Tooth bleaching is one of the most frequently performed esthetic procedures in dentistry. Although peroxide-based bleaching agents effectively promote color change, their decomposition generates reactive oxygen species that may induce oxidative stress, cytotoxicity, genotoxicity, inflammation, and oral tissue alterations. This scoping review mapped and synthesized the available evidence regarding genotoxicity and oral tissue damage associated with tooth bleaching procedures, identified the biological models and analytical methods used to investigate these outcomes, and explored differences among bleaching protocols. The review followed the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Searches were conducted in major electronic databases and supplementary searches. Ninety-four studies were included, comprising laboratory, animal, and human investigations. The most commonly used analytical methods included micronucleus assays, comet assays, oxidative stress biomarkers, molecular analyses, and histopathological evaluations. Peroxide-based bleaching agents were frequently associated with oxidative stress, cytotoxicity, genotoxicity, inflammatory responses, apoptosis, and tissue alterations, which appeared to occur in a concentration-dependent and time-dependent manner. Laboratory studies generally reported more pronounced biological effects, whereas animal and clinical investigations demonstrated the influence of physiological defense and repair mechanisms. Clinical studies frequently reported transient biological alterations. Oxidative stress emerged as the central mechanism linking peroxide exposure to cellular and tissue damage. Overall, peroxide concentration, exposure duration, and protocol design emerged as relevant factors modulating biological responses, whereas catalysts, antioxidants, and photobiomodulation therapies represented promising strategies to mitigate bleaching-induced damage. Further standardized and long-term clinical studies are required to clarify the biological significance and clinical relevance of these effects.
Prostate cancer (PCa) is one of the most heritable cancers, exhibiting significant familial aggregation, however, its underlying mechanisms remain incompletely understood. This review proposes a Genetics-Epigenetics-Environment (G-E-E) 3D framework, which not only integrates genetic factors frequently addressed in previous reviews but also incorporates overlooked intergenerational/transgenerational epigenetic inheritance (IEI/TEI) and family-shared environment (FSE). Regarding genetic factors, germline mutations (e.g. BRCA1/2, MLH1, HOXB13), single nucleotide polymorphisms (SNPs), germline copy number variations (GCNVs), and Y-chromosome haplotypes have been extensively documented in PCa familial aggregation research. Adverse parental environmental exposures can induce epigenomic abnormalities in germ cells (including DNA methylation, histone modifications, and non-coding RNAs), which can be transmitted intergenerationally or transgenerationally to drive the initiation and progression of PCa in offspring. Finally, we note that family-shared environments collectively influence all family members, thereby contributing to PCa familial aggregation. Together, these three classes of factors-genetic, epigenetic, and environmental-provide a more comprehensive perspective for explaining the familial aggregation of PCa, offering new insights into predicting its occurrence within families.
BACKGROUND:Somatic variant callers were originally developed to identify tumour-specific mutations in mixed tumour-normal samples. Increasingly, disciplines such as developmental biology, reproductive medicine, virology and mitochondrial genetics require detection of low-frequency variants from high-depth sequencing. Many laboratories therefore reuse cancer callers without clear guidance on their statistical assumptions or validation in non-cancer contexts. METHODS:We review widely used somatic callers and post-calling classifiers, summarising their underlying models and assumptions. We then synthesise peer-reviewed case studies (2020-2025) where these tools were applied to detect low-allele-fraction variants outside cancer. For each study, we extract sample type, sequencing depth, variant-allele-fraction thresholds, caller(s) used and validation approaches. We discuss technical challenges and propose practical adaptations. RESULTS:Cancer callers generally assume diploid genomes and moderate allele fractions, use Beta-binomial or Poisson-based models and apply filters for tumour/normal comparisons. In non-cancer applications, allele fractions frequently fall below 5%, confounded by ploidy differences and sequencing artefacts. Published studies demonstrate that somatic callers can be repurposed for detecting post-zygotic variants at 1-3% allele fraction, sperm mosaicism, mitochondrial heteroplasmy as low as 0.4-0.5%, minority viral variants around 5% and cfDNA variants at ≥ 1-5% allele fraction. Unique molecular identifiers, panel-of-normal filtering and machine-learning post-processing markedly improve specificity. Emerging long-read and deep-learning callers (e.g. DeepSomatic) promise enhanced sensitivity. CONCLUSIONS:Somatic callers offer versatile frameworks to interrogate low-allele-fraction variants across genomics; however, careful parameter tuning and validation are essential. Future work could integrate pangenome references and federated benchmarking datasets to make somatic variant detection more robust in diverse biological settings.
This paper compiles results from six systematic reviews and meta-analyses on associations between environmental and occupational exposure to chemicals and levels of DNA strand breaks in human leukocytes, measured by the comet assay. There are no differences in effect sizes when using different comet descriptors. However, lower central tendencies are obtained by using a non-parametric test as compared to the standard parametric analysis, indicating that the standard meta-analyses tend to overestimate the effect size. The compiled results indicate that exposures can be sorted into three groups with decreasing effect size: high (pesticides), moderate (volatile organic compounds, heavy metals and antineoplastic drugs), and low (anaesthetic gases and air pollution). Interestingly, studies from middle-income countries have higher effect sizes than those seen in studies from high-income countries. This may be related to higher exposures or lower socioeconomic status in middle-income countries. However, there is also some co-variability between studies from middle-income countries and the risk of comet assay measurement bias, assessed as information provided in published papers. Lack of information on assay controls and blinded/coded sample analysis appears to be a general issue in studies on comet assay results. Risk of exposure misclassification is mainly related to the type of exposure; there are good biomarkers for some exposures (e.g. heavy metals), whereas other exposures are more challenging to assess with biomarkers (e.g. pesticides). In conclusion, all examined exposures result in significant increases in DNA strand breaks at the population level, though to varying degrees.
Canine mammary tumors (CMTs) are the most prevalent neoplasms in intact female dogs, accounting for up to 50% of all neoplasms, with malignancy rates ranging from 50% to 89%. Human breast cancer (HBC) remains a leading cause of cancer morbidity and mortality worldwide. Both diseases exhibit remarkable biological and molecular similarity, making the domestic dog an excellent spontaneous model for studying HBC. CMTs and HBC share histopathological features. They also have comparable classification systems, including hormone receptor-based subtypes (luminal A, luminal B, HER2-positive) and the triple-negative subtype, as well as dysregulation of pathways such as PI3K/AKT and Wnt/β-catenin. Furthermore, they share several risk factors and environmental determinants. In contrast to rodent models, dogs offer natural genetic variation and comparable environmental exposures, enabling more physiological studies of cancer development. This review focuses on genomic instability, specifically microsatellite instability (MSI) and loss of heterozygosity (LOH), as an important driver of neoplastic growth in both species. MSI results from DNA mismatch repair defects, whereas LOH indicates tumor suppressor gene inactivation. Emerging evidence shows that these alterations occur in CMTs just as they do in HBC. Investigating MSI and LOH in dogs can uncover common molecular mechanisms, identify reliable biomarkers, and reveal novel therapeutic targets. Ultimately, this comparative approach reinforces the "One Health" concept, bridging veterinary and human medicine to improve cancer outcomes for both species.
