title: The immunocytochemical detection of axillary micrometastases in breast cancer.
abstract: The histological detection of tumour metastases in axillary lymph nodes from cases of breast carcinoma is of major prognostic significance, but may be difficult when metastases are of microscopic size. We have therefore investigated whether immunohistological techniques can increase the accuracy of metastasis detection in axillary lymph nodes. Forty-five cases of breast carcinoma were studied, in all of whom the axillary lymph nodes had been reported as free of metastases. Paraffin sections from these cases were stained by immunoenzymatic techniques, using monoclonal antibodies directed against human milk fat globule membrane antigen ("anti-EMA") and against epithelial intermediate filaments ("anti-keratin"). In 4/12 cases of lobular carcinoma and in 3/33 cases of ductal carcinoma, previously unsuspected micrometastases were revealed by immunohistological staining, representing an overall increase in detection rate of 15% (and of 33% for the lobular carcinoma cases). In addition to this group of 45 histologically "negative" biopsies, 12 samples were studied in which only a proportion of the nodes had been reported as containing tumour. In 5 of these cases immunostaining revealed previously undetected metastases. These findings suggest that immunohistological analysis may have a routine role to play in the staging of breast carcinoma. It is noted that the 15% increase in diagnostic accuracy achieved in the present study is comparable to the proportion of breast carcinoma patients in whom disseminated disease develops despite their axillary lymph nodes being reported as tumour-free at the time of surgery.
mesh_terms: D000469:Alkaline Phosphatase; D001365:Axilla; D001943:Breast Neoplasms / Q000473:pathology*; D005188:False Negative Reactions; D005260:Female; D006801:Humans; D007124:Immunoenzyme Techniques; D008207:Lymphatic Metastasis / Q000175:diagnosis*; D009367:Neoplasm Staging
chemical_list: D000469:Alkaline Phosphatase