Air pollution and green spaces in relation to breast cancer risk among pre and postmenopausal women: A mega cohort from Catalonia

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

Associations of air pollution and greenness with global burden of breast cancer: an ecological study

Despite the significance of the associations of air pollution and greenness with the risk of breast cancer, this topic has not been investigated on a global scale. We conducted an ecological study using 7 years of data from 162 countries. Disability-adjusted life years (DALYs) and incidence data were used to represent the breast cancer disease burden. Particulate matter with a diameter < 2.5 μm (PM2.5), ozone (O3), nitrogen dioxide (NO2), and the normalized difference vegetation index (NDVI) were adopted as our exposures. We employed generalized linear mixed models to explore the relationship between air pollution and greenness on breast cancer disease burden. The rate ratio (RR) and its 95% confidence interval (CI) indicate the effect size. There is a positive association between air pollution and the burden of breast cancer disease. Contrarily, per interquartile range increment in NDVI was negatively associated with DALYs and incidence. In terms of air pollutants and breast cancer, NDVI seems to have a significant influence on the relationship between these two conditions. A higher amount of greenness helps to alleviate the negative association of air pollution on breast cancer. PM2.5 and O3 play a mediating role in the relationship between greenness and breast cancer disease burden. In areas with higher levels of greenness, there is a possibility that the inverse association between air pollutants and the burden of breast cancer may be influenced.

Association between greenspace and cancer: evidence from a systematic review and meta-analysis of multiple large cohort studies

Cancer is a chronic disease that seriously endangers human health, and studies on its association with greenspace have been published. We aimed to systematically review the epidemiological evidence and obtain the best available evidence. PubMed, Web of Science, Embase, and Cochrane Library were used as search databases, the time limit was September 12, 2022, and the cited articles were manually supplemented. Two researchers independently performed literature screening and data extraction. We performed a meta-analysis of data using a normalized difference vegetation index (NDVI) as the greenspace measure, providing hazard ratio (HR) and corresponding 95% CI. After standardization of the data, we used a random effects model for pooling. We also assessed the risk of bias for each study and the quality of each evidence body. We identified 10,108 items and included 14 studies from 11 institutions in eight countries. All studies had a low risk of bias. Quantitative analysis of 13 studies found a beneficial association of greenspace with the mortality of lung cancer (pooled HR [95% CI]=0.965 [0.947, 0.983]) and prostate cancer (HR [95% CI]=0.939 [0.898, 0.980]) based on 0.1-unit NDVI increment and a potential beneficial association with the incidence of prostate, lung, and breast cancer. Greenspace had opposite associations with cancer mortality for urban and rural populations. Indirect comparisons did not find statistically significant differences in the effects of greenspace on different cancer outcomes. The evidence body assessment was considered to be "very low." This review indicated potential beneficial associations between greenspace for lung, prostate, and breast cancer outcomes. However, there was a lack of mediation analysis to explore the underlying mechanism of a causal association. Meanwhile, the interstudy heterogeneity was large. Therefore, future studies should consider more accurate exposure assessment and more comprehensive covariate coverage, while focusing on mediating analysis. PROSPERO: CRD42022361068.

Spatial pattern and environmental drivers of breast cancer incidence in Chinese women

Breast cancer (BC) had the highest incidence of all cancers in Chinese women. However, studies on spatial pattern and environmental drivers of BC were still lacked as they were either limited in a small area or few considered the comprehensive impact of multiple risk factors. In this study, we firstly performed spatial visualization and the spatial autocorrelation analysis based on Chinese women breast cancer incidence (BCI) data of 2012-2016. Then, we explored the environmental drivers related to BC by applying univariate correlation analysis and geographical detector model. We found that the BC high-high clusters were mainly distributed in the eastern and central regions, such as Liaoning, Hebei, Shandong, Henan, and Anhui Provinces. The BCI in Shenzhen was significantly higher than other prefectures. Urbanization rate (UR), per capita GDP (PGDP), average years of school attainment (AYSA), and average annual wind speed (WIND) had higher explanatory power on spatial variability of the BCI. PM₁₀, NO₂, and PGDP had significant nonlinear enhanced effect on other factors. Besides, normalized difference vegetation index (NDVI) was negatively associated with BCI. Therefore, high socioeconomic status, serious air pollution, high wind speed, and low vegetation cover were the risk factors for BC. Our study may able to provide evidence for BC etiology research and precise identification of areas requiring focused screening.