ABSTRACT Inorganic arsenic, a naturally occurring metalloid found in groundwater, is a well‐established human carcinogen. Epidemiological studies from highly contaminated regions link chronic arsenic exposure to increased risks of skin, lung, bladder, and kidney cancer. However, studies investigating the mechanisms driving arsenic‐related mutagenicity in human tumors remain limited. To improve our understanding, we analyzed whole‐exome sequencing (WES) data from tumor samples of 17 cancer patients treated in Dhaka, Bangladesh, with known or suspected exposure based on toenail arsenic concentrations. These patients included bladder ( n = 9), kidney ( n = 6), and lung ( n = 2) cancers. The mutational burden (mutations per megabase) across all exomes ranged from 23 to 117 for single‐base substitutions (SBS) and 2 to 13 for small insertions and deletions (indel). We showed that SBS and indel signatures, including SBS5, SBS6, ID6, and ID19 contributed the highest mutation load across all exomes. However, we did not observe associations between arsenic exposure levels and any mutational signature. We additionally analyzed WES data from two cell line models of chronic arsenic exposure, HaCaT skin epithelial and BEAS‐2B lung epithelial cells exposed to low‐dose of arsenite (100 nM) for 28 weeks. Consistent with the patient‐derived results, we observed no exposure‐related mutational burden or signature. Taken together, our findings suggest that arsenic alone may have limited independent mutagenic effects and instead may act through co‐carcinogenic mechanisms. However, limited sensitivity to detect low‐frequency mutations and small sample sizes potentially reduced our ability to capture mutational processes that may be associated with chronic arsenic exposure.
ABSTRACT This study evaluated the susceptibility to lung and kidney carcinogenesis induced by N ‐bis(2‐hydroxypropyl)nitrosamine (DHPN) in female rats whose dams received a low‐protein diet (LPD) during gestation. Pregnant Wistar rats were fed normal protein diet (NPD, 17% protein) or LPD (6% protein). After parturition, all dams were fed NPD until weaning. Then, female offspring were distributed into four groups (NPD, LPD, NPD + DHPN, and LPD + DHPN) and fed NPD. At 6 weeks old, two groups received 0.2% DHPN in drinking water for 4 weeks, and some females were euthanized 24 h after carcinogen stopping, while others were euthanized at Week 26. First, the lung was removed, fixed, histologically processed, and tissue sections were immunohistochemically stained for γ‐H2AX. Second, the lung and kidneys were removed, fixed, histologically processed, and hematoxylin–eosin stained tissue sections were obtained for histopathological analysis. Female rats whose dams received LPD developed a higher mean number of pulmonary epithelial cells positive for γ‐H2AX ( p < 0.005) and bronchioloalveolar hyperplasia and adenomas ( p < 0.001 and p < 0.001) in the lung compared with their counterparts. LPD did not alter the development of atypical tubule hyperplasia in the kidney. These findings indicated that LPD increased DHPN‐induced lung carcinogenesis in female rats.
ABSTRACT The application of machine learning approaches has shown promising results in cancer prediction. In the present study, data for nine gene‐based features that include MLH1 (rs1800734), MSH3 (rs26279), MSH6 (rs3136228), and several variants within MSH2 (rs2303423, rs4987188, rs17217772, rs63749993, rs2303426, and rs2303428), along with four additional features (Age, Gender, Smoking, and Pack Years) were used as input to develop a predictive model for assessing individual susceptibility to lung cancer. NumPy, Pandas, Scikit‐learn, and Matplotlib were major libraries used during the modeling process. The models included CatBoost, XGBoost, gradient boosting, random forest, support vector machine (SVM), K‐nearest neighbors (KNN), Gaussian Naive Bayes, and logistic regression, with their performance evaluated using stratified 5‐fold cross‐validation. The highest accuracy in predicting cancer predisposition was achieved by CatBoost (0.831 ± 0.014), with Pack Years (27.94%), Age (10.75%), and MLH1 (9.97%) as the major predictors. Precision, recall, and F 1‐score were also used to assess performance, and all were within the range of 0.83–0.84. The models were further tested for performance across histological subtypes, gender, and smoking status. Gradient Boosting (0.868 ± 0.028) and Random Forest (0.902 ± 0.020) yielded the highest accuracy as histological subtype classifiers in ADCC and SCLC, respectively. When modeled using sex‐stratified and smoking‐status‐specific models, the ensemble methods significantly outperformed logistic regression and Gaussian Naive Bayes, with MMR gene variants ( MLH1 , MSH2 ) emerging as key modulators of histology and risk stratification. This highlights the potential of ensemble methods to bridge the gap between genetic epidemiology and molecular pathology, enabling more accurate risk assessment.
ABSTRACT Per‐ and polyfluoroalkyl substances (PFAS) are synthetic chemicals used in a variety of consumer and industrial applications for their water‐ and oil‐resistant properties. Firefighters can be exposed to PFAS as part of their job through gear, aqueous film‐forming foams (AFFFs) used to extinguish aircraft and liquid fuel fires, along with exposure through other combustible materials during fire suppression activities. PFAS exposure has been linked to a variety of health conditions including cancer, obesity, reproductive issues, and immunosuppression. Epigenetic modifications may be one mechanism underlying PFAS toxicity. In this study, we used epigenetic indicators to assess association of PFAS serum concentrations with (1) epigenetic aging and (2) DNA methylation at loci within genes related to immune function. Blood leukocyte DNA methylation was quantified via the Infinium EPIC array from 184 participants in the Fire Fighter Cancer Cohort Study involved in aircraft rescue and firefighting, and serum PFAS was measured via on‐line solid phase extraction liquid chromatography isotope dilution tandem mass spectrometry. We observed inverse associations between PFAS concentrations and epigenetic clocks including between serum linear perfluorooctanoic acid (n‐PFOA) with four epigenetic clocks ( p < 0.05); however, most did not remain significant in sensitivity analyses. Associations ( q < 0.1) were observed between perfluorodecanoic acid, n‐PFOA, sum of branched perfluorooctane sulfonic acid isomers and differential methylation of specific loci within 34 immune‐related genes. Further research can help to better understand the functional impacts of the observed differential methylation on immune health.
ABSTRACT Charged particles like iron‐56 ions impose health risks in long‐term manned space exploration. This study was designed to define the impact of Trp53 status upon the manifestation of mutations in the hypoxanthine‐guanine phosphoribosyltransferase ( Hprt ) gene in splenic T‐cells following exposure of Trp53 wild‐type, hemizygous, and nullizygous lacZ transgenic mice to 1 Gy 56 Fe particles. In male and female mice necropsied at 2, 4, and 8 weeks postexposure, Hprt mutant frequencies in splenic T‐cells (measured via the Hprt mutation cloning assay) increased significantly over time to peak at 4 weeks postexposure before decreasing to lower but still elevated levels. Mutagenic potency estimates based upon the change in mutant frequency over time in exposed versus respective control groups showed that the total mutagenic response depended upon the Trp53 genetic status, with the mutagenic burden of 1 Gy being threefold and 5.3‐fold greater in Trp53 +/− and Trp53 −/− mice, respectively, compared to Trp53 +/+ mice.
