Indoor radon exposure and excess of lung cancer mortality: the case of Mexico-an ecological study

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM2.5, and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM2.5, may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute's Surveillance, Epidemiology, and End-Results data (2013-17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross [Formula: see text] activity and indoor radon) and PM2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure's association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

Radon exposure: a major cause of lung cancer in nonsmokers

Exposure to radon can impact human health. This is a nonsystematic review of articles written in English, Spanish, French, or Portuguese published in the last decade (2013-2023), using databases such as PubMed, Google Scholar, EMBASE, and SciELO. Search terms selected were radon, human health, respiratory diseases, children, and adults. After analyzing the titles and abstracts, the researchers initially identified 47 studies, which were subsequently reduced to 40 after excluding reviews, dissertations, theses, and case-control studies. The studies have shown that enclosed environments such as residences and workplaces have higher levels of radon than those outdoors. Moreover, radon is one of the leading causes of lung cancer, especially in nonsmokers. An association between exposure to radon and development of other lung diseases, such as asthma and COPD, was also observed. It is crucial to increase public awareness and implement governmental control measures to reduce radon exposure. It is essential to quantify radon levels in all types of buildings and train professionals to conduct such measurements according to proven efficacy standards. Health care professionals should also be informed about this threat and receive adequate training to deal with the effects of radon on human health.

Radiation Protection of Polydatin Against Radon Exposure Injury of Epithelial Cells and Mice

Radon exposure is significantly associated with lung cancer. Radon concentration is currently reduced mainly by physical methods, but there is a lack of protective drugs or biochemical reagents for radon damage. This study aimed to explore the protective effect of polydatin (PD) on the radon-exposed injury. The results showed that PD can significantly reduce ROS level, raise SOD activity, weaken the migration ability, increase E-cad, and decrease mesenchymal cell surface markers (FN1, Vimentin, N-cad, α-SMA, and Snail) in radon-exposed epithelial cells. In vivo, PD increased the mice weight, promoted SOD activity, and decreased MDA content, the number of bullae, pulmonary septum thickness, lung collagenous fibers, and mesenchymal cell surface markers. Furthermore, PD inhibited p-PI3K, p-AKT, and p-mTOR expression. Compared with directly adding PD on radon-exposed cells, adding PD before and after radon exposure could more obviously improve the adhesion of radon-exposed cells, significantly alleviate the migration ability, and more significantly reduce mesenchyme markers and p-AKT and p-mTOR. These results indicate that PD can reduce oxidative stress, weaken epithelial-mesenchymal transition (EMT) and lung fibrosis in radon-exposed cells/mice, and have good radiation protection against radon injury. The mechanism is related to the inhibition of the PI3K/AKT/mTOR pathway.

The level of free-circulating mtDNA in patients with radon-induced lung cancer

OBJECTIVE

According to the World Health Organization, radon is the second leading cause of lung cancer after smoking. Cell free circulating mitochondrial DNA (cf mtDNA) have been used not only as a biomarker of carcinogenesis but also as a biomarker of exposure to radiation, but nothing is known about changes in the level of cf mtDNA following radon exposure. Therefore, the purpose of this study was to estimate the cf mtDNA copy number as a biomarker of the response to radon exposure in lung cancer pathogenesis.

METHODS

207 subjects were examined including 41 radon-exposed lung cancer patients, 40 lung cancer patients without radon exposure and 126 healthy controls exposed/not exposed to high level of radon. Total cell free circulating DNA from blood samples was extracted and used to detect cell free circulating mitochondrial DNA copy number by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

Our data indicate that the level of cf mtDNA in the radon-induced lung cancer patients was significantly higher than that of the other study participants. There was a significant difference in the level of cf mtDNA in the blood plasma of healthy volunteers exposed and not exposed to high doses of radon. Moreover, in healthy volunteers living in areas with high radon levels, the mtDNA copy number was higher than that in patients with lung cancer who were not exposed to high doses of radon.

CONCLUSION

Our study provides evidence for a possible role of cf mtDNA as a promising biomarker of lung cancer induced by exposure to high dose of radon.

Polymorphisms in DNA Repair and Xenobiotic Biotransformation Enzyme Genes and Lung Cancer Risk in Coal Mine Workers

Background: Currently coal mining employs over 7 million miners globally. This occupational setting is associated with exposure to dust particles, heavy metals, polycyclic aromatic hydrocarbons and radioactive radon, significantly increasing the risk of lung cancer (LC). The susceptibility for LC is modified by genetic variations in xenobiotic detoxification and DNA repair capacity. The aim of this study was to investigate the association between GSTM1 (deletion), APEX1 (rs1130409), XPD (rs13181) and NBS1 (rs1805794) gene polymorphisms and LC risk in patients who worked in coal mines. Methods: The study included 639 residents of the coal region of Western Siberia (Kemerovo region, Russia): 395 underground miners and 244 healthy men who do not work in industrial enterprises. Genotyping was performed using real-time and allele-specific PCR. Results: The results show that polymorphisms of APEX1 (recessive model: OR_adj = 1.87; CI 95%: 1.01–3.48) and XPD (log additive model: OR_adj = 2.25; CI 95%: 1.59–3.19) genes were associated with increased LC risk. GSTM1 large deletion l was linked with decreased risk of LC formation (OR_adj = 0.59, CI 95%: 0.36–0.98). The multifactor dimensionality reduction method for 3-loci model of gene–gene interactions showed that the GSTM1 (large deletion)—APEX1 (rs1130409)—XPD (rs13181) model was related with a risk of LC development. Conclusions: The results of this study highlight an association between gene polymorphism combinations and LC risks in coal mine workers.