Mutant p53 expression and DNA analysis in human breast cancer comparison with conventional clinicopathological parameters
Rosanelli, G.P.; Steindorfer, P.; Wirnsberger, G.H.; Klimpfinger, M.; Ratschek, M.; Puerstner, P.; Auner, H.; Berhold, A.
Anticancer Research 15(2): 581-586
1995
ISSN/ISBN: 0250-7005 PMID: 7763041 Document Number: 443123
Scientific research evaluates the prognostic importance of 53 expression and DNA flow cytometry controversially. To evaluate the prognostic relevance of mutant p53 protein overexpression and DNA flow cytometry in primary breast cancer we correlated these factors with the common prognostic parameters such as tumor size, lymph node status, grading, menopausal status and receptor status. Human breast cancer specimens from 180 previously untreated patients were collected and deep frozen. On each specimen DNA-analysis by Geohde's technique (Partec PAS II) and immunohistochemical evaluation of mutant p53 protein (PAb 1801 and 240, Novocastra Lab., Great Britain) were performed. Besides TNM- and histological classification, estrogen (ER)- and progesterone (PgR) receptor content was recorded. Overexpression of mutant p53 protein was found in 34 (19%) of all specimens. All these 34 tumors were aneuploid (p = 0.007), 86% of them were receptor negative (p = 0.0001), 79% had a high tumor grade (p 0. 0001), 73% a high S-phase-fraction (SPF) (p = 0.045) and 53% were premenopausal (p = 0.0001). Tumor size and node status did not correlate significantly with p53 expression. 27 (15%) out of 180 carcinomas were diploid. There was a significant correlation between ploidy and the tumor grade (p = 0.003) and SPF (p = 0.0001), but no correlation between ploidy and tumor size (p = 0.21), node status (p = 0.33) or receptor status (p = 0.18). A low SPF was predominantly found in tumors less than 2 cm in diameter (p = 0.0001); no significant correlation was found between SPF, receptor status, tumor grade, node and menopausal status. Mutant p53 protein expression and DNA analysis in combination with common prognostic parameters might help to detect prognostically unfavourable subgroups of breast cancer patients.