Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, BO Box 301439, Houston, TX 77030-1439, USA.
Breast Cancer Res Treat. 2010 Jun;121(2):301-9. doi: 10.1007/s10549-009-0445-7. Epub 2009 Jul 15.
The goal of this study was to develop pharmacogenomic predictors in response to standard chemotherapy drugs in breast cancer cell lines and test their predictive value in patients who received treatment with the same drugs. Nineteen human breast cancer cell lines were tested for sensitivity to paclitaxel (T), 5-fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) in vitro. Baseline gene expression data were obtained for each cell line with Affymetrix U133A gene chips, and multigene predictors of sensitivity were derived for each drug separately. These predictors were applied individually and in combination to human gene expression data generated with the same Affymetrix platform from fine needle aspiration specimens of 133 stage I-III breast cancers. Tumor samples were obtained at baseline, and each patient received 6 months of preoperative TFAC chemotherapy followed by surgery. Cell line-derived prediction results were correlated with the observed pathologic response to chemotherapy. Statistically robust differentially expressed genes between sensitive and resistant cells could only be found for paclitaxel. False discovery rates associated with the informative genes were high for all other drugs. For each drug, the top 100 differentially expressed genes were combined into a drug-specific response predictor. When these cell line-based predictors were applied to patient data, there was no significant correlation between observed response and predicted response either for individual drug predictors or combined predictions. Cell line-derived predictors of response to four commonly used chemotherapy drugs did not predict response accurately in patients.
本研究的目的是开发针对乳腺癌细胞系中标准化疗药物的药物基因组预测因子,并在接受相同药物治疗的患者中测试其预测价值。对 19 个人类乳腺癌细胞系进行了体外紫杉醇(T)、5-氟尿嘧啶(F)、阿霉素(A)和环磷酰胺(C)敏感性测试。用 Affymetrix U133A 基因芯片获得每个细胞系的基线基因表达数据,并分别为每种药物推导多基因敏感性预测因子。这些预测因子分别和组合应用于从 133 例 I-III 期乳腺癌的细针抽吸标本中用相同的 Affymetrix 平台生成的人类基因表达数据。在基线时获得肿瘤样本,每个患者接受 6 个月的术前 TFAC 化疗,然后进行手术。细胞系衍生的预测结果与化疗的观察病理反应相关。仅在紫杉醇中发现了敏感和耐药细胞之间差异表达基因的统计学上稳健。对于所有其他药物,与信息基因相关的错误发现率都很高。对于每种药物,将前 100 个差异表达基因组合成一种特定药物的反应预测因子。当将这些基于细胞系的预测因子应用于患者数据时,无论是针对单个药物预测因子还是联合预测,观察到的反应与预测反应之间均无显著相关性。细胞系衍生的对四种常用化疗药物的反应预测因子并不能准确预测患者的反应。