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

 描述（由申请人提供）：癌症由起始细胞基因组内的体细胞突变引起。这些突变有多种形式，包括小的单碱基取代、大的插入和缺失、染色体重排等。突变相对于注释基因座的位置也有所不同。一些突变发生在外显子内，对蛋白质序列和功能具有直接和容易预测的影响。其他突变通过发生在影响基因表达和RNA剪接的调控区域内而间接影响基因功能。 下一代测序已经改变了探索人类癌症突变景观的潜力。然而，大量复杂数据集的快速创建以及缺乏对这些数据进行综合分析的既定方法导致了关键的研究瓶颈。迄今为止，研究主要集中在已知外显子内发生的最容易检测和解释的编码突变上。非编码基因和控制基因表达和剪接的调控元件的突变在很大程度上被忽视了。同样，对突变的临床意义的解释也仅限于少数几个特征最充分的某些基因的反复突变“热点”。拟议的项目将开发新的工具来识别和表征具有调控而不是蛋白质编码后果的突变。此外，我们将开发资源，帮助研究界解释这些突变可能的临床相关性。为了探索这些知识差距并测试我们的新工具，我们将把它们应用于基因组研究所正在进行的大规模基因组/转录组测序项目的一组肿瘤样本。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控突变驱动的，其中一部分可能提示新的治疗策略。 华盛顿大学医学院的基因组研究所是世界上少数几个成功地将医生科学家的密切互动与大规模基因组测序设施和世界一流的计算基础设施相结合的地方之一。基因组研究所在开发拟议工作所需的测序方法和生物信息学工具方面处于领先地位。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·威尔逊博士在指导基因组学科学家方面有着良好的记录。威尔逊帮助候选人建立了一个优秀的指导委员会，该委员会具有指导他进行拟议研究所需的跨学科技能。威尔逊博士沿着这些额外的导师将共同支持和指导候选人走向成功的独立职业生涯。 第一个具体目标将在指导阶段完成，将创建整合全基因组和转录组数据以及体细胞事件注释和优先级排序的新方法。特别强调将放在非编码突变的影响基因调控和剪接的表征。独立阶段将转向开发新的资源，以帮助研究人员在临床背景下解释突变。在这两个阶段中，候选人的研究将主要集中在这些问题的生物信息学方面，其重叠最小，但与导师的研究计划高度互补。从长远来看，候选人希望填补在癌症基因组学领域工作的生物信息学研究人员日益增长的需求。K99独立之路奖将是非常宝贵的，以建立他作为一个独立的研究人员在一个领域，这是在需要专门从事生物信息学和数据分析的专家

 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