Low Stromal Mast Cell Density in Canine Mammary Gland Tumours Predicts a Poor Prognosis.
J Comp Pathol
; 175: 29-38, 2020 Feb.
Article
in En
| MEDLINE
| ID: mdl-32138840
Tumour histological classification and grade are frequently used to predict the prognosis of canine mammary gland tumours. While these techniques provide some information about tumour behaviour, it is currently difficult to predict which tumours will metastasize. Mast cell density has been shown to predict metastasis in human breast cancer. The present study investigated whether the average mast cell density in 10 high-power (×400) microscopical fields (10 HPFs), evaluated by toluidine blue staining, similarly predicted the behaviour of canine mammary gland tumours. Mast cell density was evaluated in 53 canine mammary neoplasms for which the clinical outcome was known. Stromal mast cell density in malignant tumours that had subsequently developed radiographical evidence of metastasis (n = 21) was significantly lower (P <0.001) than in malignant tumours that did not show evidence of metastases (n = 20) or in benign tumours (n = 12). The density of stromal mast cells that best predicted the disease outcome was ≤10/10 HPFs. Eighty-one percent of malignant tumours with ≤10 stromal mast cells/10 HPFs subsequently metastasized, while only 9.5% of malignant tumours with >10 stromal mast cells/10 HPFs developed metastases. There was a positive correlation between stromal mast cell density and survival time (rs = 0.50, P <0.001). These findings suggest that assessing stromal mast cell density using toluidine blue staining may represent an easy to perform and cost-effective histopathological measure that, in conjunction with classification and grading, could better predict the behaviour of canine mammary neoplasms.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Mammary Neoplasms, Animal
/
Dog Diseases
/
Mast Cells
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Animals
Language:
En
Journal:
J Comp Pathol
Year:
2020
Document type:
Article
Country of publication:
United kingdom