Authors' Affiliations: Departments of Epidemiology and Biostatistics, Immunology, and Gastric Cancer, TMUCIH-J&J Joint Laboratory, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital; Department of Gastroenterology, Tianjin Medical University General Hospital, Tianjin, PR China; Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; and Janssen Research and Development, a Division of Janssen Pharmaceutica, Beerse, Belgium.
Clin Cancer Res. 2014 Feb 15;20(4):878-89. doi: 10.1158/1078-0432.CCR-13-1844. Epub 2013 Dec 18.
Our aim was to investigate whether microRNAs can predict the clinical outcome of patients with gastric cancer. We used integrated analysis of microRNA and mRNA expression profiles to identify gastric cancer microRNA subtypes and their underlying regulatory scenarios.
MicroRNA-based gastric cancer subtypes were identified by consensus clustering analysis of microRNA profiles of 90 gastric cancer tissues. Activated pathways in the subtypes were identified by gene expression profiles. Further integrated analysis was conducted to model a microRNA regulatory network for each subtype. RNA and protein expression were analyzed by RT-PCR and tissue microarray, respectively, in a cohort of 385 gastric cancer cases (including the 90 cases for profiling) to validate the key microRNAs and targets in the network. Both in vitro and in vivo experiments were carried out to further validate the findings.
MicroRNA profiles of 90 gastric cancer cases identified two microRNA subtypes significantly associated with survival. The poor-prognosis gastric cancer microRNA subtype was characterized by overexpression of epithelial-to-mesenchymal transition (EMT) markers. This gastric cancer "mesenchymal subtype" was further validated in a patient cohort comprising 385 cases. Integrated analysis identified a key microRNA regulatory network likely driving the gastric cancer mesenchymal subtype. Three of the microRNAs (miR-200c, miR-200b, and miR-125b) targeting the most genes in the network were significantly associated with survival. Functional experiments demonstrated that miR-200b suppressed ZEB1, augmented E-cadherin, inhibited cell migration, and suppressed tumor growth in a mouse model.
We have uncovered a key microRNA regulatory network that defines the mesenchymal gastric cancer subtype significantly associated with poor overall survival in gastric cancer.
我们旨在研究 microRNA 是否可以预测胃癌患者的临床结局。我们使用 microRNA 和 mRNA 表达谱的综合分析来鉴定胃癌 microRNA 亚型及其潜在的调控机制。
通过对 90 例胃癌组织的 microRNA 图谱进行共识聚类分析，鉴定基于 microRNA 的胃癌亚型。通过基因表达图谱鉴定亚型中的激活途径。进一步进行综合分析，为每个亚型构建 microRNA 调控网络模型。通过 RT-PCR 和组织微阵列分别分析了 385 例胃癌病例（包括 90 例用于分析的病例）的 RNA 和蛋白质表达，以验证网络中的关键 microRNA 和靶标。进行了体外和体内实验以进一步验证研究结果。
90 例胃癌病例的 microRNA 图谱鉴定出与生存显著相关的两种 microRNA 亚型。预后不良的胃癌 microRNA 亚型以上皮间质转化（EMT）标志物的过度表达为特征。这一胃癌“间质亚型”在包含 385 例病例的患者队列中得到进一步验证。综合分析鉴定出一个可能驱动胃癌间质亚型的关键 microRNA 调控网络。靶向网络中最多基因的三个 microRNA（miR-200c、miR-200b 和 miR-125b）与生存显著相关。功能实验表明，miR-200b 抑制 ZEB1，增加 E-钙黏蛋白，抑制细胞迁移，并在小鼠模型中抑制肿瘤生长。
我们揭示了一个关键的 microRNA 调控网络，该网络定义了与胃癌总体生存不良显著相关的间质型胃癌亚型。
