Gene Expression Patterns in Human Tumors Identified Using Transcript Sequencing

使用转录测序鉴定人类肿瘤中的基因表达模式

• 批准号: 8537844
• 负责人: David N Hayes
• 金额: $ 377.71万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-29 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8537844
• 关键词: Alternative Splicing; Base Sequence; Binding Sites; Biological Assay; Breast; Cancer Etiology; Characteristics; Chromatin; Clinical; Code; Coupled; DNA; DNA Methylation; DNA Microarray Chip; DNA Sequence; DNA copy number; Data; Development; Disease; Distant; Enhancers; Epigenetic Process; Event; Formaldehyde; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene Structure; Genes; Genome; Genomics; Glioblastoma; Head and neck structure; Human; Individual; Infectious Agent; Informatics; Instruction; Knowledge; Lead; Link; Location; Locus Control Region; Malignant Neoplasms; Malignant neoplasm of lung; Mammalian Cell; Maps; Measurement; Messenger RNA; Methods; MicroRNAs; Molecular Profiling; Mutate; Mutation; Nature; Normal tissue morphology; Nucleosomes; Oligonucleotide Microarrays; Outcome; Output; Paint; Pathogen detection; Patients; Pattern; Persons; Phase; Portraits; Procedures; Protein Isoforms; Proteins; RNA Splicing; Regulation; Regulatory Element; Relative (related person); Research Infrastructure; Role; SNP genotyping; Solid; Technology; Testing; The Cancer Genome Atlas; Time; Tissues; Transcript; Tumor Biology; Tumor Subtype; Tumor Suppressor Genes; Viral; base; cancer genome; chromatin remodeling; cost; deep sequencing; disorder subtype; experience; fusion gene; gene function; genome wide association study; genome-wide; histone modification; improved; infancy; insight; next generation; next generation sequencing; novel; pathogen; promoter; research study; tool; transcription factor; tumor

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.

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微阵列实现的定量基因表达分析，已被证明是一种有效的方法。 癌症基因组表征的非常有价值的工具，并导致了新的发展， 基于基因组的临床试验。我们用DNA微阵列研究基因表达模式的经验 乳腺癌、头颈癌和肺癌的研究已经导致了新的肿瘤亚型的鉴定， 不同的患者结果，并确定了新的肿瘤抑制基因。在癌症的试点阶段 在基因组图谱（TCGA）项目中，使用了多个平台，包括研究基因表达的工具（我们的 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。我们的合作努力确定了胶质母细胞瘤的新肿瘤亚型，并绘制了一个完整的 将突变与表达模式的拷贝数变化联系起来， 不同的疾病亚型在患者结局上存在差异。 对于TCGA项目的第二阶段，我们建议继续进行定量基因表达 在~ 2000个肿瘤上分析所有蛋白质编码基因、非蛋白质编码mRNA（ncRNA）和microRNA 每一年。这种方法已被证明是信息量最大和最全面的癌症基因组之一 可用的特征化工具。此外，我们建议生成的全球染色质组织概况， 癌症，以确定区域的“开放”染色质结构域（核小体耗尽区）。我们将使用FAIRE （甲醛辅助分离调节元件），一种简单，低成本的方法，适用于 少量的实体组织，再加上下一代的DNA测序。由于大多数的功能 组蛋白修饰和染色质重塑活动是调节核小体占有，FAIRE 有效地总结了这种表观遗传机制的功能输出在一个单一的强大的测定。最后， 我们建议对转录水平和染色质结构进行综合分析， 调节元件，其可以远离它们调节的转录物。我们对全基因组的研究 染色质组织的转录调节将提供癌症基因组的关键肖像，可以 与其他重要数据整合（有时甚至可以生成），包括突变和复制 数事件。