Onken Michael D, Ehlers Justis P, Worley Lori A, Makita Jun, Yokota Yoshifumi, Harbour J William
Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Cancer Res. 2006 May 1;66(9):4602-9. doi: 10.1158/0008-5472.CAN-05-4196.
Microarray gene expression profiling is a powerful tool for generating molecular cancer classifications. However, elucidating biological insights from these large data sets has been challenging. Previously, we identified a gene expression-based classification of primary uveal melanomas that accurately predicts metastatic death. Class 1 tumors have a low risk and class 2 tumors a high risk for metastatic death. Here, we used genes that discriminate these tumor classes to identify biological correlates of the aggressive class 2 signature. A search for Gene Ontology categories enriched in our class-discriminating gene list revealed a global down-regulation of neural crest and melanocyte-specific genes and an up-regulation of epithelial genes in class 2 tumors. Correspondingly, class 2 tumors exhibited epithelial features, such as polygonal cell morphology, up-regulation of the epithelial adhesion molecule E-cadherin, colocalization of E-cadherin and beta-catenin to the plasma membrane, and formation of cell-cell adhesions and acinar structures. One of our top class-discriminating genes was the helix-loop-helix inhibitor ID2, which was strongly down-regulated in class 2 tumors. The class 2 phenotype could be recapitulated by eliminating Id2 in cultured class 1 human uveal melanoma cells and in a mouse ocular melanoma model. Id2 seemed to suppress the epithelial-like class 2 phenotype by inhibiting an activator of the E-cadherin promoter. Consequently, Id2 loss triggered up-regulation of E-cadherin, which in turn promoted anchorage-independent cell growth, a likely antecedent to metastasis. These findings reveal new roles for Id2 and E-cadherin in uveal melanoma progression, and they identify potential targets for therapeutic intervention.
基因芯片基因表达谱分析是生成分子癌症分类的有力工具。然而,从这些大数据集中阐明生物学见解一直具有挑战性。此前,我们确定了一种基于基因表达的原发性葡萄膜黑色素瘤分类方法,该方法能准确预测转移死亡情况。1类肿瘤转移死亡风险低,2类肿瘤转移死亡风险高。在此,我们使用区分这些肿瘤类别的基因来确定侵袭性2类特征的生物学关联。在我们的类别区分基因列表中对富集的基因本体类别进行搜索,结果显示2类肿瘤中神经嵴和黑素细胞特异性基因整体下调,上皮基因上调。相应地,2类肿瘤表现出上皮特征,如多边形细胞形态、上皮粘附分子E-钙粘蛋白上调、E-钙粘蛋白和β-连环蛋白在质膜上共定位以及细胞间粘附和腺泡结构形成。我们最具类别区分能力的基因之一是螺旋-环-螺旋抑制剂ID2,它在2类肿瘤中强烈下调。通过在培养的1类人葡萄膜黑色素瘤细胞和小鼠眼黑色素瘤模型中消除Id2,可以重现2类表型。Id2似乎通过抑制E-钙粘蛋白启动子的激活剂来抑制上皮样2类表型。因此,Id2缺失引发E-钙粘蛋白上调,进而促进不依赖贴壁的细胞生长,这可能是转移的先兆。这些发现揭示了Id2和E-钙粘蛋白在葡萄膜黑色素瘤进展中的新作用,并确定了治疗干预的潜在靶点。