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Impact of mixtures of persistent organic pollutants on breast cancer aggressiveness
Introduction: Breast cancer (BC) is frequent with a poor prognosis in case of metastasis. The role of the environment has been poorly evaluated in its progression. We searched to assess whether a mixture of pollutants could be responsible of BC aggressiveness. Methods: Patients undergoing surgery for their BC were prospectively included in the METAPOP cohort. Forty-two POPs were extracted, among them 17 dioxins (PCDD/F), 16 polychlorobiphenyls (PCB), 8 polybromodiphenylethers (PBDE) and 2,2′,4,4′,5,5′-hexabromobiphenyl (PBB153) were measured in the adipose tissue surrounding the tumor. BC aggressiveness was defined using tumor size and metastasis (distant or lymph nodes). Two complementary models were used to evaluate the impact of the mixture of pollutants: the BKMR (Bayesian Kernel machine regression) and WQS (weighted quantile sum regression) models. The WQS estimates the weight (positive or negative) of a certain chemical based on its quantile and the BKMR model applies a kernel-based approach to estimate posterior inclusion probabilities. The sub-group of patients with a body mass index (BMI) > 22 kg/ m2 was also analyzed. Results: Ninety-one patients were included. Of these, 38 patients presented a metastasis, and the mean tumor size was 25.4 mm. The mean BMI was 24.5 kg/m2 (+/- 4.1). No statistical association was found in the general population. However, in patients with a BMI > 22 kg/ m2, our mixture was positively associated with tumor size (OR: 9.73 95 %CI: 1.30–18.15) and metastasis (OR = 3.98 95 %CI = 1.09–17.53) using the WQS model. Moreover, using the BKMR model on chemical families, dioxin like chemicals and PCDD were associated with a higher risk of metastasis. Discussion: These novel findings identified a mixture associated with breast cancer aggressiveness in patients with a BMI > 22 kg/ m2.
Impact of mixtures of persistent organic pollutants on breast cancer aggressiveness
Introduction: Breast cancer (BC) is frequent with a poor prognosis in case of metastasis. The role of the environment has been poorly evaluated in its progression. We searched to assess whether a mixture of pollutants could be responsible of BC aggressiveness. Methods: Patients undergoing surgery for their BC were prospectively included in the METAPOP cohort. Forty-two POPs were extracted, among them 17 dioxins (PCDD/F), 16 polychlorobiphenyls (PCB), 8 polybromodiphenylethers (PBDE) and 2,2′,4,4′,5,5′-hexabromobiphenyl (PBB153) were measured in the adipose tissue surrounding the tumor. BC aggressiveness was defined using tumor size and metastasis (distant or lymph nodes). Two complementary models were used to evaluate the impact of the mixture of pollutants: the BKMR (Bayesian Kernel machine regression) and WQS (weighted quantile sum regression) models. The WQS estimates the weight (positive or negative) of a certain chemical based on its quantile and the BKMR model applies a kernel-based approach to estimate posterior inclusion probabilities. The sub-group of patients with a body mass index (BMI) > 22 kg/ m2 was also analyzed. Results: Ninety-one patients were included. Of these, 38 patients presented a metastasis, and the mean tumor size was 25.4 mm. The mean BMI was 24.5 kg/m2 (+/- 4.1). No statistical association was found in the general population. However, in patients with a BMI > 22 kg/ m2, our mixture was positively associated with tumor size (OR: 9.73 95 %CI: 1.30–18.15) and metastasis (OR = 3.98 95 %CI = 1.09–17.53) using the WQS model. Moreover, using the BKMR model on chemical families, dioxin like chemicals and PCDD were associated with a higher risk of metastasis. Discussion: These novel findings identified a mixture associated with breast cancer aggressiveness in patients with a BMI > 22 kg/ m2.
Impact of mixtures of persistent organic pollutants on breast cancer aggressiveness
Louise Benoit (author) / Meriem Koual (author) / Céline Tomkiewicz (author) / Anne-Sophie Bats (author) / Jean-Philippe Antignac (author) / Xavier Coumoul (author) / Robert Barouki (author) / German Cano-Sancho (author)
2022
Article (Journal)
Electronic Resource
Unknown
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