Multivariate analysis of DNA ploidy, p53, c-erbB-2 proteins, EGFR, and steroid hormone receptors for prediction of poor short term prognosis in breast cancer.

BACKGROUND: Several molecular-genetic alterations in breast cancer, including aneuploidy, aberrant expression of p53, c-erbB-2 and EGFR, have been associated with poor prognosis in breast cancer patients particularly those who are lymph node negative. To determine the importance of molecular-genetic factors relative to more traditional surgical-pathologic prognostic factors, multivariate analysis was performed on lymph node positive breast cancer cases.

METHODS: One hundred fresh samples of primary breast carcinoma were studied with flow cytometry for DNA ploidy. On the same specimens steroid hormone receptors (ER and PR) were measured in the cytosol fraction using Abbott ELIZA assays, c-erbB-2 and EGFR were determined in the membrane fraction and mutant p53 protein in the nuclear fraction by Oncogene Science ELISA procedures. In addition, information regarding surgical-pathologic features of the tumor was obtained. Multivariate analysis using Cox's proportional hazards model was done to identify variables predictive of poor prognosis.

RESULTS: Using univariate analysis, tumor size, lymph node number, p53, c-erbB-2 were predictive of poor short term prognosis. By multivariate analysis, only c-erbB-2 (P = 0.001) and p53 (P = 0.05) were significant. Subsgroup analysis by nodal status yields a significant association of c-erbB-2 (P = 0.001) and p53 (P = 0.04) with lymph node positive breast cancer.

CONCLUSIONS: Among molecular-genetic prognostic factors, c-erbB-2 was the most strongly predictive of poor short term prognosis followed by p53 in lymph node positive breast cancer.