Ambient PM2.5 and Annual Lung Cancer Incidence: A Nationwide Study in 295 Chinese Counties

Associations between fine particulate matter and colorectal cancer: a systematic review and meta-analysis

Colorectal cancer (CRC) is the second deadliest cancer worldwide. The impact of fine particulate matter (PM2.5) on many diseases is a global concern, yet its association with CRC is unclear. This study aimed to assess the effect of PM2.5 exposure on CRC. We searched PubMed, Web of Science, and Google Scholar databases for population-based articles published before September 2022, providing risk estimates with 95% confidence intervals (CI). Among 85,743 articles, we identified 10 eligible studies across multiple countries and regions in North America and Asia. We calculated the overall risk, incidence and mortality and performed subgroup analyses according to countries and regions. The results revealed an association between PM2.5 and increased risk of CRC (total risk, 1.19 [95% CI 1.12-1.28]; incidence, OR=1.18 [95% CI 1.09-1.28]; mortality, OR=1.21 [95% CI 1.09-1.35]). The elevated risks of CRC associated with PM2.5 were different across countries and regions, at 1.34 [95% CI 1.20-1.49], 1.00 [95% CI 1.00-1.00], 1.08 [95% CI 1.06-1.10], 1.18 [95% CI 1.07-1.29], 1.01 [95% CI 0.79-1.30], in the United States, China, Taiwan, Thailand, and Hong Kong, respectively. Incidence and mortality risks were higher in North America than those in Asia. In particular, the incidence and mortality were highest in the United States (1.61 [95% CI 1.38-1.89] and 1.29 [95% CI 1.17-1.42], respectively) than those in other countries. This study is the first comprehensive meta-analysis to find a strong association between PM2.5 exposure and increased CRC risk.

Influence of the atmospheric environment on spatial variation of lung cancer incidence in China

Conducting this research contributes to a deeper understanding of the correlation between atmospheric environmental quality and lung cancer incidence, and provides the scientific basis for formulating effective environmental protection and lung cancer prevention and control strategies. Lung cancer incidence in China has strong spatial variation. However, few studies have systematically revealed the characteristics of the spatial variation in lung cancer incidence, and have explained the causes of this spatial variation in lung cancer incidence from the perspectives of multiple components of the atmospheric environment to explain this spatial variation in lung cancer incidence. To address research limitations, we first analyze the spatial variation and spatial correlation characteristics of lung cancer incidence in China. Then, we build a spatial regression model using GeoDa software with lung cancer incidence as the dependent variable, five atmospheric environment factors-particulate matter 2.5 (PM2.5) concentration, temperature, atmospheric pressure, and elevation as explanatory variables, and four socio-economic characteristics as control variables to systematically analyze the influence and intensity of these factors on lung cancer incidence. The results show that lung cancer incidence in China has apparent changes in geographical and spatial unevenness, and spatial autocorrelation characteristics. In China, the lung cancer incidence is relatively high in Northeast China, while some areas of high lung cancer incidence still exist in Central China, Southwest China and South China, although the overall lung cancer incidence is relatively low. The atmospheric environment significantly affects lung cancer incidence. Different elements of the atmospheric environment vary in the direction and extent of their influence on the development of lung cancer. A 1% increase in PM2.5 concentration is associated with a level of 0.002975 increase in lung cancer incidence. Atmospheric pressure positively affects lung cancer incidence, and an increase in atmospheric pressure by 1% increases lung cancer incidence by a level of 0.026061. Conversely, a 1% increase in temperature is linked to a level of 0.006443 decreases in lung cancer incidence, and a negative correlation exists between elevation and lung cancer incidence, where an increase in elevation by 1% correlates with a decrease in lung cancer incidence by a level of 0.000934. The core influencing factors of lung cancer incidence in the seven geographical divisions of China exhibit variations. This study facilitates our understanding of the spatial variation characteristics of lung cancer incidence in China on a finer scale, while also offering a more diverse perspective on the impact of the atmospheric environment on lung cancer incidence.

Exploring the link between ambient PM2.5 concentrations and respiratory diseases in the elderly: a study in the Muang district of Khon Kaen, Thailand

The impact of air pollution is a major public health concern. However, there are few studies on the correlation between PM2.5 and respiratory infections. This study aimed to determine a link between PM2.5 and respiratory diseases among the elderly in Thailand. The data source for this study consisted of 43 electronic files from the Khon Kaen Provincial Health Office covering years 2020 and 2021 and surveyed a total of 43,534 people. The generalized linear mixed model (GLMM) was used to determine the adjusted odds ratio (AOR), and 95 % CI. We found that exposure to PM2.5 concentrations (in 10 μg m-3 increments) was associated with respiratory diseases (AOR: 3.98; 95 % CI [1.53-10.31]). Respondents who are male, aged less than 80 years, single, self-employed, or working as contractors, have a body mass index (BMI) not equal to the standard, have NCDs (hypertension, diabetes mellitus, and cardiovascular disease), are smokers, live in sub-districts where more than 5 % of the land is planted to sugarcane, or live in close proximity to a biomass power plant were at significantly higher risk of developing respiratory diseases (p<0.05). Therefore, environmental factors including ambient PM2.5 concentrations, the proportion of sugarcane plantation areas, and biomass power plants impact the occurrence of respiratory diseases among the elderly. Also, demographic factors and NCDs are serious issues. Systematic approaches to reducing PM2.5 levels in industrial and agricultural sectors are necessary for both the general population and vulnerable groups, including the elderly and NCD patients.

Assessment of spatial variation in lung cancer incidence and air pollutants: spatial regression modeling approach

A notable finding is that Kerala's capital Thiruvananthapuram has shown an increasing trend in lung cancer (LC) incidence. Long-term exposure to air pollution is a significant environmental risk factor for LC. This study investigated the spatial association between LC and exposure to air pollutants in Thiruvananthapuram, using Spatial Lag Model (SLM), Spatial Error Model (SEM), and Geographically Weighted Regression (GWR). The results showed that overall LC incidence rate was 111 per 105 males (age >60 years), whereas spatial distribution map revealed that 48% of the area had an incidence rate greater than 150. The results revealed a significant association between PM2.5 and LC. SLM was identified as the best model that predicted 62% variation in LC. GWR model improved model performance and made better local predictions in the southeastern parts of the study area. This study explores the effectiveness of spatial regression techniques for dealing spatial effects and pinpointing high-risk areas.

PM2.5 regulates the progression of lung adenocarcinoma through the axis of HCG18, miR-195 and ATG14

Relevant studies have indicated the association of HCG18 with tumour occurrence and progression. In this study, we observed that PM2.5 can enhance the growth of lung adenocarcinoma cells by modulating the expression of HCG18. Further investigations, including overexpression and knockout experiments, elucidated that HCG18 suppresses miR-195, which in turn upregulates the expression of ATG14, resulting in the upregulation of autophagy. Consequently, exposure to PM2.5 leads to elevated HCG18 expression in lung tissues, which in turn increases Atg14 expression and activates autophagy pathways through inhibition of miR-195, thereby contributing to oncogenesis.

Nontargeted Identification of Organic Components in Fine Particulate Matter Related to Lung Tumor Metastasis Based on an Adverse Outcome Pathway Strategy

Emerging studies implicate fine particulate matter (PM2.5) and its organic components (OCs) as urgent hazard factors for lung cancer progression in nonsmokers. Establishing the adverse outcome pathway (AOP)-directed nontargeted identification method, this study aimed to explore whether PM2.5 exposure in coal-burning areas promoted lung tumor metastasis and how we identify its effective OCs to support traceability and control of regional PM2.5 pollution. First, we used a nude mouse model of lung cancer for PM2.5 exposure and found that the exposure significantly promoted the hematogenous metastases of A549-Luc cells in lung tissues and the adverse outcomes (AOs), with key events (KEs) including the changed expression of epithelial-mesenchymal transition (EMT) markers, such as suppression of E-cad and increased expression of Fib. Subsequently, using AOs and KEs as adverse outcome directors, we identified a total of 35 candidate chemicals based on the in vitro model and nontargeted analysis. Among them, tributyl phosphate (C12H27O4P), 2-bromotetradecane (C14H29Br), and methyl decanoate (C11H22O2) made greater contributions to the AOs. Finally, we clarified the interactions between these OCs and EMT-activating transcription factors (EMT-ATFs) as the molecular initiation event (MIE) to support the feasibility of the above identification strategy. The present study updates a new framework for identifying tumor metastasis-promoting OCs in PM2.5 and provides solid data for screening out chemicals that need priority control in polluted areas posing higher lung cancer risk.

Fine particulate matter (PM2.5) induces the stem cell-like properties of hepatocellular carcinoma by activating ROS/Nrf2/Keap1-mediated autophagy

Exposure to fine particulate matter (PM2.5) has been linked to an increased incidence and mortality of hepatocellular carcinoma (HCC). However, the impact of PM2.5 exposure on HCC progression and the underlying mechanisms remain largely unknown. This study aimed to investigate the effects of PM2.5 exposure on the stem cell-like properties of HCC cells. Our findings indicate that PM2.5 exposure significantly enhances the stemness of HCC cells (p < 0.01). Subsequently, male nude mice were divided into two groups (n = 8/group for tumor-bearing assay, n = 5/group for metastasis assay) for control and PM2.5 exposure. In vivo assays revealed that exposure to PM2.5 promoted the growth, metastasis, and epithelial-mesenchymal transition (EMT) of HCC cells (p < 0.01). Further exploration demonstrated that PM2.5 enhances the stemness of HCC cells by inducing cellular reactive oxygen species (ROS) generation (p < 0.05). Mechanistic investigation indicated that elevated intracellular ROS inhibited kelch-like ECH-associated protein 1 (Keap1) levels, promoting the upregulation and nucleus translocation of NFE2-like bZIP transcription factor 2 (Nrf2). This, in turn, induced autophagy activation, thereby promoting the stemness of HCC cells (p < 0.01). Our present study demonstrates the adverse effects of PM2.5 exposure on HCC development and highlights the mechanism of ROS/Nrf2/Keap1-mediated autophagy. For the first time, we reveal the impact of PM2.5 exposure on the poor prognosis-associated cellular phenotype of HCC and its underlying mechanism, which is expected to provide new theoretical basis for the improvement of public health.

Interleukin-37 relieves PM2.5-triggered lung injury by inhibiting autophagy through the AKT/mTOR signaling pathway in vivo and in vitro

Autophagy mediates PM2.5-related lung injury (LI) and is tightly linked to inflammation and apoptosis processes. IL-37 has been demonstrated to regulate autophagy. This research aimed to examine the involvement of IL-37 in the progression of PM2.5-related LI and assess whether autophagy serves as a mediator for its effects.To create a model of PM2.5-related LI, this research employed a nose-only PM2.5 exposure system and utilized both human IL-37 transgenic mice and wild-type mice. The hIL-37tg mice demonstrated remarkable reductions in pulmonary inflammation and pathological LI compared to the WT mice. Additionally, they exhibited activation of the AKT/mTOR signaling pathway, which served to regulate the levels of autophagy and apoptosis.Furthermore, in vitro experiments revealed a dose-dependent upregulation of autophagy and apoptotic proteins following exposure to PM2.5 DMSO extraction. Simultaneously, p-AKT and p-mTOR expression was found to decrease. However, pretreatment with IL-37 demonstrated a remarkable reduction in the levels of autophagy and apoptotic proteins, along with an elevation of p-AKT and p-mTOR. Interestingly, pretreatment with rapamycin, an autophagy inducer, weakened the therapeutic impact of IL-37. Conversely, the therapeutic impact of IL-37 was enhanced when treated with 3-MA, a potent autophagy inhibitor. Moreover, the inhibitory effect of IL-37 on autophagy was successfully reversed by administering AKT inhibitor MK2206. The findings suggest that IL-37 can inhibit both the inflammatory response and autophagy, leading to the alleviation of PM2.5-related LI. At the molecular level, IL-37 may exert its anti autophagy and anti apoptosis effects by activating the AKT/mTOR signaling pathway.

Exploring the association of PM2.5 with lung cancer incidence under different climate zones and socioeconomic conditions from 2006 to 2016 in China

Air pollution generated by urbanization and industrialization poses a significant negative impact on public health. Particularly, fine particulate matter (PM2.5) has become one of the leading causes of lung cancer mortality worldwide. The relationship between air pollutants and lung cancer has aroused global widespread concerns. Currently, the spatial agglomeration dynamic of lung cancer incidence (LCI) has been seldom discussed, and the spatial heterogeneity of lung cancer's influential factors has been ignored. Moreover, it is still unclear whether different socioeconomic levels and climate zones exhibit modification effects on the relationship between PM2.5 and LCI. In the present work, spatial autocorrelation was adopted to reveal the spatial aggregation dynamic of LCI, the emerging hot spot analysis was introduced to indicate the hot spot changes of LCI, and the geographically and temporally weighted regression (GTWR) model was used to determine the affecting factors of LCI and their spatial heterogeneity. Then, the modification effects of PM2.5 on the LCI under different socioeconomic levels and climatic zones were explored. Some findings were obtained. The LCI demonstrated a significant spatial autocorrelation, and the hot spots of LCI were mainly concentrated in eastern China. The affecting factors of LCI revealed an obvious spatial heterogeneity. PM2.5 concentration, nighttime light data, 2 m temperature, and 10 m u-component of wind represented significant positive effects on LCI, while education-related POI exhibited significant negative effects on LCI. The LCI in areas with low urbanization rates, low education levels, and extreme climate conditions was more easily affected by PM2.5 than in other areas. The results can provide a scientific basis for the prevention and control of lung cancer and related epidemics.

The Clinical and Molecular Profile of Lung Cancer Patients Harboring the TP53 R337H Germline Variant in a Brazilian Cancer Center: The Possible Mechanism of Carcinogenesis

In southern and southeastern Brazil, the TP53 founder variant c.1010G>A (R337H) has been previously documented with a prevalence of 0.3% within the general population and linked to a heightened incidence of lung adenocarcinomas (LUADs). In the present investigation, we cover clinical and molecular characterizations of lung cancer patients from the Brazilian Li-Fraumeni Syndrome Study (BLISS) database. Among the 175 diagnosed malignant neoplasms, 28 (16%) were classified as LUADs, predominantly occurring in females (68%), aged above 50 years, and never-smokers (78.6%). Significantly, LUADs manifested as the initial clinical presentation of Li-Fraumeni Syndrome in 78.6% of cases. Molecular profiling was available for 20 patients, with 14 (70%) revealing EGFR family alterations. In total, 23 alterations in cancer driver genes were identified, comprising 7 actionable mutations and 4 linked to resistance against systemic treatments. In conclusion, the carriers of TP53 R337H demonstrate a predisposition to LUAD development. Furthermore, our results indicate that environmental pollution potentially impacts the carcinogenesis of lung tumors in the carriers of TP53 R337H.

Vaping, Environmental Toxicants Exposure, and Lung Cancer Risk

Lung cancer (LC) is the second-most prevalent tumor worldwide. According to the most recent GLOBOCAN data, over 2.2 million LC cases were reported in 2020, with an estimated new death incident of 1,796,144 lung cancer cases. Genetic, lifestyle, and environmental exposure play an important role as risk factors for LC. E-cigarette, or vaping, products (EVPs) use has been dramatically increasing world-wide. There is growing concern that EVPs consumption may increase the risk of LC because EVPs contain several proven carcinogenic compounds. However, the relationship between EVPs and LC is not well established. E-cigarette contains nicotine derivatives (e.g., nitrosnornicotine, nitrosamine ketone), heavy metals (including organometal compounds), polycyclic aromatic hydrocarbons, and flavorings (aldehydes and complex organics). Several environmental toxicants have been proven to contribute to LC. Proven and plausible environmental carcinogens could be physical (ionizing and non-ionizing radiation), chemicals (such as asbestos, formaldehyde, and dioxins), and heavy metals (such as cobalt, arsenic, cadmium, chromium, and nickel). Air pollution, especially particulate matter (PM) emitted from vehicles and industrial exhausts, is linked with LC. Although extensive environmental exposure prevention policies and smoking reduction strategies have been adopted globally, the dangers remain. Combined, both EVPs and toxic environmental exposures may demonstrate significant synergistic oncogenicity. This review aims to analyze the current publications on the importance of the relationship between EVPs consumption and environmental toxicants in the pathogenesis of LC.

Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places

Background

People usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.

Methods

In this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.

Results

The final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.

Conclusion

In this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction.

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Lung cancer has become one of the most prevalent cancers in the last several decades. Studies have documented that most cases of lung cancer are caused by inhaling environmental carcinogens while how external environmental factors lead to individual lung cancer is still an open issue as the pathogenesis may come from the combined action of multiple environmental factors, and such pathogenic mechanism may vary from region to region. Based on the data of lung cancer cases from hospitals at the county level in Henan from 2016 to 2020, we analyzed the response relationship between lung cancer incidence and physical ambient factors (air quality, meteorological conditions, soil vegetation) and socioeconomic factors (occupational environment, medical level, heating mode, smoking behavior). We used a Bayesian spatio-temporal interaction model to evaluate the relative risk of disease in different regions. The results showed that smoking was still the primary determinant of lung cancer, but the influence of air quality was increasing year by year, with meteorological conditions and occupational environment playing a synergistic role in this process. The high-risk areas were concentrated in the plains of East and Central Henan and the basin of South Henan, while the low-risk areas were concentrated in the hilly areas of North and West Henan, which were related to the topography of Henan. Our study provides a better understanding of the environmental determinants of lung cancer which will help refine existing prevention strategies and recognize the areas where actions are required to prevent environment and occupation related lung cancer.

Effects of short-term high-concentration exposure to PM2.5 on pulmonary tissue damage and repair ability as well as innate immune events

Short-term heavy air pollution still occurs frequently worldwide, especially during the winter heating period in some developing countries, which is usually accompanied by the temporary explosive growth of PM_2.5. The pulmonary damage caused by PM_2.5 exposure has been determined, but there have been few studies on the repair ability after the cessation of exposure and the important role of innate immune events. This study established a short-term (30 days) high-concentration (15 mg/kg body weight) PM_2.5 exposure and recovery (15 days of exposure cessation) model by intratracheal instillation. The results showed that short-term PM_2.5 exposure increased the content of collagen fiber in rat lung tissue, which was significantly repaired after recovery by 15 days of exposure cessation. Meanwhile, exposure to PM_2.5 also caused changes in lung epithelial function, macrophage polarization and cell autophagy function. Most of these changes could be restored or reversed to a certain extent after recovery. However, there were also some biomarkers, including CLDN18.1, SP-A, SP-D, iNOS, CD206, Beclin1, p62 and LC3B, that were still significantly different between the exposure and control groups after recovery, suggesting that some toxic effects, especially epithelial function damage, were not completely repaired. In addition, there was a significant correlation between pulmonary fibrosis and innate immunity. The present study demonstrated that short-term high-concentration exposure to PM_2.5 could cause temporary lung tissue damage and related innate immune events in rats, and the repair ability existed after the cessation of exposure, but part of the damage that required special attention still persisted.

Using a human bronchial epithelial cell-based malignant transformation model to explore the function of hsa-miR-200 family in the progress of PM2.5-induced lung cancer development

Numerous studies have revealed that ambient long-term exposure to fine particulate matter (PM_2.5) is significantly related to the development of lung cancer, but the molecular mechanisms of PM_2.5 exposure-induced lung cancer remains unknown. As an important epigenetic regulator, microRNAs (miRNAs) play vital roles in responding to environment exposure and various diseases including lung cancer development. Here we constructed a PM_2.5-induced malignant transformed cell model and found that miR-200 family, especially miR-200a-3p, was involved in the process of PM_2.5 induced lung cancer. Further investigation of the function of miR-200 family (miR-200a-3p as a representative revealed that miR-200a-3p promoted cell migration by directly suppressing TNS3 expression. These results suggested that ambient PM_2.5 exposure may increase the expression of miR-200 family and then promote the proliferation and migration of lung cancer cells. Our study provided novel model and insights into the molecular mechanism of ambient PM_2.5 exposure-induced lung cancer.

Ambient fine particulate matter and cardiopulmonary health risks in China

ABSTRACT

In China, the level of ambient fine particulate matter (PM 2.5 ) pollution far exceeds the air quality standards recommended by the World Health Organization. Moreover, the health effects of PM 2.5 exposure have become a major public health issue. More than half of PM 2.5 -related excess deaths are caused by cardiopulmonary disease, which has become a major health risk associated with PM 2.5 pollution. In this review, we discussed the latest epidemiological advances relating to the health effects of PM 2.5 on cardiopulmonary diseases in China, including studies relating to the effects of PM 2.5 on mortality, morbidity, and risk factors for cardiovascular and respiratory diseases. These data provided important evidence to highlight the cardiopulmonary risk associated with PM 2.5 across the world. In the future, further studies need to be carried out to investigate the specific relationship between the constituents and sources of PM 2.5 and cardiopulmonary disease. These studies provided scientific evidence for precise reduction measurement of pollution sources and public health risks. It is also necessary to identify effective biomarkers and elucidate the biological mechanisms and pathways involved; this may help us to take steps to reduce PM 2.5 pollution and reduce the incidence of cardiopulmonary disease.

Histological types of lung cancer attributable to fine particulate, smoking, and genetic susceptibility

BACKGROUND

Fine particulate matter (PM_2.5), smoking, and genetic factors are associated with lung cancer. However, the relationship between PM_2.5, smoking and subtypes of lung cancer remains unclear. Moreover, it is unclear whether genetic risk modifies the impact of PM_2.5 and smoking on incident lung cancer.

METHODS

A total of 298,069 participants from the UK Biobank study without lung cancer at baseline were included in this study. Hazard ratios (HRs) with 95 % confidence intervals (CIs) were estimated using multivariable Cox proportional models for the association of lung cancer and its subtypes with PM_2.5, smoking, and genetic risk. Potential gene-smoking or gene-PM_2.5 interactions were also estimated. We further estimated population attributable fractions for incident lung cancer.

RESULTS

During 10.4 years of follow-up, 1683 incident lung cancer cases were identified. Our analysis found that genetic variants, smoking, and PM_2.5 were significantly associated with incident lung cancer. For different histological types of lung cancer, the HRs for squamous cell lung carcinoma associated with PM_2.5 (per 5 μg/m³ increment) and current smoking were 2.76 (95 % CI: 1.72, 4.42, p < 0.001) and 48.64 (95 % CI: 27.96, 84.61, p < 0.001), while the HRs for lung adenocarcinoma were 1.59 (95 % CI: 1.13, 2.23, p < 0.001) and 9.89 (95 % CI: 7.91, 12.36, p < 0.001), respectively. We further found that participants with high levels of PM_2.5 pollution and high genetic risk had the highest risk of incident lung cancer (HR = 1.81, 95 % CI: 1.39, 2.35, p < 0.001), while the interaction between PM_2.5 and genetic risk was not statistically significant. We observed that the population attributable fractions of lung cancer attributable to current smoking and high PM_2.5 exposure were estimated to be 67.45 % and 17.59 %.

CONCLUSION

Genetic susceptibility, smoking, and PM_2.5 are important risk factors for lung cancer. Both smoking and PM_2.5 are more closely associated with an elevated risk of squamous cell lung cancer.

PM2.5: Epigenetic Alteration in Lung Physiology and Lung Cancer Pathogenesis

Particulate matter (PM) has a very negative impact on human health, specifically the respiratory system. PM comes in many forms, among these is PM2.5,which is a major risk factor for lung cancer and other cardiovascular diseases. PM is inherent in emissions from industrial production, manufacturing, vehicle exhaust, mining, and cigarette smoking. For this reason, the composition of PM differs from area to area although its primary constituents are heavy metals and petroleum elements. PM has a long and toxic impact on human health. After extended exposure to PM2.5 the mortality rate for lung cancer patients increases. Already, lung cancer is the leading cause of death globally with the highest mortality rate. PM2.5 creates epigenetic changes in miRNA, histone modification, and DNA methylation, causing tumorigenesis followed by lung cancer.

Targeting immune cell types of tumor microenvironment to overcome resistance to PD-1/PD-L1 blockade in lung cancer

Lung cancer is the common malignant tumor with the highest mortality rate. Lung cancer patients have achieved benefits from immunotherapy, including immune checkpoint inhibitors (ICIs) therapy. Unfortunately, cancer patients acquire adaptive immune resistance, leading to poor prognosis. Tumor microenvironment (TME) has been demonstrated to play a critical role in participating in acquired adaptive immune resistance. TME is associated with molecular heterogeneity of immunotherapy efficacy in lung cancer. In this article, we discuss how immune cell types of TME are correlated with immunotherapy in lung cancer. Moreover, we describe the efficacy of immunotherapy in driven gene mutations in lung cancer, including KRAS, TP53, EGFR, ALK, ROS1, KEAP1, ZFHX3, PTCH1, PAK7, UBE3A, TNF-α, NOTCH, LRP1B, FBXW7, and STK11. We also emphasize that modulation of immune cell types of TME could be a promising strategy for improving adaptive immune resistance in lung cancer.

Fine particulate matter and cardiorespiratory health in China: A systematic review and meta-analysis of epidemiological studies

This review aimed to systematically summarize the epidemiological literature on the cardiorespiratory effects of PM_2.5 published during the 13^th Five-Year Plan period (2016-2020) in China. Original articles published between January 1, 2016 and June 30, 2021 were searched in PubMed, Web of Science, the China National Knowledge Internet Database and Wanfang Database. Random- or fixed-effects models were used to pool effect estimates where appropriate. Of 8558 records identified, 145 met the full eligibility criteria. A 10 µg/m³ increase in short-term PM_2.5 exposure was significantly associated with increases of 0.70%, 0.86%, 0.38% and 0.96% in cardiovascular mortality, respiratory mortality, cardiovascular morbidity, and respiratory morbidity, respectively. The specific diseases with significant associations included stroke, ischemic heart disease, heart failure, arrhythmia, chronic obstructive pulmonary disease, pneumonia and allergic rhinitis. The pooled estimates per 10 µg/m³ increase in long-term PM_2.5 exposure were 15.1%, 11.9% and 21.0% increases in cardiovascular, stroke and lung cancer mortality, and 17.4%, 11.0% and 4.88% increases in cardiovascular, hypertension and lung cancer incidence respectively. Adverse changes in blood pressure, heart rate variability, systemic inflammation, blood lipids, lung function and airway inflammation were observed for either short-term or long-term PM_2.5 exposure, or both. Collectively, we summarized representative exposure-response relationships between short- and long-term PM_2.5 exposure and a wide range of cardiorespiratory outcomes applicable to China. The magnitudes of estimates were generally smaller in short-term associations and comparable in long-term associations compared with those in developed countries. Our findings are helpful for future standard revisions and policy formulation. There are still some notable gaps that merit further investigation in China.

PM2.5 promotes NSCLC carcinogenesis through translationally and transcriptionally activating DLAT-mediated glycolysis reprograming

Background

Airborne fine particulate matter (PM2.5) has been associated with lung cancer development and progression in never smokers. However, the molecular mechanisms underlying PM2.5-induced lung cancer remain largely unknown. The aim of this study was to explore the mechanisms by which PM2.5 regulated the carcinogenesis of non-small cell lung cancer (NSCLC).

Methods

Paralleled ribosome sequencing (Ribo-seq) and RNA sequencing (RNA-seq) were performed to identify PM2.5-associated genes for further study. Quantitative real time-PCR (qRT-PCR), Western blot, and immunohistochemistry (IHC) were used to determine mRNA and protein expression levels in tissues and cells. The biological roles of PM2.5 and PM2.5-dysregulated gene were assessed by gain- and loss-of-function experiments, biochemical analyses, and Seahorse XF glycolysis stress assays. Human tissue microarray analysis and ¹⁸F-FDG PET/CT scans in patients with NSCLC were used to verify the experimental findings. Polysome fractionation experiments, chromatin immunoprecipitation (ChIP), and dual-luciferase reporter assay were implemented to explore the molecular mechanisms.

Results

We found that PM2.5 induced a translation shift towards glycolysis pathway genes and increased glycolysis metabolism, as evidenced by increased L-lactate and pyruvate concentrations or higher extracellular acidification rate (ECAR) in vitro and in vivo. Particularly, PM2.5 enhanced the expression of glycolytic gene DLAT, which promoted glycolysis but suppressed acetyl-CoA production and enhanced the malignancy of NSCLC cells. Clinically, high expression of DLAT was positively associated with tumor size, poorer prognosis, and SUVmax values of ¹⁸F-FDG-PET/CT scans in patients with NSCLC. Mechanistically, PM2.5 activated eIF4E, consequently up-regulating the expression level of DLAT in polysomes. PM2.5 also stimulated transcription factor Sp1, which further augmented transcription activity of DLAT promoter.

Conclusions

This study demonstrated that PM2.5-activated overexpression of DLAT and enhancement in glycolysis metabolism contributed to the tumorigenesis of NSCLC, suggesting that DLAT-associated pathway may be a therapeutic target for NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02437-8.

Association of high PM2.5 levels with short-term and medium-term lung function recovery in patients with pulmonary lobectomy

The association between exposure to ambient fine particulate matter with an aerodynamic diameter of ≤ 2.5 μm (PM_2.5) and short- and medium-term lung function recovery (LFR) in patients undergoing lobectomy remains uncertain. This study investigated the associations between PM_2.5 concentrations and LFR in adult patients (n = 526) who underwent video-assisted thoracoscopic (VATS) lobectomy in Guangzhou, China between January 2018 and June 2021. All patients underwent at least two spirometry tests. Environmental PM_2.5 concentrations in the same period were collected from the nearest monitoring station. A multiple linear regression (MLR) model was employed to investigate the associations between changes in PM_2.5 concentrations and LFR in patients who underwent lobectomy after adjusting for potential confounders. We assessed short- and medium-term LFR in patients who underwent lobectomy. The three- and 6-month average PM_2.5 concentrations in each patient's residential area were divided into regional mild pollution (PM_2.5 <25 μg/m³), moderate pollution (25 μg/m³ ≤ PM_2.5 <35 μg/m³), and severe pollution (35 μg/m³ ≤ PM_2.5) periods. The MLR model confirmed that PM_2.5 was an independent risk factor affecting short-term forced lung capacity (FVC), forced expiratory volume in 1 s (FEV1), and maximum expiratory flow at 50% vital capacity (MEF₅₀) recovery (adjusted P = 0.041, 0.014, 0.016, respectively). The MLR model confirmed that PM_2.5 was an independent risk factor affecting medium-term MEF₅₀ recovery (adjusted P = 0.046). Compared with the moderate and severe pollution periods, the short- and medium-term LFR (FVC, FEV1, MEF₅₀) of patients in the mild pollution period were faster and better (P < 0.001, P < 0.001, P < 0.001, P = 0.048, P = 0.010, P = 0.013, respectively). Thus, exposure to high PM_2.5 levels was associated with significantly reduced speed and degree of short- and medium-term LFR in patients who underwent lobectomy.

Long-term PM2.5 exposure in association with chronic respiratory diseases morbidity: A cohort study in Northern China

Several literatures have examined the risk of chronic respiratory diseases in association with short-term ambient PM2.5 exposure in China. However, little evidence has examined the chronic impacts of PM2.5 exposure on morbidity of chronic respiratory diseases in cohorts from high pollution countries. Our study aims to investigate the associations. Based on a retrospective cohort among adults in northern China, a Cox regression model with time-varying PM2.5 exposure and a concentration-response (C-R) curve model were performed to access the relationships between incidence of chronic respiratory diseases and long-term PM2.5 exposure during a mean follow-up time of 9.8 years. Individual annual average PM2.5 estimates were obtained from a satellite-based model with high resolution. The incident date of a chronic respiratory disease was identified according to self-reported physician diagnosis time and/or intake of medication for treatment. Among 38,047 urban subjects analyzed in all-cause chronic respiratory disease cohort, 482 developed new cases. In CB (38,369), asthma (38,783), and COPD (38,921) cohorts, the onsets were 276, 89, and 14, respectively. After multivariable adjustment, hazard ratio and 95% confidence interval for morbidity of all-cause chronic respiratory disease, CB, asthma, and COPD were 1.15 (1.01, 1.31), 1.20 (1.00, 1.42), 0.76 (0.55, 1.04), and 0.66 (0.29, 1.47) with each 10 μg/m3 increment in PM2.5, respectively. Stronger effect estimates were suggested in alcohol drinkers across stratified analyses. Additionally, the shape of C-R curve showed an increasing linear relationship before 75.00 μg/m3 concentrations of PM2.5 for new-onset all-cause chronic respiratory disease, and leveled off at higher levels. These findings indicated that long-term exposure to high-level PM2.5 increased the risks of incident chronic respiratory diseases in China. Further evidence of C-R curves is warranted to clarify the associations of adverse chronic respiratory outcomes involving air pollution.

Short-term effects of indoor and outdoor air pollution on the lung cancer morbidity in Henan Province, Central China

Lung cancer is one of the most common cancer types and a major cause of death. The relationship between lung cancer morbidity and exposure to air pollutants is of particular concern. However, the relationship and difference in lung cancer morbidity between indoor and outdoor air pollution effects remain unclear. In this paper, the aim was to comprehensively investigate the spatial relationships between the lung cancer morbidity and indoor-outdoor air pollution in Henan based on the standard deviation ellipse, spatial autocorrelation analysis and GeoDetector. The results indicated that (1) the spatial distribution of lung cancer morbidity was related to the geomorphology, while high-morbidity areas were concentrated in the plains and basins of Central, Eastern and Southern Henan. (2) Among the selected outdoor air pollutants, PM_2.5, NO₂, SO₂, O₃ and CO were significantly correlated with the lung cancer morbidity. The degree of indoor air pollution was measured by the use of heating energy, and the proportions of coal-heating households, households with coal/biomass stoves and households with heated kangs were highly decisive in regard to the lung cancer morbidity. (3) The interaction between two factors was more notable than a single factor in explaining the lung cancer morbidity. Moreover, the interaction type was mainly nonlinear enhancement, and the proportion of households with coal/biomass stoves imposed the strongest interaction effect on the other factors.

Toxicological effects of traffic-related air pollution on the lungs: Evidence, biomarkers and intervention

BACKGROUND

Numerous epidemiological studies have recently observed that exposure to traffic-related air pollution (TRAP) is associated with increased risk of various respiratory diseases. Major gaps in knowledge remain regarding the toxicological effects.

OBJECTIVES

We examined the toxicological effects of the gasoline exhaust particles (GEP), a paradigm of TRAP, in rats, with an objective to provide the evidence, obtain the biomarkers, and suggest effective intervention measure.

METHODS

We measured the airway hyperresponsiveness (AHR), inflammatory cells in the bronchoalveolar lavage (BAL) fluid, histological changes in the lung tissues, and the biomarkers so as to systematically examine the toxicological effects of GEPs at different dose levels (0.5, 2.5, 5 mg/kg BW). The intervention of vitamin E (VE), a natural antioxidant, on the toxicological effects was investigated.

RESULTS

The lung injury caused by GEP exposure was first indicated by the airway hyperresponsiveness (AHR). Compared with the control group, GEP exposure significantly increased the airway resistances and decreased the lung compliance; the higher the dose of GEP, the more serious the lung injury. Lung injury was also revealed by the increase of inflammatory cells, including the lymphocytes and neutrophils, in the BAL fluid. With the increase of GEP dose, histological changes in the lung tissues were further observed: inflammatory cell infiltration increased and alveolar wall thickened. The toxicology of GEP was demonstrated by the increase of the biomarkers of the oxidative stress, the pro-inflammatory cytokines and the apoptosis cytokine. However, administration of VE was found to be effective in restoring airway injury.

CONCLUSION

The toxicological effects of traffic-related air pollution (TRAP) on rat lungs are supported by evidence and biomarkers, and vitamin E intervention is feasible.

Seasonal characteristics of temperature variability impacts on childhood asthma hospitalization in Hefei, China: Does PM2.5 modify the association?

OBJECTIVES

Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM_2.5.

METHODS

A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM_2.5 were tested by introducing the cross-basis of TV and binary PM_2.5 as an interaction term.

RESULTS

The risk estimates peaked at TV_0-3 and TV_0-4 in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV_0-3. In addition, the risks of TV were higher under the high PM_2.5 level compared with the low PM_2.5 level in the cool season, although no significant differences between them.

CONCLUSIONS

TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM_2.5 need more attention.

Does air pollution contribute to urban-rural disparity in male lung cancer diseases in China?

It remains unknown whether exposure to ambient air pollution can be a mediator linking socioeconomic indicator to health outcome. The present study aims to examine the mediation effect of PM2.5 air pollution on the association between urban-rural division and the incidence (mortality) rate of male lung cancer. We performed a nationwide analysis in 353 counties (districts) of China between 2006 and 2015. A structural equation model was developed to determine the mediation effect of exposure to PM2.5. We also tested whether the findings of the mediation effect of exposure to PM2.5 are sensitive to the controls of smoking factors and additional air pollutant, and PM2.5 exposures with different lag structures. According to the results, we found that exposure to PM2.5 significantly mediated the association between urban-rural division and the incidence rate of male lung cancer. Specifically, there were significant associations between urban-rural division, exposure to PM2.5, and the incidence rate of male lung cancer, with PM2.5 exposure accounting for 29.80% of total urban-rural difference in incidence rates of male lung cancer. A similar pattern of results was observed for the mortality rate of male lung cancer. That is, there was a significant mediation effect by PM2.5 on the association of the mortality rate with urban-rural division. The findings of exposure to PM2.5 as a mediator were robust in the three sensitivity analyses. In conclusion, urban-rural difference in exposures to PM2.5 may be a potential factor that contributes to urban-rural disparity in male lung cancer diseases in China. The findings inform that air pollution management and control may be effective measures to alleviate the great difference in male lung cancer diseases between urban and rural areas in China.

Real-world PM2.5 exposure induces pathological injury and DNA damage associated with miRNAs and DNA methylation alteration in rat lungs

Fine particulate matter (PM_2.5) has been demonstrated to threaten public health and increase lung cancer risk. DNA damage is involved in the pathogenesis of lung cancer. However, the mechanisms of epigenetic modification of lung DNA damage are still unclear. This study developed a real-world air PM_2.5 inhalation system and exposed rats for 1 and 2 months, respectively, and investigated rat lungs pathological changes, inflammation, oxidative stress, and DNA damage effects. OGG1 and MTH1 expression was measured, along with their DNA methylation status and related miRNAs expression. The results showed that PM_2.5 exposure led to pathological injury, influenced levels of inflammatory cytokines and oxidative stress factors in rat lungs. Of note, 2-month PM_2.5 exposure aggravated pathological injury. Besides, PM_2.5 significantly elevated OGG1 expression and suppressed MTH1 expression, which was correlated to oxidative stress and partially mediated by reducing OGG1 DNA methylation status and increasing miRNAs expression related to MTH1 in DNA damage with increases of γ-H2AX, 8-OHdG and GADD153. PM_2.5 also activated c-fos and c-jun levels and inactivated PTEN levels in rat lungs. These suggested that epigenetic modification was probably a potential mechanism by which PM_2.5-induced genotoxicity in rat lungs.

Spatial-Temporal Evolution of Health Impact and Economic Loss upon Exposure to PM2.5 in China

Exposure to PM_2.5 can seriously endanger public health. Policies for controlling PM_2.5 need to consider health hazards under different circumstances. Unlike most studies on the concentration, distribution, and influencing factors of PM_2.5, the present study focuses on the impact of PM_2.5 on human health. We analysed the spatial-temporal evolution of health impact and economic loss caused by PM_2.5 exposure using the log-linear exposure-response function and benefit transfer method. The results indicate that the number of people affected by PM_2.5 pollution fluctuated and began to decline after reaching a peak in 2014, benefiting from the Air Pollution Prevention and Control Action Plan. Regarding the total economic loss, the temporal pattern continued to rise until 2014 and then declined, with an annual mean of 86,886.94 million USD, accounting for 1.71% of China’s GDP. For the spatial pattern, the health impact and economic loss show a strong spatial correlation and remarkable polarisation phenomena, with high values in East China, North China, Central China, and South China, but low values in Southwest China, Northwest China, and Northeast China. The spatial-temporal characterisation of PM_2.5 health hazards is visualised and analysed accordingly, which can provide a reference for more comprehensive and effective policy decisions.

PM Dimensional Characterization in an Urban Mediterranean Area: Case Studies on the Separation between Fine and Coarse Atmospheric Aerosol

Fine particulate matter (PM) is object of particular attention due to its health effects. It is currently regulated by adopting PM2.5 as an indicator to control anthropogenic combustion emissions. Therefore, it is crucial to collect aerosol samples representative of such sources, without including PM from natural sources. Thus, a clean separation between coarse and fine mode aerosol should be set. With this purpose, aerosol size mass distribution was taken in the aerodynamic diameter range from 0.5 to 10 µm. In comparison with a base scenario, characterized by local pollution sources, three case studies were considered, involving desert dust advection, sea salt advection and forest fire aerosol from a remote area. In the base scenario, PM2.5 represented a suitable fine-mode indicator, whereas it was considerably affected by coarse PM in case of desert dust and sea salt aerosol advection. Such interference was considerably reduced by setting the fine/coarse separation at 1.0 µm. Such separation underrepresented fine PM from forest fire long-range transport, nonetheless in the case studies considered, PM1 represented the best indicator of fine aerosol since less affected by coarse natural sources. The data presented clearly support the results from other studies associating the health effects of PM2.5 to PM1, rather than to PM1–2.5. Overall, there is a need to reconsider PM2.5 as an indicator of fine atmospheric aerosol.

The lag effect of exposure to PM2.5 on esophageal cancer in urban-rural areas across China

Exposure to PM2.5 pollution is a significant health concern and increases risks for cancers in China. However, the studies regarding the effect of PM2.5 and esophageal cancer incidence (ECI) among urban-rural areas are limited. In this study, we examined the sex- and area-specific association between exposure to PM2.5 and ECI, as well as explored the corresponding lag effects on ECI using a geographical weighted Poisson regression. We found significantly positive effect on ECI for males and females in different models, with the greatest increase of 1.44% (95% CI: 1.30%, 1.59%) and 2.42% (95% CI: 2.17%, 2.66%) in per 10 ug/m3 increase of PM2.5 for males and females at single year lag7 and lag4 after all covariates controlled, respectively. We also found that the long-term effect of PM2.5 on ECI was relatively stable at all moving average year lags. Moreover, rural areas had higher ECI risks for males (0.17%) and females (0.64%) with longer lag period than urban areas. In addition, higher risks for both sexes appeared in north, northwestern, and east China. The findings indicated that long-term exposure to PM2.5 was significantly associated with increased risks for ECI, which reinforce a comprehensive understanding for ECI related to PM2.5.

Exposure to long-range transported particulate matter and modeling age-related particle deposition

Exposure to particulate matter (PM) is known to cause cardiovascular disease and increase mortality and morbidity. Asian dust (AD) is a meteorological phenomenon which affects much of East Asia year-round but especially during the spring months. Here, we have characterized concentrations of PM₁₀ and classified synoptic air flow trajectories using HYSPLIT model for Asian dust events (from March to April) in Jeju island, Korea. The ADE is a phenomenon in which sand and dust in the deserts of China or Mongolia rise mainly in spring and are blown away by western winds and gradually subside. The calculated inhaled PM₁₀ doses from specific microenvironments (home, work or school, and transportation) were from 5.28 to 101.48 μg depending on age group and different microenvironments while the calculated PM₁₀ inhaled doses for ADE ranged within 67.92 -769.27 μg. Also, we have evaluated the contribution of specific microenvironments to the exposure for different age groups using time-activity patterns and calculated inhaled PM₁₀ doses and deposited mass/mass flux so as to estimate exposure using multiple-path particle dosimetry (MPPD) model. The monthly average outdoor PM₁₀ concentration range was 29.3-65.4 μg/m³, whereas the monthly PM₁₀ concentration for ADE was 127.0-342.0 μg/m³. Air masses from clusters 1 and 2 were 24% and 29% (in 2017), clusters 2 and 3 were 24% and 32% (in 2018), and clusters 1 and 3 were 28% and 26% (in 2019) for ADE. In the aerosol deposition based on MPPD model, the corresponding values for daily particle deposited mass for two age groups ranged from 8.64 ×10^-5 μg (age 8) to 8.64 ×10^-4 μg (age 21). We assessed the PM_2.5 exposure considering time-activity patterns, age groups, and ADE exposure evaluation caused by long-range transport airflow; this could be helpful for assessing PM₁₀ exposure-related health evaluation.

Lipid changes in extrapulmonary organs and serum of rats after chronic exposure to ambient fine particulate matter

Fine particulate matter (PM_2.5) is able to pass through the respiratory barrier to enter the circulatory system and can consequently spread to the whole body to cause toxicity. Although our previous studies have revealed significantly altered levels of phosphorylcholine-containing lipids in the lungs of rats after chronic inhalation exposure to PM_2.5, the effects of PM_2.5 on phosphorylcholine-containing lipids in the extrapulmonary organs have not yet been elucidated. In this study, we examined the lipid effects of chronic PM_2.5 exposure on various organs and serum by using a rat inhalation model followed by a mass spectrometry-based lipidomic approach. Male Sprague-Dawley rats were continuously exposed at the whole body level to nonfiltered and nonconcentrated ambient air from the outside environment of Taipei city for 8 months, while the control rats inhaled filtered air simultaneously. After exposure, serum samples and various organs, including the testis, pancreas, heart, liver, kidney, spleen, and epididymis, were collected for lipid extraction and analysis to examine the changes in phosphorylcholine-containing lipids after exposure. The results from the partial least squares discriminant analysis models demonstrated that the lipid profiles in the PM_2.5 exposure group were different from those in the control group in the rat testis, pancreas, heart, liver, kidney and serum. The greatest PM_2.5-induced lipid effects were observed in the testes. Decreased lyso-phosphatidylcholines (PCs) as well as increased unsaturated diacyl-PCs and sphingomyelins in the testes may be related to maintaining the membrane integrity of spermatozoa, antioxidation, and cell signaling. Additionally, our results showed that decreased PC(16:0/18:1) was observed in both the serum and testes. In conclusion, exposure to chronic environmental concentrations of PM_2.5 caused lipid perturbation, especially in the testes of rats. This study highlighted the susceptibility of the testes and suggested possible molecular events for future study.

Effects of PM2.5 on Chronic Airway Diseases: A Review of Research Progress

The adverse effects of polluted air on human health have been increasingly appreciated worldwide. It is estimated that outdoor air pollution is associated with the death of 4.2 million people globally each year. Accumulating epidemiological studies indicate that exposure to ambient fine particulate matter (PM2.5), one of the important air pollutants, significantly contributes to respiratory mortality and morbidity. PM2.5 causes lung damage mainly by inducing inflammatory response and oxidative stress. In this paper, we reviewed the research results of our group on the effects of PM2.5 on chronic obstructive pulmonary disease, asthma, and lung cancer. And recent research progress on epidemiological studies and potential mechanisms were also discussed. Reducing air pollution, although remaining a major challenge, is the best and most effective way to prevent the onset and progression of respiratory diseases.

REDD1 (regulated in development and DNA damage-1)/autophagy inhibition ameliorates fine particulate matter (PM2.5) -induced inflammation and apoptosis in BEAS-2B cells

This study aimed to investigate the implication of REDD1 on airborne particle matter-induced lung injury and whether it is mediated through autophagy. Cell viability in BEAS-2B cells induced by PM2.5 was measured by CCK-8. RT-qPCR and Western blot were performed to determine mRNA and protein levels of REDD1 as well as inflammatory cytokines, respectively. Cell apoptosis was observed with TUNEL staining. The expression of autophagy-related genes was detected by Western blot. Autophagy level was observed with GFP-LC3 staining. PM2.5 induced the expression of REDD1 in BEAS-2B cells. The inhibition by silencing REDD1 ameliorated the viability damage, blocked the inflammatory response and reduced the number of apoptotic BEAS-2B cells all induced by PM2.5. It was also found that PM2.5 induced autophagy in BEAS-2B cells, which was reversed by interference with REDD1. Furthermore, interference with REDD1 alleviated PM2.5-induced cell damage, inflammatory response and apoptosis in BEAS-2B cells through inhibiting autophagy. REDD1/autophagy inhibition ameliorates PM2.5-induced viability damage, inflammation and apoptosis in BEAS-2B cells.

Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010-2016: A multistage approach

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM_2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM_2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM_2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM_2.5 and lung cancer mortality attributable to PM_2.5 across YRD during 2010-2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R² and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9-8 times higher than the other major cities (7-year average: 192,000 μg·people/m³·km²). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%-33% higher than in low-risk areas. There were 12,574-14,504 total lung cancer deaths attributable to PM_2.5, and lung cancer deaths in each square kilometer of urban areas were 7-13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.

The Inducible Role of Ambient Particulate Matter in Cancer Progression via Oxidative Stress-Mediated Reactive Oxygen Species Pathways: A Recent Perception

Simple Summary

Particulate matter, especially the fine fraction PM2.5, is officially stated as carcinogenic to human. There are compelling evidences on the association between PM2.5 exposure and lung cancer, and there are also some preliminary data reporting the significant links between this fraction with non-lung cancers. The underlying mechanisms remain unclear. Further studies related to such scope are highly required. The purpose of this work is to systemically analyze recent findings concerning the relationship between PM2.5 and cancer, and to thoroughly present the oxidative stress pathways mediated by reactive oxygen species as the key mechanism for carcinogenesis induced by PM2.5. This will provide a more comprehensive and updated knowledge regarding carcinogenic capacity of PM2.5 to both clinicians and public health workers, contributing to preventive and therapeutic strategies to fight against cancer in human.

Abstract

Cancer is one of the leading causes of premature death and overall death in the world. On the other hand, fine particulate matter, which is less than 2.5 microns in aerodynamic diameter, is a global health problem due to its small diameter but high toxicity. Accumulating evidence has demonstrated the positive associations between this pollutant with both lung and non-lung cancer processes. However, the underlying mechanisms are yet to be elucidated. The present review summarizes and analyzes the most recent findings on the relationship between fine particulate matter and various types of cancer along with the oxidative stress mechanisms as its possible carcinogenic mechanisms. Also, promising antioxidant therapies against cancer induced by this poison factor are discussed.