Gene Expression Patterns in Human Tumors Identified Using Transcript Sequencing

基因表达提供了促进肿瘤恶性的细胞变化的快照。 定量基因表达分析，特别是通过DNA微阵列实现的，已被证明是一种 非常有价值的癌症基因组表征工具，并导致了新的 基于基因组的临床测试。我们自己使用DNA微阵列研究基因表达模式的经验 对于乳腺癌、头颈部和肺癌，导致了新的肿瘤亚型的识别 不同的患者结果，并已确定新的肿瘤抑制基因。在癌症的试验阶段 基因组图谱(TCGA)计划，使用了多个平台，包括研究基因表达的工具(OUR 作用)、肿瘤基因组DNA拷贝数改变、SNP基因型、DNA甲基化和基因突变 分析。我们的合作发现了胶质母细胞瘤的新的肿瘤亚型，并描绘了一个完整的 图片链接突变以复制数量变化到表达模式，这识别了生物上的不同 患者预后不同的疾病亚型。 对于TCGA项目的第二阶段，我们建议继续进行定量基因表达 On-2000肿瘤中所有蛋白质编码基因、非蛋白质编码mRNAs(NcRNAs)和microRNAs的分析 每年。这种方法已被证明是最有信息量和最全面的癌症基因组之一。 可用的角色化工具。此外，我们建议生成全球染色质组织简档 癌症识别“开放”染色质区域(核小体缺失区域)。我们将使用FIRE (甲醛辅助分离调节元件)，一种简单、低成本的方法，适用于 少量的固体组织，与下一代DNA测序相结合。由于MOST的功能 组蛋白修饰和染色质重塑活性是调节核小体占有率 在一次稳健的分析中有效地总结了这种表观遗传机制的功能输出。最后， 我们建议对转录水平和染色质化学结构进行综合分析，以定位重要的 监管要素，这可能与他们监管的成绩单(S)相距甚远。我们对全基因组的研究 染色质组织的转录调控将提供癌症基因组的关键画像，可以 与其他重要数据集成(有时确实可以生成)，包括突变和复制 对事件进行编号。

Gene expression provides a snapshot of the cellular changes that promote tumor malignancy. Quantitative gene expression analysis, especially as implemented by DNA microarrays, has proven to be an extremely valuable tool for cancer genome characterization, and has lead to the development of new genomic-based clinical tests. Our own experience with DNA microarrays to study gene expression patterns for breast, head & neck, and lung cancers has lead to the identification of novel subtypes of tumors with distinct patient outcomes and has identified new tumor suppressor genes. In the pilot phase of The Cancer Genome Atlas (TCGA) project, multiple platforms were used including tools to study gene expression (our role), tumor genomic DNA copy number alterations, SNP genotypes, DNA methylation and gene mutational analyses. Our collaborative efforts identified new tumor subtypes of glioblastoma and painted an integrated picture linking mutations to copy number changes to expression patterns, which identified biologically distinct subtypes of disease with differences in patient outcomes. For the second phase of TCGA project, we propose to continue to perform quantitative gene expression profiling of all protein-coding genes, non-protein coding mRNAs(ncRNAs) and microRNAs, on -2000 tumors per year. This approach has proven to be one of the most informative and comprehensive cancer genome characterization tools available. In addition, we propose to generate global chromatin organization profiles of cancer to identify regions of "open" chromatin domains (nucleosome-depleted regions). We will use FAIRE (Formaldehyde-Assisted isolation of Regulatory Elements), a simple, low-cost method amenable to use on small quantities of solid tissue, coupled to next-generation DNA sequencing. Since the function of most histone modifications and chromatin remodeling activities is to regulate nucleosome occupancy, FAIRE effectively summarizes the functional output of such epigenetic mechanisms in a single robust assay. Lastly, we propose to perform integrated analyses of transcript levels with chromatin stoicture to map important regulatory elements, which can be distant to the transcript(s) that they regulate. Our study of genome-wide transcript regulation with chromatin organization will provide a critical portrait of the cancer genome that can be integrated with (and indeed can sometimes generate) other important data, including mutations and copy number events.