Oncology Department, Weatherall Institute of Molecular Medicine, University of Oxford and Genomics Research, Wellcome Trust Centre for Human Genetics, Oxford, UK.
Cancer Res. 2011 Sep 1;71(17):5635-45. doi: 10.1158/0008-5472.CAN-11-0489. Epub 2011 Jul 7.
microRNA expression profiling plays an emerging role in cancer classification and identification of therapeutic strategies. In this study, we have evaluated the benefits of a joint microRNA-mRNA analysis in breast cancer. Matched mRNA and microRNA global expression profiling was conducted in a well-annotated cohort of 207 cases with complete 10-year follow-up. Penalized Cox regression including microRNA expression, mRNA expression, and clinical covariates was used to identify microRNAs associated with distant relapse-free survival (DRFS) that provide independent prognostic information, and are not simply surrogates of previously identified prognostic covariates. Penalized regression was chosen to prevent overfitting. Furthermore, microRNA-mRNA relationships were explored by global expression analysis, and exploited to validate results in several published cohorts (n = 592 with DRFS, n = 1,050 with recurrence-free survival). Four microRNAs were independently associated with DRFS in estrogen receptor (ER)-positive (3 novel and 1 known; miR-128a) and 6 in ER-negative (5 novel and 1 known; miR-210) cases. Of the latter, miR-342, -27b, and -150 were prognostic also in triple receptor-negative tumors. Coordinated expression of predicted target genes and prognostic microRNAs strengthened these results, most significantly for miR-210, -128a, and -27b, whose targets were prognostic in meta-analysis of several cohorts. In addition, miR-210 and -128a showed coordinated expression with their cognate pri-microRNAs, which were themselves prognostic in independent cohorts. Our integrated microRNA-mRNA global profiling approach has identified microRNAs independently associated with prognosis in breast cancer. Furthermore, it has validated known and predicted microRNA-target interactions, and elucidated their association with key pathways that could represent novel therapeutic targets.
microRNA 表达谱分析在癌症分类和治疗策略的确定中发挥着新兴作用。在这项研究中，我们评估了联合 microRNA-mRNA 分析在乳腺癌中的益处。在一个具有完整 10 年随访的经过充分注释的 207 例病例队列中进行了匹配的 mRNA 和 microRNA 全局表达谱分析。使用包含 microRNA 表达、mRNA 表达和临床协变量的惩罚 Cox 回归来识别与远处无复发生存（DRFS）相关的 microRNAs，这些 microRNAs提供独立的预后信息，而不仅仅是先前确定的预后协变量的替代物。选择惩罚回归以防止过度拟合。此外，通过全局表达分析探索了 microRNA-mRNA 关系，并在几个已发表的队列中进行了验证（DRFS 为 592 例，无复发生存为 1050 例）。有 4 个 microRNA 独立地与雌激素受体（ER）阳性（3 个新的和 1 个已知的；miR-128a）和 6 个 ER 阴性（5 个新的和 1 个已知的；miR-210）病例的 DRFS 相关。其中，miR-342、-27b 和 -150 在三阴性肿瘤中也具有预后意义。预测靶基因和预后 microRNA 的协调表达增强了这些结果，miR-210、-128a 和 -27b 的靶基因在几个队列的荟萃分析中具有预后意义，这一结果最为显著。此外，miR-210 和 -128a 与它们同源的 pri-microRNA 表现出协调表达，这些 pri-microRNA 在独立的队列中也具有预后意义。我们的整合 microRNA-mRNA 全局分析方法已经确定了与乳腺癌预后独立相关的 microRNA。此外，它验证了已知和预测的 microRNA-靶标相互作用，并阐明了它们与关键途径的关联，这些途径可能代表新的治疗靶点。
