Search Results (97)

Background: Triple-negative breast cancers (TNBCs) are among the most aggressive breast tumors, due not only to the absence of clinically functional biomarkers used in other molecular subtypes, but also their marked heterogeneity and pronounced migratory and invasive behavior. The search for new molecules of interest for risk prediction, diagnosis and therapy stems from the class of long non-coding RNAs (lncRNAs), which often display context-dependent (“dual”) functions and tissue specificity. Among them, lncRNA LINC01133 stands out for its dysregulation across cancer, although its molecular role in TNBC remains unclear. Methods: In the present study, we used the human TNBC cell line Hs578T to generate a cell panel comprising the parental line (Hs578T_wt), the control line (Hs578T_ctr), and the LINC01133 knockout line (Hs578T_ko). Subsequently, we performed bulk RNA-Seq to identify KO-associated Differentially Expressed Genes (DEGs) using ko_vs_ctr as the primary contrast. Functional interpretation was achieved by Over-Representation Analysis (ORA) using Gene Ontology. We then conducted a comparative patient-cohort analysis using TCGA-BRCA Basal-like/TNBC cases (TCGA/BRCA n = 1098; Basal-like/TNBC n = 199), classified with the AIMS algorithm, and evaluated concordance between KO-associated signatures and patient tumor expression patterns via trend-based analyses across the LINC01133 expression levels and associated genes. Results: A total of 265 KO-dominant DEGs were identified in Hs578T_ko, reflecting transcriptional changes consistent with tumor progression, with enrichment of pathways associated with LINC01133 knockout including cell adhesion, cell–cell interactions, epithelial–mesenchymal transition (EMT), and extracellular matrix (ECM) remodeling. The main DEGs included ITIH5, GLUL, CACNB2, PDX1, ASPN, PTGER3, MFAP4, PI15, EPHB6, and CPA3 with additional candidates, such as KAZN and the lncRNA gene SSC4D, which have been implicated in migration/invasion, ECM remodeling, or signaling across multiple tumor contexts. Translational analyses in TCGA-BRCA basal-like tumors suggested a descriptive association in which lower LINC01133 levels were accompanied by shifts in the expression trends of genes linked to ECM/EMT programs and modulation of genes related to cell adhesion and protease inhibition. Conclusions: These results suggest a transcriptional model in which LINC01133 is associated with TNBC-related gene expression programs in a concentration-dependent manner, with loss of LINC01133 being associated with a transcriptomic shift toward pro-migratory/ECM remodeling signatures. While functional validation is required to establish causality, these data support LINC01133 as a molecule of interest in breast cancer research. Full article

Non-coding RNAs (ncRNAs) have emerged as promising biomarkers for prostate cancer (PCa), yet evidence remains dispersed across heterogeneous studies and their regulatory context is seldom analyzed in an integrated manner. This study systematically maps ncRNAs reported as diagnostic biomarkers for PCa and characterizes their molecular interactions through in silico analyses. A comprehensive evidence-mapping strategy across major bibliographic databases identified 693 studies, of which 58 met eligibility criteria. Differentially expressed ncRNAs were extracted and classified by RNA type. Subsequently, miRNA–target prediction, miRNA–protein interaction network construction, and functional enrichment analyses were performed to explore the regulatory landscape of miRNA-associated proteins. Results: The final dataset included 4500 participants (2871 PCa cases and 2093 controls) and reported 94 differentially expressed miRNAs, eight lncRNAs, and several circRNAs, snoRNAs, snRNAs, and piRNAs. In silico analyses predicted 13,493 miRNA–mRNA interactions converging on 4916 unique target genes, with an additional 2481 prostate tissue-specific targets. The miRNA–protein network comprised 845 nodes and 2335 edges, revealing highly connected miRNAs (e.g., hsa-miR-16-5p, hsa-miR-20a-5p) and protein hubs (QKI, YOD1, TBL1XR1; prostate-specific CDK6, ACVR2B). Enrichment analysis showed strong overrepresentation of metabolic process-related GO terms and cancer-associated KEGG pathways. Conclusions: These findings refine the list of promising ncRNA biomarkers and highlight candidates for future clinical validation. Full article

Background/Objectives: Parkinson’s disease (PD) is an adult-onset neurodegenerative disorder whose pathogenesis is still not completely understood. Several lines of evidence suggest that alterations in epigenetic architecture may contribute to the development of this condition. Here, we present a pilot DNA methylation study from peripheral blood in a cohort of Sicilian PD patients and matched controls. Peripheral tissue analysis has previously been shown to reflect molecular and functional profiles relevant to neurological diseases, supporting their validity as a proxy for studying brain-related epigenetic mechanisms. Methods: We analyzed 20 PD patients and 20 healthy controls (19 males and 21 females overall), matched for sex, with an age range of 60–87 years (mean 72.3 years). Peripheral blood DNA was extracted and processed using the Illumina Infinium MethylationEPIC v2.0 BeadChip, which interrogates over 935,000 CpG sites across the genome, including promoters, enhancers, CpG islands, and other regulatory elements. The assay relies on sodium bisulfite conversion of DNA to detect methylation status at single-base resolution. Results: Epigenome-wide association study (EWAS) data allowed for multiple levels of analysis, including immune cell-type deconvolution, estimation of biological age (epigenetic clocks), quantification of stochastic epigenetic mutations (SEMs) as a measure of epigenomic stability, and differential methylation profiling. Immune cell-type inference revealed an increased but not significant proportion of monocytes in PD patients, consistent with previous reports. In contrast, epigenetic clock analysis did not reveal significant differences in biological age acceleration between cases and controls, partially at odds with earlier studies—likely due to the limited sample size. SEMs burden did not differ significantly between groups. Epivariations reveal genes involved in pathways known to be altered in dopaminergic neuron dysfunction and α-synuclein toxicity. Differential methylation analysis, however, yielded 167 CpG sites, of which 55 were located within genes, corresponding to 54 unique loci. Gene Ontology enrichment analysis highlighted significant overrepresentation of pathways with neurological relevance, including regulation of synapse structure and activity, axonogenesis, neuron migration, and synapse organization. Notably, alterations in KIAA0319, a gene involved in neuronal migration, synaptic formation, and cortical development, have previously been associated with Parkinson’s disease at the gene expression level, while methylation changes in FAM50B have been reported in neurotoxic and cognitive contexts; our data suggest, for the first time, a potential epigenetic involvement of both genes in Parkinson’s disease. Conclusions: This pilot study on a Sicilian population provides further evidence that DNA methylation profiling can yield valuable molecular insights into PD. Despite the small sample size, our results confirm previously reported findings and highlight biological pathways relevant to neuronal structure and function that may contribute to disease pathogenesis. These data support the potential of epigenetic profiling of peripheral blood as a tool to advance the understanding of PD and generate hypotheses for future large-scale studies. Full article

We recently identified significant differences between porcine arterial and venous smooth muscle cells (ApSMCs and VpSMCs) in the expression of numerous genes and activity of several important signaling pathways. To understand the mechanisms that are responsible for these differences, we performed a genome-wide comparison of VpSMCs and ApSMCs using bulk RNA sequencing. A principal component analysis (PCA) plot and heatmaps revealed a clear separation of the two groups of samples. Using a standard cutoff (≥2-fold change, false discovery rate (FDR) ≤ 0.05), 466 genes were highly expressed in ApSMCs, and 358 genes were highly expressed in VpSMCs. Functional pathway analyses were conducted using the Gene Set Enrichment Analysis (GSEA) tool. The top 15 enriched pathways of the GSEA and Overrepresentation Analysis (ORA) results were detected by comparing the dataset against the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) biological process, GO cellular component, GO molecular function, and WikiPathways databases. Both the GSEA and ORA results revealed that the top enriched pathways are mostly linked to cell cycle, cell structure, and cell differentiation. Further analysis of differentially expressed genes (DEGs) in a specific pathway identified that different sets of genes were utilized to regulate the same pathway between ApSMCs and VpSMCs. For example, in the cell cycle pathway, TGFB1, GADD45A, and TP53 were expressed highly in ApSMCs, while SKP2, PCK1, CDK1, and PPP2CA were expressed highly in VpSMCs. This study identified key differences in the gene expression patterns of two subsets of VSMCs and found that different sets of genes are utilized in specific signaling pathways within the different subtypes of cells, which provides crucial information for developing vein- or artery-specific strategies to prevent corresponding vascular diseases. Full article

Cardiometabolic phenotypes such as obesity and impaired insulin action are key determinants of type 2 diabetes (T2D). Growing evidence highlights the postprandial state as a critical window in metabolic regulation, where epigenetic mechanisms, particularly DNA methylation in insulin-sensitive tissues, may play pivotal roles. However, their dynamics across prandial states in subcutaneous adipose tissue (SAT) remain unclear. We analyzed genome-wide DNA methylation in paired fasting and postprandial SAT biopsies from 29 asymptomatic, drug-naïve individuals classified as controls (n = 8), prediabetes n = 9), or T2D (n = 12). Postprandial samples followed a standardized mixed-meal test. DNA methylation was quantified using the Illumina MethylationEPIC array and analyzed through the Chip Analysis Methylation Pipeline (ChAMP) pipeline. Differential methylation was more pronounced postprandially, especially in the T2D group. After adjusting for age and sex, 4599 differentially methylated CpG sites (DMCs) were identified, with increased hypermethylation in T2D. A total of 130 DMCs across 99 genes, including LCLAT1, HLA-C, ZNF714, and HOOK2, were shared by prediabetes and T2D groups. Over-representation analysis revealed 202 enriched pathways related to insulin resistance, AMPK signaling, and immune responses. Additionally, 110 Differentially Methylated Regions (DMRs), including ZNF577 and AGPAT1, were detected. These findings reveal early, prandial-dependent epigenetic alterations in SAT that precede overt dysglycemia, offering insights into personalized prevention in T2D. Full article

Network pharmacology is a powerful approach for studying complex drug–target interactions and biological pathways. However, existing tools often require extensive manual intervention and lack integrated analysis capabilities. Here, we present NeXus v1.2, an automated platform for network pharmacology and multi-method enrichment analysis including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) that addresses these limitations. NeXus v1.2 enables the seamless integration of multi-layer biological relationships, handling complex interactions between genes, compounds, and plants while maintaining analytical rigor. The platform implements three enrichment methodologies: Over-Representation Analysis (ORA), GSEA, and GSVA, circumventing limitations associated with arbitrary threshold-based approaches. NeXus v1.2 was validated using multiple datasets spanning 111 to 10,847 genes, demonstrating robust scalability and performance across dataset sizes. The platform was initially tested using a representative dataset comprising 111 genes, 32 compounds, and 3 plants, showing consistent performance in processing various relationship patterns, including shared compounds between plants and multitargeted genes. The processing time for this dataset was 4.8 s with peak memory usage of 480 MB. Large-scale validation with datasets up to 10,847 genes confirmed scalability, with linear time complexity and completion times under 3 min. NeXus v1.2 automatically generates comprehensive visualizations, including network maps, enrichment analyses, and relationship patterns, while maintaining the biological context of interactions. The tool successfully processed and analyzed enrichment patterns across multiple functional domains, generating publication-quality visualization outputs at 300 DPI resolution. The platform demonstrated enhanced automation in handling incomplete relationship data and maintaining analytical integrity across different biological layers. Compared to manual workflows requiring 15–25 min, NeXus v1.2 reduced the analysis time to under 5 s (>95% reduction) while ensuring the comprehensive coverage of biological relationships. NeXus v1.2 provides improved automation and integration for network pharmacology analysis, offering an efficient and user-friendly platform for complex biological network analysis. Its modular architecture enables the future integration of AI technologies and expansion into various therapeutic applications. Full article

Cell–cell interactions play a pivotal role in maintaining tissue homeostasis and driving disease progression. Conventional Cell–cell interactions modeling approaches depend on ligand–receptor databases, which often fail to capture context-specific or newly emerging signaling mechanisms. To address this limitation, we propose a data-driven computational framework, data-driven cell–cell interaction inference (DD-CC-II), which employs a graph-based model using eigen-cells to represent cell groups. DD-CC-II uses eigen-cells (i.e., functional module within the cell population) to characterize cell groups and construct correlation coefficient networks to model between-group associations. Correlation coefficient networks between eigen-cells are constructed, and their statistical significance is evaluated via over-representation analysis and hypergeometric testing. Monte Carlo simulations demonstrate that DD-CC-II achieves superior performance in inferring CCIs compared with ligand–receptor-based methods. The application to whole-blood RNA-seq data from the Japan COVID-19 Task Force revealed severity stage-specific interaction patterns. Markers such as FOS, CXCL8, and HLA-A were associated with high severity, whereas IL1B, CD3D, and CCL5 were related to low severity. The systemic lupus erythematosus pathway emerged as a potential immune mechanism underlying disease severity. Overall, DD-CC-II provides a data-centric approach for mapping the cellular communication landscape, facilitating a better understanding of disease progression at the intercellular level. Full article

Prosopis cineraria (L.) Druce is a keystone tree species in the arid and semi-arid regions of West and South Asia, with critical ecological, cultural, and conservation significance. In the United Arab Emirates (UAE) and other regions of the Arabian Peninsula, this beneficial tree is called Ghaf. Despite its importance, genomic resources and population-level diversity data for the tree remain limited. Here, we present the first comprehensive population genomics study of Ghaf based on whole-genome resequencing of 204 individual trees collected across the UAE. Following Single-Nucleotide Polymorphism (SNP) discovery and stringent filtering, we analyzed 57,183 high-quality LD-pruned SNPs to assess population structure, diversity, and gene flow. Principal component analysis (PCA), sparse non-negative matrix factorization (sNMF), and discriminant analysis of principal components (DAPC) revealed four well-defined genetic clusters, broadly corresponding to geographic origins. The genetic diversity varied significantly among the groups, with observed heterozygosity (Ho), inbreeding coefficients (F), and nucleotide diversity ($\pi$) showing strong population-specific trends. Genome-wide fixation index F_ST scans identified multiple highly differentiated genomic regions, enriched for genes involved in stress response, transport, and signaling. Functional enrichment using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam annotations indicated overrepresentation of protein kinase activity, ATP binding, and hormone signaling pathways. TreeMix analysis revealed gene flow into one of the genetic clusters from both others, suggesting historical admixture and geographic connectivity. This work provides foundational insights into the population genomic profile of P. cineraria, supporting conservation planning, restoration strategies, and long-term genetic monitoring in arid ecosystems. Full article

Malignant melanoma (MM) affects not only humans but also animals, with gray horses being particularly predisposed to acquiring the disease. Multiomics have greatly advanced the understanding of human MM. In contrasty little is known regarding the pathogenesis of gray-horse melanoma and the unique phenomenon of melanoma “dormancy” in some animals. To help close this gap in knowledge, melanoma tissue and intact skin collected from gray horses were subjected to transcriptome analysis using RNAseq. In the next step, cultured primary tumor cells and normal skin fibroblasts were established from gray horses, and their protein expression profiles were determined. The obtained data unambiguously identified gray-horse melanoma (ghM) as a malignant tumor, as reflected by the overrepresentation of pathways typically activated in human melanoma and other human cancers. These included the RAS/RAF/MAPK, the IRS/IGF1R, and the PI3K/AKT signaling networks. In addition, the obtained data suggest that the key molecules RAC1, RAS, and BRAF, which are frequently mutated in human melanoma, may also contain activating mutations in ghM, whilst PTEN may harbor loss-of-function mutations. This issue will be subject to downstream analyses determining the mutational status in ghM to further advance the understanding of this frequent disease in gray horses. Full article

Background and Objectives: Rectal cancer management increasingly relies on watch-and-wait strategies after neoadjuvant chemoradiotherapy (nCRT). Accurate, non-invasive prediction of pathological complete response (pCR) remains elusive. Emerging evidence suggests that gut-microbiome composition modulates radio-chemosensitivity. We systematically reviewed primary studies that correlated baseline or on-treatment gut-microbiome features with nCRT response in locally advanced rectal cancer (LARC). Methods: MEDLINE, Embase and PubMed were searched from inception to 30 April 2025. Eligibility required (i) prospective or retrospective human studies of LARC, (ii) faecal or mucosal microbiome profiling by 16S, metagenomics, or metatranscriptomics, and (iii) response assessment using tumour-regression grade or pCR. Narrative synthesis and random-effects proportion meta-analysis were performed where data were homogeneous. Results: Twelve studies (n = 1354 unique patients, median sample = 73, range 22–735) met inclusion. Four independent machine-learning models achieved an Area Under the Receiver Operating Characteristic curve AUROC ≥ 0.85 for pCR prediction. Consistently enriched taxa in responders included Lachnospiraceae bacterium, Blautia wexlerae, Roseburia spp., and Intestinimonas butyriciproducens. Non-responders showed over-representation of Fusobacterium nucleatum, Bacteroides fragilis, and Prevotella spp. Two studies linked butyrate-producing modules to radiosensitivity, whereas nucleotide-biosynthesis pathways conferred resistance. Pooled pCR rate in patients with a “butyrate-rich” baseline profile was 44% (95% CI 35–54) versus 21% (95% CI 15–29) in controls (I² = 18%). Conclusions: Despite heterogeneity, convergent functional and taxonomic signals underpin a microbiome-based radiosensitivity axis in LARC. Multi-centre validation cohorts and intervention trials manipulating these taxa, such as prebiotics or live-biotherapeutics, are warranted before clinical deployment. Full article

Biochanin A, a naturally occurring isoflavone derived from legumes, possesses anti-inflammatory, estrogenic, and anticancer activities. In this study, we investigated the cytotoxic effects and underlying molecular mechanisms of Biochanin A in acute myeloid leukemia (AML) cell lines, U937 and THP-1, using in vitro cytotoxicity assays, RNA sequencing, and bioinformatic analyses. Biochanin A induced dose-dependent apoptosis, as evidenced by caspase-7 activation and PARP1 cleavage. Over-representation analysis (ORA) revealed that differentially expressed genes (DEGs) were significantly enriched in pathways related to inflammatory responses, DNA replication, and cell cycle regulation. Gene set enrichment analysis (GSEA) further confirmed the upregulation of apoptosis- and inflammation-related pathways and the downregulation of MYC targets, cholesterol biosynthesis, and G2/M checkpoint gene sets. RT-qPCR analysis demonstrated that Biochanin A downregulated oncogenes such as RUNX1, BCL2, and MYC while upregulating CHOP (GADD153), CDKN1A (p21), and SQSTM1 (p62), contributing to apoptosis and cell cycle arrest across both cell lines. Notably, Biochanin A downregulated PLK1 and UHRF1 in THP-1 cells, indicating a disruption of mitotic progression and epigenetic regulation. In contrast, in U937 cells, Biochanin A upregulated TXNIP and downregulated CCND2, highlighting the involvement of oxidative stress and G1/S cell cycle arrest. These findings support the potential of Biochanin A as a promising therapeutic candidate for AML through both shared and distinct regulatory pathways. Full article

Sickle cell disease (SCD) is a group of recessive diseases caused by the β^S sickling mutation of HBB in homozygosity or in compound heterozygosity with other pathogenic HBB mutations. Patients with severe SCD typically experience painful vaso-occlusive crises and other pain-related phenomena, including acute chest syndrome, priapism, dactylitis, avascular necrosis, and splenic sequestration and infarction. High variability of pain-related phenomena per SCD genotype indicates genetic disease modifiers (GDMs) as pathology determinants and, thus, as critical to prognosis, treatment choice, and therapy development. Articles likely holding genetic information for SCD pain phenomena were identified in PubMed and SCOPUS for article quality assessment and extraction of corresponding GDMs and observations indicative of development areas in our understanding of SCD GDMs. This process led to the initial selection of 183 articles matching the search terms, which, after two-step selection, resulted in the inclusion of 100 articles for content analysis and of significant findings for GDMs from 37 articles. Published data point to gender effects and to 51 GDM SNVs, deletions, and regions, including globin genes and significant overrepresentation of gene ontology pathways related, e.g., to oxidative stress, hypoxia, and regulation of blood pressure. Analyzed articles further pointed to additional candidate GDMs affecting SCD VOC and pain phenomena and to potential confounding factors for GWAS analyses. We found that despite the critical importance of VOC and pain phenomena for SCD pathology, corresponding clinically relevant genetic insights are held back by a shortage of large-scale, systematic multi-ethnic efforts, as undertaken by the INHERENT Network. Full article

Maternal nutrition’s impact on liver transcriptome in beef cattle offspring is still underexplored. We investigated the long-term effects of maternal nutrition strategies on the liver transcriptome of pre-slaughter Nelore bulls. Pregnant cows were divided into three groups, each receiving different nutritional regimens: NP (control, only mineral supplementation), PP (late gestation protein–energy supplementation), and FP (protein–energy supplementation throughout pregnancy). Liver samples were collected from male offspring aged 22.5 ± 1 months and analyzed using RNA-Seq (n = 5 per treatment). Principal component analysis (PCA) and differential gene expression analysis were carried out in an R statistical environment. Genes were considered significant when FDR < 0.05. The over-representation analysis (ORA) was performed using the clusterProfiler package from R. Metabolic pathways were considered significant when the Q-value < 0.1. The PCA showed overlapping clusters among the groups. We identified 16 differentially expressed genes (DEGs) associated with PP × NP contrast, four with FP × NP, and two with FP × PP. The ORA revealed two significant pathways (thiamine and butanoate metabolism). The identified genes and pathways were associated with vitamins, energy, oxidative metabolism, and immune function. This study emphasizes the more significant long-term effects of the PP treatment on the offspring’s liver transcriptome compared to the FP treatment. Full article

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication difficulties and repetitive behaviors. Emerging evidence suggests a potential link between ASD and celiac disease (CD), possibly mediated by immune dysregulation and nutrient deficiencies. This study explores the shared biological pathways between ASD and CD using an in silico approach. Methods: Gene–disease associations for ASD and CD were retrieved from DisGeNET using MedGen Concept IDs (C1510586 and C0007570, respectively). An over-representation analysis (ORA) was conducted using GeneTrail 3.2 to identify significantly enriched biological pathways, which were then compared for overlap. A false discovery rate (FDR) < 0.05 was considered statistically significant. Results: The gene–disease association analysis identified 536 ASD-related genes and 52 CD-related genes. The ORA revealed several shared biological pathways, including immune pathways, cellular metabolism, and micronutrient processing (e.g., folate, selenium, vitamin A). These findings suggest immune dysfunction and nutrient malabsorption as potential mechanistic links between ASD and CD. Conclusions: The observed pathway overlap supports the hypothesis that immune dysregulation and metabolic disturbances contribute to both ASD and CD. Nutrient deficiencies, driven by CD-associated malabsorption, may exacerbate ASD symptoms. Additionally, sensory processing abnormalities in ASD could impact dietary choices, complicating gluten-free diet adherence. Future studies should validate these findings in clinical cohorts and explore dietary interventions, such as targeted supplementation, to mitigate ASD symptoms in individuals with CD. Full article

Alzheimer’s disease (AD) is the most common form of dementia, characterized by β-amyloid (Aβ) plaques and neurofibrillary tangles, leading to neuronal loss and cognitive impairments. Recent studies have reported the dysregulation of RNA splicing in AD pathogenesis. Our previous transcriptomic study demonstrated the neuroprotective effect of the phytocannabinoid cannabinerol (CBNR) against the cell viability loss induced by Aβ in differentiated SH-SY5Y cells. This study also highlighted the deregulation of genes involved in mRNA splicing after Aβ exposure or CBNR pre-treatment. Here, we investigated whether CBNR could restore the splicing defects induced by Aβ in an AD in vitro model. Using the rMATS computational tool for detecting differential alternative splicing events (DASEs) from RNA-Seq data, we obtained 96 DASEs regulated in both conditions and, remarkably, they were all restored by CBNR pre-treatment. The pathway analysis indicated an over-representation of the “Alzheimer’s disease–amyloid secretase pathway”. Additionally, we observed that Aβ exposure increased the frequency of retained introns (RIs) among the shared DASEs, and that this frequency returned to normality by CBNR pre-treatment. Interestingly, most of these RIs contain a premature in-frame stop codon within the RNA sequence. Finally, analyzing the DASE regions for miRNA hybridization, we found 33 potential DASE/miRNA interactions that were relevant in AD pathogenesis. These findings revealed a novel trans-gene regulation by CBNR, potentially explaining part of its neuroprotective role. This is the first study demonstrating the involvement of a cannabinoid in the regulation of mRNA splicing in an AD model. Full article