High-Throughput Tumor Genomic Profiling by Massively Parallel Sequencing

描述（由申请人提供）：癌症的诊断和治疗决定历来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来预测临床行为并指定靶向治疗的最佳使用。最终，个性化癌症药物的交付将需要在临床和转化领域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，这是一个基于质谱的基因分型平台，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、分析灵敏度和可识别的基因组改变类型方面仍然有限。最近，通过大规模平行测序（MPS）技术，已经可以在技术上可行和经济上可获得多方面的肿瘤特征。因此，该应用程序的目标是将OncoMap方法迁移到MPS平台（Illumina），并通过诸如溶液相外显子捕获和样品条形码等创新来增强功能。与达纳-法伯癌症研究所和布罗德研究所的同事一起，我们已经生成了初步数据，显示了这些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，在这个R33应用程序中，我们将实现一个变革性的系统肿瘤基因组分析平台，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、液相外显子捕获和单分子测序的方法，以同时在至少12个肿瘤样本中对约150个癌症基因进行稳健的突变分析（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的石蜡包埋肿瘤组织的DNA来测试MPS-OncoMap的性能，这些组织的“基本真相”是已知的多种遗传改变。最后，我们将在生产规模上实现MPS-OncoMap，为许多转化肿瘤学应用提供系统分析。实现这些目标可能会为全面的肿瘤基因组分析提供明确的途径，并在转化和临床肿瘤学领域产生深远的影响。

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.