Overexpression of P53 is prognostic for aromatase inhibitor resistance in early stage postmenopausal patients with ER-positive breast cancer / 中国癌症杂志
China Oncology
; (12): 354-360, 2014.
Article
em Zh
| WPRIM
| ID: wpr-447512
Biblioteca responsável:
WPRO
ABSTRACT
Background and purpose:Tumor suppressor gene P53 has long been studied in tumors, including breast cancer. More studies focused on the relationship between P53 and prognosis of breast cancer and found that P53 overexpression suggested a bad prognosis. However, the effect of P53 on early stage postmenopausal patients with ER-positive breast cancer has not been clariifed yet. This study was to investigate the role of P53 plays in aromatase inhibitor (AI) resistance among early stage postmenopausal patients with ER-positive breast cancer patients. Methods:A total number of 293 operable breast cancer patients who received surgical treatment during Jul. 2000 to Jul. 2006 in Fudan University Shanghai Cancer Center were enrolled into this study. All patients received AI treatment. The SPSS 12.0 software was used to estimate the survival rate. Univariate and multivariate analysis were also performed via above software. Results:The median follow-up time is 72 months (6-140 months). The 5 year disease free survival (DFS) of P53 positive and negative were 78%and 89%. The results showed that P53 overexpression (HR=1.729, 95%CI:1.038-2.880, P=0.035), pathological stage (HR=2.270, 95%CI:1.399-3.681, P=0.001);histological grade (HR=2.328, 95%CI:1.312-4.133, P=0.004); age (HR=1.988, 95%CI:1.511-2.617, P<0.005) were still the independent risk factors of recurrence and metastasis in breast cancer patients treated with AI. Conclusion:P53 overexpression correlated strongly with AI resistance in early stage postmenopausal patients with ER-positive breast cancer patients who were treated with AI and conifrmed the relevance of previously described prognostic factors. It is reasonable to take P53 expression into account when we evaluate the risk of breast cancer patients and decide the anti-cancer treatment strategy.
Texto completo:
1
Base de dados:
WPRIM
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
Zh
Revista:
China Oncology
Ano de publicação:
2014
Tipo de documento:
Article