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Updated: Apr 17, 2026

Changes in Mammary Gland Morphology and Breast Cancer Risk in Rats
Published on: October 16, 2010
Pollutants in pet dogs: a model for environmental links to breast cancer
Sabine Sévère1, Philippe Marchand1, Ingrid Guiffard1
1LUNAM University, Nantes-Atlantic College of Veterinary Medicine and Food Sciences (Oniris), USC 1329 INRA Laboratoire d'Etude des résidus et Contaminants dans les Aliments (LABERCA), Site de la Chantrerie - CS50707, 44307 Nantes cedex 3, France.
Purpose:
Invasive breast carcinoma is the most common cancer in women as in non-ovariectomised pet dogs, which are already identified as a valuable spontaneous preclinical model for that disease. Geographical and time trends suggest that environmental factors may play an important role in the etiology and pathogenesis of breast cancer. Persistent organic pollutants (POPs) fit perfectly with these trends and are known to interact with hormonal receptors implicated in breast cancer subtyping. The aim of this innovating study was to evaluate the interest of the companion dog model in assessing chemical exposure and breast cancer associations, in order to identify common etiological features with the human disease in a context of comparative oncology.
Methods:
We monitored a hundred of molecules belonging to a large panel of POPs (dioxins, dioxin-like and non dioxin-like polychlorobisphenyls, organochlorine pesticides, brominated flame retardants, perfluorinated alkylated substances) in companion dogs diagnosed for mammary adenocarcinoma (n = 54) and non cancer controls (n = 47).
Results:
All targeted chemical families were able to be detected in canine samples. We identified pollutants associated with mammary cancer belonging to the dioxin like-PCB family (notably PCB-118, -156, -105, -114) that were already pointed out in human epidemiological studies on breast cancer, and that fit with the fundamental role of the Aryl Hydrocarbon Receptor in the promotion of breast cancer.
Conclusions:
Similarities observed in the spontaneous dog model are very helpful to progress in interpretation of human breast cancer-environment relationships. This study provides a new insight focusing on this discrete but recurrent signature.
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