Bredel Markus, Bredel Claudia, Juric Dejan, Harsh Griffith R, Vogel Hannes, Recht Lawrence D, Sikic Branimir I
Division of Oncology, Center for Clinical Sciences Research, Stanford University School of Medicine, Stanford, California 94305-5151, USA.
Cancer Res. 2005 Oct 1;65(19):8679-89. doi: 10.1158/0008-5472.CAN-05-1204.
Gene expression profiling has proven useful in subclassification and outcome prognostication for human glial brain tumors. The analysis of biological significance of the hundreds or thousands of alterations in gene expression found in genomic profiling remains a major challenge. Moreover, it is increasingly evident that genes do not act as individual units but collaborate in overlapping networks, the deregulation of which is a hallmark of cancer. Thus, we have here applied refined network knowledge to the analysis of key functions and pathways associated with gliomagenesis in a set of 50 human gliomas of various histogenesis, using cDNA microarrays, inferential and descriptive statistics, and dynamic mapping of gene expression data into a functional annotation database. Highest-significance networks were assembled around the myc oncogene in gliomagenesis and around the integrin signaling pathway in the glioblastoma subtype, which is paradigmatic for its strong migratory and invasive behavior. Three novel MYC-interacting genes (UBE2C, EMP1, and FBXW7) with cancer-related functions were identified as network constituents differentially expressed in gliomas, as was CD151 as a new component of a network that mediates glioblastoma cell invasion. Complementary, unsupervised relevance network analysis showed a conserved self-organization of modules of interconnected genes with functions in cell cycle regulation in human gliomas. This approach has extended existing knowledge about the organizational pattern of gene expression in human gliomas and identified potential novel targets for future therapeutic development.
基因表达谱分析已被证明在人类胶质脑肿瘤的亚分类和预后预测中很有用。分析基因组谱中发现的数百或数千个基因表达改变的生物学意义仍然是一项重大挑战。此外,越来越明显的是,基因并非作为单个单元起作用,而是在重叠网络中协同作用,这些网络的失调是癌症的一个标志。因此,我们在此应用了精细的网络知识,通过cDNA微阵列、推断性和描述性统计以及将基因表达数据动态映射到功能注释数据库,对一组50例不同组织发生类型的人类胶质瘤中与胶质瘤发生相关的关键功能和通路进行分析。最高显著性网络围绕胶质瘤发生中的myc癌基因以及胶质母细胞瘤亚型中的整合素信号通路组装而成,胶质母细胞瘤亚型以其强烈的迁移和侵袭行为为典型特征。三个具有癌症相关功能的新型MYC相互作用基因(UBE2C、EMP1和FBXW7)被鉴定为在胶质瘤中差异表达的网络成分,CD151作为介导胶质母细胞瘤细胞侵袭的网络的一个新成分也是如此。互补的无监督相关性网络分析显示,在人类胶质瘤中,具有细胞周期调控功能的相互连接基因模块存在保守的自组织。这种方法扩展了关于人类胶质瘤基因表达组织模式的现有知识,并确定了未来治疗发展的潜在新靶点。