Search Results (1,502)

Background: Head and neck squamous cell carcinoma remains a highly aggressive malignancy with limited predictive biomarkers for prognosis and radiotherapy response. Increasing evidence indicates that pseudogenes are functionally active regulators of cancer biology, yet their clinical relevance in HNSCC is poorly defined. Methods: Using transcriptomic and clinical data from The Cancer Genome Atlas, we analyzed the expression and clinical significance of two pseudogenes, ANXA2P2 and PA2G4P4, in HNSCC. Associations with clinicopathological features, HPV status, tumor subtypes, survival, genomic instability, radiotherapy response, and immune landscape were assessed using bioinformatic tools. Results: Both pseudogenes were significantly upregulated in HNSCC compared to normal tissues. Higher expression levels correlated with adverse clinicopathological features, increased tumor proliferation and wound-healing capacity, and unfavorable TCGA molecular subtypes. High ANXA2P2 and PA2G4P4 expression was associated with reduced overall survival, while their combined low-expression signature identified patients with significantly improved overall and disease-free survival. Notably, lower expression of both pseudogenes was observed in patients responding to radiotherapy, whereas higher expression was linked to genomic instability parameters and enrichment of oncogenic pathways, including MYC, PI3K/AKT/mTOR, cell cycle regulation, and DNA repair. ANXA2P2 expression differed significantly by HPV status, showing reduced levels in HPV-positive tumors. Furthermore, pseudogene expression stratified distinct immune profiles, including immune subtypes, stromal and immune scores, and specific immune cell populations. Conclusions:ANXA2P2 and PA2G4P4 are clinically relevant pseudogenes associated with tumor aggressiveness, immune modulation, and radiotherapy response in HNSCC. These findings support their potential utility as prognostic and predictive biomarkers and provide a rationale for further functional validation in experimental models. Full article

Background: Cancer-associated fibroblasts (CAFs) are key mediators of metastatic progression in non-small cell lung cancer (NSCLC). Fibroblast activation protein (FAP) serves as the hallmark of CAF activation. However, the upstream regulation of FAP remains elusive, limiting stroma-targeted therapy development. Methods: ⁶⁸Ga-FAP inhibitor (FAPI)-04 PET/CT imaging was performed on 61 NSCLC patients to evaluate the clinical significance of FAP. CAFs and normal fibroblasts (NFs) were isolated from patient tissues. Bioinformatic analysis and qRT-PCR were employed to screen and validate miRNAs. Functional assays (CCK-8, collagen contraction, wound healing, transwell co-culture) were utilized to investigate the role of miR-624-5p in regulating fibroblast activation and the effects on the metastatic potential of NSCLC cells. The targeting relationship between miR-624-5p and FAP was validated using FISH, dual-luciferase assay, and Western blotting. Results: ⁶⁸Ga-FAPI-04 uptake was higher in advanced NSCLC (p < 0.001) and correlated with tumor size, lymph node metastases, and distant metastases (p < 0.05). Isolated primary CAFs significantly enhanced the migration and invasion of A549 and PC9 cells compared to NFs (p < 0.001). We identified miR-624-5p as a significantly downregulated miRNA in CAFs (p < 0.001). Functionally, miR-624-5p overexpression inhibited CAF proliferation and collagen contraction (p < 0.01) and reduced the proliferation, migration, and invasion capabilities of A549 and PC9 cells (p < 0.001). Mechanistically, miR-624-5p bound to FAP mRNA and negatively regulated FAP expression (p < 0.001), thus suppressing CAF activation and tumor metastasis. Conclusions: Our findings establish miR-624-5p as a novel upstream regulator that suppresses FAP expression, consequently inhibiting CAF activation and its pro-metastatic function. Targeting the miR-624-5p/FAP axis represents a promising therapeutic strategy for NSCLC metastasis. Full article

Background: Gastric signet-ring cell carcinoma (GSRCC) is a distinct subtype of gastric cancer characterized by unique biological features, leading to low rates of early diagnosis, poor prognosis, and limited response to chemotherapy and immunotherapy. Effective targeted therapies for GSRCC remain scarce. Given these treatment challenges and the potential efficacy of antibody-drug conjugates (ADCs) in clinical settings, this study focuses on identifying novel ADCs with significant potential to improve the treatment outcomes of GSRCC. Methods: We conducted a comprehensive bioinformatics analysis of GSRCC using multi-omics data (including transcriptomics and proteomics) and identified the poliovirus receptor (PVR) as a potential therapeutic target for GSRCC. We selected deruxtecan (DXd) as an effective carrier for developing an ADC targeting GSRCC. The synthesized PVR monoclonal antibody-DXd complex (PVR-DXd) has a drug-to-antibody ratio (DAR) of 4. Results: PVR-DXd demonstrated potent antitumor activity in a human GSRCC xenograft model, effectively eliminating tumors while sparing normal tissue, highlighting its potential as a novel and impactful targeted therapy for this aggressive subtype of gastric signet ring cell carcinoma. Conclusions: This preliminary study supports the further development of PVR-DXd as a candidate therapy for advanced GSRCC. Full article

Breast cancer (BC) is the most frequently diagnosed malignancy in women and remains a leading cause of cancer-related mortality worldwide. Among the oncogenic microRNAs, hsa-miR-21 has been consistently implicated in tumorigenesis, yet a comprehensive network-level understanding of its regulatory landscape in BC is lacking. In this study, we performed an integrative bioinformatics analysis to characterize the molecular pathways and prognostic impact of hsa-miR-21. Experimentally validated mRNA targets were retrieved from miRTarBase and used to construct a high-confidence protein–protein interaction network via STRING, followed by hub-gene prioritization in Cytoscape. Functional enrichment analyses were conducted with DAVID to assess Gene Ontology (GO) categories and KEGG pathways. Survival analyses were performed in large BC cohorts from METABRIC and TCGA using the Kaplan–Meier Plotter. We identified 12 hub genes that are central regulators of apoptosis, proliferation, immune signaling, and transcriptional control. GO and KEGG analyses revealed enrichment in cancer-related, immune, and metabolic pathways, underscoring the pleiotropic role of miR-21. While miR-21 expression alone was not significantly associated with overall survival, a composite hub-gene signature demonstrated strong prognostic value. These findings highlight the importance of network-level biomarkers in BC and provide a reproducible framework for dissecting the clinical relevance of disease-associated miRNAs. Full article

Cancer remains one of the most common causes of death worldwide and imposes enormous social and economic burdens. Human tumor-associated NADH oxidase (ENOX2, also known as tNOX) is a cancer cell-specialized NADH oxidase that is expressed on the membranes of cancer cells. In this study, we investigated the potential role of ENOX2 in regulating stemness properties in oral cancer through a combination of in vitro, in vivo, and bioinformatics approaches. We found that ENOX2 physically interacted with the stem cell transcription factor, SOX2, in co-immunoprecipitation experiments. The expression and activity of ENOX2 were elevated in p53-functional SAS and p53-mutated HSC-3 oral cancer cell spheroids compared with their monolayer counterparts. Consistently, SIRT1, a downstream effector modulated by ENOX2 through NAD⁺ generation, was also upregulated in spheroid cultures. Functional studies further established that ENOX2 overexpression significantly enhanced spheroid formation, self-renewal properties, stem cell marker expression, and PKCδ expression, whereas ENOX2 knockdown produced the opposite effects. In xenograft models, ENOX2-overexpressing oral cancer cell spheroids exhibited enhanced tumorigenicity, while ENOX2-silenced spheroids formed significantly smaller tumors. Complementary analyses of public transcriptomic and proteomic datasets revealed elevated ENOX2 expression in human head and neck tumor tissues compared with adjacent normal tissues. Based on these findings and literature-supported correlations, we propose a putative ENOX2-SIRT1-SOX2 regulatory framework that may contribute to the acquisition and maintenance of stem-like properties of oral cancer cells. While the ENOX2–SOX2 interaction was experimentally validated, the roles of SIRT1 and other downstream components are inferred from bioinformatic analyses and prior studies; thus, this axis represents a hypothetical model that warrants further mechanistic investigation. Collectively, our results identify ENOX2 as a potential regulator of oral cancer stemness and provide a conceptual foundation for future studies aimed at elucidating its downstream pathways and clinical relevance in head and neck tumors. Full article

Pathogenic germline variants in the ATM gene are associated with a 20–30% lifetime risk of breast cancer. Crucially, a relevant fraction of loss-of-function variants in breast cancer susceptibility genes disrupts pre-mRNA splicing. We aimed to perform splicing analysis of ATM splice-site variants identified in the large-scale sequencing project BRIDGES (Breast Cancer After Diagnostic Gene Sequencing). To this end, we bioinformatically selected 47 splice-site variants across 17 exons that were genetically engineered into three minigenes and assayed in MCF-7 cells. Aberrant splicing was observed in 38 variants. Of these, 30 variants, including 7 missense, yielded no or negligible expression of the minigene full-length (mgFL) transcript. A total of 69 different transcripts were characterized, 48 of which harboured a premature termination codon. Some variants, such as c.2922-1G>A, generated complex patterns with up to 10 different transcripts. Alternative 3′ or 5′ splice-site usage was the predominant event. Integration of ATM minigene read-outs into the ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based specifications for the ATM gene enabled the classification of 30 ATM variants as pathogenic or likely pathogenic and 9 as likely benign. Overall, splicing assays provide key information for variant interpretation and the clinical management of patients. Full article

Disruption of the blood–milk barrier and inhibition of enzymatic activity caused by abnormal external stimuli, accompanied by the occurrence of autophagy, are among the major factors contributing to the onset of clinical mastitis (CM) in dairy cows. However, the molecular mechanisms through which external stimuli and autophagy regulate CM in dairy cows are not fully understood. This study examined mammary gland (MG) tissue samples collected from healthy dairy cows and those with CM caused by Staphylococcus aureus (n = 3 per group) to observe histological changes and autophagic phenomena, identify candidate biomolecular targets involved in external stimuli in dairy cows affected by mastitis through proteomic and bioinformatic analyses, and analyze their expression and distribution patterns in MG tissues. Pathological examination revealed that the MG tissues of the CM group exhibited significant alveoli collapse and inflammatory cell infiltration, accompanied by autolysosome and phagolysosome activation, and elevated expression of lysosomal and autophagic markers. Bioinformatic analysis identified five biological processes (BPs) and 144 differentially expressed proteins (DEPs) associated with external stimuli, among which beclin 1 (BECN1) was involved in all five BPs. Pathway enrichment analysis revealed that BECN1 participated in six autophagy-related signaling pathways. BECN1 was localized in the cytoplasm of mammary epithelial cells, and both mRNA and protein levels of BECN1 were significantly upregulated in the CM group compared with those in the controls (p < 0.01). These findings suggest that BECN1 expression is closely associated with CM in dairy cows and correlates with autophagy-related responses to external stimuli, and its elevated expression is positively correlated with Staphylococcus aureus–induced CM severity. Our results offer preliminary observations relevant to the molecular mechanisms by which BECN1, the autophagy-regulating biomolecule BECN1 influences the development of CM. Full article

Gliomas are notoriously difficult to treat owing to their pronounced heterogeneity and highly variable treatment responses. This reality drives the development of precise diagnostic and prognostic methods. This review explores the modern arsenal of bioinformatic tools aimed at refining diagnosis and stratifying glioma patients by different malignancy grades and types. We perform a comparative analysis of software solutions for processing whole-exome sequencing data, analyzing DNA methylation profiles, and interpreting transcriptomic data, highlighting their key advantages and limited applicability in routine clinical practice. Special emphasis is placed on the contribution of bioinformatics to fundamental oncology, as these tools aid in the discovery of new biomarker genes and potential targets for targeted therapy. The ninth section discusses the role of computational models in predicting immunotherapy efficacy. It demonstrates how integrative data analysis—including tumor mutational burden assessment, characterization of the tumor immune microenvironment, and neoantigen identification—can help identify patients who are most likely to respond to immune checkpoint inhibitors and other immunotherapeutic approaches. The obtained data provide compelling justification for including immunotherapy in standard glioma treatment protocols, provided that candidates are accurately selected based on comprehensive bioinformatic analysis. The tools discussed pave the way for transitioning from an empirical to a personalized approach in glioma patient management. However, we also note that this field remains largely in the preclinical research stage and has not yet revolutionized clinical practice. This review is intended for biological scientists and clinicians who find traditional bioinformatic tools difficult to use. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease, is a highly prevalent hepatic condition closely linked to metabolic syndrome (MetS). Epigenetic regulators such as microRNAs (miRNAs) have emerged as critical modulators of the molecular pathways underlying MASLD pathogenesis, offering new perspectives for non-invasive diagnosis and targeted therapy. This study aimed to identify and characterize target genes and pathways regulated by two key hepatic miRNAs, namely miR-122 and miR-29a, through a comprehensive in silico bioinformatics approach, to better understand their functional roles in MASLD and MetS. Methods: Target genes of miR-122 and miR-29a were predicted using three databases (TargetScan, DIANA-microT-CDS, and miRWalk), and those identified by at least two databases were selected for downstream analyses. Functional enrichment was performed using Gene Ontology and KEGG pathway analysis. Gene networks and biological process maps were constructed using Metascape, clusterProfiler and Cytoscape. Results: miR-122 was found to negatively regulate genes involved in lipid metabolism, insulin signaling, and inflammatory pathways, including PPARGC1A, PPARA, LPL, TLR4, and HMGCR, contributing to insulin resistance and liver dysfunction. By contrast, miR-29a demonstrated potential hepatoprotective effects by targeting LEP, INSR, IL13, and IL18, enhancing insulin sensitivity and reducing fibrogenic activity. Enrichment analysis revealed strong associations with biological processes, such as STAT phosphorylation, lipid homeostasis, and inflammatory signaling, as well as associations with cellular components, including lipoproteins and plasma membranes. miR-122 and miR-29a exhibit opposing regulatory functions in MASLD pathogenesis. Whereas miR-122 is associated with disease progression, miR-29a acts protectively. These miRNAs may serve as promising biomarkers and therapeutic targets in MASLD and related metabolic conditions. Further validation through experimental and clinical studies is warranted. Full article

Lipodystrophies are rare syndromes characterized by partial or complete loss of subcutaneous adipose tissue leading to ectopic lipid deposition, insulin resistance, and the same metabolic derangements observed in obesity. Given the role of gut microbiota in metabolic disorders, we investigated whether its signature in obesity may be mirrored by that found in lipodystrophies, possibly contributing to their overlapping metabolic abnormalities. In this cross-sectional study, we included 8 individuals with lipodystrophy (LD), 16 individuals with obesity (Ob)—further categorized into 8 metabolically healthy (MHO) and 8 metabolically unhealthy (MUHO)—and 16 normal-weight controls (N). We assessed clinical and metabolic characteristics and performed 16S rRNA sequencing and bioinformatic analyses on fecal samples to characterize the gut microbiome. LD presented significantly lower body mass index (BMI) and waist circumference than Ob, but, from a metabolic perspective, LD showed similarity with MUHO and presented significantly lower levels of HDL-C and higher triglycerides compared to both N and MHO. Gut microbiota analysis revealed reduced α-diversity in LD, MHO and MUHO compared to N, whilst β-diversity and Firmicutes/Bacteroidetes ratio differences were not significant. At the phylum level, differential abundance analysis revealed that LD individuals exhibit similar microbial characteristics to MUHO and higher Verrucomicrobiota levels compared to MHO. The shared gut microbiota signature suggests another potential unexplored link between the pathogenesis of metabolic complications in lipodystrophies and obesity, providing novel insights into the complex interplay between dysbiosis and adiposopathy. Larger longitudinal studies are needed to explore the role of specific taxa and for a more precise characterization of different lipodystrophy subtypes. Full article

Background: Preeclampsia (PE) is a hypertensive disorder of pregnancy associated with oxidative stress and mitochondrial dysfunction. NRF1 and NRF2 are transcription factors that regulate mitochondrial activity and antioxidant defense. This study investigated their expression patterns in placentas from preeclamptic and severe preeclamptic pregnancies by immunohistochemical and bioinformatical methods. Methods: Placentas from 40 healthy controls, 40 PE, and 40 sPE patients were analyzed by histological and immunohistochemical techniques. Protein–protein interaction networks for NRF1, NRF2, and PE-related proteins were constructed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape software, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis performed via ShinyGO, with significance set at false discovery rate (FDR) < 0.05. Results: NRF1 expression was significantly decreased in PE and sPE groups compared to controls, with notably negative staining in syncytial knots and fibrinoid areas. Conversely, NRF2 expression significantly increased, showing intense positivity in syncytiotrophoblasts, stromal cells, and vascular structures. Pathway analysis revealed that decreased NRF1 expression was associated with glutathione metabolism, hypoxia inducible factor-1 (HIF-1) signaling, and AMP-Activated Protein Kinase (AMPK) signaling pathways. Increased NRF2 expression was associated predominantly with inflammatory and immune response pathways, including AGE-RAGE signaling and pathogen–response pathways. Conclusions: Differential expressions of NRF1 and NRF2 in preeclamptic placentas reflect distinct yet interconnected responses to oxidative stress and inflammation. These transcription factors have potential clinical relevance as biomarkers for PE severity assessment and as targets for future therapeutic interventions. Full article

As genomic technologies continue to evolve, understanding the scope and limitations of available prenatal testing methods is essential for accurate diagnosis and counseling. Chromosomal microarray analysis (CMA) and exome sequencing (ES) have emerged as key complementary tools in this setting. This review aims to outline the technical principles underlying CMA and ES and to compare their diagnostic capabilities and limitations in the prenatal context. This narrative review includes a literature search, with additional relevant articles identified through manual screening of reference lists from key publications and review articles. Due to the narrative nature of this review, no formal inclusion or exclusion criteria or quantitative synthesis were applied. Special focus was placed on clinical indications, variant interpretation challenges—particularly uncertain and incidental findings—gene selection strategies, and implications for prenatal counseling. Indications for both tests have increased over time but differ substantially. CMA is becoming the standard prenatal genetic test, particularly in the evaluation of fetal structural anomalies, whereas ES remains restricted to selected fetal structural anomalies. Interpretation of molecular results remains a major challenge, especially for variants of uncertain significance and incidental findings with unclear or unexpected implications for pregnancy management. For ES, agnostic gene selection strategies showed superior diagnostic yield compared with phenotype-driven approaches, likely reflecting the limited characterization of prenatal phenotypes. Continuous refinement of clinical indications, bioinformatic pipelines, variant classification criteria, and gene curation strategies is critical to ensure that prenatal results are accurate and clinically meaningful. Together, ongoing improvements in technology, interpretation, and clinical integration have the potential to transform prenatal genomics into a more precise, informed, and ethically responsible field. Full article

Background: Prostate cancer (PCa) is a prevalent malignancy with a rising incidence. Advanced PCa, often resistant to therapy, remains a major clinical challenge, underscoring the need to identify novel molecular drivers. Methods: Utilizing transcriptomic data from the TCGA and GEO databases, we identified APOBEC3C (A3C) as a key candidate through WGCNA, differential expression analysis, and LASSO regression. Its clinical relevance was assessed via Kaplan–Meier survival analysis. Then, we validated A3C expression patterns using immunohistochemistry and Western blot in normal and malignant prostate cell lines. The functional effects of A3C on proliferation, migration, and invasion and mechanisms of such were evaluated through in vitro gain- and loss-of-function assays (CCK-8, Ki67 staining, wound healing, Transwell, Western blot, etc.). Results:A3C was significantly downregulated in PCa, and this low expression strongly correlated with adverse clinicopathological features, including advanced T stage, higher Gleason scores, and worse survival. Bioinformatically, high A3C expression was associated with an activated anti-tumor immune microenvironment, characterized by enhanced CD8+ T cell infiltration, reduced M2 macrophage abundance, and upregulation of the immune checkpoint CD40. In vitro, A3C overexpression effectively suppressed PCa cell proliferation, migration, and invasion, while its knockdown promoted these malignant phenotypes. Mechanistically, A3C enhances the expression of the STING1 and its downstream related molecules Caspase-1, IL-18, and IL-1β; upregulates DNA damage-protective genes (GSTP1 and GPX3); and enhances the expression of cell cycle regulator GAS1. Conclusions: This study establishes A3C as a suppressor in PCa, which impedes tumor progression by regulating key molecules involved in cellular inflammation, cell cycle arrest, and DNA damage response. Full article

Background/Objectives: Rapid and accurate pathogen identification and antimicrobial susceptibility testing (AST) are critical for the proper management of patients with bloodstream infection (BSI). Real-time whole-genome sequencing (WGS) represents an attractive opportunity for exhaustive pathogen identification and antimicrobial susceptibility prediction (ASP). This feasibility study introduces BacT-Seq, a WGS-based prototype assay for the rapid and accurate identification of pathogens and the prediction of antimicrobial susceptibility from positive blood cultures using Oxford Nanopore Technologies (ONT) sequencing. Methods: A total of 200 positive blood culture samples from patients with a confirmed BSI were included in this study. DNA isolation from blood cultures was optimized prior to GridION (ONT) sequencing. Pathogen identification and several ASP methods were compared to conventional identification and phenotypic AST methods. Results: Most of the mono-microbial (89%) and poly-microbial (88%) samples were identified by BacT-Seq in less than 10 min of sequencing. While identification of poly-microbial samples remains challenging, identification of mono-microbial samples by sequencing was non-inferior to that of the conventional approach, even revealing an added value in terms of exhaustivity and/or taxonomic resolution. Machine-learning-based ASP models yielded 80% predictions in 2.5 h of sequencing. Their ability to predict resistance phenotypes varied with the microbial species evaluated, from 55/57 (96.5%) for Escherichia coli to 24/48 (50.0%) for Pseudomonas aeruginosa. Conclusions: This study demonstrates the feasibility of implementation of the BacT-Seq platform for the fast and accurate identification of pathogens from positive blood cultures. BacT-Seq performance of resistance predictions by bioinformatics tools is promising but requires further optimization and validation before clinical implementation. Full article

Background: Pancreatic adenocarcinoma (PAAD), often referred to as the “king of cancers,” remains poorly understood in terms of the regulatory mechanisms involving brown adipocytes (BAs). Methods: Bioinformatics approaches were employed to explore the role of BAs in PAAD progression, utilizing transcriptomic data from public databases. Prognostic genes were identified through differential expression analysis, univariate Cox regression, and machine learning. A risk model categorizing patients into high- and low-risk groups was developed, accompanied by a nomogram. Functional analysis, immune microenvironment profiling, somatic mutation analysis, and drug sensitivity testing were performed, with further validation via gene localization, immunohistochemistry, and clinical sample analysis. Results: Six prognostic genes (SERPINB5, CALU, TFRC, LY6D, SFRP1, and GBP2) were identified, with the model and nomogram exhibiting robust predictive performance. Notable differences between the high- and low-risk groups were found in immune pathways, cell infiltration, tumor mutational burden, and drug sensitivity (e.g., axitinib). Conclusions: SERPINB5, SFRP1, and TFRC were highly expressed in PAAD samples, providing new insights into potential therapeutic strategies in PAAD treatment. Full article