This study aimed to identify differentially expressed non-coding RNAs (ncRNAs) associated with preterm birth (PTB) and determine biological pathways being influenced in the context of PTB. We processed cell-free RNA sequencing data and identified seventeen differentially expressed (DE) ncRNAs that could be involved in the onset of PTB. Per the validation via customized RT-qPCR, the recorded variations in expressions of eleven ncRNAs were concordant with the in-silico analyses. The results of this study provide insights into the role of DE ncRNAs and their impact on pregnancy-related biological pathways that could lead to PTB. Further studies are required to elucidate the precise mechanisms by which these DE ncRNAs contribute to adverse pregnancy outcomes (APOs) and their potential as diagnostic biomarkers.

Concussion affects over 400 000 Canadians annually, with a range of causes and impacts on health-related quality of life. Research to date has disproportionately focused on athletes, military personnel and level I trauma centre patients, and may not be applicable to the broader community. The TRANSCENDENT Concussion Research Program aims to address patient- and clinician-identified research priorities, through the integration of clinical data from patients of all ages and injury mechanisms, patient-reported outcomes and objective biomarkers across factors of intersectionality. Seeking guidance from our Community Advisory Committee will ensure meaningful patient partnership and research findings that are relevant to the wider concussion community.

This prospective observational cohort study will recruit 5500 participants over 5 years from three 360 Concussion Care clinic locations across Ontario, Canada, with a subset of participants enrolling in specific objective assessments including testing of autonomic function, exercise tolerance, vision, advanced neuroimaging and fluid biomarkers. Analysis will be predicated on pre-specified research questions, and data shared with the Ontario Brain Institute's Brain-CODE database. This work will represent one of the largest concussion databases to date, and by sharing it, we will advance the field of concussion and prevent siloing within brain health research.

This study was approved by the Children's Hospital of Eastern Ontario Research Ethics Board and preregistered on OSF (25 June 2024); https://doi.org/10.17605/OSF.IO/HYDZC. Dissemination of findings will be multifaceted, including conference presentations, peer-reviewed publications and sharing of adapted materials (eg, videos, infographics, plain language summaries) with community groups and key knowledge users.

Autism spectrum disorder (ASD) is a brain developmental disability with a not-fully clarified etiogenesis. Current ASD research largely focuses on coding regions of the genome, but up to date much less is known about the contribution of non-coding elements to ASD risk. The non-coding genome is largely made of DNA repetitive sequences (RS). Although RS were considered slightly more than "junk DNA", today RS have a recognized role in almost every aspect of human biology, especially in developing human brain. Our aim was to test if RS transcription may play a role in ASD.

Global RS transcription was firstly investigated in postmortem dorsolateral prefrontal cortex of 13 ASD patients and 39 matched controls. Results were validated in independent datasets.

AmnSINE1 was the only RS significantly downregulated in ASD specimens. The role of AmnSINE1 in ASD has been investigated at multiple levels, showing that the 1,416 genes containing AmnSINE1 are associated with nervous system development and autism susceptibility. This has been confirmed in a different experimental setting, such as in organoid models of the human cerebral cortex, harboring different ASD causative mutations. AmnSINE1 related genes are transcriptionally co-regulated and are involved not only in brain formation but can specifically be involved in ASD development. Looking for a possible direct role of AmnSINE1 non-coding transcripts in ASD, we report that AmnSINE1 transcripts may alter the miRNA regulatory landscape for genes involved in neurogenesis.

Our findings provide preliminary evidence supporting a role for AmnSINE1 in ASD development.

Epigenetics and epigenomics are captivating fields of molecular biology, dedicated to the exploration of heritable alterations in gene expression and cellular phenotypes, which transpire devoid of any discernible modifications to the fundamental DNA sequence. This intricate regulatory apparatus encompasses multiple mechanisms, prominently featuring DNA methylation, histone modifications, and the involvement of non-coding RNA molecules in pivotal roles. To achieve a comprehensive grasp of these diverse mechanisms, it is imperative to conduct research employing animal models as proxies for human studies. Since experimental animal models like mice and rats struggle to replicate the diverse environmental conditions experienced by humans, this review focuses on comparing common epigenetic alterations in naturally occurring tumors in canine models, which share the human environment, with those in humans. Through this, we emphasize the importance of an epigenetic regulation in the comparative medical approach to a deeper understanding of cancers and further development of cancer treatments. Additionally, we elucidate epigenetic modifications pertinent to specific developmental stages, the ageing process, and the progression of various diseases.

Spotted knifejaw (Oplegnathus punctatus), an economically important species in marine aquaculture, employs a unique sex determination mechanism based on a complex sex chromosome system (X1X1X2X2/X1X2Y). Males (2n = 47) possess one fewer chromosome than females (2n = 48), and their karyotype includes an unusually large neo-Y chromosome. Additionally, a pronounced sexual dimorphism in growth rate is observed, with males exhibiting a faster growth rate than females. In this study, we conducted a comprehensive whole-genome scan, which initially revealed structural variations in the anti-inflammatory itih4 gene between male and female O. punctatus. Additionally, we designed a pair of primers to detect DNA sequence variations within the itih4a/itih4b gene. These variations are located in the intergenic region of the fusion Y chromosome in male O. punctatus, compared to the homologous X chromosome in females. In females without DNA insertions in the itih4a/itih4b intergenic region, a single band of 351 bp is amplified. By contrast, in males with DNA insertions, two bands are amplified (755 bp and 351 bp). The 755 bp band specifically indicates the presence of a DNA insertion in the itih4a/itih4b intergenic region on the Y chromosome, associated with male-specific genetic traits. Our study will facilitate the rapid identification of the genetic sex of both male and female O. punctatus individuals.

Long non-coding RNA (LncRNA) play pivotal roles in various cellular processes, and elucidating their subcellular localization can offer crucial insights into their functional significance. Accurate prediction of lncRNA subcellular localization is of paramount importance. Despite numerous computational methods developed for this purpose, existing approaches still encounter challenges stemming from the complexity of data representation and the difficulty in capturing nucleotide distribution information within sequences.

In this study, we propose a novel deep learning-based model, termed MGBLncLoc, which incorporates a unique multi-class encoding technique known as generalized encoding based on the Distribution Density of Multi-Class Nucleotide Groups (MCD-ND). This encoding approach enables more precise reflection of nucleotide distributions, distinguishing between constant and discriminative regions within sequences, thereby enhancing prediction performance. Additionally, our deep learning model integrates advanced neural network modules, including Multi-Dconv Head Transposed Attention, Gated-Dconv Feed-forward Network, Convolutional Neural Network, and Bidirectional Gated Recurrent Unit, to comprehensively exploit sequence features of lncRNA.

Comparative analysis against commonly used sequence feature encoding methods and existing prediction models validates the effectiveness of MGBLncLoc, demonstrating superior performance. This research offers novel insights and effective solutions for predicting lncRNA subcellular localization, thereby providing valuable support for related biological investigations.

The aim of this study was to summarize the main findings of non-coding RNA (ncRNAs) in Turner syndrome (TS), correlating these biomolecules with the clinical manifestations in affected patients.

Searches were conducted in the databases of the United States National Library of Medicine (PubMed), Scientific Electronic Library Online (SciELO), and ScienceDirect, covering original English articles published from 2014 to 2023. Descriptors used included "lncRNAs and Turner Syndrome," "miRNAs and Turner Syndrome," and "circRNAs and Turner Syndrome." The studies that were included addressed the role of ncRNAs in the clinical characteristics of patients with TS. Exclusion criteria comprised texts in abstracts, reports, reviews, and monographs.

We identified 147 studies, of which seven were included. In the analysis of microRNAs, miR-486-5p and miR-320a stood out, being associated with ovarian development; miR-126-3p and miR-126-5p were related to greater aortic stiffness. Regarding long non-coding RNAs, the downregulation of XIST indicated dysfunctions in X chromosome inactivation. Concerning circular RNAs, circPPP2R3B, circCSF2RA, and circPCTN were related to immunological functions, while circ_0090421, circ_0090392, and circ_0089945 were linked to cardiac development.

The data from these studies demonstrate that these biomolecules play crucial roles in processes related to specific characteristics observed in TS patients. Besides being suggested as potential biomarkers, they may be useful in clinical practice.

Oral cancers are a significant global health concern, with a high incidence of treatment failure primarily due to the development of drug resistance. Long non-coding RNAs (lncRNAs) have emerged as critical regulators of gene expression, playing pivotal roles in various cellular processes, including tumor progression and response to therapy. This review explores the multifaceted roles of lncRNAs in the development of drug resistance in oral cancers. We highlight the mechanisms by which lncRNAs modulate drug efflux, apoptosis, epithelial-mesenchymal transition (EMT), and other pathways associated with chemoresistance. Key lncRNAs implicated in resistance to commonly used chemotherapeutic agents in oral cancers are discussed, along with their potential as therapeutic targets. Understanding the involvement of lncRNAs in drug resistance mechanisms offers promising avenues for overcoming treatment barriers and improving patient outcomes. This review underscores the need for further research to elucidate the precise roles of lncRNAs in oral cancer resistance and their translation into clinical interventions.

Long noncoding RNAs (lncRNAs) have been implicated in a diverse array of human immune diseases; however, a comprehensive understanding of the expression and function of lncRNAs in the peripheral blood leukocytes of individuals suffering from house dust mite (HDM)-induced allergic rhinitis (AR) remains elusive.

To explore the potential roles and functions of long noncoding RNAs (lncRNAs) in the pathogenesis of AR.

Sequencing analysis was performed on peripheral blood leukocytes collected from patients with HDM-induced AR and healthy controls (HCs) to elucidate the expression patterns of lncRNAs. Differentially expressed (DE) lncRNAs were identified and validated, and further correlation analyses were conducted to explore their associations with visual analog scale (VAS) scores and cytokine levels in the serum and nasal secretions. Additionally, bioinformatics analyses were performed to predict the potential pathways influenced by DE lncRNAs. Finally, the diagnostic potential of these lncRNAs in AR was assessed via receiver operating characteristic (ROC) curve analysis.

Significant differences in the expression profiles of lncRNAs and mRNAs were detected between AR patients and HCs. Four lncRNAs were markedly upregulated in AR patients. AC011524.2 was positively correlated with nasal pruritus (r = 0.4492, P = 0.0411). AL133371.3 was positively correlated with runny nose (r = 0.4889, P = 0.0245). AC011524.2 was positively correlated with CXCL8 (r = 0.4504, P = 0.0035). AL133371.3 was significantly positively correlated with only IL-17 (r = 0.4028, P = 0.0100). IL-4 in the serum was positively related to IL-17 in the serum (r = 0.4163, P = 0.0002). CXCL5 in the serum was positively correlated with IFN-γ (r = 0.3336, P = 0.0354) in nasal secretions. The area under the curve (AUC) of the ROC curve resulting from the integration of the 4 lncRNAs exhibited a remarkable value of 0.940 for AR diagnosis.

Our results identified several lncRNAs associated with AR symptoms and inflammatory cytokines. Specifically, AC011524.2 and AL133371.3 exhibited strong correlations with diverse AR manifestations and serum cytokines, suggesting their pivotal role in the pathogenesis of AR, likely via neutrophil- and Th17-related pathways. However, the precise underlying mechanisms are still elusive, necessitating further exploration.

Long noncoding RNAs (lncRNAs) have been discovered to be extensively involved in eukaryotic epigenetic, transcriptional, and post-transcriptional regulatory processes with the advancements in sequencing technology and genomics research. Therefore, they play crucial roles in the body's normal physiology and various disease outcomes. Presently, numerous unknown lncRNA sequencing data require exploration. Establishing deep learning-based prediction models for lncRNAs provides valuable insights for researchers, substantially reducing time and costs associated with trial and error and facilitating the disease-relevant lncRNA identification for prognosis analysis and targeted drug development as the era of artificial intelligence progresses. However, most lncRNA-related researchers lack awareness of the latest advancements in deep learning models and model selection and application in functional research on lncRNAs. Thus, we elucidate the concept of deep learning models, explore several prevalent deep learning algorithms and their data preferences, conduct a comprehensive review of recent literature studies with exemplary predictive performance over the past 5 years in conjunction with diverse prediction functions, critically analyze and discuss the merits and limitations of current deep learning models and solutions, while also proposing prospects based on cutting-edge advancements in lncRNA research.

When mRNAs have been transcribed and processed in the nucleus, they are exported to the cytoplasm for translation. This export is mediated by the export receptor heterodimer Mex67-Mtr2 in the yeast Saccharomyces cerevisiae (TAP-p15 in humans)1,2. Interestingly, many long non-coding RNAs (lncRNAs) also leave the nucleus but it is currently unclear why they move to the cytoplasm3. Here we show that antisense RNAs (asRNAs) accelerate mRNA export by annealing with their sense counterparts through the helicase Dbp2. These double-stranded RNAs (dsRNAs) dominate export compared with single-stranded RNAs (ssRNAs) because they have a higher capacity and affinity for the export receptor Mex67. In this way, asRNAs boost gene expression, which is beneficial for cells. This is particularly important when the expression program changes. Consequently, the degradation of dsRNA, or the prevention of its formation, is toxic for cells. This mechanism illuminates the general cellular occurrence of asRNAs and explains their nuclear export.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta, leading to motor and non-motor symptoms. Emerging evidence suggests that inflammation plays a crucial role in the pathogenesis of PD, with the NLRP3 inflammasome implicated as a key mediator. Nfon-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), have recently garnered attention for their regulatory roles in various biological processes, including inflammation. This review aims to provide a mechanistic insight into how ncRNAs function as regulators of inflammatory pathways in PD, with a specific focus on the NLRP3 inflammasome. We discuss the dysregulation of miRNAs and lncRNAs in PD pathogenesis and their impact on neuroinflammation through modulation of NLRP3 activation, cytokine production, and microglial activation. Additionally, we explore the crosstalk between ncRNAs, alpha-synuclein pathology, and mitochondrial dysfunction, further elucidating the intricate network underlying PD-associated inflammation. Understanding the mechanistic roles of ncRNAs in regulating inflammatory pathways may offer novel therapeutic targets for the treatment of PD and provide insights into the broader implications of ncRNA-mediated regulation in neuroinflammatory diseases.

Diabetes mellitus, a chronic metabolic disease, often leads to numerous chronic complications, significantly contributing to global morbidity and mortality rates. High glucose levels trigger epigenetic modifications linked to pathophysiological processes like inflammation, immunity, oxidative stress, mitochondrial dysfunction, senescence and various kinds of cell death. Despite glycemic control, transient hyperglycemia can persistently harm organs, tissues, and cells, a latent effect termed "metabolic memory" that contributes to chronic diabetic complications. Understanding metabolic memory's mechanisms could offer a new approach to mitigating these complications. However, key molecules and networks underlying metabolic memory remain incompletely understood. This review traces the history of metabolic memory research, highlights its key features, discusses recent molecules involved in its mechanisms, and summarizes confirmed and potential therapeutic compounds. Additionally, we outline in vitro and in vivo models of metabolic memory. We hope this work will inform future research on metabolic memory's regulatory mechanisms and facilitate the development of effective therapeutic compounds to prevent diabetic complications.

Bovine intramuscular fat (IMF), commonly referred to as marbling, is regulated by lipid metabolism, which includes adipogenesis, lipogenesis, glycerolipid synthesis, and lipolysis. In recent years, breeding researchers have identified single nucleotide polymorphisms (SNPs) as useful marker-assisted selection tools for improving marbling scores in national breeding programs. These included causal SNPs that induce phenotypic variation. MicroRNAs (miRNAs) are small highly conserved non-coding RNA molecules that bind to multiple non-coding regions. They are involved in post-transcriptional regulation. Multiple miRNAs may regulate a given target. Previously, three SNPs in the GPAM 3' UTR and four miRNAs were identified through in silico assays. The aim of this study is to verify the binding ability of the four miRNAs to the SNPs within the 3'UTR of GPAM, and to identify the regulatory function of miR-375 in the expression of genes related to lipid metabolism in mammalian adipocytes. It was verified that the four miRNAs bind to the GPAM 3'UTR, and identified that the miR-375 sequence is highly conserved. Furthermore, it was founded that miR-375 upregulated the GPAM gene, C/EBPα, PPARγ and lipid metabolism-related genes and promoted lipid droplet accumulation in 3T3-L1 cells. In conclusion, these results suggest that miR-375 is a multifunctional regulator of multiple lipid metabolism-related genes and may aid in obesity research as a biomarker.

The role of red blood cells (RBCs) in tumorigenesis is poorly understood. We previously identified RBC-microRNAs with aberrations linked to lung cancer, including miR-93-5p. Here we find that miR-93-5p levels are elevated in RBC-derived exosomes among lung cancer patients and are associated with their shorter survivals. RBC-derived miR-93-5p transfers to cancer cells primarily through the exosomal pathway. The transferred RBC-miR-93-5p can target PTEN in cancer cells, and hence increase cell proliferation, invasion, and migration. RBC-derived miR-93-5p accelerates, whereas targeting miR-93-5p diminishes tumor growth in xenograft models. These findings reveal a novel biological function of RBCs in tumorigenesis, where they facilitate cancer progression by transferring the oncomiR via exosomes, thereby offering new diagnostic and treatment strategies for lung cancer.

Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients.

Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified. A prognostic model was developed using univariate Cox and LASSO-Cox analysis based on SRlncRNAs. The performance of the model was evaluated using Kaplan-Meier analysis, ROC curves, and ROC-AUC. Additionally, the study delved into the underlying signaling pathways and immune status associated with the divergent prognoses of TNBC patients.

The research identified a signature of six SRlncRNAs (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, and MIR193BHG) for TNBC. Risk scores derived from this signature were found to correlate with the abundance of plasma cells. Furthermore, the nominated chemotherapy drugs for TNBC exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns of these SRlncRNAs in TNBC stem cells, affirming the potential of the SRlncRNAs signature as a prognostic biomarker.

The identified signature not only demonstrates predictive power in terms of patient outcomes but also provides insights into the underlying biology, signaling pathways, and immune status associated with TNBC prognosis. The findings suggest the possibility of guiding personalized treatments, including immune checkpoint gene therapy and chemotherapy strategies, based on the risk scores derived from the SRlncRNA signature. Overall, this research contributes valuable knowledge towards advancing precision medicine in the context of TNBC.

Condyloma acuminatum (CA) is a prevalent sexually transmitted disease caused by low-risk human papillomavirus infection, characterized by high transmission and recurrence rates. Long non-coding RNAs (lncRNAs) play a crucial role in regulating gene transcription and are involved in various biological processes. Although recent studies have demonstrated the involvement of lncRNAs in cervical cancer, their expression profile and function in CA remain poorly understood. In this study, we aimed to identify messenger RNA (mRNA) and lncRNA expression patterns in CA using high-throughput lncRNA sequencing. We found that 3033 differentially expressed genes (DEGs) and 1090 differentially expressed lncRNAs (DELs) were significantly altered in CA compared to healthy controls. The results from quantitative reverse transcription polymerase chain reaction and immunohistochemical staining are in accordance with the observed trends in the sequencing data. Functional enrichment analysis revealed that upregulated DEGs in CA were involved in biological processes such as virus response, immune response, cell cycle regulation, the tumor necrosis factor signaling pathway, and the P53 signaling pathway. Co-expression network analysis identified potential target genes of DELs, with enrichment in biological processes such as cell differentiation, the intrinsic apoptotic signaling pathway, and pathways such as virus infection, pathways in cancer, T helper 17 cell differentiation, the mitogen-activated protein kinase signaling pathway, and the Wnt signaling pathway. Collectively, our findings indicate significant changes in the transcriptome profile, including mRNAs and lncRNAs, in CA compared to healthy controls. Our study provides new insights into the potential functions of lncRNAs in the pathogenesis of CA and identifies potential therapeutic targets for this disease.

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.

Exosomes are extracellular vesicles that can contain DNA, RNA, proteins, and metabolites. They are secreted by cells and play a regulatory role in various biological responses by mediating cell-to-cell communication. Moreover, exosomes are of interest in developing therapies for retinal vascular disorders because they can deliver various substances to cellular targets. According to recent research, exosomes can be used as a strategy for managing retinal vascular diseases, and they are being investigated for therapeutic purposes in eye conditions, including glaucoma, dry eye syndrome, retinal ischemia, diabetic retinopathy, and age-related macular degeneration. However, the role of exosomal noncoding RNA in retinal vascular diseases is not fully understood. Here, we reviewed the latest research on the biological role of exosomal noncoding RNA in treating retinal vascular diseases. Research has shown that noncoding RNAs, including microRNAs, circular RNAs, and long noncoding RNAs play a significant role in the regulation of retinal vascular diseases. Furthermore, through exosome engineering, the expression of relevant noncoding RNAs in exosomes can be controlled to regulate retinal vascular diseases. Therefore, this review suggests that exosomal noncoding RNA could be considered as a biomarker for diagnosis and as a therapeutic target for treating retinal vascular disease.

Multidrug resistance (MDR) is one of the primary factors that produces treatment failure in patients receiving cancer chemotherapy. MDR is a complex multifactorial phenomenon, characterized by a decrease or abrogation of the efficacy of a wide spectrum of anticancer drugs that are structurally and mechanistically distinct. The overexpression of the ATP-binding cassette (ABC) transporters, notably ABCG2 and ABCB1, are one of the primary mediators of MDR in cancer cells, which promotes the efflux of certain chemotherapeutic drugs from cancer cells, thereby decreasing or abolishing their therapeutic efficacy. A number of studies have suggested that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), play a pivotal role in mediating the upregulation of ABC transporters in certain MDR cancer cells. This review will provide updated information about the induction of ABC transporters due to the aberrant regulation of ncRNAs in cancer cells. We will also discuss the measurement and biological profile of circulating ncRNAs in various body fluids as potential biomarkers for predicting the response of cancer patients to chemotherapy. Sequence variations, such as alternative polyadenylation of mRNA and single nucleotide polymorphism (SNPs) at miRNA target sites, which may indicate the interaction of miRNA-mediated gene regulation with genetic variations to modulate the MDR phenotype, will be reviewed. Finally, we will highlight novel strategies that could be used to modulate ncRNAs and circumvent ABC transporter-mediated MDR.

Neuroinflammation is considered a balanced inflammatory response important in the intrinsic repair process after injury or infection. Under chronic states of disease, injury, or infection, persistent neuroinflammation results in a heightened presence of cytokines, chemokines, and reactive oxygen species that result in tissue damage. In the CNS, the surrounding microglia normally contain macrophages and other innate immune cells that perform active immune surveillance. The resulting cytokines produced by these macrophages affect the growth, development, and responsiveness of the microglia present in both white and gray matter regions of the CNS. Controlling the levels of these cytokines ultimately improves neurocognitive function and results in the repair of lesions associated with neurologic disease. MicroRNAs (miRNAs) are master regulators of the genome and subsequently control the activity of inflammatory responses crucial in sustaining a robust and acute immunological response towards an acute infection while dampening pathways that result in heightened levels of cytokines and chemokines associated with chronic neuroinflammation. Numerous reports have directly implicated miRNAs in controlling the abundance and activity of interleukins, TGF-B, NF-kB, and toll-like receptor-signaling intrinsically linked with the development of neurological disorders such as Parkinson's, ALS, epilepsy, Alzheimer's, and neuromuscular degeneration. This review is focused on discussing the role miRNAs play in regulating or initiating these chronic neurological states, many of which maintain the level and/or activity of neuron-specific secondary messengers. Dysregulated miRNAs present in the microglia, astrocytes, oligodendrocytes, and epididymal cells, contribute to an overall glial-specific inflammatory niche that impacts the activity of neuronal conductivity, signaling action potentials, neurotransmitter robustness, neuron-neuron specific communication, and neuron-muscular connections. Understanding which miRNAs regulate microglial activation is a crucial step forward in developing non-coding RNA-based therapeutics to treat and potentially correct the behavioral and cognitive deficits typically found in patients suffering from chronic neuroinflammation.

Metabolic diseases and their complications impose health and economic burdens worldwide. Evidence from past experimental studies and clinical trials suggests our body may have the ability to remember the past metabolic environment, such as hyperglycemia or hyperlipidemia, thus leading to chronic inflammatory disorders and other diseases even after the elimination of these metabolic environments. The long-term effects of that aberrant metabolism on the body have been summarized as metabolic memory and are found to assume a crucial role in states of health and disease. Multiple molecular mechanisms collectively participate in metabolic memory management, resulting in different cellular alterations as well as tissue and organ dysfunctions, culminating in disease progression and even affecting offspring. The elucidation and expansion of the concept of metabolic memory provides more comprehensive insight into pathogenic mechanisms underlying metabolic diseases and complications and promises to be a new target in disease detection and management. Here, we retrace the history of relevant research on metabolic memory and summarize its salient characteristics. We provide a detailed discussion of the mechanisms by which metabolic memory may be involved in disease development at molecular, cellular, and organ levels, with emphasis on the impact of epigenetic modulations. Finally, we present some of the pivotal findings arguing in favor of targeting metabolic memory to develop therapeutic strategies for metabolic diseases and provide the latest reflections on the consequences of metabolic memory as well as their implications for human health and diseases.

Long noncoding RNAs have been shown to be involved in a myriad of physiological and pathological pathways. To date, malignant pleural mesothelioma (MPM) is considered an extremely aggressive cancer. One reason for this is the late diagnosis of the disease, which can occur within 30-40 years of asbestos exposure. There is an immense need for the development of new, sensitive, inexpensive and easy methods for the early detection of this disease other than invasive methods such as biopsy. The aim of this study was to determine the expression of circulating lncRNAs in mesothelioma patient plasma to identify potential biomarkers. Ten previously identified lncRNAs that were shown to be aberrantly expressed in mesothelioma tissues were selected as candidates for subsequent validation. The expression of the ten selected candidate lncRNAs was verified via quantitative PCR (qPCR) in human plasma samples from mesothelioma patients versus healthy controls. The expression levels of circulating GAS5, SNHG8 and MALAT1 were significantly greater in plasma samples from patients than in those from controls. The ROC analysis of both MALAT1 and SNHG8 revealed 88.89% sensitivity and 66.67% specificity. The sensitivity of these markers was greater than that of GAS5 (sensitivity 72.22% and specificity 66.67%). The regression model for GAS5 was statistically significant, while that for SNHG8 and MALAT1 was not significant due to the small sample size. The area under the curve (AUC) of the three ROC curves was acceptable and significant: 0.7519 for GAS5, 0.7352 for SNHG8 and 0.7185 for MALAT1. This finding confirmed their ability to be used as markers. The three lncRNAs were not affected by age, sex or smoking status. The three lncRNAs showed great potential as independent predictive diagnostic biomarkers. Although the prediction model for MALAT1 did not significantly differ, MALAT1 was significantly expressed in patients more than in controls (p = 0.0266), and the recorded sensitivity and specificity were greater than those of GAS5.

Non-coding RNA (ncRNA) plays an important role in many fundamental biological processes, and it may be closely associated with many complex human diseases. NcRNAs exert their functions by interacting with proteins. Therefore, identifying novel ncRNA-protein interactions (NPIs) is important for understanding the mechanism of ncRNAs role. The computational approach has the advantage of low cost and high efficiency. Machine learning and deep learning have achieved great success by making full use of sequence information and structure information. Graph neural network (GNN) is a deep learning algorithm for complex network link prediction, which can extract and discover features in graph topology data. In this study, we propose a new computational model called GATLGEMF. We used a line graph transformation strategy to obtain the most valuable feature information and input this feature information into the attention network to predict NPIs. The results on four benchmark datasets show that our method achieves superior performance. We further compare GATLGEMF with the state-of-the-art existing methods to evaluate the model performance. GATLGEMF shows the best performance with the area under curve (AUC) of 92.41% and 98.93% on RPI2241 and NPInter v2.0 datasets, respectively. In addition, a case study shows that GATLGEMF has the ability to predict new interactions based on known interactions. The source code is available at https://github.com/JianjunTan-Beijing/GATLGEMF.

In recent decades, colorectal cancer (CRC) has turned into one of the most widespread malignancies, and the incidence of this malignancy is expected to increase. Despite considerable improvements in therapeutic approaches, the prognosis, and the management of CRC face many problems. Likely, the main limitation in the successful treatment of CRC is the lack of appropriate clinical therapeutic targets. As an effective target, the signal transducer and activator of transcription 3 (STAT3) are regulated by a wide range of genes and involved in cellular processes, including cell growth, migration, invasion, immunosuppression, and angiogenesis. Aberrant regulation of STAT3 signaling leads to cellular dysfunction, diseases, and malignancies, including CRC. Consequently, targeting this signaling pathway is considered one of the therapeutic strategies used in CRC treatment. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are non-coding RNA molecules with partial or no protein-coding activity that participate in gene regulation at epigenetic, transcriptional, and post-transcriptional levels and regulate multiple signaling pathways, including STAT3 signaling (especially JAK/STAT). Therefore, these regulatory molecules are suggested to be very promising targets to present new insights into overcoming the limitations of conventional therapeutic strategies. Therefore, the current review study aimed to summarize the therapeutic and diagnostic significance of miRNAs and lncRNAs and their therapeutic and diagnostic significance related to the expression and activity of STAT3 in CRC.

Urothelial carcinoma (UC) is a common malignancy that remains a clinical challenge: Non-muscle-invasive urothelial carcinoma (NMIUC) has a high rate of recurrence and risk of progression, while muscle-invasive urothelial carcinoma (MIUC) has a high mortality. Although some new treatments, such as immunotherapies, have shown potential effects on some patients, most cases of advanced UC remain incurable. While treatments based on epigenetic mechanisms, whether combined with traditional platinum-based chemotherapy or emerging immunotherapy, show therapeutic advantages. With the advancement of sequencing and bioinformatics, the study of epigenomics, containing DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA, is increasingly linked with the occurrence and progression of UC. Since the epigenetics of UC is a constantly developing field of medicine, this review aims to summarize the latest research on epigenetic regulation of UC, generalize the mechanism of epigenetics in UC, and reveal the potential epigenetic therapies in the clinical setting, in order to provide some new clues on the discovery of new drugs based on the epigenetics.

MicroRNAs (miRNAs) are a type of non-coding RNA whose dysregulation is frequently associated with the onset and progression of human cancers. miR-142, an ultra-conserved miRNA with both active -3p and -5p mature strands and wide-ranging physiological targets, has been the subject of countless studies over the years. Due to its preferential expression in hematopoietic cells, miR-142 has been found to be associated with numerous types of lymphomas and leukemias. This review elucidates the multifaceted role of miR-142 in human physiology, its influence on hematopoiesis and hematopoietic cells, and its intriguing involvement in exosome-mediated miR-142 transport. Moreover, we offer a comprehensive exploration of the genetic and molecular landscape of the miR-142 genomic locus, highlighting its mutations and dysregulation within hematological malignancies. Finally, we discuss potential avenues for harnessing the therapeutic potential of miR-142 in the context of hematological malignancies.

In contrast to miRNA expression, little attention has been given to piwiRNA (piRNA) expression among endometriosis patients. The aim of the present study was to explore the human piRNAome and to investigate a potential piRNA saliva-based diagnostic signature for endometriosis.

Data from the prospective "ENDOmiRNA" study (ClinicalTrials.gov Identifier: NCT04728152) were used. Saliva samples from 200 patients were analyzed in order to evaluate human piRNA expression using the piRNA bank. Next Generation Sequencing (NGS), barcoding of unique molecular identifiers and both Artificial Intelligence (AI) and machine learning (ML) were used. For each piRNA, sensitivity, specificity, and ROC AUC values were calculated for the diagnosis of endometriosis.

201 piRNAs were identified, none had an AUC ≥ 0.70, and only three piRNAs (piR-004153, piR001918, piR-020401) had an AUC between ≥ 0.6 and < 0.70. Seven were differentially expressed: piR-004153, piR-001918, piR-020401, piR-012864, piR-017716, piR-020326 and piR-016904. The respective correlation and accuracy to diagnose endometriosis according to the F1-score, sensitivity, specificity, and AUC ranged from 0 to 0.862 %, 0-0.961 %, 0.085-1, and 0.425-0.618. A correlation was observed between the patients' age (≥35 years) and piR-004153 (p = 0.002) and piR-017716 (p = 0.030). Among the 201 piRNAs, four were differentially expressed in patients with and without hormonal treatment: piR-004153 (p = 0.015), piR-020401 (p = 0.001), piR-012864 (p = 0.036) and piR-017716 (p = 0.009).

Our results support the link between piRNAs and endometriosis physiopathology and establish its utility as a potential diagnostic biomarker using saliva samples. Per se, piRNA expression should be analyzed along with the clinical status of a patient.

The PI3K/AKT/mTOR signaling pathway plays a significant role in the development of T-cell acute lymphoblastic leukemia (T-ALL). Rapamycin is a potential therapeutic strategy for hematological malignancies due to its ability to suppress mTOR activity. Additionally, microRNAs (miRNAs) have emerged as key regulators in T-ALL pathophysiology and treatment. This study aimed to investigate the combined effects of rapamycin and miRNAs in inhibiting the PI3K/AKT/mTOR pathway in T-ALL cells.

Bioinformatic algorithms were used to find miRNAs that inhibit the PI3K/AKT/mTOR pathway. Twenty-five bone marrow samples were collected from T-ALL patients, alongside five control bone marrow samples from non-leukemia patients. The Jurkat cell line was chosen as a representative model for T-ALL. Gene and miRNA expression levels were assessed using quantitative real-time PCR (qRT-PCR). Two miRNAs exhibiting down-regulation in both clinical samples and Jurkat cells were transfected to the Jurkat cell line to investigate their impact on target gene expression. Furthermore, in order to evaluate the potential of combination therapy involving miRNAs and rapamycin, apoptosis and cell cycle assays were carried out.

Six miRNAs (miR-3143, miR-3182, miR-99a/100, miR-155, miR-576-5p, and miR-501- 3p) were predicted as inhibitors of PI3K/AKT/mTOR pathway. The expression analysis of both clinical samples and the Jurkat cell line revealed a simultaneous downregulation of miR-3143 and miR-3182. Transfection investigation demonstrated that the exogenous overexpression of miR-3143 and miR-3182 can effectively inhibit PI3K/AKT/mTOR signaling in the Jurkat cell line. Moreover, when used as a dual inhibitor along with rapamycin, miR-3143 and miR-3182 significantly increased apoptosis and caused cell cycle arrest in the Jurkat cell line.

These preliminary results highlight the potential for improving T-ALL treatment through multi-targeted therapeutic strategies involving rapamycin and miR-3143/miR-3182.

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas technology is a molecular tool specific to sequences for engineering genomes. Among diverse clusters of Cas proteins, the class 2/type II CRISPR/Cas9 system, despite several challenges, such as off-target effects, editing efficiency, and efficient delivery, has shown great promise for driver gene mutation discovery, high-throughput gene screening, epigenetic modulation, nucleic acid detection, disease modeling, and more importantly for therapeutic purposes. CRISPR-based clinical and experimental methods have applications across a wide range of areas, especially for cancer research and, possibly, anticancer therapy. On the other hand, given the influential role of microRNAs (miRNAs) in the regulations of cellular division, carcinogenicity, tumorigenesis, migration/invasion, and angiogenesis in diverse normal and pathogenic cellular processes, in different stages of cancer, miRNAs are either oncogenes or tumor suppressors, according to what type of cancer they are involved in. Hence, these noncoding RNA molecules are conceivable biomarkers for diagnosis and therapeutic targets. Moreover, they are suggested to be adequate predictors for cancer prediction. Conclusive evidence proves that CRISPR/Cas system can be applied to target small non-coding RNAs. However, the majority of studies have highlighted the application of the CRISPR/Cas system for targeting protein-coding regions. In this review, we specifically discuss diverse applications of CRISPR-based tools for probing miRNA gene function and miRNA-based therapeutic involvement in different types of cancers.

Epilepsy is a neurological disorder that impacts millions of people worldwide, and it is characterized by the occurrence of recurrent seizures. The pathogenesis of epilepsy is complex, involving dysregulation of various genes and signaling pathways. MicroRNAs (miRNAs) are a group of small non-coding RNAs that play a vital role in the regulation of gene expression. They have been found to be involved in the pathogenesis of epilepsy, acting as key regulators of neuronal excitability and synaptic plasticity. In recent years, there has been a growing interest in exploring the miRNA regulatory network in epilepsy. This review summarizes the current knowledge of the regulatory miRNAs involved in inflammation and apoptosis in epilepsy and discusses its potential as a new avenue for developing targeted therapies for the treatment of epilepsy.

There is evidence to suggest that microRNA-140-5p (miR-140), which acts as a suppressor, is often elevated and has a role in various malignancies. Nevertheless, neither the function nor the mechanisms in chondrocytes linked with bone disorders, e.g., tibial dyschondroplasia (TD), have been satisfactorily established. The purpose of this study was to look into the role of microRNA-140-5p (miR-140) and its interaction with HDAC4 in chondrocytes, as well as the implications for tibial dyschondroplasia (TD), with a particular focus on the relationship between low miR-140 expression and poor pathologic characteristics, as well as its physiological effects on chondrocyte growth, differentiation, and chondrodysplasia. In this investigation, we discovered that TD had a reduced expression level of the miR-140. There was a correlation between low miR-140 expression, poor pathologic characteristics, and the short overall survival of chondrocytes. Our findings show an aberrant reduction in miR-140 expression, and HDAC4 overexpression caused disengagement in resting and proliferation zones. This further resulted in uncontrolled cell proliferation, differentiation, and chondrodysplasia. Mechanistically, HDAC4 inhibited the downstream transcription factors MEF2C and Runx2 and interacted with Col-Ⅱ, Col-X, and COMP. However, miR-140 binding to the 3'-UTR of HDAC4 resulted in the growth and differentiation of chondrocytes. Moreover, the expression of HDAC4 through LMK-235 was significantly decreased, and the expression was significantly increased under ITSA-1, referring to a positive feedback circuit of miR-140 and HDAC4 for endochondral bone ossification. Furthermore, as a prospective treatment, the flavonoids of Rhizoma drynariae (TFRD) therapy increased the expression of miR-140. Compared to the TD group, TFRD treatment increased the expression of growth-promoting and chondrocyte differentiation markers, implying that TFRD can promote chondrocyte proliferation and differentiation in the tibial growth plate. Hence, directing this circuit may represent a promising target for chondrocyte-related bone disorders and all associated pathological bone conditions.

Non-coding RNA (ncRNA) classes take over important housekeeping and regulatory functions and are quite heterogeneous in terms of length, sequence conservation and secondary structure. High-throughput sequencing reveals that the expressed novel ncRNAs and their classification are important to understand cell regulation and identify potential diagnostic and therapeutic biomarkers. To improve the classification of ncRNAs, we investigated different approaches of utilizing primary sequences and secondary structures as well as the late integration of both using machine learning models, including different neural network architectures. As input, we used the newest version of RNAcentral, focusing on six ncRNA classes, including lncRNA, rRNA, tRNA, miRNA, snRNA and snoRNA. The late integration of graph-encoded structural features and primary sequences in our MncR classifier achieved an overall accuracy of >97%, which could not be increased by more fine-grained subclassification. In comparison to the actual best-performing tool ncRDense, we had a minimal increase of 0.5% in all four overlapping ncRNA classes on a similar test set of sequences. In summary, MncR is not only more accurate than current ncRNA prediction tools but also allows the prediction of long ncRNA classes (lncRNAs, certain rRNAs) up to 12.000 nts and is trained on a more diverse ncRNA dataset retrieved from RNAcentral.

Prostate cancer is the most commonly diagnosed malignancy and the third leading cause of cancer deaths. GWAS have identified variants associated with prostate cancer susceptibility; however, mechanistic and functional validation of these mutations is lacking. We used CRISPR-Cas9 genome editing to introduce a missense variant identified in the ELAC2 gene, which encodes a dually localised nuclear and mitochondrial RNA processing enzyme, into the mouse Elac2 gene as well as to generate a prostate-specific knockout of Elac2. These mutations caused enlargement and inflammation of the prostate and nodule formation. The Elac2 variant or knockout mice on the background of the transgenic adenocarcinoma of the mouse prostate (TRAMP) model show that Elac2 mutation with a secondary genetic insult exacerbated the onset and progression of prostate cancer. Multiomic profiling revealed defects in energy metabolism that activated proinflammatory and tumorigenic pathways as a consequence of impaired noncoding RNA processing and reduced protein synthesis. Our physiologically relevant models show that the ELAC2 variant is a predisposing factor for prostate cancer and identify changes that underlie the pathogenesis of this cancer.

The view of long noncoding RNAs as nonfunctional "garbage" has been definitely outdated by the large body of evidence indicating this class of ncRNAs as "golden junk", especially in precision oncology. Indeed, in light of their oncogenic role and the higher expression in multiple cancer types compared with paired adjacent tissues, the clinical interest for lncRNAs as diagnostic and/or prognostic biomarkers has been rapidly increasing. The emergence of large-scale sequencing technologies, their subsequent diffusion even in small research and clinical centers, the technological advances for the detection of low-copy lncRNAs in body fluids, coupled to the huge reduction of operating costs, have nowadays made possible to rapidly and comprehensively profile them in multiple tumors and large cohorts. In this review, we first summarize some relevant data about the oncogenic role of well-studied lncRNAs having a clinical relevance. Then, we focus on the description of their potential use as diagnostic/prognostic biomarkers, including an updated overview about licensed patents or clinical trials on lncRNAs in oncology.

Head and neck squamous cell carcinoma (HNSCC) is a group of cancers originating from the mucosal epithelium in the oral cavity, larynx, oropharynx, nasopharynx, and hypopharynx. Molecular factors can be key in the diagnosis, prognosis, and treatment of HNSCC patients. Long non-coding RNAs (lncRNAs) are molecular regulators composed of 200 to 100,000 nucleotides that act on the modulation of genes that activate signaling pathways associated with oncogenic processes such as proliferation, migration, invasion, and metastasis in tumor cells. However, up until now, few studies have discussed the participation of lncRNAs in modeling the tumor microenvironment (TME) to generate a protumor or antitumor environment. Nevertheless, some immune-related lncRNAs have clinical relevance, since AL139158.2, AL031985.3, AC104794.2, AC099343.3, AL357519.1, SBDSP1, AS1AC108010.1, and TM4SF19-AS1 have been associated with overall survival (OS). MANCR is also related to poor OS and disease-specific survival. MiR31HG, TM4SF19-AS1, and LINC01123 are associated with poor prognosis. Meanwhile, LINC02195 and TRG-AS1 overexpression is associated with favorable prognosis. Moreover, ANRIL lncRNA induces resistance to cisplatin by inhibiting apoptosis. A superior understanding of the molecular mechanisms of lncRNAs that modify the characteristics of TME could contribute to increasing the efficacy of immunotherapy.

Asthma is characterized by chronic inflammation and airway remodeling. However, limited study is conducted on the gene expression profiles of ovalbumin (OVA) induced asthma in mice. Here, we explored the gene expression profiles in lung tissues from mice with OVA-induced asthma using microarray and bioinformatics analysis.

For establishment of OVA-induced asthma model, mice first received intraperitoneal sensitization with OVA on day 0, 7 and 14, followed by atomizing inhalation of OVA 3 times a week for 8 weeks. The lung tissues were collected and subjected to microarray analysis, bioinformatics analysis and expression validation.

Microarray data of lung tissues suggested that 3754 lncRNAs and 2976 mRNAs were differentially expressed in lung tissues between control and asthmatic mice, including 1647 up-regulated and 2106 down-regulated lncRNAs, and 1201 up-regulated and 1766 down-regulated mRNAs. GO analysis displayed that the up-regulated genes were enriched in inflammatory response, leukocyte migration involved in inflammatory response, and Notch signaling pathway. KEGG pathway analysis indicated that the enriched pathway terms of the up-regulated gene included Toll-like receptor signaling pathway and Th17 cell differentiation signaling pathway. Additionally, based on the previously published literatures on asthma and inflammation, we screened out down-regulated genes, such as Smg7, Sumo2, and Stat5a, and up-regulated genes, such as Myl9, Fos and Tlr4. According to the mRNA-lncRNA co-expression network, we selected lncRNAs associated with above genes, including the down-regulated lncRNAs of NONMMUT032848, NONMMUT008873, NONMMUT009478, and NONMMUT006807, and the up-regulated lncRNAs of NONMMUT052633, NONMMUT05340 and NONMMUT042325. The expression changes of the above genes were validated in lung tissues by real-time quantitaive PCR and Western blot.

Overall, we performed gene microarray on lung samples from OVA-induced asthmatic mice and summarized core mRNAs and their related lncRNAs. This study may provide evidence for further research on the therapeutic targets of asthma.

Mutations in and dysregulation of long non-coding RNAs (lncRNAs) are closely associated with the development of various human complex diseases, but only a few lncRNAs have been experimentally confirmed to be associated with human diseases. Predicting new potential lncRNA-disease associations (LDAs) will help us to understand the pathogenesis of human diseases and to detect disease markers, as well as in disease diagnosis, prevention and treatment. Computational methods can effectively narrow down the screening scope of biological experiments, thereby reducing the duration and cost of such experiments. In this review, we outline recent advances in computational methods for predicting LDAs, focusing on LDA databases, lncRNA/disease similarity calculations, and advanced computational models. In addition, we analyze the limitations of various computational models and discuss future challenges and directions for development.

The human upper respiratory tract is the first site of contact for inhaled respiratory viruses and elaborates an array of innate immune responses. Seasonal variation in respiratory viral infections and the importance of ambient temperature in modulating immune responses to infections have been well recognized; however, the underlying biological mechanisms remain understudied.

We investigated the role of nasal epithelium-derived extracellular vesicles (EVs) in innate Toll-like receptor 3 (TLR3)-dependent antiviral immunity.

We evaluated the secretion and composition of nasal epithelial EVs after TLR3 stimulation in human autologous cells and fresh human nasal mucosal surgical specimens. We also explored the antiviral activity and mechanisms of TLR3-stimulated EVs against respiratory viruses as well as the effect of cool ambient temperature on TLR3-dependent antiviral immunity.

We found that polyinosinic:polycytidylic acid, aka poly(I:C), exposure induced a swarm-like increase in the secretion of nasal epithelial EVs via the TLR3 signaling. EVs participated in TLR3-dependent antiviral immunity, protecting the host from viral infections through both EV-mediated functional delivery of miR-17 and direct virion neutralization after binding to virus ligands via surface receptors, including LDLR and ICAM-1. These potent antiviral immune defense functions mediated by TLR3-stimulated EVs were impaired by cold exposure via a decrease in total EV secretion as well as diminished microRNA packaging and antiviral binding affinity of individual EV.

TLR3-dependent nasal epithelial EVs exhibit multiple innate antiviral mechanisms to suppress respiratory viral infections. Furthermore, our study provides a direct quantitative mechanistic explanation for seasonal variation in upper respiratory tract infection prevalence.

The high-grade astrocytoma, glioblastoma multiforme (GBM), is the most common primary tumour of the brain, known for being aggressive and developing drug resistance. The non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), have critical functions in tumorigenesis and cancer drug resistance. Hence, we profiled miRNAs, piRNAs, and genes in U-87 MG GBM cells by next-generation sequencing and performed target prediction, pathway enrichment, protein-protein interaction, co-expression studies, and qRT-PCR validations to predict their possible roles in the malignancy. The study identified 335 miRNAs, 665 piRNAs, and 4286 genes differentially expressed (DE) in GBM. Among them 128 DE genes (DEGs) were targeted by both miRNAs and piRNAs, while 1817 and 192 were targeted solely by miRNAs or piRNAs, respectively. Interestingly, all the DEG targets enriched in cancer processes were overexpressed in GBM. Among these, BRAF was solely targeted by two piRNAs and this was found to be co-expressed with 19 sole targets of 5 miRNAs, including CCND1, and both were found to regulate cell proliferation in cancer. We conjectured that upregulated HRH1 and ATXN3 were targeted by both piRNAs and miRNAs, and along with BRAF and CCND1 might induce cell proliferation in GBM through G-protein-coupled receptor or Akt signalling pathways due to downregulation of the respective targeting small RNAs. These targets were also linked to the progression and overall survival of GBM patients, suggesting that they could be used as biomarkers. Overall, this study has identified a few novel ncRNA targets, which might aid in a better understanding of GBM pathogenesis.

All cell types express long non-coding RNAs (lncRNAs), which have the potential to play a role in carcinogenesis by altering the levels of their expression. Squamous cell carcinoma of the esophagus (ESCC) is a deadly disease with a poor prognosis and a high frequency of lymphatic metastases. Understanding the functional role and signaling pathways of two neighboring lncRNAs, CCAT1 and PVT1, in this oncogene's pathogenesis may help us determine ESCC. Furthermore, it is still unclear whether these lncRNAs are linked to the clinicopathological characteristics of patients with ESCC.

For this study, we used biopsy from the Imam Khomeini Cancer Institute's tumor bank in Tehran, Iran to obtain 40 ESCC tumor samples and their normal margin counterparts. The expression levels of the CCAT1, PVT1, and c-MYC genes were assessed using quantitative Real-Time RT-PCR. Additionally, demographic data and clinical-pathologic characteristics, such as tumor grade, tumor stage, lymph node, and metastasis, were taken into consideration. Graphpad prism version 8 was used for bioinformatics analyses.

Comparing ESCC tissues to non-tumor tissues, we found significant upregulation of PVT1, CCAT1, and c-MYC. Patients with ESCC who had increased PVT1 expression also had higher rates of advanced stage and lymph node metastasis, whereas increased CCAT1 expression was only linked to advanced stage and wasn't associated with lymph node metastasis. In predicting ESCC, CCAT1 (p < 0.05) was found to be an important factor. Overall survival was reduced by c-MYC and PVT1 overexpression (p < 0.001), according to Kaplan-Meier analysis. PVT1, CCAT1, and c-MYC were found to interact with 23 miRNAs with high and medium score classes, as shown in a bioinformatics study. We summarized the experimentally proven interactions between c-MYC, PVT1, and CCAT1 and other miRNAs, lncRNAs, and proteins.

This is the first report that CCAT1, PVT1 and c-MYC have been found to be up-regulated simultaneously in ESCC. It is possible that these genes may be involved in ESCC as a result of these findings. Therefore, as consequence, more research is needed to determine whether or not these lncRNAs play an oncogenic role in ESCC development and progression, as well as the regulatory mechanisms that control them.