Background: Human breast cancer is classified by gene expression profile into subtypes consisting of two hormone (oestrogen and/or progesterone) receptor-positive types (luminal-like A and luminal-like B) and three hormone receptor-negative types [human epidermal growth factor receptor 2-expressing, basal-like, and unclassified ("normal-like")]. Immunohistochemical surrogate panels are also proposed to potentially identify the molecular-based groups. The present study aimed to apply an immunohistochemical panel (anti-ER, -PR, -ERB-B2, -CK 5/6 and -CK14) in a series of canine malignant mammary tumours to verify the molecular-based classification, its correlation with invasion and grade, and its use as a prognostic aid in veterinary practice.Results: Thirty-five tumours with luminal pattern (ER+ and PR+) were subgrouped into 13 A type and 22 B type, if ERB-B2 positive or negative. Most luminal-like A and basal-like tumours were grade 1 carcinomas, while the percentage of luminal B tumours was higher in grades 2 and 3 (Pearson Chi-square P = 0.009). No difference in the percentage of molecular subtypes was found between simple and complex/mixed carcinomas (Pearson Chi-square P = 0.47). No significant results were obtained by survival analysis, even if basal-like tumours had a more favourable prognosis than luminal-like lesions.Conclusion: The panel of antibodies identified only three tumour groups (luminal-like A and B, and basal-like) in the dog. Even though canine mammary tumours may be a model of human breast cancer, the existence of the same carcinoma molecular subtypes in women awaits confirmation. Canine mammary carcinomas show high molecular heterogeneity, which would benefit from a classification based on molecular differences. Stage and grade showed independent associations with survival in the multivariate regression, while molecular subtype grouping and histological type did not show associations. This suggests that caution should be used when applying this classification to the dog, in which invasion and grade supply the most important prognostic information.
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