[Clinical features and prognosis analysis of different breast cancer molecular subtypes].

Zhonghua zhong liu za zhi [Chinese journal of oncology]

PubMedID: 21575463

Yang Q, Chen J, Li HJ, Yu M, Tian CX, Lü Q. [Clinical features and prognosis analysis of different breast cancer molecular subtypes]. Zhonghua Zhong Liu Za Zhi. 2011;33(1):42-6.
OBJECTIVE
To investigate the clinical characteristics and prognosis of different breast cancer molecular subtypes.

METHODS
Clinicopathological and follow-up data of 1153 cases of operable breast cancer were analyzed retrospectively. Their molecular subtypes were categorized as luminal A, luminal B, Her-2 over-expressing and basal-like subtypes, based on detection of ER, PR, Her-2 expression. The correlation of prognosis of different molecular subtypes with age, tumor size, lymph node status and clinical staging was analyzed.

RESULTS
Among the 1153 cases, 791 cases (68.6%) were of luminal A subtype, 50 cases (4.3%) luminal B subtype, 53 cases (4.6%) Her-2(+)subtype, and 259 cases (22.5%) basal-like subtype. There were no statistically significant differences among different molecular subtypes regarding the age, tumor size, lymph node status, and clinical stage. 1006 cases had complete follow-up data and the analysis showed that distant metastasis of Her-2 over-expressing subtype was significantly higher than that in other subtypes (P = 0.005), but the differences of local recurrence rate in different molecular subtypes was not statistically significant (P > 0.05). Kaplan-Meier method was used to analyze the survival prognosis of different molecular subtypes, showing both DFS rate and OS rate of Her-2 over-expressing subtype were the lowest, with a statistically significant difference (Log rank test, P < 0.05). Univariate and multivariate analyses showed that molecular typing and lymph node status were independent prognostic factors affecting both DFS and OS.

CONCLUSIONS
Her-2 over-expressing subtype has the worst prognosis. Molecular subtypes may provide important information to predict the prognosis of breast cancer and might be an important basis for individualized treatment of breast cancer in future.