The National Cancer Institute^s Office of Cancer Genomics

美国国家癌症研究所癌症基因组学办公室

• 批准号: 7733478
• 负责人: Daniela Gerhard
• 金额: $ 145.33万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7733478
• 关键词: Acute Lymphocytic Leukemia; Address; Atlases; Binding; Biological; Biological Assay; Biological Factors; Biology; Brain; Canada; Cancer Biology; Cancer Genome Anatomy Project; Cancerous; Case-Control Studies; Cattle; Cells; Chemicals; Child; Chromosome abnormality; Chromosomes; Classification; Clinical; Cohort Studies; Collection; Commit; Communities; Compatible; Complementary DNA; Complex; DNA Resequencing; DNA Sequence; Data; Databases; Detection; Development; Diagnosis; Disease; Division of Cancer Epidemiology and Genetics; Doctor of Philosophy; Early Diagnosis; Epigenetic Process; Expressed Sequence Tags; Face; Family; Gene Expression; Gene Expression Regulation; Gene Frequency; Gene Mutation; Genes; Genetic; Genetic Markers; Genetic Programming; Genetic Variation; Genome; Genomic Segment; Genomics; Genotype; Goals; Homo sapiens; Human; Human Cloning; Human Genetics; Informatics; Information Technology; International; Internet; Knowledge; Lead; Legal patent; Length; Linkage Disequilibrium; Lung; Malignant Childhood Neoplasm; Malignant Neoplasms; Malignant neoplasm of prostate; Methods; Minor; Mission; Molecular; Molecular Profiling; Molecular Target; Mus; Mutation; National Cancer Institute; Nested Case-Control Study; Neuroblastoma; Normal Cell; Numbers; Office of Cancer Genomics; Open Reading Frames; Outcome; Ovarian; Participant; Pattern; Phase; Phenotype; Pilot Projects; Play; Polymorphism Analysis; Population; Predisposition; Premalignant; Prevention; Procedures; Prostate; Proteomics; Publications; RNA Interference; Range; Rattus; Reading; Reagent; Recovery; Research; Research Infrastructure; Research Personnel; Resolution; Resources; Role; Running; Sampling; Scanning; Scientist; Screening procedure; Signal Transduction; Single Nucleotide Polymorphism; Site; Structure; Subgroup; Synthesis Chemistry; System; Techniques; Technology; Testing; Time; Tissues; Today; Translating; United States National Institutes of Health; Variant; analytical method; anticancer research; base; burden of illness; cancer Biomedical Informatics Grid; cancer genetics; cancer genome; cancer genomics; cancer therapy; cancer type; chemical genetics; cost; data integration; design; follow-up; genome wide association study; improved; insight; interest; malignant breast neoplasm; novel; programs; protein expression; repository; serial analysis of gene expression; small molecule; small molecule libraries; therapeutic target; tool; tumor

The Office of Cancer Genomics supports, leads, and/or manages six major research programs, listed in order of their inception Cancer Genome Anatomy Project (CGAP) The NCI CGAP is an online resource designed to characterize biological tissues and provide cDNA clones to the research community. To support these outcomes, CGAP provides a wide range of genomic data that include gene expression profiles of normal, precancerous, and cancerous cells (based on expressed sequence tags (EST) and serial analysis of gene expression (SAGE)), single nucleotide polymorphism (SNP) analysis of cancer-related genes, and the 50,000+-case Mitelman database of chromosomal aberrations in cancer. By collaborating with scientists worldwide, CGAP seeks to increase its scientific expertise and expand its databases for the benefit of all cancer researchers. Access to all CGAP data, clones, and analytic tools is made available to the research community through the CGAP web site and distribution system. Mammalian Gene Collection (MGC) The goal of the Mammalian Gene Collection (MGC), a trans-NIH initiative, is to provide full-length open reading frame (FL-ORF) clones for human, mouse, and rat genes. The MGC recently organized an international consortium of seven participants to create expression-ready clones for all Homo sapiens genes, which can be used by the research community for expression of proteins for large-scale proteomic analyses. In 2005, the project added the cow cDNAs generated by Genome Canada. Alternative methods based on gene-specific amplification have recently been developed to target the recovery of human and mouse genes absent from the MGC collection. Initiative for Chemical Genetics (ICG) Synthetic chemistry has enabled the creation of large collections of complex and diverse small molecules, patterned after natural products, which are tested for the ability to induce specific biological phenotypes. The NCIs Initiative for Chemical Genetics provides a systematic approach to study biology using such small molecules, to develop new screening tools and compounds, and to accelerate the development of new cancer strategies and therapies. As detailed below, the ICG focuses efforts on a number of deliverables, including biological assays, chemical libraries, a repository of chemical probes, and a scientific database. Discoveries made through the ICG program to date have resulted in more than 100 publications and 17 patents. The Cancer Genome Atlas (TCGA) The Cancer Genome Atlas (TCGA) pilot project is a three-year, $100 million-dollar collaborative effort between the NCI and the NHGRI that will test the feasibility of a large-scale systematic approach to identify genetic alterations in human cancer. The project, which was initially presented to the NCI BSA in November of 2005, was formally launched in FY 2006. The Atlas will profile three tumor types (brain, lung, and ovarian) by analyzing the expression profiles and genomic changes associated with each cancer sample. This characterization will be followed by the sequencing of genes and regions that are altered in a significant number of samples in each cancer type. The integration of these data types will provide insights into functional aspects of gene regulation and its role in cancer biology. In addition, the pilot project will create a comprehensive database, including clinical outcomes data, which will serve as a publicly-available resource to identify new genes and chromosomal regions of interest in cancer research. Advanced technology platforms will play key roles in the genomic analysis, and a caBIG-compatible infrastructure will facilitate data access by the scientific community. Although the pilot project is slated to run for three years, it is expected that results generated will be translated into findings with meaningful clinical impact well beyond this time frame. Cancer Genetic Markers of Susceptibility (CGEMS) CGEMS is a three-year, $14 million-dollar initiative to conduct whole-genome association studies to identify genes that confer susceptibility to prostate and breast cancer. Coordinated through the NCIs Division of Cancer Epidemiology and Genetics, the Core Genotyping Facility, and the OCG, the project capitalizes on new knowledge of single nucleotide polymorphisms (SNPs) in human genetic variation and technical advances in ultra-high-throughput genotyping. SNPs are the most common form of human genomic variation; most of the approximately ten million SNPs with a minor allele frequency greater than 5 percent occur in genomic segments in which they correlate highly with each other (i.e., they are in linkage disequilibrium). Data from the International HapMap Project Phase 2 indicate that a minimum of 550,000 carefully-chosen SNPs will be required to conduct a comprehensive whole-genome SNP scan. CGEMS is designed to conduct whole-genome scans in nested case-control studies of prostate and breast cancer from ongoing population-based cohort studies. Each whole-genome scan will analyze approximately 1,200 cases and 1,200 controls. Because the large number of SNP comparisons in a whole-genome scan will likely generate many false positive signals, follow-up sequential replication studies will be used to validate true positive associations. Using this procedure, CGEMS will assess the 15,000-20,000 top candidate SNPs from the whole-genome scans in follow-up case-control studies. Rapid public access to data generated by CGEMS will be facilitated by caBIG. The data generated by CGEMS prostate cancer study is available through the CGEMS data access portal. Therapeutically Applicable Research to Generate Effective Treatments (TARGET) The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative is committed to focusing genomics tools to rapidly identify potential therapeutic targets in childhood cancers so that new, more effective treatments can be developed in shorter time and ultimately bring new hope to children and their families who face the devastating burden of these diseases. The TARGET Initiative seeks to identify the genomic changes associated with Acute Lymphoblastic Leukemia (ALL) and Neuroblastoma, both childhood cancers. The research conducted by TARGET is divided into three distinct yet tightly integrated components that together form a system for selecting new molecular targets for the development of novel therapies for these childhood cancers: -Genomic Characterization: Gene expression studies (using high-resolution array-based methods to determine differences in the patterns of gene expression in cancer samples and non-cancerous samples) and genome structure studies (using high-resolution array-based methods to characterize genome structural changes that correlate with each cancer, such as chromosome region gains and losses) are integrated to provide a complete genomic "overview" of each cancer. -Gene Resequencing: Up-to-date genetic sequencing techniques are used to "read" genes that have been identified to have altered expression and/or structural alterations to identify the specific cancer-related mutations in the DNA sequence. -Identification of Therapeutic Targets: RNA interference (RNAi) is used to identify and initially validate potential targets identified from the genomic characterization and resequencing efforts.

癌症基因组学办公室支持，潜在客户和/或管理六个主要的研究计划，按其成立顺序列出 癌症基因组解剖项目（CGAP） NCI CGAP是一种在线资源，旨在表征生物组织并为研究界提供cDNA克隆。 To support these outcomes, CGAP provides a wide range of genomic data that include gene expression profiles of normal, precancerous, and cancerous cells (based on expressed sequence tags (EST) and serial analysis of gene expression (SAGE)), single nucleotide polymorphism (SNP) analysis of cancer-related genes, and the 50,000+-case Mitelman database of chromosomal aberrations in cancer. 通过与全球科学家合作，CGAP试图提高其科学专业知识并扩展其数据库，以使所有癌症研究人员受益。通过CGAP网站和分发系统，可以访问所有CGAP数据，克隆和分析工具。 哺乳动物基因收集（MGC） Trans-NIH倡议的哺乳动物基因收集（MGC）的目标是为人，小鼠和大鼠基因提供全长开放阅读框（FL-ORF）克隆。 MGC最近组织了一个由七名参与者组成的国际联盟，为所有智人基因创建了表达的克隆，研究界可以将其用于蛋白质的表达，以进行大规模蛋白质组学分析。 2005年，该项目增加了加拿大基因组产生的牛CDNA。最近已经开发了基于基因特异性扩增的替代方法，以靶向MGC收集中没有人类和小鼠基因的恢复。 化学遗传学倡议（ICG） 合成化学已使成立于天然产物的大量复杂而多样的小分子的集合创建，这些分子已通过诱导特定的生物学表型的能力进行了测试。 NCIS化学遗传学计划提供了一种系统的方法，可以使用如此小的分子研究生物学，开发新的筛查工具和化合物，并加速新的癌症策略和疗法的发展。如下所述，ICG将精力集中在许多可交付成果上，包括生物测定，化学库，化学探针的存储库和科学数据库。迄今为止通过ICG计划通过的发现已获得100多个出版物和17项专利。 癌症基因组地图集（​​TCGA） 癌症基因组地图集（​​TCGA）试点项目是NCI和NHGRI之间为期三年，1亿美元的合作努力，它将测试大规模系统性方法的可行性，以鉴定人类癌症的遗传改变。该项目最初于2005年11月提交给NCI BSA，于2006财年正式启动。 通过分析与每种癌症样本相关的表达谱和基因组变化，地图集将介绍三种肿瘤类型（大脑，肺和卵巢）。此表征将在每种癌症类型的大量样品中改变基因和区域的测序。这些数据类型的整合将为基因调节的功能方面及其在癌症生物学中的作用提供见解。 此外，试点项目将创建一个全面的数据库，包括临床结果数据，该数据将作为一种公共可用的资源，以确定在癌症研究中具有兴趣的新基因和染色体区域。先进的技术平台将在基因组分析中扮演关键角色，与Cabig兼容的基础架构将有助于科学界的数据访问。尽管试点项目计划运行三年，但预计产生的结果将被转化为具有有意义的临床影响的发现，远远超出了这个时间范围。 易感性的癌症遗传标记（CGEM） CGEM是一项为期三年，1400万美元的倡议，旨在进行全基因组协会研究，以识别具有前列腺癌和乳腺癌易感性的基因。通过癌症流行病学和遗传学，核心基因分型设施和OCG协调的项目，该项目利用了超高直播基因分型的人类遗传变异的单核苷酸多态性（SNP）的新知识。 SNP是人类基因组变异的最常见形式。在基因组段中，大多数大约一千万个具有次要等位基因频率的SNP都大于5％，它们相互高度相关（即它们处于链接不平衡）。国际HAPMAP项目第2阶段的数据表明，必须至少需要550,000个精心挑选的SNP才能进行全面的全基因组SNP扫描。 CGEM旨在通过正在进行的基于人群的队列研究对前列腺和乳腺癌的嵌套病例对照研究进行全基因组扫描。每个全基因组扫描将分析大约1200例病例和1200例对照。由于全基因组扫描中的大量SNP比较可能会产生许多假阳性信号，因此将使用后续顺序复制研究来验证真正的正相关。使用此程序，CGEM将在后续病例对照研究中评估全基因组扫描中的15,000-20,000名顶级候选SNP。 Cabig将促进CGEM生成的数据的迅速访问。 CGEMS前列腺癌研究产生的数据可通过CGEMS数据访问门户网站获得。 治疗上适用的研究以生成有效的治疗（目标） 治疗上适用的研究以生成有效的治疗（目标）计划致力于集中基因组学工具，以迅速识别儿童癌症中潜在的治疗靶标，以便在较短的时间内开发出新的，更有效的治疗方法，并最终为面临这些疾病造成破坏负担的儿童及其家人带来新的希望。 目标倡议旨在确定与急性淋巴细胞白血病（ALL）和神经母细胞瘤相关的基因组变化。 目标进行的研究分为三个不同但紧密整合的组件，共同构成了一个系统，用于选择新的分子靶标，以开发这些童年癌症的新型疗法： - 基因组表征：基因表达研究（使用基于高分辨率阵列的方法来确定癌症样本和非癌性样品中基因表达模式的差异）和基因组结构研究（使用基于高分辨率阵列的方法来表征与每个癌症相关的基因组结构变化，例如渐变组地区的增长和损失，从而使每个癌症都整合了癌症。 - 重新定位：最新的遗传测序技术用于“读取”已鉴定为改变表达和/或结构变化的基因，以鉴定DNA序列中与癌症相关的特定突变。 - 治疗靶标的识别：RNA干扰（RNAI）用于识别并最初从基因组表征和重新统计工作中鉴定出的潜在靶标。