Search Results (10,796)

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, with tumor recurrence and metastasis posing significant challenges despite advances in targeted therapies and immunotherapy. Cellular dormancy, a reversible, quiescent state marked by cell cycle arrest, has emerged as a key driver of therapeutic resistance and disease relapse, particularly in small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Multiple mechanisms, including autophagy, stress-adaptive signaling, microenvironmental cues, and epigenetic dysregulation, have been implicated in the regulation of dormancy and long-term cell survival. Among these, epigenetic modifications such as DNA methylation, histone modifications, and non-coding RNAs (ncRNAs) play pivotal roles in maintaining dormancy by repressing proliferative gene expression programs. Increasing evidence suggests that dormant tumor cells harbor distinct epigenomic signatures, which may serve as predictive biomarkers for minimal residual disease (MRD) and relapse risk. This review summarizes current advances in understanding the epigenetic regulation of cellular dormancy in lung cancer, with a particular emphasis on the interplay between epigenetic modifiers and oncogenic signaling pathways. Furthermore, emerging molecular targets and associated therapeutic agents currently under clinical evaluation are presented, emphasizing how a deeper understanding of the epigenetic landscape governing dormancy may inform the development of novel interventions to improve long-term clinical outcomes in lung cancer patients. Full article

The oblique distribution of orebodies is a fundamental characteristic of the spatial arrangement of orebody groups in non-magmatic hydrothermal deposits and is closely related to shearing. The Daliangzi Pb–Zn deposit in the Sichuan–Yunnan–Guizhou Pb–Zn polymetallic metallogenic area is a typical representative of epigenetic hydrothermal deposits controlled by a strike-slip–fault-fold structure. However, the underlying ore-controlling mechanism of this strike-slip–fault-fold structure remains unclear; as a result, achieving breakthroughs in mineral exploration in the deposit’s deep and peripheral zones is directly hindered. This paper focuses on the Daliangzi Pb–Zn deposit. Based on the Theory and Methods of Ore-field Geomechanics, the hierarchical structural ore-controlling pattern of the deposit is clarified, identifying the NE-trending tectonic zone from the Middle-Late Indosinian to Early Yanshanian as the Pb–Zn metallogenic tectonic system. It proposes the spatial oblique distribution patterns of the deposits, ore sections, orebodies, and ore blocks, along with the mechanical mechanisms of multi-scale structural ore control. A compound negative flower structure–fault-fold–diapiric ore-controlling model was constructed for the Daliangzi Pb–Zn deposit. Finally, the locations of concealed orebodies at different scales within the Daliangzi Pb–Zn deposit and its surrounding areas were predicted; moreover, the locations of concealed orebodies at various depths within the deposit area were also predicted. Full article

Apple represents one of the most economically significant fruit crops worldwide, and the performance of its scion is largely determined by the physiological and genetic characteristics of the rootstock. Despite their superior ecological adaptability and growth-controlling attributes, many dwarfing apple rootstocks exhibit inherently poor rooting competence, which poses a critical limitation to their large-scale clonal propagation and commercial utilization. Adventitious root (AR) formation is a pivotal yet highly intricate developmental process that governs the success of asexual propagation. It is orchestrated by a complex network of hormonal signaling, transcriptional regulation, metabolic reprogramming, and environmental cues. Over the past decade, remarkable advances have elucidated the physiological, biochemical, and molecular frameworks underpinning AR formation in apple rootstocks. This review provides an integrative synthesis of current progress in vegetative propagation techniques—including cutting, layering, and tissue culture—and systematically dissects the endogenous and exogenous factors influencing AR development. Particular emphasis is placed on the regulatory interplay among phytohormones, carbohydrate and nitrogen metabolism, phenolic compounds, transcription factors (such as WUSCHEL-RELATED HOMEOBOX (WOX), LATERAL ORGAN BOUNDARIES DOMAIN (LBD), and RESPONSE FACTOR (ARF families), and epigenetic modulators that collectively coordinate root induction and emergence. Furthermore, emerging insights into multi-omics integration and genotype-specific molecular regulation are discussed as strategic pathways toward enhancing propagation efficiency. Collectively, this review establishes a comprehensive theoretical framework for optimizing the asexual propagation of apple rootstocks and provides critical molecular guidance for breeding novel, easy-to-root genotypes that can drive the sustainable intensification of global apple production. Full article

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, increasingly arising in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Epigenetic dysregulation, particularly DNA methylation, has been implicated in MASLD-HCC development, yet the roles that the principal DNA methylation precursor metabolites, S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), play in this association are unclear. Objective: We investigated associations of circulating SAM, SAH, the SAM/SAH ratio, with MASLD-HCC. Methods: In a multi-center pilot case–control study, we evaluated 69 MASLD-HCC cases and 136 cancer-free MASLD controls. Plasma SAM and SAH levels were quantified by liquid chromatography–tandem mass spectrometry. Metabolite levels were categorized as greater than or less than the median based on distribution in controls. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for age, sex, body mass index, smoking status, and type 2 diabetes. Results: MASLD-HCC cases had significantly higher plasma SAM levels (mean 121 vs. 96 nmol/L; p = 0.001) and SAM/SAH ratios (2.09 vs. 1.48; p = 6.42 × 10⁻⁷) than MASLD controls. In multivariable-adjusted models, elevated SAM levels (OR_{≥median vs. <median} = 2.76; 95% CI: 1.38–5.72) and higher SAM/SAH ratio (OR_{≥median vs. <median} = 2.30; 95% CI: 1.15–4.73) were associated with higher odds of MASLD-HCC. SAH alone was associated with MASLD-HCC. Conclusions: Higher plasma SAM levels and SAM/SAH ratios are independently linked to MASLD-HCC development. These metabolites might serve as noninvasive markers for HCC risk stratification in patients with MASLD and improve early detection efforts for MASLD-HCC. Full article

The adoption of liquid biopsy approaches in clinical practice has triggered a significant paradigm shift in the diagnostic, prognostic, and predictive outcomes for cancer patients. Circulating tumor DNA (ctDNA) is considered a valuable biomarker for monitoring tumor burden and its mutational dynamics. In this context, not all cell-free DNA (cfDNA) molecules are derived from tumor cells. Furthermore, due to tumor heterogeneity, not all ctDNA molecules contain cancer-associated alleles, complicating the direct quantification of the circulating tumor allele fraction (cTF) within the total cfDNA. Cancer arises from the accumulation of multiple genetic and epigenetic changes. Each of these molecular features can be exploited as the basis of methodological strategies used in ctDNA quantification. Different layers of omics data, from genomics, evaluating mutational analysis of somatic single-nucleotide variants and copy number alterations, to epigenomics, primarily consisting of the evaluation of methylation profiles and fragmentation patterns, can be used for this purpose. Some of these approaches can be effective in a multi-modal manner. To date, the quantification approaches for estimating cTF vary enormously, making direct comparisons and an assessment of their translational value challenging. Moreover, the lack of regulatory approval for many of these assays is a critical barrier to their widespread clinical adoption. This review explores the different omics approaches described for ctDNA quantification, outlining strengths and limitations, and highlighting their valuable applications in clinical settings. Full article

Frontotemporal dementia (FTD) represents a cluster of adult-onset neurodegenerative diseases resulting from a combination of genetic and epigenetic factors. Currently, treatment is symptomatic and there are no licensed disease-modifying therapies available. The aim of this review was to provide an overview of ongoing or recently completed clinical studies targeting disease modification in FTD. A structured search of interventional trials of pharmacological compounds was conducted on three clinical trial registries (National Library of Medicine Clinical Trials, European Union Clinical Trials, and the Australian New Zealand Clinical Trials registries) up to September 2025. Twelve interventional trials were found. Half targeted autosomal-dominant progranulin (GRN) mutations (n = 6) and half examined therapies targeting neuroinflammatory-induced sporadic FTD (n = 6). The interim results of the early-phase (1/2) randomized controlled trials (RCTs), comprising three ongoing gene replacement studies (PROCLAIM, ASPIRE-FTD, upliFT-D) and one immune-modulating monoclonal antibody (INFRONT, now in phase 3)—all targeting the FTD-GRN mutation—show safety, tolerability, and effectiveness in restoring progranulin levels. Two recently completed phase 2 RCTs for sporadic FTD targeting neuroinflammation, the PEA-FTD and C9orf72 ALS/FTD trials, show disease-modifying potential. While interim results from six trials suggest clear mechanistic efficacy, prospective high-quality later-phase RCTs are required to ascertain long-term clinical efficacy. Since familial FTD encompasses less than half of the people with this disease, it is important to continue exploring the underlying pathophysiology, neuroimmunology, and treatment of epigenetic-induced sporadic FTD. Full article

Type I interferons (IFN-I) are pivotal effectors of innate immunity and constitute a central axis of host defense against pathogens. Sensing of exogenous or endogenous nucleic acids by pattern-recognition receptors—exemplified by Toll-like receptors—triggers transcriptional induction of IFN-I. Engagement of the heterodimeric IFN-I receptor on nucleated cells reprograms cellular states via canonical Janus kinase–signal transducer and activator of transcription (JAK–STAT) signaling as well as STAT-independent, noncanonical pathways. This axis is tempered by multilayered regulatory mechanisms, including epigenetic remodeling, and important aspects remain incompletely defined. Dysregulation of IFN-I activity underlies diverse autoimmune disorders, notably systemic lupus erythematosus, wherein IFN-responsive gene signatures stratify disease endotypes, reflect disease activity trajectories, and predict therapeutic responsiveness. In recent years, therapeutic strategies targeting this pathway are now available: anti-IFN-I receptor therapy for systemic lupus erythematosus (SLE) and JAK inhibition for rheumatoid arthritis (RA) and giant cell arteritis (GCA). Altogether, a refined understanding of the IFN-I axis furnishes a pragmatic framework for patient stratification, response prediction, and mechanism-informed therapy design across immune-mediated diseases. Full article

Nowadays, the explosive growth of knowledge in the epigenetics field has highlighted DNA methyltransferase 1 (DNMT1) as a key regulator of genomic methylation patterns and a promising therapeutic target in several diseases. In light of the increasing clinical interest in epigenetic enzymes, the present study aimed to develop a robust computational framework for the discovery of novel DNMT1 inhibitors, merging both structure and data-driven strategies. Particularly, the study compiled a dataset of established DNMT1 inhibitors and calculated a series of molecular properties, thus enabling the training of a machine learning model to capture critical structure–activity relationships (SARs). When benchmarked against known active compounds, the model effectively discriminated between putative inhibitors and non-inhibitors with high accuracy. In parallel, molecular docking was conducted to screen additional uncharacterized compounds, estimating their binding affinity to human DNMT1. Their respective properties were then extracted and fed into the aforementioned model to predict their inhibitory potential. Our comparative evaluation against known human DNMT1 inhibitors demonstrated high predictive accuracy, confirming the reliability of the proposed integrated approach. By uniting molecular docking with data-driven SAR modelling, this workflow offers an expedited fast-track avenue for identifying promising human DNMT1 inhibitors while reducing experimental overhead. The results highlight the effectiveness of combining cheminformatics, machine learning, and in silico techniques to guide rational drug design, and accelerate the discovery of novel epigenetic inhibitors. Full article

Genomics has developed in step with progress in computing. As computational capabilities have grown, analyses have expanded from simple statistics to artificial intelligence (AI)-based approaches within genomics. The decline in sequencing costs has led to the accumulation of diverse genomic datasets, rapidly accelerating AI for genomic analysis. AI models are now developed and applied across many functional domains, including the prediction of transcription factor binding sites, epigenetic elements, DNA methylation, and noncoding sequence functional annotation. With the maturation of architectures such as deep neural networks, convolutional neural networks, recurrent neural networks, and transformers, many genomic models now accommodate longer inputs, capture long-range context, and integrate complex multi-omics data, thereby steadily improving predictive accuracy. Moreover, the emergence of generative AI has enabled models that can simulate and design genomic sequences. The introduction of generative AI into genomics goes beyond inferring function to the capability of replicating functional genomes. These advances will help advance genome interpretation and accelerate our ability to chart and navigate the genomic landscape. Full article

Background: Trait convergence or parallelism is widely seen across the animal and plant kingdoms. For example, the evolution of eyes in cephalopods and vertebrate lineages, wings in bats and insects, or shark and dolphin body shapes are examples of convergent evolution. Such traits develop as a function of environmental pressures or opportunities that lead to similar outcomes despite the independent origins of underlying tissues, cells, and gene transcriptional patterns. Our current understanding of the molecular processes underlying these phenomena is gene-centric and focuses on how convergence involves the recruitment of novel genes, the recombination of gene products, and the duplication and divergence of genetic substrates. Scope: Despite the independent origins of a given trait, these model organisms still possess some form of epigenetic processes conserved in eukaryotes that mediate gene-by-environment interactions. These traits evolve under similar environmental pressures, so attention should be given to plastic molecular processes that shape gene function along these evolutionary paths. Key Mechanisms: Here, we propose that epigenetic processes such as histone-modifying machinery are essential in mediating the dialog between environment and gene function, leading to trait convergence across disparate lineages. We propose that epigenetic modifications not only mediate gene-by-environment interactions but also bias the distribution of de novo mutations and recombination, thereby channeling evolutionary trajectories toward convergence. An inclusive view of the epigenetic landscape may provide a parsimonious understanding of trait evolution. Full article

Background/Objectives: Human breast milk is a mammary gland secretion with a dynamic composition, containing important bioactive factors for infant growth. Epigenetic factors, like microRNAs, are found in breast milk and can regulate gene expression and, thus, infant growth. Obesity is, among others, a major global health concern with long-term consequences, making its prevention during early life a public health priority. Maternal lifestyle factors, including diet and body weight status, may influence infant growth patterns and susceptibility to obesity. The aim of this review is to explore the hypothesis that miRNA content in breast milk might be influenced by maternal obesity, eventually affecting the obesity risk in offspring. Methods: This systematic review was carried out in line with the PRISMA 2020 statement and included observational (cohort) studies that met the inclusion criteria and compare the expression of miRNAs in OW/OB lactating mothers and associate this to the obesity development in the offspring. Results: According to the included studies, the most common miRNAs are miR-148a, miR-30 family, and miR-let7 family, with miR-30b and miR-let7a among the most discussed that participate in adipogenesis. Some of these miRNAs secreted in breast milk pass on a genetic predisposition for obesity to the next generation, while others provide a protective role against obesity in the offspring. Conclusions: Eventually, even though individual miRNAs may fluctuate, the overall miRNA profile remains stable. The findings underscore the importance of balanced maternal nutrition and optimal health during lactation, both for supporting healthy infant development and for potentially reducing the risk of obesity later in life. Full article

Radiotherapy (RT) remains a cornerstone of cancer treatment, offering spatially precise cytotoxicity against malignant cells. However, emerging evidence reveals that ionizing radiation (IR) exerts biological effects beyond the targeted tumor volume, manifesting as radiation bystander effects (BEs) and other non-targeted effects (NTEs). These phenomena challenge the traditional paradigm of RT as a localized intervention, highlighting systemic and long-term consequences in non-irradiated tissues. This comprehensive review synthesizes molecular, cellular, and clinical insights about BEs, elucidating the complex intercellular signaling networks gap junctions, cytokines, extracellular vesicles, and oxidative stress that propagate damage, genomic instability, and inflammation. We explore the role of mitochondrial dysfunction, epigenetic reprogramming, immune modulation, and stem cell niche disruption in shaping BEs outcomes. Clinically, BEs contribute to neurocognitive decline, cardiovascular disease, pulmonary fibrosis, gastrointestinal toxicity, and secondary malignancies, particularly in pediatric and long-term cancer survivors. The review also evaluates countermeasures including antioxidants, COX-2 inhibitors, exosome blockers, and FLASH RT, alongside emerging strategies targeting cfCh, inflammasomes, and senescence-associated secretory phenotypes. We discuss the dual nature of BEs: their potential to both harm and heal, underscoring adaptive responses and immune priming in specific contexts. By integrating mechanistic depth with translational relevance, this work posits that radiation BEs are a modifiable axis of RT biology. Recognizing and mitigating BEs is imperative for optimizing therapeutic efficacy, minimizing collateral damage, and enhancing survivorship outcomes. This review advocates for a paradigm shift in RT planning and post-treatment care, emphasizing precision, personalization, and systemic awareness in modern oncology. Full article

Inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases with complex aetiology involving genetic, immunological, and environmental factors and intestinal microbiota disorders. Mutations in genes such as NOD2, ATG16L1, IRGM, TLR4, and IL23R disrupt the functioning of the intestinal barrier and the immune response, increasing susceptibility to chronic inflammation. Recent studies indicate that interactions between diet, gene expression, and epigenetic mechanisms play a key role in modulating the course of IBD, e.g., DNA methylation, histone modifications, and microRNA activity. The use of bioactive dietary components in combination with epigenome modulation is a promising tool in the treatment of IBD, enabling the reduction in chronic inflammation, improving intestinal barrier function, and supporting the immune response. Full article

The limitations of conventional cancer therapies, including toxicity and resistance, underscore the need for safer and more versatile alternatives that can either complement or substitute existing regimens. Garcinol, a polyisoprenylated benzophenone derived primarily from the rind and leaves of Garcinia indica and Garcinia cambogia, has drawn significant interest in recent decades. Although traditionally used to relieve inflammatory disorders, its biomedical relevance expanded considerably after reports in the late 20th century demonstrated antimicrobial and subsequently anti-cancer properties. A growing body of cell-based research, supported by a smaller set of animal experiments, now suggests that garcinol acts as a potent epigenetic modulator. Its activities include inhibition of histone acetyltransferases (HATs), a groundbreaking research followed by regulation of oncogenic microRNAs, and modulation of signaling pathways critical to tumor progression. This review integrates current findings on garcinol’s dual role as a HAT inhibitor and regulator of oncogenic networks with updates on in vitro and in vivo studies with a more focused approach on in vivo animal models, highlighting its potential as an emerging therapeutic against malignancies and inflammatory diseases. Nonetheless, translation into clinical settings remains premature, as robust in vivo evidence is sparse and human trials are lacking. Moving forward, systematic investigations are required to clarify safety profiles, establish effective dosing strategies, and evaluate its efficacy across different cancer types. Full article

Cryptorchidism, characterized by undescended testes, is associated with infertility and increased cancer risk through complex, multifactorial pathophysiological mechanisms involving interconnected alterations in testicular microenvironment, including but not limited to elevated temperature, hormonal dysregulation, altered vascular perfusion, and immune responses. These factors interact synergistically to drive testicular pathology. Using a surgically induced bilateral cryptorchid mouse model established at postnatal day 21 (PND21), we investigated phase-specific pathological mechanisms through analyses at prepubertal (PND35) and sexually mature (PND70) phases. Our transcriptome analysis revealed distinct molecular signatures at different developmental phases, with prepubertal cryptorchid testes showing 2570 differentially expressed genes predominantly enriched in immunoproteasome components and inflammatory pathways, while sexually mature testes exhibited 883 differentially expressed genes primarily related to extracellular matrix (ECM) remodeling and oncogenic pathways. Prepubertal molecular changes indicated immunoproteasome activation and inflammatory responses, whereas mature-phase alterations were characterized by ECM reorganization and fibrotic remodeling. Functional analysis demonstrated prepubertal enrichment in spermatogenesis regulation and interferon responses, while mature-phase signatures were associated with apoptosis, epithelial–mesenchymal transition, and inflammatory signaling cascades. Phase-specific oncogenic pathway correlations revealed distinct mechanisms: metabolic reprogramming and epigenetic regulation in prepubertal testes versus structural remodeling and invasion-related pathways in mature testes. Molecular validation confirmed elevated PI3K-Akt and NF-κB signaling at both developmental phases, identifying these as potential therapeutic targets. This first phase-resolved characterization of cryptorchidism pathology provides insights into developmental phase-specific mechanisms and suggests timing-dependent therapeutic strategies. Although differing from human congenital cryptorchidism in developmental timing and etiology, our surgically induced model recapitulates anatomical testicular malposition with multiple inseparable pathophysiological alterations, and the identified molecular signatures reflect integrated responses to the complex cryptorchid microenvironment. Full article