High-Throughput Tumor Genomic Profiling by Massively Parallel Sequencing

通过大规模并行测序进行高通量肿瘤基因组分析

• 批准号: 8035051
• 负责人: Levi A. Garraway
• 金额: $ 22.5万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-20 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8035051
• 关键词: Address; Affect; Algorithms; Anatomic Sites; Antineoplastic Agents; Base Sequence; Behavior; Biological Assay; Cancer Etiology; Cancer Gene Mutation; Cancer Patient; Cancer cell line; Cell physiology; Clinical; Clinical Oncology; DNA; Dana-Farber Cancer Institute; Data; Doctor of Medicine; Doctor of Philosophy; Drug Delivery Systems; Exons; Formalin; Freezing; Genetic; Genetic Polymorphism; Genomics; Genotype; Goals; Human; Hybrids; Individual; Institutes; Knowledge; Lead; Malignant Neoplasms; Medical; Medicine; Methodology; Methods; Molecular Epidemiology of Cancer; Mutation; Oncogenes; Paraffin Embedding; Patients; Performance; Phase; Production; Proteins; Sampling; Sensitivity and Specificity; Solutions; Somatic Mutation; Specific qualifier value; Specimen; Speed; Technology; Testing; Tissues; Tumor Tissue; base; cancer diagnosis; cancer genomics; cancer therapy; cost; cost effective; drug metabolism; empowered; genetic profiling; genotyping technology; innovation; insertion/deletion mutation; oncology; performance tests; single molecule; therapeutic target; tumor

DESCRIPTION (provided by applicant): Cancer diagnosis and treatment decisions have historically been based on anatomic sites of origin and spread; however, the emerging paradigm incorporates key genetic attributes of a given tumor to predict clinical behavior and specify the optimal use of targeted therapeutics. Ultimately, the delivery of personalized cancer medicine will require systematic characterization of all therapeutically informative tumor genomic alterations in the clinical and translational arena. Previously, we developed and deployed OncoMap, a mass spectrometric genotyping-based platform that enables high-throughput profiling of hundreds of known mutations across dozens of cancer genes. This platform performs well and has launched a robust translational oncology effort. However, the mass spectrometric genotyping technology remains limited in scope, assay sensitivity, and the type of genomic alteration that can be identified. Recently, it has become possible to render multi-faceted tumor characterization both technologically feasible and economically accessible through massively parallel sequencing (MPS) technology. Thus, the goal of this application is to migrate the OncoMap approach to an MPS platform (Illumina), empowered by innovations such as solution-phase exon capture and sample barcoding. Together with our colleagues at the Dana-Farber Cancer Institute and Broad Institute, we have generated preliminary data showing the feasibility and promise of each of these components, thereby raising the possibility of comprehensive tumor sequencing at a low per-sample cost. Accordingly, in this R33 application we will implement a transformative platform for systematic tumor genomic profiling, which we call "MPS-OncoMap." To accomplish this we will optimize the methodology for sample barcoding technology, solution-phase exon capture, and single-molecule sequencing to enable robust mutation profiling (base mutations, amplifications, and deletions) across ~150 cancer genes in at least 12 tumor samples simultaneously. We will test the performance of MPS-OncoMap using DNA from cancer cell lines, frozen tumors, and formalin-fixed, paraffin-embedded tumor tissue for which the "ground truth" is known for multiple genetic alterations. Finally, we will implement MPS-OncoMap at production scale to enable systematic analyses for many translational oncology applications. Achieving these Aims may inform a definitive path to comprehensive tumor genomic profiling with far-reaching impact in the translational and clinical oncology arena. PUBLIC HEALTH RELEVANCE: High-Throughput Cancer Gene Mutation Profiling y Massively Parallel Sequencing PIs: Levi A. Garraway, M.D., Ph.D. and Laura E. MacConaill, Ph.D. Many cancers are caused by mutations in the DNA that give rise to altered proteins or cellular processes. The use of anticancer drugs targeting such proteins can lead to significant clinical benefit, but it remains impractical to profile the tumor of each cancer patient for the presence of such alterations. This application seeks to adapt a powerful new sequencing technology together with other innovations to make it possible to detect many informative cancer gene mutations in clinical tumor specimens. Once implemented, this approach could speed the advent of personalized cancer medicine.

描述（由申请人提供）：癌症诊断和治疗决策历史上一直基于起源和扩散的解剖部位;然而，新兴的范例结合了给定肿瘤的关键遗传属性，以预测临床行为并指定靶向治疗的最佳使用。最终，个性化癌症药物的递送将需要在临床和转化竞技场中对所有治疗信息肿瘤基因组改变进行系统表征。 此前，我们开发并部署了OncoMap，这是一种基于质谱基因分型的平台，可以对数十种癌症基因中的数百种已知突变进行高通量分析。该平台表现良好，并启动了强大的转化肿瘤学工作。然而，质谱基因分型技术在范围、测定灵敏度和可以鉴定的基因组改变的类型方面仍然有限。 最近，通过大规模平行测序（MPS）技术，可以实现多方面的肿瘤表征，在技术上可行且经济上可行。因此，本申请的目标是将OncoMap方法迁移到MPS平台（Illumina），该平台由解决方案阶段外显子捕获和样品条形码等创新技术授权。我们与Dana-Farber癌症研究所和Broad研究所的同事一起，已经生成了初步数据，显示了每个组件的可行性和前景，从而提高了以低样本成本进行全面肿瘤测序的可能性。 因此，在此R33应用程序中，我们将实施一个用于系统性肿瘤基因组分析的变革平台，我们称之为“MPS-OncoMap”。“为了实现这一目标，我们将优化样品条形码技术，溶液阶段外显子捕获和单分子测序的方法，以同时在至少12个肿瘤样品中的约150个癌症基因中实现稳健的突变谱分析（碱基突变，扩增和缺失）。我们将使用来自癌细胞系、冷冻肿瘤和福尔马林固定、石蜡包埋的肿瘤组织的DNA测试MPS-OncoMap的性能，其中“基础事实”已知有多种遗传改变。最后，我们将在生产规模上实施MPS-OncoMap，以实现对许多转化肿瘤学应用的系统分析。实现这些目标可能为全面的肿瘤基因组分析提供明确的途径，在转化和临床肿瘤学竞技场中具有深远的影响。 公共卫生相关性：高通量癌症基因突变分析和大规模平行测序PI：Levi A. Garraway，医学博士，博士和Laura E. MacConaill博士许多癌症是由DNA突变引起的，这些突变引起蛋白质或细胞过程的改变。靶向这些蛋白质的抗癌药物的使用可以导致显著的临床益处，但是针对这些改变的存在对每个癌症患者的肿瘤进行分析仍然是不切实际的。该应用旨在采用强大的新测序技术以及其他创新技术，以便能够检测临床肿瘤标本中的许多信息性癌症基因突变。一旦实施，这种方法可以加速个性化癌症药物的出现。