首页> 中文期刊>临床与实验病理学杂志 >乳腺癌新辅助化疗前后病理组织学及分子指标变化

乳腺癌新辅助化疗前后病理组织学及分子指标变化

     

摘要

目的 观察乳腺癌新辅助化疗(neoadjuvant chemotherapy,NCT)前后病理形态学改变和ER、PR、HER-2及Ki-67等分子指标表达的变化,分析化疗效果与乳腺癌临床病理特征的关系.方法 收集93例经NCT的浸润性乳腺癌进行回顾性分析,依据Miller-Payne(MP)法分级系统对化疗效果进行病理评价.结果 乳腺癌NCT后肿瘤细胞、间质以及腋窝淋巴结均出现不同程度形态学改变.患者年龄(Z=-1.993,P=0.046)和肿瘤组织学分级(χ2 =7.261,P=0.027)以及分子分型(χ2 =8.289,P=0.040)与NCT效果有关,而肿瘤直径(Z=-1.091,P =0.275)和淋巴结状态(Z =-1.107,P= 0.268)与NCT效果无关.治疗前后,ER、PR、HER-2和Ki-67可出现不同程度变化,表达一致率依次为81.0%、72.2%、83.5%和55.7%,各组间差异无统计学意义(χ2 =0.428,P=0.934).结论 NCT对肿瘤细胞、间质和淋巴结组织学形态均有明显影响,分子指标也可出现一定改变.客观评价化疗后病理形态学和分子指标变化,对临床预后判断及个体化治疗具有积极意义.%Purpose To observe the changes of histopathology and expression levels of ER, PR, HER-2 and Ki-67 in breast cancer after neoadjuvant chemotherapy (NTC), and to evaluate the relationship between the curative effect and clinico-pathological characteristics of breast cancer. Methods 93 ca-ses of invasive breast cancer with NTC were collected and retro-spectively analyzed. Pathologic evaluation of chemotherapeutic effect were evaluated by Miller-Payne (MP) grading system. Results Tumor cells, tumor stroma and lymph nodes status presented different histopathological changes after NTC. There were significant relationship between curative effect and patients age (Z=-1.993, P=0.046 ), histological grade (χ2=7.261, P=0.027), molecular subtypes (χ2=8.289, P=0.040), while it had no statistical relationship between curative effect and tumor size (Z=-1.091, P=0.275) and lymph node status (Z=-1.107, P = 0.268). Expression of ER, PR, HER-2 and Ki-67 showed different degrees of change before and after NTC. The concordance rates of ER, PR, HER-2 and Ki-67 were 81.0%, 72.2%, 83.5% and 55.7%, respective-ly. And there was no significant difference in expression of these four molecular indicators before and after NTC (χ2 =0.428, P=0.934). Conclusion The histomorphology of tumor cell, tumor stroma and lymph node status can be influenced by NTC. Objective evaluation of the changes of histopathology and molecular indicators after NTC may valuable in predicting clinical prognosis and guiding individual treatment of breast cancer.

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