INTEGRATED ANALYSIS & INTERPRETATION OF WHOLE GENOME, EXOME & TRANSCRIPTOME SEQUENCE DATA IN CANCER

综合分析

• 批准号: 9061766
• 负责人: Malachi Griffith
• 金额: $ 13.2万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9061766
• 关键词: Address; Affect; Allogenic; Amino Acid Sequence; Area; Automobile Driving; Award; Bioinformatics; Biological Assay; Breast; Cancer Patient; Cataloging; Catalogs; Cells; Chromosomal Rearrangement; Clinical; Code; Communities; Complex; DNA; Data; Data Analyses; Data Set; Databases; Development; Diagnostic; Disease; Disease remission; Equilibrium; Event; Exons; FLT3 gene; FLT3 inhibitor; Future; Gene Expression; Gene Expression Regulation; Gene Mutation; Generations; Genes; Genome; Genomics; Goals; Health; Hot Spot; Human; Individual; Institutes; Introns; Knowledge; Label; Liver; Malignant Neoplasms; Manuals; Mentors; Methods; Molecular Abnormality; Mutate; Mutation; Nucleic Acid Regulatory Sequences; Pathway interactions; Patients; Pattern; Peptide Sequence Determination; Pharmaceutical Preparations; Phase; Physicians; Positioning Attribute; Process; Proteins; RNA; RNA Sequence Analysis; RNA Sequences; RNA Splicing; Receptor Protein-Tyrosine Kinases; Regulation; Regulator Genes; Regulatory Element; Relapse; Research; Research Infrastructure; Research Personnel; Resources; Sampling; Scientist; Single base substitution; Somatic Mutation; Spliced Genes; Staging; Technology; Testing; Transplantation; Universities; Untranslated RNA; Variant; Washington; Work; cancer genome; cancer genomics; cancer therapy; cancer type; career; clinically actionable; clinically relevant; clinically significant; cohort; exhaust; exome; exome sequencing; gain of function; gene function; genome analysis; genome sequencing; genome-wide; improved; insertion/deletion mutation; knowledge base; medical schools; molecular marker; next generation sequencing; novel; novel therapeutics; overexpression; personalized medicine; prognostic; programs; protein function; skills; standard of care; tool; transcriptome; transcriptome sequencing; tumor; tumor progression; whole genome

 DESCRIPTION (provided by applicant): Cancer is caused by somatic mutations within the genome of an initiating cell. These mutations take many forms including small single base substitutions, large insertions and deletions, chromosomal rearrangements, and so on. Mutations also vary with respect to their position relative to annotated gene loci. Some mutations occur within exons and have direct and readily predicted effects on protein sequence and function. Other mutations affect gene function indirectly by occurring within regulatory regions that influence gene expression and RNA splicing. Next generation sequencing has transformed the potential to explore the mutational landscapes of human cancers. However, rapid creation of massive complex datasets and a dearth of established methods for integrated analysis of this data have resulted in a critical research bottleneck. To date, research has focused heavily on the most easily detected and interpreted coding mutations occurring within known exons. Mutations in non-coding genes and regulatory elements that govern gene expression and splicing have been largely overlooked. Similarly, interpretation of the clinical significance of mutations has been limited to a handful of the most well characterized recurrently mutated `hot-spots' of certain genes. The proposed project will develop new tools to identify and characterize mutations with regulatory rather than protein coding consequences. Furthermore, we will develop resources to help the research community interpret the possible clinical relevance of these mutations. To explore these knowledge gaps and test our new tools we will apply them to a cohort of tumor samples from ongoing large scale genome/transcriptome sequencing projects at the Genome Institute. We have preliminary data to suggest that progression of these tumors may be driven by currently unknown regulatory mutations and that a subset of these may suggest novel therapeutic strategies. The Genome Institute at Washington University School of Medicine is one of few places in the world that successfully combines close interaction of physician scientists with a large-scale genome sequencing facility and world class computing infrastructure. The Genome Institute is a leader in the development of sequencing methods and bioinformatics tools needed for the proposed work. This is demonstrated by the candidate's comprehensive preliminary results. The candidate's mentor, Dr. Richard Wilson has an established track record of mentoring genomics scientists. Dr. Wilson has helped the candidate to establish an outstanding mentoring committee with the interdisciplinary skills needed to guide him in the proposed research. Dr. Wilson along with these additional mentors will collaboratively support and guide the candidate towards a successful independent career. The first specific aim, to be completed during the mentored phase will create new methods for integration of whole genome and transcriptome data as well as annotation and prioritization of somatic events. Particular emphasis will be placed on the characterization of non-coding mutations that affect gene regulation and splicing. The independent phase will move towards development of novel resources to help researchers interpret mutations in a clinical context. In both phases, the candidate's research will focus heavily on the bioinformatics aspect of these problems in a way that has minimal overlap but is highly complementary to the mentor's research program. In the long term, the candidate hopes to fill a growing need for bioinformatics investigators working in the area of cancer genomics. A K99 Pathway to Independence award will be invaluable to establishing him as an independent investigator in a field that is in need of experts specializing in bioinformatics and data analysis

 描述（由适用提供）：癌症是由启动细胞基因组中的体细胞突变引起的。这些突变采用多种形式，包括小型的单碱基取代，大插入和缺失，染色体重排等。相对于注释的基因局部，突变的位置也有所不同。某些突变发生在外显子内，并很容易预测对蛋白质序列和功能的影响。其他突变通过在影响基因表达和RNA剪接的调节区域内通过发生的，从而间接影响基因功能。下一代测序改变了探索人类癌症突变景观的潜力。然而，快速创建大型复杂数据集以及对该数据进行综合分析的已建立方法的死亡导致了重要的研究瓶颈。迄今为止，研究重点关注已知外显子内发生的最容易检测到的编码突变。在很大程度上忽略了控制基因表达和剪接的非编码基因和调节元件的突变。同样，对突变的临床意义的解释仅限于某些基因的少数经过良好特征性的经常突变的“热点”。拟议的项目将开发新的工具，以识别和表征具有调节性而不是蛋白质编码后果的突变。此外，我们将开发资源来帮助研究界解释这些突变的可能临床相关性。为了探索这些知识差距并测试我们的新工具，我们将将它们应用于基因组研究所正在进行的大规模基因组/转录组测序项目中的一系列肿瘤样本。我们有初步数据，表明这些肿瘤的进展可能是由目前未知的调节突变驱动的，并且其中的一部分可能暗示了新型的治疗策略。华盛顿大学医学院的基因组学院是世界上少数几个成功结合物理科学家与大规模基因组测序设施和世界一流计算基础设施的互动的地方之一。基因组研究所是拟议工作所需的测序方法和生物信息学工具开发的领导者。候选人的全面初步结果证明了这一点。候选人的导师理查德·威尔逊（Richard Wilson）博士拥有指导基因组学科学家的既定记录。威尔逊博士帮助候选人建立了一个杰出的心理委员会，并在拟议的研究中指导他所需的跨学科技能。威尔逊博士以及这些额外的导师将协作支持并指导候选人取得成功的独立职业。要在指导阶段完成的第一个特定目标将创建整个基因组和转录组数据的集成以及体细胞事件的注释和优先级的新方法。特别重点将放在影响基因调节和剪接的非编码突变的表征上。独立阶段将朝着开发新的资源发展，以帮助研究人员在临床背景下解释突变。在这两个阶段中，候选人的研究都将重点关注这些问题的生物信息学方面，其重叠方式最小，但非常完全符合精神研究计划。从长远来看，候选人希望满足对在癌症基因组学领域工作的生物信息学研究者的日益增长的需求。 K99独立奖的奖项将是无价的，将他确立为需要专门从事生物信息学和数据分析的专家的领域的独立调查员