Environmental and Molecular Mutagenesis最新文献

This study was arranged to assign the LC₅₀ value and effects of metaflumizone (MFZ) in Oncorhynchus mykiss blood/liver tissue with a multibiomarker approach. In addition, the positive/negative responses of the colemanite (COL) substance for integrating therapeutic agents into aquaculture were also discussed. Hematology profile revealed that red blood cell (RBC), hemoglobin (Hgb), and hematocrit (Hct) decreased temporally as a result of MFZ application compared to the control group. When cortisol results were evaluated, it was determined that MFZ induced cortisol levels at 48th and 96th hours. It was noted that antioxidant enzyme activities were significantly inhibited in blood/liver tissue taken at 48th/96th hour samples of MFZ application. After MFZ exposure, malondialdehyde (MDA) and myeloperoxidase (MPO) values increased, and this situation was interpreted as statistically meaningful. Nuclear factor erythroid 2 level (Nrf-2) was inhibited depending on time when the administration and control groups were compared. In the MFZ + COL group, inhibition was found to be alleviated. In the 48th and 96th hour analyses of blood/liver tissue, it was determined that interleukin-6 (IL-6) and tumor necrosis factor alfa (TNF-α) values were induced in MFZ applied groups, and COL tried to inhibit this situation. MFZ application showed a significant increase in 8-OHdG content and caspase 3 level, which was statistically significant (p < 0.05) over time. COL (single and/or MFZ) suppressed the accumulation of 8-hidroksi-2′-deoksiguanozin (8-OHdG) and caspase-3 levels as treatment, resulting in similar results to the control group. However, COL administration showed attenuation of all parameters with respect to these MFZ-induced toxicities, possibly because of its free radical scavenging and anti-inflammatory features.

Ovarian cancer (OC), the third most common and fatal gynecological malignancy, is a heterogeneous disease characterized by genomic instability. The interaction between genetic and environmental factors, including xenobiotics, plays a crucial role in OC initiation, progression, and treatment resistance. Xenobiotic metabolism (XM) is a key process for metabolizing and detoxifying environmental carcinogens, drugs, and other xenobiotics. Variations in XM genes (XMGs), such as those encoding cytochrome P450s (CYPs), UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs), N-acetyltransferases, and glutathione S-transferases (GSTs), can alter enzyme activity, thereby affecting detoxification, hormone metabolism, and clinical outcomes. Previous research has shown the effects of genetic variants on XM in OC, underscoring the importance of pharmacogenomics in tailoring personalized treatments. However, challenges persist, including individual variability, study inconsistencies, and insufficient ovarian-specific data on XM. This review provides a comprehensive overview of XM in OC. It emphasizes the importance of phase I and II enzymes in detoxification and biotransformation, and ABC transporters in drug metabolism and chemoresistance. This review provides insights into the emerging roles of CYPs, GSTs, glutathione peroxidases, myeloperoxidase, catalase, superoxide dismutase, SULTs, and UGTs, and addresses the need for further research to understand their influence on OC risk and prognosis. By addressing the gaps in ovarian-specific XM research, including their role in susceptibility and treatment response, these insights have the potential to advance targeted therapeutic strategies and overcome the challenges of chemoresistance in OC.

The ability to predict rodent lifetime tumor responses from short-term exposures and a scientific basis for rodent to human extrapolation are unmet needs in cancer risk assessment. To address these needs, quantitation of cancer driver mutations (CDMs) was integrated with an error-corrected, next generation sequencing (NGS) approach. The method developed, CarcSeq, involves performing multiple, high-fidelity PCR reactions to amplify hotspot CDM-containing target sequences, tagging amplicons with 9 base unique identifier sequences, and constructing libraries from the pooled amplicons. Single-strand consensus sequences were constructed for error correction. A metric of variability in CDM levels, median absolute deviation in mutant fraction (MAD), is being developed as a biomarker of clonal expansion. This study leveraged the sex-related difference in spontaneous lung tumor development in the rasH2-Tg mouse model to validate and refine the CarcSeq approach for assessing clonal expansion. Significantly greater MAD was observed in male as compared to female rasH2-Tg mice, along with more recurrent mutations and a higher proportion of mutations conferring a potentially selectable phenotype in males, consistent with the greater propensity for spontaneous lung tumorigenesis in males. In the analysis of MAD, use of a sex-specific median and classification of lung-specific drivers based on a COSMIC-reported mutation frequency ≥ 5% performed better than use of the overall median MF and classification based on COSMIC's top ranked lung neoplasia genes. Thus, this study provides further validation of the CarcSeq/MAD biomarker approach and technical insight into best practices in evaluating clonal expansion based on measurement of cancer driver gene mutations.

Current genotoxicity testing strategies face several challenges, including a high incidence of misleading positive results that lead to unnecessary animal testing, limited mechanistic insights, insufficient integration of innovative methodologies, and a lack of quantitative assessment. Despite rapid advancements in technology and scientific understanding, genotoxicity testing batteries have remained largely unchanged for years. To modernize genotoxicity assessment and incorporate innovative approaches, the development of Integrated Approaches for Testing and Assessment (IATAs) is essential. These frameworks combine existing knowledge with data from New Approach Methodologies (NAMs) aiming to reduce or eliminate reliance on in vivo testing. Genotoxicity is particularly well-suited for IATA development as numerous cutting-edge, non-animal methods have emerged in recent years, including 3D test systems, Prediscreen, MultiFlow, ToxTracker, and transcriptomic-based biomarkers such as GENOMARK and TGx-DDI. However, the integration of NAMs into IATAs must be systematic and scientifically robust. In this process, the Adverse Outcome Pathway (AOP) framework plays a crucial role by linking molecular-level events to adverse health effects, thereby supporting the structured selection of NAMs. This article explores the key challenges and gaps within the current European regulatory frameworks for chemical compound genotoxicity assessment and discusses how an AOP-based IATA can address these issues. Additionally, we present a global AOP network for permanent DNA damage, designed to guide IATA development and improve regulatory decision-making. This integrated approach has the potential to enhance the accuracy, efficiency, and ethical standards of genotoxicity assessment while reducing reliance on animal testing.

Genotoxicity assays play a significant role in protecting clinical trial subjects from potential increased risk of genotoxic hazard and cancer during drug development. Traditional genetic toxicology assays typically provide binary outcomes with limited mechanistic insight. This study evaluates machine learning (ML) models based on an in-house implementation of MultiFlow DNA Damage Assay and MicroFlow Assays, and compared these results to previously published Litron assays. Our ML models demonstrated high accuracy, with MultiFlow data achieving 96% balanced accuracy for mode of action (MoA) prediction and 99% for genotoxicity prediction in repeated cross-validation. We collected and interpreted the MicroFlow and MultiFlow data in a dose–response format. The dose–response data enabled us to improve assay inference and model accuracy. In addition, we conducted case studies using toxicogenomic data, including the Toxicogenomic DNA Damage Inducing (TGx-DDI) transcriptomic biomarker and bulk RNA-seq, on a small set of compounds where the MoA is not clearly defined by MultiFlow or MicroFlow. The integration of toxicogenomics provided deeper insights into the molecular mechanisms of genotoxicity, allowing for the identification of specific pathways affected by these compounds. These findings emphasize the importance of careful endpoint selection and data interpretation. Overall, this study enhances the precision of genotoxicity predictions by integrating toxicogenomics, offering a framework for future genotoxicity safety assessments.

Several error-corrected sequencing (ECS) methods can detect ultralow-frequency mutations and support mutagenicity assessments. While ECS can be applied to any DNA-containing sample, spontaneous mutations that accumulate in immortalized cell cultures—likely due to DNA replication errors—may elevate background mutation frequencies (MFs) and potentially confound ECS-based mutagenicity assessments. This study identified mutations unique to individual cells in TK6 and L5178Y populations by comparing the genomes of single-cell-derived clones to their parental cultures. These mutations resulted in MFs of 9 × 10⁻⁷ and 6 × 10⁻⁷ mutations per base pair (mut/bp) in commercially available TK6 and L5178Y cell populations, respectively. Freshly derived clonal populations from single TK6 and L5178Y cells exhibited lower MFs (0.5 × 10⁻⁷ and 1 × 10⁻⁷ mut/bp, respectively). These results suggest that commercially available TK6 and L5178Y cell populations have accumulated significant levels of background mutations that could affect the interpretation of ECS experiments. To test this hypothesis, commercially available and freshly derived clonal TK6 cell populations were grown for 5 days in medium containing 0.5, 2, and 8 μg/mL of the in vitro mutagen N4-hydroxycytidine and analyzed by HiFi sequencing, an ECS method. The results showed that freshly derived clonal populations had lower background MFs and greater relative MF fold increases upon mutagen exposure than the commercially available cell population. An alternative data analysis approach, based on absolute MF changes within each cell population, yielded more comparable results for commercial and clonal populations. These findings underscore the impact of background MFs on in vitro ECS analyses.

Under the influence of multiple anthropogenic pressures, from industrial to agricultural activities, estuaries have long been regarded as particularly sensitive ecosystems to contamination. The present study aimed at investigating the genotoxic potential of a contaminated sediment sample from an urban and industrial area of the Sado Estuary, by combining the analysis of multiple endpoints in the LacZ plasmid-based transgenic mouse model exposed for 28 days to contaminated estuarine sediment extracts through drinking water. The DNA and chromosome damaging effects were monitored in peripheral blood at 7-day intervals using the standard and enzyme-modified Comet assay, as well as the micronucleus assays in peripheral blood cells. After euthanasia, DNA damage was analyzed in several mouse tissues, and LacZ mutant frequencies were determined in the liver. Livers were also surveyed for histopathological analysis. A time-dependent increase in micronuclei frequency was seen at all tested doses, in spite of no induction of DNA damage in any organ or mutation induction in the liver of exposed mice. The liver from mice exposed to sediment extracts did not reveal major alterations besides evidence of inflammation. Overall, the integration of the endpoints analyzed in the mice is suggestive of potential chronic, rather than acute, adverse effects in vivo, and points to the need for further research in the resident human population in the area. This experimental design can be used to assess the genotoxicity of complex environmental mixtures, understand how they work, and reduce costs and resources while speeding up data collection and interpretation.