Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study
Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study
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DOI：
10.1016/s1470-2045(16)30108-5
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发表时间：
2016-08-01
期刊：
影响因子：
51.1
通讯作者：
Mezzanzanica, Delia
中科院分区：
文献类型：
--
作者：
Bagnoli, Marina;Canevari, Silvana;Mezzanzanica, Delia
背景 在大多数上皮性卵巢癌患者的治疗中，复发或进展的风险仍然很高，分子预测因子的开发可能是按风险对患者进行分层的宝贵工具。我们的目标是开发一种基于 microRNA (miRNA) 的分子分类器，可以预测上皮性卵巢癌患者的进展或复发风险。方法我们分析了诊断时收集的三组样本中的 miRNA 表达谱。我们使用来自意大利多中心卵巢癌试验（队列 OC179）的 179 个样本来开发模型，并使用来自两个癌症中心（队列 OC263）的 263 个样本和来自癌症基因组图谱上皮性卵巢癌系列（队列 OC452）的 452 个样本来验证模型。主要临床终点是无进展生存期，我们对 OC179 的 miRNA 表达谱采用半监督预测方法，以识别预测进展风险的 miRNA。我们使用 Cox 回归模型进行多变量分析来评估该模型的独立预后作用。结果我们确定了 35 个预测进展或复发风险的 miRNA，并使用它们创建了一个预后模型，即基于 35-miRNA 的卵巢癌复发或进展风险预测因子 (MiROvaR)。 MiROvaR 能够将 OC179 患者分为高风险组（89 名患者；中位无进展生存期 18 个月 [95% CI 15-22]）和低风险组（90 名患者；中位无进展生存期 38 个月 [24-不可估计]；风险比 [HR] 1.85 [1.29-2.64]，p=0.00082）。 MiROvaR 是两个验证组中进展的显着预测因子（OC263 HR 3.16，95% CI 2.33-4.29，p
Background Risk of relapse or progression remains high in the treatment of most patients with epithelial ovarian cancer, and development of a molecular predictor could be a valuable tool for stratification of patients by risk. We aimed to develop a microRNA (miRNA)-based molecular classifier that can predict risk of progression or relapse in patients with epithelial ovarian cancer.Methods We analysed miRNA expression profiles in three cohorts of samples collected at diagnosis. We used 179 samples from a Multicenter Italian Trial in Ovarian cancer trial (cohort OC179) to develop the model and 263 samples from two cancer centres (cohort OC263) and 452 samples from The Cancer Genome Atlas epithelial ovarian cancer series (cohort OC452) to validate the model. The primary clinical endpoint was progression-free survival, and we adapted a semi-supervised prediction method to the miRNA expression profile of OC179 to identify miRNAs that predict risk of progression. We assessed the independent prognostic role of the model using multivariable analysis with a Cox regression model.Findings We identified 35 miRNAs that predicted risk of progression or relapse and used them to create a prognostic model, the 35-miRNA-based predictor of Risk of Ovarian Cancer Relapse or progression (MiROvaR). MiROvaR was able to classify patients in OC179 into a high-risk group (89 patients; median progression-free survival 18 months [95% CI 15-22]) and a low-risk group (90 patients; median progression-free survival 38 months [24-not estimable]; hazard ratio [HR] 1.85 [1.29-2.64], p=0.00082). MiROvaR was a significant predictor of progression in the two validation sets (OC263 HR 3.16, 95% CI 2.33-4.29, p