matched non-glucose tolerant (NGT) and GDM mother.

Methods: In a case-control study, micro-RNA was quantified from forty-five serum (MB n = 15, CB n = 15, and PL n = 15) and matched placental tissue using stem-loop RT-qPCR followed by target prediction, network construction and functional and pathways enrichment analysis. Further, target genes were verified in-vitro through transfection and RT-qPCR.

Results: Five miRNAs, namely hsa-let 7a-5P, hsa-miR7-5P, hsa-miR9-5P, hsa-miR18a-5P, and hsamiR23a- 3P were significantly over-expressed (p < 0.05) in all three samples namely PL, CB, and MB of GDM patients. However, the sample-wise comparison reveals higher expression of miRNA 7 in MB while lowest in CB than control. Furthermore, a comparison of fold change expression of target genes discloses a lower expression of IRS1, IRS2, and RAF1 in MB while comparatively higher expression of NRAS in MB and CB. In-vitro validation reveals lower expression of IRS1/2 and RAF1 in response to overexpression of miR-7 and vice-versa. Thus it is evident that increased miRNA7 expression causes down-regulation of its target genes IRS1, IRS2, and RAF1 in GDM mother compared to control. Further, target prediction, pathway enrichment, and hormone analysis (significantly higher FSH & LH in MB of GDM compared to NGT) revealed insulin signaling, inflammatory and GnRH signaling as major pathways regulated by miRNA7.

Conclusion: Thus, an elevated level of miRNA7 may be associated with the progression of GDM by altering the multiple pathways like insulin, GnRH, and inflammatory signaling pathways via targeting IRS1, IRS2, and RAF1, implicating a new therapeutic target for GDM.

Background: Breast cancer (BC) is one of the main causes of cancer-related death in women worldwide. It is necessary to find methods for prognosis and early detection of BC. MicroRNAs inhibit the expression of special target genes at the post-transcriptional stage and have a fundamental role in various cancers. They function as oncogenes or tumor suppressors. MiR-125a- 5p acts as a tumor suppressor in some cancers through a signal transducer and activator of transcription 3 (STAT3) suppression. STAT3 is activated in response to cytokines and growth factors, affecting the transcription of target genes.

Objective: We examined the association between miR-125a-5p and STAT3 expression levels in breast cancer patients for the first time through a case-control study on an Iranian population.

Methods: Total RNAs were extracted from breast cancer and healthy tissues using TRIzol Reagent. Complementary DNA synthesis was performed, and Real-time PCR was done using miR-125a and STAT3-specific primers. GAPDH and U48 genes were used as internal controls. Statistical analysis of the results was conducted by SPSS v.19.0 software.

Results: We obtained a significant association between miR-125a-5p down-regulation and breast cancer disease (0.4333 in patients vs. 1.656 in controls, p-value = 0.009). STAT3 expression was significantly up-regulated in BC samples relative to healthy subjects (1.324 vs. 0.6557, respectively) and p-value <0.0001.

Conclusion: We investigated that decreased miR-125a-5p expression levels were significantly associated with increased STAT3 expression in BC tissues. Therefore, the expression changes of miR- 125a-5p can be an important potential biomarker for early diagnosis of breast cancer. Also, the miRNA molecule may have serious therapeutic potential.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate the translation of mRNA and protein, mainly at the posttranscriptional level. Global expression profiling of miRNAs has demonstrated a broad spectrum of aberrations that correlated with several diseases, and miRNA- 10a and miRNA-10b were the first examined miRNAs to be involved in abnormal activities upon dysregulation, including many types of cancers and progressive diseases. It is expected that the same miRNAs behave inconsistently within different types of cancer. This review aims to provide a set of information about our updated understanding of miRNA-10a and miRNA-10b and their clinical significance, molecular targets, current research gaps, and possible future applications of such potent regulators.

Allergic asthma is a complicated disease that is affected by many factors. Numerous cytokines and signaling pathways are attributed to the cause of asthma symptoms. MicroRNAs (miRNAs) are a group of small non-coding single-stranded RNA molecules that are involved in gene silencing and posttranscriptional regulation of gene expression by targeting mRNAs. In pathological conditions, altered expression of microRNAs differentially regulates cytokines and signaling pathways and therefore, can be the underlying reason for the pathogenesis of allergic asthma. Indeed, microRNAs participate in airway inflammation via inducing airway structural cells and activating immune responses by targeting cytokines and signaling pathways. Thus, to make a complete understanding of allergic asthma, it is necessary to investigate the communication network of microRNAs with cytokines and signaling pathways which is contributed to the pathogenesis of allergic asthma. Here, we shed light on this aspect of asthma pathology by Summarizing our current knowledge of this topic.

Background: Toxoplasma gondii (T. gondii) is an intracellular zoonotic protozoan parasite known to effectively modulate the host system for its survival. A large number of microRNAs (miRNAs) regulated by different strains of T. gondii in diverse types of host cells/tissues/organs have been reported across multiple studies.

Objective: We aimed to decipher the complexity of T. gondii regulated spectrum of miRNAs to derive a set of core miRNAs central to different strains of T. gondii infection in diverse human cell lines.

Methods: We first assembled miRNAs hat are regulated by T. gondii altered across the various assortment of infections and time points of T. gondii infection in multiple cell types. For these assembled datasets, we employed specific criteria to filter the core miRNAs regulated by T. gondii. Subsequently, accounting for the spectrum of miRNA-mRNA target combinations, we applied a novel confidence criterion to extract their core experimentally-validated mRNA targets in human cell systems.

Results: This analysis resulted in the extraction of 74 core differentially regulated miRNAs and their 319 high-confidence mRNA targets. Based on these core miRNA-mRNA pairs, we derived the central biological processes perturbed by T. gondii in diverse human cell systems. Further, our analysis also resulted in the identification of novel autocrine/paracrine signalling factors that could be associated with host response modulated by T. gondii.

Conclusion: The current analysis derived a set of core miRNAs, their targets, and associated biological processes fine-tuned by T. gondii for its survival within the invaded cells.

MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation and degradation of mRNA and have been associated with many diseases. Artificial Intelligence (AI) is an evolving cluster of interrelated fields, with machine learning (ML) standing out as one of the most prominent AI fields, with a plethora of applications in almost every aspect of human life. ML could be defined as computer algorithms that learn from past data to predict future data. This review comprehensively reviews the current applications of microRNA-based ML models in healthcare. The majority of the identified studies investigated the role of microRNA-based ML models in the management of cancer and specifically gastric cancer (maximum diagnostic accuracy (Accmax): 94%), pancreatic cancer (Accmax: 93%), colorectal cancer (Accmax: 100%), breast cancer (Accmax: 97%), ovarian cancer, neck squamous cell carcinoma, liver cancer, lung cancer (Accmax: 100%), and melanoma. Except for cancer, microRNA-based ML models have been applied for a plethora of other diseases, including ulcerative colitis (Accmax: 92.8%), endometriosis, gestational diabetes mellitus (Accmax: 86%), hearing loss, ischemic stroke, coronary heart disease (Accmax: 96%), tuberculosis, pulmonary arterial hypertension (Accmax: 83%), dementia (Accmax: 82.9%), major cardiovascular events in end-stage renal disease patients, and alcohol dependence (Accmax: 79.1%). Our findings suggest that the development of microRNA-based ML models could be used to enhance the diagnostic accuracy of a plethora of diseases while at the same time substituting or minimizing the use of more invasive diagnostic means (such as endoscopy). Even not as fast as anticipated, AI will eventually infiltrate the entire healthcare industry. AI is the key to a clinical practice where medicine's inherent complexity is embraced. Therefore, AI will become a reality that physicians should conform with to avoid becoming obsolete.

Viruses are microscopic biological entities that can cause diseases. Viruses require a host cell to replicate and generate progeny. Once inside, viruses hijack the main cellular machinery for their benefit, disrupting cell functions and causing detrimental effects on cell physiology. MicroRNAs are short, non-coding RNAs that regulate gene expression. Recent works have shown that cell-miRNAs can modulate antiviral defense during viral infection, and viruses can disrupt these existing miRNA networks. Furthermore, multiple RNA viruses encode their own miRNAs to evade the host immune response. In this review, we analyze the activities of both, miRNAs as pro-viral modulators and miRNAs as anti-viral agents and their relationship with the development of the disease.

Background: In 2019, severe acute respiratory coronavirus II (or SARS-COV-2) emerged in Wuhan, China, rapidly becoming a global pandemic. Coronavirus genus (Coronaviridae) has the largest single-stranded positive-sense RNA genome (~30 kb) among the human infected single-stranded RNA viruses.

Objectives: For the study of active therapeutic plant-derived miRNA(s), it may be possible to uptake the miRNAs and their biological role in the host cell. In this study, we bioinformatically searched plant miRNAs that can potentially interact with the Sars-CoV-2 genome within the 3'- UTR region and have prompt antiviral activity.

Materials and methods: We searched the plant miRNAs that target the 3'-UTR flanking region of the Sars-CoV-2 genome by employing the RNAHybrid, RNA22, and STarMir miRNA/target prediction tools.

Results: The RNAHybrid algorithm found 63 plant miRNAs having hybridization energy with less or equal to -25 kcal.mol-1. Besides, RNA22 and STarMir tools identified eight interactions between the plant miRNAs and the targeted RNA sequence. pvu-miR159a. 2 and sbi-miR5387b were predicted as the most effectively interacting miRNAs in targeting the 3'-UTR sequence, not only by the RNA22 tool but also by the STarMir tool at the same position. However, the GC content of the pvumiR159a. 2 is 55% instead of sbi-miR5387b, which is a GC enriched sequence (71.43%) that may activate TLR receptors.

Conclusion: In our opinion, they are potent plant-derived miRNA candidates that have a great chance of targeting the Sars-CoV-2 genome in the 3'-UTR region in vitro. Therefore, we propose pvu-miR159a.2 for studying antiviral miRNA-based therapies without any essential side effects in vivo.

It is estimated that 2-4% of live births will have a birth defect (BD). The availability of biomarkers for the prenatal detection of BDs will facilitate early risk assessment, prompt medical intervention and ameliorating disease severity. miRNA expression levels are often found to be altered in many diseases. There is, thus, a growing interest in determining whether miRNAs, particularly extracellular miRNAs, can predict, diagnose, or monitor BDs. These miRNAs, typically encapsulated in exosomes, are released by cells (including those of the fetus and placenta) into the extracellular milieu, such as blood, urine, saliva and cerebrospinal fluid, thereby enabling interaction with target cells. Exosomal miRNAs are stable, protected from degradation, and retain functionality. The observation that placental and fetal miRNAs can be detected in maternal serum, provides a strong rationale for adopting miRNAs as noninvasive prenatal biomarkers for BDs. In this mini-review, we examine the current state of research involving the use of miRNAs as prognostic and diagnostic biomarkers for BD.