Multivariate analysis of DNA ploidy, p53, c-erbB-2 proteins, EGFR, and steroid hormone receptors for 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 particularly in lymph node negative patients. To determine the importance of molecular-genetic factors relative to more traditional surgical-pathologic prognostic factors, a multivariate analysis was performed particularly in lymph node positive breast cancer cases.

METHODS

One hundred fresh samples of primary breast carcinoma have been studied with flow cytometry for DNA ploidy. On the same specimens steroid hormone receptors (ER and PR) were measured in cytosol fraction using Abbott ELIZA assays, c-erbB-2 and EGFR were determined in the tissue homogenate 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

With univariate analysis, tumor size, lymphnode number, p53, c-erbB-2 were predictive of poor short term prognosis. In the multivariate analysis, only c-erbB-2 (P = 0.001) and p53 (P = 0.05) were significant. Subgroup analysis by nodal status yielded 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.