Genomics of Acute Myelogenous Leukemia (AML): Somatic Mutations & Consequences

急性髓性白血病 (AML) 的基因组学：体细胞突变

• 批准号: 7465874
• 负责人: TIMOTHY J. LEY
• 金额: $ 29.01万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7465874
• 关键词: Acute; Acute Myelocytic Leukemia; Affect; Algorithms; Alleles; Biological; Cancer and Leukemia Group B; Candidate Disease Gene; Classification; Clinical; Cloning; DNA Resequencing; DNA Sequence; Data; Databases; Disease; Disease Progression; Exons; FLT3 gene; Facility Construction Funding Category; Frequencies; Gene Expression; Gene Expression Profiling; Genes; Genome; Genomics; Goals; Individual; Informatics; Introns; Laboratories; Leukemia, Myeloid, Acute, M1; Loss of Heterozygosity; Mining; Mutation; Myeloid Leukemia; Numbers; Outcome; Output; Pathogenesis; Pathway interactions; Patients; Pattern; Plasmids; Polymerase Chain Reaction; Resolution; SNP genotyping; Sampling; Sequence Analysis; Somatic Mutation; Standards of Weights and Measures; Uniparental Disomy; Validation; base; comparative genomic hybridization; cost; experience; gene function; interest; member; mutant; novel; outcome forecast; promoter; tumor; validation studies

The long-term goal of this project is to integrate the analysis of all genomic studies of the GAML PPG to identify and validate acquired genetic changes that may contribute to the pathogenesis of AML. Somatic mutations that are predicted to change the function of a gene will be analyzed to assess their consequences on patient outcomes, on patterns of gene expression, and on AML-relevant pathways. To identify these mutations, high-resolution genomic screens and large scale resequencing studies will be required. In the GAML PPG, several cores and projects are generating genome-wide databases that must be carefully coanalyzed to identify candidate genes for resequencing and validation studies. These databases also must be mined to define relationships between the mutations and the biological pathways that they affect. To achieve these goals, we propose these Specific Aims: Specific Aim 1: We will analyze the outputs of multiple genomic screens to prioritize candidate genes for resequencing, and we will define and validate somatic mutations in AML samples. Exonbased resequencing studies (Core D) are difficult and expensive to perform, and candidate genes for these studies must therefore be carefully prioritized using data generated by high-resolution genomic screens. Array-based gene expression profiling, high resolution array-based comparative genomic hybridization, and high resolution array-based SNP genotyping studies will be used to identify genes and/or loci that are deleted, amplified, or duplicated from one parental allele (uniparental disomy), or that have aberrant patterns of expression; whole genome resequencing studies of 10 M1 AML genomes (Project 1) will also be analyzed to define potentially important mutations that will be validated using the 94 matched tumor-germline AML samples from the Discovery Set. When potentially important somatic mutations are identified, we will perform additional studies to verify the mutation and its frequency in the AML sample of interest (i.e. bacterial cloning and resequencing of the mutant exon in 96 clones from the sample), and we will further define the mutation's frequency in 94 fully annotated AML cases obtained from Cancer and Leukemia Group B (CALGB). Specific Aim 2: We will define the clinical and gene expression consequences of validated somatic mutations, and define biologic pathways altered by these mutations. We will use statistical approaches to define the effects of mutations on clinical outcomes. Novel informatics approaches (e.g. promoter analyses, pathway/interaction network construction, etc.) will be used to define the effects of mutations on patterns of gene expression, and to identify potentially relevant biological pathways that are affected by AML mutations. These algorithms will be used to identify additional genes for resequencing studies. Selected mutations and pathways identified by these studies will be biologically validated in the laboratories of PPG members.

该项目的长期目标是将对GAML PPG的所有基因组研究的分析整合到 识别和验证可能有助于急性髓细胞白血病发病机制的获得性基因变化。体细胞 被预测会改变基因功能的突变将被分析以评估其后果 对患者结局、基因表达模式和急性髓细胞白血病相关途径的影响。要确定这些 将需要突变、高分辨率基因组筛选和大规模的重新测序研究。在 GAML PPG、几个核心和项目正在生成必须仔细协同分析的全基因组数据库 为重新测序和验证研究确定候选基因。这些数据库还必须 以确定突变及其影响的生物途径之间的关系。至 为了实现这些目标，我们提出了以下具体目标： 具体目标1：我们将分析多个基因组筛查的结果，以确定候选人的优先顺序 基因重新测序，我们将定义和验证AML样本中的体细胞突变。基于Exon的 重新测序研究(核心D)是困难和昂贵的执行，这些候选基因 因此，必须使用高分辨率基因组筛选产生的数据仔细地确定研究的优先顺序。 基于阵列的基因表达谱，基于高分辨率阵列的比较基因组杂交，以及 基于高分辨率阵列的SNP基因分型研究将用于识别 来自一个亲本等位基因的缺失、扩增或复制(单亲二体)，或具有异常模式 还将分析10个M1 AML基因组的全基因组重测序研究(项目1) 以确定潜在的重要突变，这些突变将使用94个匹配的肿瘤生殖系AML进行验证 Discovery集合中的样本。当潜在的重要体细胞突变被确定后，我们将执行 在感兴趣的AML样本中验证突变及其频率的其他研究(即细菌克隆 并对样本中96个克隆中的突变外显子进行了重新测序)，我们将进一步定义突变的 从癌症和白血病B组(CALGB)获得的94例完全注释的AML病例的频率。 具体目标2：我们将确定经验证的体细胞的临床和基因表达后果 突变，并定义由这些突变改变的生物途径。我们将使用统计方法 确定突变对临床结果影响的方法。新的信息学方法(例如 启动子分析、途径/相互作用网络构建等)将用于定义 基因表达模式上的突变，并识别潜在相关的生物通路 受到急性髓系白血病突变的影响。这些算法将被用来识别额外的基因进行重新测序 学习。这些研究确定的选定突变和途径将在 PPG成员的实验室。