Value of pre-treatment biomarkers in prediction of response to neoadjuvant endocrine therapy for hormone receptor-positive postmenopausal breast cancer

治疗前生物标志物在预测激素受体阳性绝经后乳腺癌新辅助内分泌治疗反应中的价值

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Abstract

OBJECTIVE: To determine the predictive ability of biomarkers for responses to neoadjuvant endocrine therapy (NET) in postmenopausal breast cancer. METHODS: Consecutive 160 postmenopausal women with T1-3N0-1M0 hormone receptor (HR)-positive invasive breast cancer were treated with anastrozole for 16 weeks before surgery. New slides of tumor specimens taken before and after treatment were conducted centrally for biomarker analysis and classified using the Applied Imaging Ariol MB-8 system. The pathological response was evaluated using the Miller & Payne classification. The cell cycle response was classified according to the change in the Ki67 index after treatment. Multivariable logistic regression analysis was used to calculate the combined index of the biomarkers. Receiver operating characteristic (ROC) curves were used to determine whether parameters may predict response. RESULTS: The correlation between the pathological and cell cycle responses was low (Spearman correlation coefficient =0.241, P<0.001; Kappa value =0.119, P=0.032). The cell cycle response was significantly associated with pre-treatment estrogen receptor (ER) status (P=0.001), progesterone receptor (PgR) status (P<0.001), human epidermal growth factor receptor 2 (Her-2) status (P=0.050) and the Ki67 index (P<0.001), but the pathological response was not correlated with these factors. Pre-treatment ER levels [area under the curve (AUC) =0.634, 95% confidence interval (95% CI), 0.534-0.735, P=0.008] and combined index of pre-treatment ER and PgR levels (AUC =0.684, 95% CI, 0.591-0.776, P<0.001) could not predict the cell cycle response, but combined index including per-treatment ER/PR/Her-2/Ki67 expression levels could (AUC =0.830, 95% CI, 0.759-0.902, P<0.001). CONCLUSIONS: The combined use of pre-treatment ER/PgR/Her-2/Ki67 expression levels, instead of HR expression levels, may predict the cell cycle response to NET.

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