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首页> 外文会议>Pacific Symposium on Biocomputing >AN INTEGRATED FRAMEWORK FOR REPORTING CLINICALLY RELEVANT BIOMARKERS FROM PAIRED TUMOR/NORMAL GENOMIC AND TRANSCRIPTOMIC SEQUENCING DATA IN SUPPORT OF CLINICAL TRIALS IN PERSONALIZED MEDICINE
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AN INTEGRATED FRAMEWORK FOR REPORTING CLINICALLY RELEVANT BIOMARKERS FROM PAIRED TUMOR/NORMAL GENOMIC AND TRANSCRIPTOMIC SEQUENCING DATA IN SUPPORT OF CLINICAL TRIALS IN PERSONALIZED MEDICINE

机译：一种综合框架，用于报告来自配对肿瘤/正常基因组和转录组序列测序数据的临床相关的生物标志物，以支持个性化医学中的临床试验

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The ability to rapidly sequence the tumor and germline DNA of an individual holds the eventual promise of revolutionizing our ability to match targeted therapies to tumors harboring the associated genetic biomarkers. Analyzing high throughput genomic data consisting of millions of base pairs and discovering alterations in clinically actionable genes in a structured and real time manner is at the crux of personalized testing. This requires a computational architecture that can monitor and track a system within a regulated environment as terabytes of data are reduced to a small number of therapeutically relevant variants, delivered as a diagnostic laboratory developed test. These high complexity assays require data structures that enable real-time and retrospective ad-hoc analysis, with a capability of updating to keep up with the rapidly changing genomic and therapeutic options, all under a regulated environment that is relevant under both CMS and FDA depending on application. We describe a flexible computational framework that uses a paired tumor/normal sample allowing for complete analysis and reporting in approximately 24 hours, providing identification of single nucleotide changes, small insertions and deletions, chromosomal rearrangements, gene fusions and gene expression with positive predictive values over 90%. In this paper we present the challenges in integrating clinical, genomic and annotation databases to provide interpreted draft reports which we utilize within ongoing clinical research protocols. We demonstrate the need to retire from existing performance measurements of accuracy and specificity and measure metrics that are meaningful to a genomic diagnostic environment. This paper presents a three-tier infrastructure that is currently being used to analyze an individual genome and provide available therapeutic options via a clinical report. Our framework utilizes a non-relational variant-centric database that is scaleable to a large amount of data and addresses the challenges and limitations of a relational database system. Our system is continuously monitored via multiple trackers each catering differently to the diversity of users involved in this process. These trackers designed in analytics web-app framework provide status updates for an individual sample accurate to a few minutes. In this paper, we also present our outcome delivery process that is designed and delivered adhering to the standards defined by various regulation agencies involved in clinical genomic testing.
机译：快速测序肿瘤和个人的生殖细胞DNA的能力持有革命化我们对靶向治疗匹配肿瘤窝藏相关的遗传标志物能力的最终承诺。分析高吞吐量由数百万个碱基对的基因组数据和结构化和实时的方式发现改建临床可行的基因是个性化测试的症结所在。这需要一个计算架构，可以监控和监管的环境中跟踪系统TB级的数据减少到少数治疗相关的变种，作为提供诊断实验室开发的测试。这些高度复杂的试验要求的数据结构，使实时和追溯即席分析，以更新的能力，以跟上快速变化的基因组和治疗方案，所有这些都是相关的一个规范的环境下下，CMS和FDA都取决于在应用程序。我们描述了使用配对的肿瘤/正常样品允许完整的分析和在大约24小时报告，上提供的单核苷酸变化，小的插入和缺失，染色体重排，基因融合和基因表达与阳性预测值识别柔性计算框架90％。在本文中，我们提出了挑战，在整合临床，基因组和注释数据库，以提供我们利用内正在进行的临床研究方案的解释草案的报告。我们证明需要从准确性和特异性措施的指标是有意义的基因诊断环境的现有性能测量退休。本文介绍了当前正在用来分析一个人的基因组，并通过提供临床报告提供治疗选择三层架构。我们的架构利用非关系变异为中心的数据库，该数据库可扩展到大量的数据和地址的关系数据库系统所面临的挑战和限制。我们的系统，持续向多个跟踪每个餐饮不同监测，参与这一进程的用户的多样性。这些跟踪器在分析web应用框架，专为单个样品精确到几分钟，提供状态更新。在本文中，我们也提出我们正在设计和交付坚持通过参与临床试验的基因组调控各机构定义的标准结果分娩过程。

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