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对乳腺肿瘤细胞系进行基因表达谱分析,以预测对微管稳定剂的治疗反应。

Gene expression profiling of breast tumor cell lines to predict for therapeutic response to microtubule-stabilizing agents.

机构信息

Département de Pharmacologie Moléculaire and U891 INSERM, Centre de Recherche En Cancérologie de Marseille, Institut Paoli-Calmettes, Marseille, France.

出版信息

Breast Cancer Res Treat. 2012 Apr;132(3):1035-47. doi: 10.1007/s10549-011-1687-8. Epub 2011 Jul 27.

Abstract

Microtubule-targeting agents, including taxanes (Tax) and ixabepilone (Ixa), are important components of modern breast cancer chemotherapy regimens, but no molecular parameter is currently available that can predict for their efficiency. We sought to develop pharmacogenomic predictors of Tax- and Ixa-response from a large panel of human breast tumor cell lines (BTCL), then to evaluate their performance in clinical samples. Thirty-two BTCL, representative of the molecular diversity of breast cancers (BC), were treated in vitro with Tax (paclitaxel (Pac), docetaxel (Doc)), and ixabepilone (Ixa), then classified as drug-sensitive or resistant according to their 50% inhibitory concentrations (IC50s). Baseline gene expression data were obtained using Affymetrix U133 Plus 2.0 human oligonucleotide microarrays. Gene expression set (GES) predictors of response to taxanes were derived, then tested for validation internally and in publicly available gene expression datasets. In vitro IC50s of Pac and Doc were almost identical, whereas some Tax-resistant BTCL retained sensitivity to Ixa. GES predictors for Tax-sensitivity (333 genes) and Ixa-sensitivity (79 genes) were defined. They displayed a limited number of overlapping genes. Both were validated by leave-n-out cross-validation (n = 4; for overall accuracy (OA), P = 0.028 for Tax, and P = 0.0005 for Ixa). The GES predictor of Tax-sensitivity was tested on publicly available external datasets and significantly predicted Pac-sensitivity in 16 BTCL (P = 0.04 for OA), and pathological complete response to Pac-based neoadjuvant chemotherapy in BC patients (P = 0.0045 for OA). Applying Tax and Ixa-GES to a dataset of clinically annotated early BC patients identified subsets of tumors with potentially distinct phenotypes of drug sensitivity: predicted Ixa-sensitive/Tax-resistant BC were significantly (P < 0.05, Fischer's exact test) more frequently ER/PR-positive, Ki67-negative, and luminal subtype than predicted Ixa-resistant/Tax-sensitive BC. Genomic predictors for Tax- and Ixa-sensitivity can be derived from BTCL and may be helpful for better selecting cytotoxic treatment in BC patients.

摘要

微管靶向药物,包括紫杉醇类(Tax)和伊沙匹隆(Ixa),是现代乳腺癌化疗方案的重要组成部分,但目前尚无可用的分子参数来预测其疗效。我们试图从大量的人乳腺癌细胞系(BTCL)中开发出预测 Tax 和 Ixa 反应的药物基因组学预测因子,然后在临床样本中评估它们的性能。32 种 BTCL 代表了乳腺癌(BC)的分子多样性,在体外用 Tax(紫杉醇(Pac)、多西紫杉醇(Doc))和伊沙匹隆(Ixa)处理,然后根据它们的 50%抑制浓度(IC50)将其分类为敏感或耐药。使用 Affymetrix U133 Plus 2.0 人类寡核苷酸微阵列获得基线基因表达数据。从这些数据中提取出对紫杉醇类药物反应的基因表达集(GES)预测因子,然后在内部和公开的基因表达数据集进行验证。Pac 和 Doc 的体外 IC50 几乎相同,而一些 Tax 耐药的 BTCL 仍对 Ixa 敏感。确定了 Tax 敏感性(333 个基因)和 Ixa 敏感性(79 个基因)的 GES 预测因子。它们显示出有限数量的重叠基因。这两种方法都通过留一法交叉验证(n = 4;对于总准确率(OA),Tax 的 P 值为 0.028,Ixa 的 P 值为 0.0005)进行了验证。在公开的外部数据集上测试了 Tax 敏感性的 GES 预测因子,该预测因子在 16 个 BTCL 中显著预测了 Pac 的敏感性(OA 的 P = 0.04),并预测了 BC 患者基于 Pac 的新辅助化疗的病理完全缓解(OA 的 P = 0.0045)。将 Tax 和 Ixa-GES 应用于临床注释的早期 BC 患者数据集,确定了具有潜在不同药物敏感性表型的肿瘤亚组:预测的 Ixa 敏感/Tax 耐药 BC 显著(P < 0.05,Fisher 精确检验)ER/PR 阳性、Ki67 阴性和管腔亚型的频率更高,而预测的 Ixa 耐药/Tax 敏感 BC 则较少。Tax 和 Ixa 敏感性的基因组预测因子可以从 BTCL 中得出,这可能有助于更好地选择 BC 患者的细胞毒性治疗。

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