Molecular Therapies Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Functional Genomics, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Lancet Oncol. 2016 Aug;17(8):1137-1146. doi: 10.1016/S1470-2045(16)30108-5. Epub 2016 Jul 9.
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.
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.
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<0·0001; OC452 HR 1·39, 95% CI 1·11-1·74, p=0·0047) and maintained its independent prognostic effect when adjusted for relevant clinical covariates using multivariable analyses (OC179: adjusted HR 1·48, 95% CI 1·03-2·13, p=0·036; OC263: adjusted HR 3·09 [2·24-4·28], p<0·0001; and OC452: HR 1·41 [1·11-1·79], p=0·0047).
MiROvaR is a potential predictor of epithelial ovarian cancer progression and has prognostic value independent of relevant clinical covariates. MiROvaR warrants further investigation for the development of a clinical-grade prognostic assay.
AIRC and CARIPLO Foundation.
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，因此开发一种分子预测因子可以成为通过风险分层患者的有价值的工具。我们旨在开发一种基于 microRNA（miRNA）的分子分类器，该分类器可以预测上皮性卵巢癌患者的进展或复发风险。
我们分析了三个诊断样本集的 miRNA 表达谱。我们使用来自意大利多中心卵巢癌试验（OC179 队列）的 179 个样本来开发模型，使用来自两个癌症中心的 263 个样本（OC263 队列）和来自癌症基因组图谱上皮性卵巢癌系列的 452 个样本（OC452 队列）来验证模型。主要临床终点是无进展生存期，我们采用半监督预测方法对 OC179 的 miRNA 表达谱进行分析，以确定预测进展风险的 miRNA。我们使用 Cox 回归模型的多变量分析来评估模型的独立预后作用。
我们确定了 35 个可以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，即卵巢癌复发或进展的 35-microRNA 预测因子（MiROvaR）。MiROvaR 能够将 OC179 中的患者分为高风险组（89 例；中位无进展生存期 18 个月[95%CI 15-22]）和低风险组（90 例；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 是两个验证集（OC263 HR 3.16，95%CI 2.33-4.29，p<0.0001；OC452 HR 1.39，95%CI 1.11-1.74，p=0.0047）中进展的重要预测因子，并且在使用多变量分析调整相关临床协变量时，它仍然保持独立的预后作用（OC179：调整 HR 1.48，95%CI 1.03-2.13，p=0.036；OC263：调整 HR 3.09[2.24-4.28]，p<0.0001；OC452：HR 1.41[1.11-1.79]，p=0.0047）。
MiROvaR 是上皮性卵巢癌进展的潜在预测因子，具有独立于相关临床协变量的预后价值。MiROvaR 值得进一步研究，以开发临床级别的预后检测。
AIRC 和 CARIPLO 基金会。
