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2024
Breast Cancer Res
A nested case-control study within the French E3N-Generations cohort examined 523 breast cancer cases and 523 matched controls to investigate whether thirteen metabolic health biomarkers mediate the relationship between exposure to three air pollutants (nitrogen dioxide, PCB153, and benzo[a]pyrene) and breast cancer risk. The study found that benzo[a]pyrene exposure was associated with a significant 2.32-fold increased breast cancer risk (highest vs. lowest quartile), PCB153 showed inconsistent positive associations, and nitrogen dioxide showed no association; among biomarkers, estradiol was associated with increased breast cancer risk (OR = 1.22 per SD). Four-way decomposition mediation analysis revealed suggestive evidence that albumin, HDL and LDL cholesterol, parathormone, and estradiol may partially mediate the associations between all three pollutants and breast cancer risk, though findings were limited by statistical power. These results provide preliminary mechanistic insights suggesting that air pollutants may influence breast cancer risk through alterations in metabolic biomarkers—particularly lipid metabolism and hormone regulation—though larger studies are needed to confirm these pathways and establish the clinical significance of these mediating effects in the relationship between environmental exposures and breast cancer development.
2021
PLOS One
A case-control study in Ethiopia examined 50 breast cancer patients and 50 controls to investigate whether exposure to organochlorine pesticides is a risk factor for breast cancer in a low- and middle-income country context. Ten organochlorine pesticides were detected in participants’ serum, with heptachlor found at highest concentrations; mean serum levels of p,p’-DDE, p,p’-DDT, heptachlor, gamma-chlordane, endosulfan, and dibutyl-chlorendate were significantly higher in breast cancer patients than controls, and p,p’-DDT and gamma-chlordane emerged as significant predictors of breast cancer, with each unit increase in p,p’-DDT concentration doubling breast cancer odds (AOR = 2.03; 95% CI: 1.04-3.97) and each unit increase in gamma-chlordane tripling the odds (AOR = 3.12; 95% CI: 1.19-8.20). These findings suggest that organochlorine pesticide exposure may be a significant breast cancer risk factor in Ethiopia, where environmental contamination from these persistent organic pollutants remains a concern despite global restrictions. The study highlights the public health importance of reducing exposure to these banned or restricted pesticides in developing countries and emphasizes the need for continuous biomonitoring of persistent organic pollutants to inform disease prevention strategies and mitigation measures, particularly as breast cancer incidence rises in low- and middle-income countries where environmental regulation may be less stringent.
2019
Int J Env Res Public Health
A French population-based case-control study (CECILE study) of 695 breast cancer cases and 1,055 controls measured plasma levels of organochlorine compounds (OCs)—p,p’-DDE and PCB153—at the time of diagnosis and used a physiologically-based pharmacokinetic (PBPK) model to estimate PCB153 exposure levels during adolescence (ages 11-20), when breast tissue may be particularly susceptible to hormonal disruption. The study found no clear association between measured OC levels at diagnosis and breast cancer risk overall, though there was a trend toward decreasing breast cancer odds ratios with increasing OC levels in women aged 50 and over; similarly, negative associations were observed between breast cancer and estimated adolescent PCB153 exposure levels. The PBPK modeling revealed that women born after 1960 had the highest estimated PCB153 exposures during adolescence (coinciding with peak environmental contamination), while older women had very low adolescent exposures, yet the unexpected negative associations between OC levels and breast cancer risk remained unexplained and may represent study artifacts. Despite these puzzling findings, the study demonstrates that PBPK models can be valuable tools in epidemiological research for back-estimating exposures during critical developmental windows, which could help address important questions about how early-life environmental exposures influence cancer risk decades later.