Park Sarah, Shimizu Chikako, Shimoyama Tatsu, Takeda Masayuki, Ando Masashi, Kohno Tsutomu, Katsumata Noriyuki, Kang Yoon-Koo, Nishio Kazuto, Fujiwara Yasuhiro
Shien Lab, National Cancer Center Hospital, Tokyo, Japan.
Breast Cancer Res Treat. 2006 Sep;99(1):9-17. doi: 10.1007/s10549-006-9175-2. Epub 2006 Jun 5.
Drug resistance is a major obstacle to the successful chemotherapy. Several ATP-binding cassette (ABC) transporters including ABCB1, ABCC1 and ABCG2 have been known to be important mediators of chemoresistance. Using oligonucleotide microarrays (HG-U133 Plus 2.0; Affymetrix), we analyzed the ABC transporter gene expression profiles in breast cancer patients who underwent sequential weekly paclitaxel/FEC (5-fluorouracil, epirubicin and cyclophosphamide) neoadjuvant chemotherapy. We compared the ABC transporter expression profile between two classes of pretreatment tumor samples divided by the patients' pathological response to neoadjuvant chemotherapy (residual disease [RD] versus pathologic complete response [pCR]) ABCB3, ABCC7 and ABCF2 showed significantly high expression in the pCR. Several ABC transporters including ABCC5, ABCA12, ABCA1 ABCC13, ABCB6 and ABCC11 showed significantly increased expression in the RD (p<0.05). We evaluated the feasibility of developing a multigene predictor model of pathologic response to neoadjuvant chemotherapy using gene expression profiles of ABC transporters. The prediction error was evaluated by leave-one-out cross-validation (LOOCV). A multigene predictor model with the ABC transporters differentially expressed between the two classes (p<or=0.003) showed an average 92.8% of predictive accuracy (95% CI, 88.0-97.4%) with a 93.2% (95% CI, 85.2-100%) positive predictive value for pCR, a 93.6% (95% CI, 87.8-99.4%) negative predictive value, a sensitivity of 88.1%(95% CI, 76.8-99.4%), and a specificity of 95.9% (91.1% CI, 87.8-100%). Our results suggest that several ABC transporters in human breast cancer cells may affect the clinical response to neoadjuvant chemotherapy, and transcriptional profiling of these genes may be useful to predict the pathologic response to sequential weekly paclitaxel/FEC in breast cancer patients.
耐药性是化疗成功的主要障碍。已知包括ABCB1、ABCC1和ABCG2在内的几种ATP结合盒(ABC)转运蛋白是化疗耐药的重要介质。我们使用寡核苷酸微阵列(HG-U133 Plus 2.0;Affymetrix)分析了接受每周一次紫杉醇/FEC(5-氟尿嘧啶、表柔比星和环磷酰胺)新辅助化疗的乳腺癌患者的ABC转运蛋白基因表达谱。我们比较了根据患者对新辅助化疗的病理反应(残留疾病[RD]与病理完全缓解[pCR])划分的两类治疗前肿瘤样本之间的ABC转运蛋白表达谱。ABCB3、ABCC7和ABCF2在pCR中显示出显著高表达。包括ABCC5、ABCA12、ABCA1、ABCC13、ABCB6和ABCC11在内的几种ABC转运蛋白在RD中显示出显著增加的表达(p<0.05)。我们评估了使用ABC转运蛋白的基因表达谱建立新辅助化疗病理反应多基因预测模型的可行性。通过留一法交叉验证(LOOCV)评估预测误差。一个具有在两类之间差异表达的ABC转运蛋白的多基因预测模型(p≤0.003)显示平均预测准确率为92.8%(95%CI,88.0 - 97.4%),pCR的阳性预测值为93.2%(95%CI,85.2 - 100%),阴性预测值为93.6%(95%CI,87.8 - 99.4%),敏感性为88.1%(95%CI,76.8 - 99.4%),特异性为95.9%(91.1%CI,87.8 - 100%)。我们的结果表明,人乳腺癌细胞中的几种ABC转运蛋白可能影响对新辅助化疗的临床反应,并且这些基因的转录谱分析可能有助于预测乳腺癌患者对每周一次紫杉醇/FEC序贯治疗的病理反应。