Search Results (817)

Adenosine receptors (ARs) are G protein-coupled receptors that are widely expressed across tissues, traditionally associated with cardiovascular, neurological, and immune regulation. Recent studies, however, have highlighted their non-canonical functions, revealing critical roles in metabolism, immunometabolism, and epigenetic regulation. AR subtypes, particularly A2A and A2B, modulate glucose and lipid metabolism, mitochondrial activity, and energy homeostasis. In immune cells, AR signaling influences metabolic reprogramming and polarization through key regulators such as mTOR, AMPK, and HIF-1α, contributing to immune tolerance or activation depending on the context. Additionally, ARs have been implicated in epigenetic modulation, affecting DNA methylation, histone acetylation, and non-coding RNA expression via metabolite-sensitive mechanisms. Therapeutically, AR-targeting agents are being explored for cancer and chronic inflammatory diseases. While clinical trials with A2A antagonists in oncology show encouraging results, challenges remain due to receptor redundancy, systemic effects, and the need for tissue-specific selectivity. Future strategies involve biased agonism, allosteric modulators, and combination therapies guided by biomarker-based patient stratification. Overall, ARs are emerging as integrative hubs connecting extracellular signals with cellular metabolic and epigenetic machinery. Understanding these non-canonical roles may unlock novel therapeutic opportunities across diverse disease landscapes. Full article

Reparative tertiary dentinogenesis requires the recruitment and odontogenic differentiation of dental pulp stem cells (DPSCs). Extracellular vesicles (EVs) as bioactive molecules have gained attention in regenerative medicine for their ability to mediate tissue repair through intercellular communication, influencing cell recruitment, proliferation, and differentiation. This study aimed to evaluate the effects of EVs on DPSC homing and odontogenic differentiation for dentin regeneration. DPSC-derived EVs were cultured in either growth (EV-G) or odontogenic differentiation (EV-O) conditions and isolated using a modified precipitation method. EVs were characterized by nanoparticle tracking analysis, scanning electron microscopy, antibody array, and cellular uptake assay. Treatment with 5 × 10⁸ EVs/mL significantly enhanced DPSC chemotaxis and proliferation compared with a no-treatment control and a lower dosage of EV (5 × 10⁷ EVs/mL). Gene expression and biochemical analyses revealed that EV-O up-regulated odontogenic markers including collagen type 1A1 (COL1A1), runt-related transcription factor 2 (RUNX2), and alkaline phosphatase (ALP). EV-O enhanced dentin regeneration by approximately 55% over vehicle controls in a rabbit partial dentinotomy/pulpotomy model. We identified key microRNAs (miR-21-5p, miR-221-3p, and miR-708-3p) in EV-O involved in cell homing and odontogenesis. In conclusion, our EV-based cell homing and odontogenic differentiation strategy has significant therapeutic potential for dentin regeneration. Full article

Background: Lipid nanoparticles (LNPs) represent one of the most effective non-viral vectors for nucleic acid delivery and have demonstrated clinical success in siRNA therapies and mRNA vaccines. While considerable research has focused on optimizing ionizable lipids and helper lipids, the impact of PEGylated lipid content on LNP-mediated mRNA delivery, especially in terms of in vitro transfection efficiency and in vivo performance, remains insufficiently understood. Methods: In this study, LNPs were formulated using a self-synthesized ionizable lipid and varying molar ratios of DMG-PEG2000. Nanoparticles were prepared via nanoprecipitation, and their physicochemical properties, mRNA encapsulation efficiency, cellular uptake, and transfection efficiency were evaluated in HeLa and DC2.4 cells. In vivo delivery efficiency and organ distribution were assessed in mice following intravenous administration. Results: The PEGylated lipid content exerted a significant influence on both the in vitro and in vivo performance of LNPs. A bell-shaped relationship between PEG content and transfection efficiency was observed: 1.5% DMG-PEG2000 yielded optimal mRNA transfection in vitro, while 5% DMG-PEG2000 resulted in the highest transgene expression in vivo. This discrepancy in optimal PEG content may be attributed to the trade-off between cellular uptake and systemic circulation: lower PEG levels enhance cellular internalization, whereas higher PEG levels improve stability and in vivo bioavailability at the expense of cellular entry. Furthermore, varying the PEG-lipid content enabled the partial modulation of organ distribution, offering a formulation-based strategy to influence biodistribution without altering the ionizable lipid structure. Conclusions: This study highlights the critical role of PEGylated lipid content in balancing nanoparticle stability, cellular uptake, and in vivo delivery performance. Our findings provide valuable mechanistic insights and suggest a straightforward formulation-based strategy to optimize LNP/mRNA systems for therapeutic applications. Full article

The enterovirus Coxsackievirus B3 causes a range of serious health problems, including aseptic meningitis, myocarditis, and pancreatitis. Currently, Coxsackievirus B3 has no targeted antiviral treatments or vaccines, leaving supportive care as the primary management option. Understanding how Coxsackievirus B3 interacts with and alters the blood–brain barrier may help identify new therapies to combat this often-devastating infection. We reanalyzed a previously published RNA sequencing dataset for Coxsackievirus B3-infected human-induced pluripotent stem-cell-derived brain endothelial cells (iBECs) to examine how Coxsackievirus B3 altered mRNA expression. By integrating GSEA, EnrichR, and iLINCs-based perturbagen analysis, we present a novel, systems-level approach to uncover potential drug repurposing candidates for CVB3 infection. We found dynamic changes in host transcriptomic response to Coxsackievirus B3 infection at 2- and 5-day infection time points. Downregulated pathways included ribosomal biogenesis and protein synthesis, while upregulated pathways included a defense response to viruses, and interferon production. Using iLINCs transcriptomic analysis, MEK, PDGFR, and VEGF inhibitors were identified as possible novel antiviral therapeutics. Our findings further elucidate Coxsackievirus B3-associated pathways in (iBECs) and highlight potential drug repurposing candidates, including pelitinib and neratinib, which may disrupt Coxsackievirus B3 pathology at the blood–brain barrier (BBB). Full article

Neuropathic pain is a significant global clinical issue that poses substantial challenges to both public health and the economy due to its complex underlying mechanisms. It has emerged as a serious health concern worldwide. Recent studies involving dorsal root ganglion (DRG) stimulation have provided strong evidence supporting its effectiveness in alleviating chronic pain and its potential for sustaining long-term pain relief. In addition to that, there has been ongoing research with clinical evidence relating to the role of small non-coding ribonucleic acids known as microRNAs in regulating gene expressions affecting pain signals. The signal pathway involves alterations in neuronal excitation, synaptic transmission, dysregulated signaling, and subsequent pro-inflammatory response activation and pain development. When microRNAs are dysregulated in the dorsal root ganglia neurons, they polarize macrophages from anti-inflammatory M2 to inflammatory M1 macrophages causing pain signal generation. By reversing this polarization, a therapeutic activity can be induced. However, the direct delivery of these nucleotides has been challenging due to limitations such as rapid clearance, degradation, and reduction in half-life. Therefore, safe and efficient carrier vehicles are fundamental for microRNA delivery. Here, we present a comprehensive analysis of miRNA-based nano-systems for chronic neuropathic pain, focusing on their impact in dorsal root ganglia. This review provides a critical evaluation of various delivery platforms, including viral, polymeric, lipid-based, and inorganic nanocarriers, emphasizing their therapeutic potential as well as their limitations in the treatment of chronic neuropathic pain. Innovative strategies such as hybrid nanocarriers and stimulus-responsive systems are also proposed to enhance the prospects for clinical translation. Serving as a roadmap for future research, this review aims to guide the development and optimization of miRNA-based therapies for effective and sustained neuropathic pain management. Full article

Circular RNAs (circRNAs) are covalently closed RNA molecules generated through a non-canonical splicing event known as back-splicing. This particular class of non-coding RNAs has attracted growing interest due to its evolutionary conservation across eukaryotes, high expression in the central nervous system, and frequent dysregulation in various pathological conditions, including cancer. Traditionally, circRNAs have been characterised by their ability to function as microRNA (miRNA) and protein sponges. However, recent discoveries from multiple research groups have uncovered a novel and potentially transformative mechanism of action: the direct interaction of circRNAs with messenger RNAs (mRNAs) to regulate their fate. These interactions can influence mRNA stability and translation, revealing a new layer of post-transcriptional gene regulation. In this review, we present and analyse the latest evidence supporting the emerging role of circRNAs in diverse biological contexts. We highlight the growing body of research demonstrating circRNA-mRNA interactions as a functional regulatory mechanism and explore their involvement in key physiological and pathophysiological processes. Understanding this novel mechanism expands our knowledge of RNA-based regulation and opens new opportunities for therapeutic strategies targeting circRNA-mRNA networks in human disease. Full article

Radon (Rn) exposure has a strong association with lung cancer risk and is influenced by epigenetic modifications. To investigate the characterization of DNA methylation (DNAm) episignatures for radon-induced lung cancer, we detected the specific changes in DNAm in blood and lung tissues using reduced representation bisulfite sequencing (RRBS). We identified the differentially methylated regions (DMRs) induced by radon exposure. The bioinformatics analysis of the DMR-mapped genes revealed that pathways in cancer were affected by radon exposure. Among them, the DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 were repeated between lung tissue and blood, and validated by the MassArray. In addition, radon exposure promoted lung cancer development in the genetic engineering mouse model (GEMM), accompanied by decreased MAPK10 and increased PLCG1, PLCβ3, and PIK3R2 with mRNA and protein levels. Conclusively, radon exposure significantly changes the genomic DNAm patterns in lung tissue and blood. The DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 have a significant influence on radon-induced lung cancer. This brings a new perspective to understanding the pathways involved in radon-induced lung cancer and offers potential targets for developing blood-based biomarkers and epigenetic therapeutics. Full article

Chemical modifications are the standard for small interfering RNAs (siRNAs) in therapeutic applications, but predicting their off-target effects remains a significant challenge. Current approaches often rely on sequence-based encodings, which fail to fully capture the structural and protein–RNA interaction details critical for off-target prediction. In this study, we developed a framework to generate reproducible structure-based chemical features, incorporating both molecular fingerprints and computationally derived siRNA–hAgo2 complex structures. Using an RNA-Seq off-target study, we generated over 30,000 siRNA–gene data points and systematically compared nine distinct types of feature representation strategies. Among the datasets, the highest predictive performance was achieved by Dataset 3, which used extended connectivity fingerprints (ECFPs) to encode siRNA and mRNA features. An energy-minimized dataset (7R), representing siRNA–hAgo2 structural alignments, was the second-best performer, underscoring the value of incorporating reproducible structural information into feature engineering. Our findings demonstrate that combining detailed structural representations with sequence-based features enables the generation of robust, reproducible chemical features for machine learning models, offering a promising path forward for off-target prediction and siRNA therapeutic design that can be seamlessly extended to include any modification, such as clinically relevant 2′-F or 2′-OMe. Full article

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high recurrence rates even after curative resection and adjuvant chemotherapy. Although immunotherapeutic approaches, such as immune checkpoint blockade (ICB), have revolutionized the treatment of some solid tumor malignancies, this has not been the case for PDAC. Several characteristics of PDAC, including its distinctive desmoplastic tumor microenvironment (TME), intratumor heterogeneity, and poor antigenicity and immune cell infiltration, contribute to its dismal immunotherapeutic landscape. Cancer vaccines offer one approach to overcoming these barriers, particularly in the resectable or borderline resectable settings, where tumor burden is low and immunosuppression is less pronounced. Various vaccination platforms have been tested in the clinical setting, from off-the-shelf peptide-based vaccines (e.g., AMPLFIFY-201 study, where over 80% of participants exhibited T-cell and biomarker responses) to personalized neoantigen mRNA vaccine approaches (e.g., autogene cevumeran, with significant responders experiencing longer median recurrence-free survival (RFS)). The key considerations for enhancing the efficacy of vaccination include combinations with chemotherapy, radiotherapy, and/or ICBs, as well as selecting appropriate immunomodulators or adjuvants. Recent results suggest that with continued mechanistic advancement and novel therapeutic development, cancer vaccines may finally be poised for clinical success in PDAC. Full article

Background and Purpose: Glioblastoma remains a therapeutic challenge with a poor prognosis despite multimodal treatments. Reporter-based magnetic resonance imaging (MRI) offers a promising approach for tumor visualization, but its efficacy depends on sufficient reporter gene expression. This study aimed to develop a chimeric element-regulated ferritin heavy chain 1 (FTH1) reporter system to enhance MRI-based glioma detection while enabling targeted therapy via transferrin receptor (TfR)-mediated drug delivery. Methods: Using gene cloning techniques, we constructed a chimeric FTH1 expression system comprising tumor-specific PEG3 promoter (transcriptional control), bFGF-2 5′UTR (translational enhancement), and WPRE (mRNA stabilization). Lentiviral vectors delivered constructs to U251 glioblastoma cells and xenografts. FTH1/TfR expression was validated by Western blot and immunofluorescence. Iron accumulation was assessed via Prussian blue staining and TEM. MRI evaluated T2 signal changes. Transferrin-modified doxorubicin liposomes (Tf-LPD) were characterized for size and drug loading and tested for cellular uptake and cytotoxicity in vitro. In vivo therapeutic efficacy was assessed in nude mouse models through tumor volume measurement, MR imaging, and histopathology. Results: The chimeric system increased FTH1 expression significantly over PEG3-only controls (p < 0.01), with an increase of nearly 1.5-fold compared to the negative and blank groups and approximately a two-fold increase relative to the single promoter group, with corresponding TfR upregulation. Enhanced iron accumulation reduced T2 relaxation times significantly (p < 0.01), improving MR contrast. Tf-LPD (115 nm, 70% encapsulation) showed TfR-dependent uptake, inducing obvious apoptosis in high-TfR cells compared with that in controls. In vivo, Tf-LPD reduced tumor growth markedly in chimeric-system xenografts versus controls, with concurrent MR signal attenuation. Conclusions: The chimeric regulatory strategy overcomes limitations of single-element systems, demonstrating significant potential for integrated glioma theranostics. Its modular design may be adaptable to other reporter genes and malignancies. Full article

N6-methyladenosine (m6A) represents the most common and thoroughly investigated RNA modification and exerts essential functions in regulating gene expression through influencing the RNA stability, the translation efficiency, alternative splicing, and nuclear export processes. The rapid development of high-throughput sequencing approaches, including miCLIP and MeRIP-seq, has profoundly transformed epitranscriptomics research. These techniques facilitate the detailed transcriptome-wide profiling of m6A modifications, shedding light on their crucial roles in diverse biological pathways. This review comprehensively examines the identification, mechanisms of regulation, and functional consequences of m6A modifications. It emphasizes their critical roles in physiological contexts, encompassing immune function, neuronal development, and the differentiation of stem cells. Additionally, the review discusses the contributions of m6A dysregulation to pathological conditions, including cancer, neurodegenerative diseases, and disorders of metabolism. We also discuss the development and application of machine-learning algorithms for m6A site prediction, emphasizing the integration of sequence-based, structural, and evolutionary conservation features to enhance the predictive accuracy. Furthermore, the potential of applying the findings from m6A research in precision medicine and drug development is examined. By synthesizing the current knowledge and emerging trends, this review aims to provide a comprehensive understanding of m6A biology and its translational potential, offering new perspectives for future research and therapeutic innovation. Full article

Background: Many patients harbor minimal residual disease (MRD)—small clusters of residual tumor cells that survive therapy and evade conventional detection but drive recurrence. Although advances in molecular and computational methods have improved circulating tumor DNA (ctDNA)-based MRD detection, these approaches face challenges: ctDNA shedding fluctuates widely across tumor types, disease stages, and histological features. Additionally, low levels of driver mutations originating from healthy tissues can create background noise, complicating the accurate identification of bona fide tumor-specific signals. These limitations underscore the need for refined technologies to further enhance MRD detection beyond DNA sequences in solid malignancies. Methods: Profiling circulating cell-free mRNA (cfmRNA), which is hyperactive in tumor and non-tumor microenvironments, could address these limitations to inform postoperative surveillance and treatment strategies. This study reported the development of OncoMRD BREAST, a customized, gene signature-informed cfmRNA assay for residual disease monitoring in breast cancer. OncoMRD BREAST introduces several advanced technologies that distinguish it from the existing ctDNA-MRD tests. It builds on the patient-derived gene signature for capturing tumor activities while introducing significant upgrades to its liquid biopsy transcriptomic profiling, digital scoring systems, and tracking capabilities. Results: The OncoMRD BREAST test processes inputs from multiple cutting-edge biomarkers—tumor and non-tumor microenvironment—to provide enhanced awareness of tumor activities in real time. By fusing data from these diverse intra- and inter-cellular networks, OncoMRD BREAST significantly improves the sensitivity and reliability of MRD detection and prognosis analysis, even under challenging and complex conditions. In a proof-of-concept real-world pilot trial, OncoMRD BREAST’s rapid quantification of potential tumor activity helped reduce the risk of incorrect treatment strategies, while advanced predictive analytics contributed to the overall benefits and improved outcomes of patients. Conclusions: By tailoring the assay to individual tumor profiles, we aimed to enhance early identification of residual disease and optimize therapeutic decision-making. OncoMRD BREAST is the world’s first and only gene signature-powered test for monitoring residual disease in solid tumors. Full article

Background/Objectives: Long non-coding RNAs (lncRNAs) play significant roles in tissue development and disease progression and have emerged as crucial regulators of gene expression. The hepatocyte nuclear factor alpha antisense RNA 1 (HNF1A-AS1) lncRNA is a particularly intriguing regulatory molecule in liver biology that is involved in the regulation of cytochrome P450 enzymes via epigenetic mechanisms. Despite the growing recognition of lncRNAs in liver disease, the comprehensive role of HNF1A-AS1 in liver function remains unclear. This study aimed to investigate the roles of the mouse homolog of the human HNF1A-AS1 lncRNA HNF1A opposite strand 1 (Hnf1aos1) in liver function, gene expression, and cellular processes using a mouse model to identify potential therapeutic targets for liver disorders. Methods: The knockdown of Hnf1aos1 was performed in in vitro mouse liver cell lines using siRNA and in vivo livers of AAV-shRNA complexes. Changes in the global expression landscapes of mRNA and proteins were revealed using RNA-seq and proteomics, respectively. Changes in the selected genes were further validated via real-time quantitative polymerase chain reaction (RT-qPCR). Phenotypic changes were assessed via histological and absorbance-based assays. Results: After the knockdown of Hnf1aos1, RNA-seq and proteomics analysis revealed the differential gene expression of the mRNAs and proteins involved in the processes of molecular transport, liver regeneration, and immune signaling pathways. The downregulation of ABCA1 and SREBF1 indicates their role in cholesterol transport and fatty acid and triglyceride synthesis. Additionally, significant reductions in hepatic triglyceride levels were observed in the Hnf1aos1-knockdown group, underscoring the impact on lipid regulation. Notably, the knockdown of Hnf1aos1 also led to an almost complete depletion of CYP7A1, the rate-limiting enzyme in bile acid synthesis, highlighting its role in cholesterol homeostasis and hepatotoxicity. Histological assessments confirmed these molecular findings, with increased hepatic inflammation, hepatocyte swelling, and disrupted liver architecture observed in the Hnf1aos1-knockdown mice. Conclusions: This study illustrated that Hnf1aos1 is a critical regulator of liver health, influencing both lipid metabolism and immune pathways. It maintains hepatic lipid homeostasis, modulates lipid-induced inflammatory responses, and contributes to viral immunity, indirectly affecting glucose and lipid metabolic balance. Full article

Usher syndrome, a rare genetic disorder causing both hearing and vision loss, presents significant diagnostic and therapeutic challenges due to its complex genetic basis. The identification of reliable biomarkers for early detection and intervention is crucial for improving patient outcomes. In this study, we present a machine learning-based hybrid sequential feature selection approach to identify key mRNA biomarkers associated with Usher syndrome. Beginning with a dataset of 42,334 mRNA features, our approach successfully reduced dimensionality and identified 58 top mRNA biomarkers that distinguish Usher syndrome from control samples. We employed a combination of feature selection techniques, including variance thresholding, recursive feature elimination, and Lasso regression, integrated within a nested cross-validation framework. The selected biomarkers were further validated using multiple machine learning models, including Logistic Regression, Random Forest, and Support Vector Machines, demonstrating robust classification performance. To assess the biological relevance of the computationally identified mRNA biomarkers, we experimentally validated candidates from the top 10 selected mRNAs using droplet digital PCR (ddPCR). The ddPCR results were consistent with expression patterns observed in the integrated transcriptomic metadata, reinforcing the credibility of our machine learning-driven biomarker discovery framework. Our findings highlight the potential of machine learning-driven biomarker discovery to enhance the detection of Usher syndrome. Full article

Nipah and Hendra viruses are lethal zoonotic pathogens with no approved vaccines or therapeutics. mRNA produced via in vitro transcription enables endogenous protein expression and cost reduction. Here, we systematically screened natural and artificial untranslated regions (UTRs) and identified an optimal combination for expressing henipavirus-neutralizing antibody 1E5. We generated mRNA-1E5 encapsulated in lipid nanoparticles (mRNA-1E5-LNPs). In vitro, mRNA-1E5-LNPs achieved functional antibody expression levels of >1500 ng/mL. In BALB/c mice, intravenous administration of mRNA-1E5-LNPs induced rapid antibody elevation (peak at day 3), without hepatic toxicity or tissue inflammation. We established two Hendra pseudovirus models in biosafety level 2 facilities to evaluate the efficacy of mRNA-1E5-LNPs. Low-dose prophylactic administration effectively blocked entry of the Hendra pseudovirus. Notably, a single 0.5 mg/kg dose of mRNA-1E5-LNPs, stored at 4 °C for two months and administered 7 days prior, provided good protection. Our findings provide a therapeutic strategy for henipaviral infections and a blueprint for the development of mRNA-based antibodies against emerging viruses. Full article