Search Results (134)

Background/Objectives: Acute radiotherapy-induced skin toxicity is a common complication in breast cancer treatment, with marked interindividual variability not fully explained by clinical factors. This study investigated the contribution of germline mutations in DNA repair and tumor suppressor genes to acute radiodermatitis in a homogeneous cohort treated with hypofractionated intensity-modulated radiotherapy with inverse planning, with adjustment for potential lifestyle confounders. Methods: Mutations were grouped into four functional categories: homologous recombination repair (HRR), Fanconi anemia (FA), DNA damage response (DDR), and tumor suppressor (TS) genes. Ordinal logistic regression models adjusted for clinical covariates evaluated pooled and functional category-specific mutation effects. Results: Overall, any mutation significantly increased the risk of higher-grade acute radiodermatitis (OR = 2.24, p = 0.003), an effect driven primarily by HRR and FA mutations, as exclusion of these mutations rendered the association non-significant (OR = 1.785, p = 0.064). Functional category-based analyses showed that HRR (OR = 2.60, p = 0.002) and FA (OR = 2.62, p = 0.002) mutations were the strongest predictors, reflecting overlapping roles in double-strand break and interstrand crosslink repair. DDR and TS mutations showed no significant effect. Conclusions: These results highlight the key role of high-fidelity DNA repair in normal tissue radiosensitivity and demonstrate that functional genetic stratification has diagnostic value as a pre-treatment predictive biomarker framework, enabling identification of patients at increased risk of acute skin toxicity and supporting personalized radiotherapy planning. Full article

Objectives: This study aimed to fill the data gap regarding the prevalence of germline (g) BRCA1/2 mutations in patients with metastatic breast cancer (mBC) in France. Methods: A prospective gBRCA1/BRCA2 mutation analysis was proposed to all patients with mBC treated in seven French centers between 19 February and 30 November 2015. The BRCA TrueTM test (Pathway Genomics^®, San Diego, CA, USA) analyzed the coding and flanking regions of BRCA1 and BRCA2 genes using next-generation sequencing, Sanger sequencing, and multiplex ligation-dependent probe amplification. Results: Among 407 included mBC patients, 11 (2.7%) carried pathogenic gBRCA1/2 mutations. Of these, five (45%) would not have met standard criteria for genetic screening. Compared with non-carriers, gBRCA1/2 carriers were significantly younger at mBC diagnosis (47.5 vs. 60.7 years, p = 0.0006), had higher-grade tumor histology (p = 0.044), and had a higher rate of contralateral recurrence (36.4% vs. 11.6%, p = 0.035), with comparable adjusted survival (median overall survival 74.9 vs. 100.1 months, p = 0.97). Variants of uncertain significance were identified in 17 (4.2%) patients. Conclusions: The 2.7% prevalence of gBRCA1/2 mutations in this prospective French mBC cohort was relatively low. Nearly half of the mutation carriers would not have been routinely referred for oncogenetic counseling, underscoring the potential value of broader genetic screening in this population. Full article

Background/Objectives: Fig (Ficus carica L.) seed oil represents an underexplored by-product with considerable nutraceutical potential. However, systematic evaluation of genotype × environment (G × E) interactions affecting its biochemical composition remains limited. This study assessed compositional variability across fig varieties, identified metabolic trade-offs, and developed rapid authentication protocols using FTIR-ATR spectroscopy to support predictive G × E models and marker-assisted selection. Methods: Thirty-seven fig varieties were evaluated across two consecutive harvest years (2023–2024) in Morocco. Conventional biochemical analyses measured total phenolic content (TPC), total flavonoid content (TFC), DPPH and ABTS antioxidant activities, and oil yield. FTIR-ATR spectroscopy characterized spectral variations, with ANOVA assessing effects of year, variety, and G × E interactions. Principal Component Analysis (PCA) discriminated genotypes and years. Results: TPC varied substantially (16.5–115.1 mg GAE/100 g oil), declining 36% from 2023 (48.7 ± 16.6 mg GAE/100 g) to 2024 (31.2 ± 16.6 mg GAE/100 g; F = 1372.84, p < 0.001), with TFC showing parallel trends (15.6 vs. 11.8 mg QCE/100 g). DPPH activity increased 34% in 2024 (58.5% vs. 43.7%), while ABTS activity decreased 18.6% from 32.34 ± 14.28% to 26.31 ± 6.10% (p < 0.001). Oil yield decreased from 26.7% to 21.2% and negatively correlated with phenolic accumulation (r = −0.49, p < 0.001). FTIR-ATR identified diagnostic peaks (e.g., 3012, 2928 cm⁻¹), with significant G × E effects (p < 0.001). PCA captured 75.4–84.5% variance, discriminating genotypes and years. Stable high-value cultivars included ‘Dottato Perguerolles’, ‘VCR 276/49’, and ‘Ferqouch Jmel’. Conclusions: Genotypic differences and year-to-year environmental conditions significantly influence fig seed oil composition. The observed negative correlation between oil yield and phenolic content indicates a trade-off between lipid biosynthesis and secondary metabolism. FTIR-ATR spectroscopy coupled with multivariate analysis enables reliable variety discrimination and year differentiation, supporting the development of stable cultivars for nutraceutical applications. Full article

Idiopathic Pulmonary Fibrosis (IPF) is a severe, chronic, progressive lung disease classified within interstitial lung disorders. It predominantly affects individuals aged 50 to 70 years, with a prognosis of 3–5 years post-diagnosis. The pathophysiology of IPF is complex, involving an interplay of genetic predisposition, environmental exposures, and age-related factors. A significant genetic component is evident, with key contributions from rare variants in telomere maintenance genes (e.g., TERT and TERC) and surfactant protein genes (e.g., SFTPA and SFTPC), as well as a strong association with a common promoter variant in the MUC5B gene. The diagnosis is established through high-resolution computed tomography (HRCT) and, when necessary, histopathological analysis. The search for reliable biomarkers is a key area of research, with molecules such as KL-6, SP-A, SP-D, and MMP-7 showing potential for aiding in diagnosis, prognosis, and monitoring disease activity. While antifibrotic therapies (Pirfenidone and Nintedanib) have revolutionized management by slowing the decline in lung function, the therapeutic landscape continues to evolve. Ongoing research efforts are focused on integrating clinical, radiological, genetic, and biomarker data to facilitate early diagnosis and develop personalized treatment strategies to improve patient outcomes. Full article

Background/Objectives: Individuals carrying pathogenic/likely pathogenic (P/LP) variants associated with hereditary breast and ovarian cancer (HBOC) and Lynch Syndrome (LS)- have increased risk for various types of cancer. The study compared health behaviors, i.e., smoking, alcohol consumption, level of physical activity, and body mass index (BMI) among affected and unaffected (never diagnosed) individuals with P/LP variants associated with HBOC or LS. Methods: We used baseline and 18-month follow-up data from individuals with HBOC- or LS-associated P/LP variants from the Swiss CASCADE study, an open-ended, prospective, family-based cohort. Generalized linear models with random effects were applied. Results: A total of 856 records from 518 participants (HBOC: 410; LS: 108) were analyzed. More than half (58%) of participants had at least one cancer diagnosis. After controlling for potential confounders, the proportion of current smokers was not significantly different between the two groups (ß = 3.5, p = 0.24). Alcohol intake was not associated with cancer diagnosis (adjusted: ß = −0.2, p = 0.57), although it was positively associated with time since genetic testing (ß = 0.11, p < 0.01). Levels of physical activity were lower among affected individuals compared to unaffected (adjusted: ß = −0.5, p = 0.03). There was no difference in BMI between the two groups. Conclusions: No significant differences in health behaviors, i.e., smoking, alcohol consumption, or BMI, were detected in individuals with P/LP variants associated with HBOC or LS unaffected by cancer and those with cancer diagnosis. Lower levels of physical activity in those with a cancer diagnosis could potentially be attributed to cancer treatment. Future studies should examine whether adjustments in health behavior are associated with the genetic diagnosis. Full article

This study focuses on the genetic and clinical characterization of Monogenic Forms of Diabetes (MFD), which are frequently underdiagnosed or misclassified due to clinical similarities with type 1 and type 2 diabetes. Researchers performed Exome Sequencing on 11 Tunisian patients suspected of having MFD. The pathogenicity of genetic variants was assessed using filtering and bioinformatics prediction tools. The ORVAL online tool was used to predict the likelihood of combinations of pathogenic variants. Sanger sequencing confirmed likely pathogenic predicted variants in patients and assessed familial segregation. We identified 15 potentially pathogenic variants in 14 genes linked to MFD, including MODY-3, and isolated diabetes with low penetrance for Wolfram syndrome. Additionally, syndromic forms such as partial familial lipodystrophy types 2 and 4, and Wolfram syndrome were detected. Five patients exhibited characteristics of unspecified MFD. This study underscores the importance of genetic screening in individuals with diabetes who have a family history of the disease, particularly those with associated comorbidities. Our findings emphasize the crucial role of genetic testing in refining diabetes classification, leading to more accurate diagnoses. Therefore, integrating genetic research into clinical practice is essential to improving healthcare outcomes for patients with diabetes. Full article

Mitochondrial DNA (mtDNA) mutations are prevalent across cancer genomes, and growing evidence implicates their multifaceted role in energy metabolism with tumorigenesis. Ovarian cancer, in particular, demonstrates high mtDNA copy numbers and increased incidences of truncating and missense mtDNA mutations, with heteroplasmy levels predictive of prognosis. This review provides a comprehensive description of published mtDNA sequencing data in ovarian cancer, the majority being high-grade serous samples, encompassing both coding and non-coding regions. MtDNA mutations within non-coding regions, such as the D-loop control region, can affect mtDNA replication and transcription, hence affecting overall mtDNA copy numbers, while mtDNA mutations within coding regions can directly impact respiratory complex function and downstream metabolic pathways. MtDNA mutations may serve as clinically valuable diagnostic biomarkers for ovarian cancer and predictors for chemoresistance. We also explore ongoing efforts to deepen our understanding of mitochondrial oncogenetics through the creation of novel cancer models enabled by mitochondrial gene editing techniques. Developing robust human ovarian cancer cell models will be critical to elucidate mechanistic and phenotypic consequences of mtDNA mutations, assess drug response and resistance and identify new therapeutic targets to advance precision oncology in this emerging field. Full article

This study analyzes global data on human exposure to pesticides, focusing on glyphosate, POPs, carbamates, and organophosphates, which are among the most widely used in agricultural and urban environments, providing an overview of global human contamination by these substances. Current research has increasingly focused on the unintended consequences of pesticide use, including food, water, and soil contamination, biodiversity loss (especially beneficial insects such as pollinators), and the growing evidence of adverse impacts on human health (neurological, reproductive, endocrine, and carcinogenic effects). Therefore, we compiled information from several existing studies that evaluated pesticide residues in human biological samples, specifically urine, blood, and breast milk, to assess the extent of exposure. The analysis takes a global perspective, highlighting the importance of monitoring exposure in countries that demonstrate exceptionally high pesticide use (in terms of absolute volume), such as Brazil, the United States, and China, which are among the largest global consumers. The data cover both contemporary pesticides, whose consumption is driven by intensive agriculture in these and other countries, and persistent legacy compounds (POPs) that continue to circulate in nature and accumulate in the human body decades after their ban in many countries. Globally, there is a wide disparity in global regulations, and many developing countries continue to use pesticides that have been banned or severely restricted in more developed nations. Finally, it provides a critical overview of global data on human pesticide contamination. The data reinforce the critical importance of establishing preventive initiatives and strengthening surveillance and monitoring systems to detect and control pesticide residues in human populations globally, ultimately aiming to mitigate the harms of chronic pesticide exposure to human health and well-being. Full article

Identification of two or more pathogenic/likely pathogenic (P/LP) variants in cancer susceptibility genes carried by the same patient have important consequences for patient management. We have limited information about the effect of double heterozygosity (DH) in cancer susceptibility genes. The prevalence of DH among Hungarian cancer patients referred to oncogenetic counselling, and comparison of their phenotypes to single variant carriers were performed. In total, 2050 patients were analysed by multigene panel sequencing. Variants of 48 established cancer predisposition genes by ACMG guidelines were evaluated. In overall, P/LP variants were found in 19.8% of cases. DH was observed in 16 cases, amount to 0.8% of all patients, and to 4.0% of positive cases. Appearance of multiple primary tumours was not associated with DH compared to non-P/LP and single P/LP carriers (p = 0.71 and p = 0.54, respectively). Within a cohort of patients referred with suspected HBOC syndrome, earlier tumour formation was observed when DH cases were compared to non-P/LP carriers (p = 0.01), but difference between single and DH carriers was not statistically significant (p = 0.19; Bonferroni corrected alpha = 0.017). Our observations provide information about the incidence of DH status among Hungarian hereditary cancer patients and suggest that DH did not increase the risk of cancer compared to individuals with single P/LP mutation. Full article

This study aimed to assess the chemical composition and antibacterial potential of essential oils (EOs) from two plants: clove buds (Syzygium aromaticum) and fennel seeds (Foeniculum vulgare) EOs. The major compounds, eugenol and estragole, were isolated from these oils and tested against Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The EOs were obtained via hydrodistillation and analyzed using Gas Chromatography–Mass Spectrometry (GC-MS). Clove oil was found to be rich in eugenol (68.51%), while fennel seed oil was dominated by estragole (93.30%). Antibacterial activity, assessed by the agar disc diffusion method and supported by MIC/MBC testing, revealed that eugenol exhibited the highest efficacy, with MIC values ranging from 0.58 to 1.15 mg/mL and MBC values from 1.15 to 2.30 mg/mL, particularly against S. aureus and P. aeruginosa. In silico analysis was conducted to evaluate pharmacokinetics, toxicity, and molecular docking interactions. ADME predictions indicated good oral bioavailability and high membrane permeability for both compounds, with eugenol displaying superior solubility and better compliance with Lipinski’s Rule of Five. Molecular docking simulations confirmed the antibacterial potential, with eugenol showing stronger binding affinities to bacterial targets (−7.8 kcal/mol), forming more stable and diverse interactions compared to estragole. However, toxicity predictions indicated potential mutagenic, carcinogenic, and cardiotoxic (hERG inhibition) risks for both compounds. Full article

Muscle dystrophies are a group of genetic disorders characterized by progressive muscle degeneration. Prednisone is a glucocorticoid drug widely used to prevent muscle weakness in these diseases. Despite its known beneficial role, the effect of intermittent delivery on monocytes’ polarization and on dystrophic muscle microenvironment has not yet been thoroughly investigated. In this study, our aim was to identify the phenotype of monocyte subsets in blood and the expression of fibrosis-related genes in dystrophic muscle biopsies in patients receiving intermittent prednisone therapy. We found an increased rate of classical monocytes and a decreased rate of non-classical monocytes that expressed anti-inflammatory marker CD206 in treated patients. In dystrophic muscles, 21 fibrosis-related genes were altered, among which we identified CCAAT/enhancer-binding protein beta CEBPB. Both classical monocytes and CEBPB are known for their roles in stimulating collagen 1 production, a probable marker hampering monocyte/macrophage function. Hence, in some patients with muscular dystrophy, intermittent prednisone treatment could shift the monocytes’ phenotype toward an M2, senescent-like profile. This seems to decrease the inflammatory infiltrate in muscle tissue, an observation that needs to be further confirmed. Full article

Latent tuberculosis infection (LTBi) affects nearly a quarter of the global population, yet current diagnostic methods are limited by low sensitivity and specificity. This study applied an integrative bioinformatics framework, incorporating machine learning techniques, to identify robust gene expression biomarkers associated with LTBi. We analyzed four publicly available transcriptomic datasets from peripheral blood mononuclear cells (PBMCs), representing latent, active, and healthy states. Differentially expressed genes (DEGs) were identified, followed by gene ontology (GO) enrichment, functional clustering, and miRNA interaction analysis. Semantic similarity, unsupervised clustering, and pathway enrichment were applied to refine the gene list. Key biomarkers were prioritized using receiver operating characteristic (ROC) curve analysis, with CCL2 and CXCL10 emerging as top candidates (AUC > 0.85). This multi-step approach demonstrates the potential of combining transcriptomic profiling with established machine learning and bioinformatics tools to uncover candidate biomarkers for improved LTBi detection, and it also provides a foundation for future experimental validation. Full article

The upcoming wave of personalized medicine, driven by genomic diagnostics and artificial intelligence, demands clearly defined pre-laboratory and laboratory procedures to ensure the acquisition of DNA and RNA of sufficient quantity and quality. In prostate cancer oncogenetics, diagnostic and prognostic assessments increasingly rely on personalized approaches, including Comprehensive Genomic Profiling (CGP). In this pilot study, we aimed to establish optimal pre-analytical and analytical conditions for selected genetic diagnostic methods using tissue samples acquired through multiparametric MRI-guided biopsy. Tissue specimens from thirteen patients were processed for DNA isolation, fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS). Comparative analyses were performed on DNA derived from both fresh and formalin-fixed, paraffin-embedded (FFPE) samples. Sequencing quality metrics demonstrated markedly superior performance in fresh tissue compared to FFPE. These results highlight the importance of standardized tissue collection and processing protocols to enable reliable molecular diagnostics in prostate cancer. Our findings support the feasibility of integrating high-quality genomic testing into routine biopsy workflows and emphasize the need for further large-scale validation. Full article

Background/Objectives: Radiotherapy is a cornerstone in the treatment of breast cancer, yet its use is frequently accompanied by skin toxicities that vary in severity and timing among patients. The objective of this meta-analysis is to systematically evaluate the pooled impact of genetic variations on the risk and severity of acute and late skin side effects from radiotherapy in breast cancer patients. Materials and Methods: A systematic literature search was conducted across PubMed, Embase, and Scopus to identify studies published between 2014 and 2024 that examined associations between genetic polymorphisms and radiotherapy-induced skin toxicity. Studies were selected based on predefined inclusion and exclusion criteria, and data were synthesized using a random-effects meta-analysis model. The risk of bias was evaluated using the ROBINS-I tool, and publication bias was assessed through funnel plots and Egger’s test. Results: A total of 11 studies involving breast cancer patients were included, identifying associations between various gene polymorphisms and skin toxicity. The pooled analysis revealed that patients with specific genetic variants had a 53% increased risk of acute skin side effects and a 44% increased risk of late effects. Notable implicated genes included XRCC2, IFNG, ATM, TGFB1, and PER3. Significant heterogeneity and publication bias were noted across studies, warranting cautious interpretation. Conclusions: This meta-analysis highlights the role of genetic variation in predicting radiotherapy-induced skin toxicity in breast cancer patients. These findings support the future development of predictive biomarkers and personalized radiotherapy strategies to minimize treatment-related toxicity. Full article

Introduction: This study investigates the distribution and interaction of three polymorphisms—XRCC1 (rs1799782), CHEK2 (rs17879961), and XPD (rs238406)—in Romanian breast cancer patients, aiming to understand their association with histopathological subtypes, age, and BMI. Materials and Methods: This retrospective study analyzed 36 breast cancer patients from a Romanian clinic (2020–2024) with complete genetic data for XRCC1 (rs1799782), CHEK2 (rs17879961), and XPD (rs238406). The patients had invasive, non-metastatic breast cancer and no history of other cancers. Statistical analysis with Jamovi included descriptive stats, McNemar’s test for genotype associations, and multinomial logistic regression to explore links between variants, age, BMI, and tumor subtypes. Results: McNemar tests showed no significant association between XRCC1 and CHEK2 (p = 0.180), nor between XRCC1 and XPD (p = 0.03) or XPD and CHEK2 (p = 0.049) after applying the Bonferroni correction (α = 0.0167), indicating no statistically significant genetic dependency among these variants. A multinomial logistic regression model found that genetic variants, BMI, and age significantly predicted breast cancer subtypes, particularly CDI TNB. All predictors remained significant in the comparisons of CDI TNB vs. CDI LB/CDI LA. Notably, these associations remained unchanged even after applying the Bonferroni correction (α = 0.0021), confirming the robustness of the findings. Conclusions: This study identifies significant associations between XRCC1, CHEK2, and XPD gene variants and CDI TNB, suggesting a role of DNA repair deficiencies in its pathogenesis. Protective genotypes were under-represented in TNB cases. Limited links with luminal subtypes highlight TNB’s distinct genetic profile. Results support further research on these polymorphisms as markers for TNB risk and precision treatment. Full article