Prospective comparison of clinical and genomic multivariate predictors of response to neoadjuvant chemotherapy in breast cancer.
Prospective comparison of clinical and genomic multivariate predictors of response to neoadjuvant chemotherapy in breast cancer.
复制标题
DOI：
10.1158/1078-0432.ccr-09-2247
复制
发表时间：
2010-01-15
期刊：
影响因子：
--
通讯作者：
Pusztai L
中科院分区：
文献类型：
--
作者：
Lee JK;Coutant C;Kim YC;Qi Y;Theodorescu D;Symmans WF;Baggerly K;Rouzier R;Pusztai L
已经提出了几种不同的多变量预测模型，使用常规临床变量或多基因签名来预测乳腺癌联合化疗的病理完全反应。我们的目标是在一个独立的患者队列中比较四个概念上不同的预测因素的表现。在术前紫杉醇、5-FU、多柔比星和环磷酰胺联合化疗之前，对100例I-III期乳腺癌细针穿刺进行基因表达谱分析。病理反应与临床列线图、人类癌症衍生的基因组预测因子（DLDA 30）、基于细胞系的基因组预测因子（体外-COXEN）和优化的细胞系衍生（体内-COXEN）预测因子的预测结果相关。100个测试用例中没有一个用于开发这些预测因子。使用源自细胞系的4种单独药物敏感性预测的组合的体外COXEN不具有预测性，AUC：0.5（95%CI：0.41-0.59）。临床列线图（AUC：0.73，95%CI：0.65-0.80）和DLDA 30（AUC：0.73，95%CI [0.66-0.80]）基因组预测因子具有相似的性能。使用来自细胞系的信息基因但在单独的人类数据集上训练的体内-COXEN也显示出显著的预测值，AUC：0.67（95%CI：0.60-0.74）。这3个不同的预测得分彼此相关，在单变量分析中有显著性，但在多变量分析中无显著性。三个概念上不同的预测因子在该验证研究中表现相似，并且倾向于将相同的患者识别为应答者。仅依赖于来自细胞系的个体药物敏感性预测的复合物的基因组预测物没有显示出任何预测价值。
Several different multivariate prediction models using routine clinical variables or multi-gene signatures have been proposed to predict pathologic complete response to combination chemotherapy in breast cancer. Our goal was to compare the performance of four conceptually different predictors in an independent cohort of patients. Gene expression profiling was performed on fine needle aspirations of 100 stage I-III breast cancers prior to preoperative paclitaxel, 5-FU, doxorubicin and cyclophosphamide combination chemotherapy. Pathologic response was correlated with prediction results from a clinical nomogram, a human cancer-derived genomic predictor (DLDA30), a cell line-based genomic predictor (in vitro-COXEN), and an optimized cell line-derived (in vivo-COXEN) predictor. None of the 100 test cases were used in the development of these predictors. The in vitro-COXEN using a combination of 4 individual drug sensitivity predictions derived from cell lines was not predictive, AUC:0.5 (95%CI: 0.41-0.59). The clinical nomogram (AUC: 0.73, 95%CI: 0.65-0.80) and the DLDA30 (AUC: 0.73, 95%CI [0.66-0.80]) genomic predictor had similar performances. The in vivo-COXEN that used informative genes from cell lines but was trained on a separate human data set also showed significant predictive value, AUC: 0.67 (95%CI: 0.60-0.74). These 3 different prediction scores correlated with each other and were significant in univariate but not in multivariate analysis. Three conceptually different predictors performed similarly in this validation study and tended to identify the same patients as responders. A genomic predictor that relied solely on a composite of individual drug sensitivity predictions from cell lines did not show any predictive value.