Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Clin Cancer Res. 2012 Jun 1;18(11):3197-206. doi: 10.1158/1078-0432.CCR-12-0056. Epub 2012 Apr 5.
This study assesses the ability of multidrug resistance (MDR)-associated gene expression patterns to predict survival in patients with newly diagnosed carcinoma of the ovary. The scope of this research differs substantially from that of previous reports, as a very large set of genes was evaluated whose expression has been shown to affect response to chemotherapy.
We applied a customized TaqMan low density array, a highly sensitive and specific assay, to study the expression profiles of 380 MDR-linked genes in 80 tumor specimens collected at initial surgery to debulk primary serous carcinoma. The RNA expression profiles of these drug resistance genes were correlated with clinical outcomes.
Leave-one-out cross-validation was used to estimate the ability of MDR gene expression to predict survival. Although gene expression alone does not predict overall survival (OS; P = 0.06), four covariates (age, stage, CA125 level, and surgical debulking) do (P = 0.03). When gene expression was added to the covariates, we found an 11-gene signature that provides a major improvement in OS prediction (log-rank statistic P < 0.003). The predictive power of this 11-gene signature was confirmed by dividing high- and low-risk patient groups, as defined by their clinical covariates, into four specific risk groups on the basis of expression levels.
This study reveals an 11-gene signature that allows a more precise prognosis for patients with serous cancer of the ovary treated with carboplatin- and paclitaxel-based therapy. These 11 new targets offer opportunities for new therapies to improve clinical outcome in ovarian cancer.
本研究评估多药耐药（MDR）相关基因表达模式预测新诊断卵巢癌患者生存能力的能力。本研究的范围与之前的报告有很大不同，因为评估了非常大量的基因，其表达已被证明影响化疗反应。
我们应用了定制的 TaqMan 低密度阵列，一种高度敏感和特异的检测方法，来研究 80 个初始手术采集的肿瘤标本中 380 个与 MDR 相关的基因的表达谱，以减少原发性浆液性癌的原发性肿瘤。这些药物抗性基因的 RNA 表达谱与临床结果相关。
采用留一法交叉验证来估计 MDR 基因表达预测生存的能力。尽管基因表达本身不能预测总生存期（OS；P = 0.06），但四个协变量（年龄、分期、CA125 水平和手术减瘤）可以预测（P = 0.03）。当基因表达被添加到协变量中时，我们发现了一个 11 个基因的特征，该特征可显著改善 OS 预测（对数秩统计 P < 0.003）。该 11 个基因特征的预测能力通过将高风险和低风险患者组（根据其临床协变量定义）根据表达水平分为四个特定的风险组来得到确认。
本研究揭示了一个 11 个基因的特征，可对接受卡铂和紫杉醇为基础的治疗的浆液性卵巢癌患者进行更精确的预后。这 11 个新靶标为改善卵巢癌的临床结果提供了新的治疗机会。
