Identification of Somatic Mutations in Rare Subclones of Solid Tumors

实体瘤罕见亚克隆中体细胞突变的鉴定

• 批准号: 8337324
• 负责人: Olivier Harismendy
• 金额: $ 15.47万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-22 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8337324
• 关键词: Affect; Biological Assay; Biological Markers; Breast; Calibration; Cancer cell line; Cell Fraction; Cell Line; Cells; Clinic; Clinical; Clinical Trials; Clonal Evolution; Collaborations; Colon; Colonic Neoplasms; DNA; DNA Sequence; DNA amplification; Data; Databases; Detection; Disease; Disease Progression; Dissection; Drug resistance; Emerging Technologies; Ensure; Formalin; Freezing; Frequencies; Funding; Gene-Modified; Genome; Goals; High Prevalence; Laboratories; Lasers; Libraries; Ligation; Malignant Neoplasms; Measures; Methods; Microfluidics; Modeling; Mutate; Mutation; Neoplasm Metastasis; Noise; Non-Malignant; Normal Cell; Normal tissue morphology; Oncogenes; Oncogenic; Oncologist; One-Step dentin bonding system; Paraffin Embedding; Performance; Pharmaceutical Preparations; Phase; Preparation; Prevalence; Research Project Grants; Sampling; Sensitivity and Specificity; Series; Side; Signal Pathway; Signal Transduction; Site; Solid Neoplasm; Somatic Mutation; Specificity; TP53 gene; Technology; Tissues; Training; Translational Research; Validation; Variant; assay development; base; cancer cell; cancer recurrence; cancer therapy; cost; cost effective; design; improved; malignant breast neoplasm; meetings; neoplastic cell; response; tumor

DESCRIPTION (provided by applicant): Cells within a tumor sample are known to be heterogeneous, due to the contamination from non-malignant tissue or the presence of multiple sub-clones, each carrying different somatic mutations. The majority of somatic mutations identified to date are clustered (mutational hotspots) in the functional sites of a few "cancer genes" with key roles in cell signaling pathways of proliferation and survival. Somatic mutations in cancer genes modify their oncogenic potential or affect sensitivity to therapy. Currently available assays that are able to detect rare somatic mutations are not comprehensive. They are usually focused on a few commonly mutated loci, and not implemented in clinical setting due to cost or technical reasons. Therefore, a current technological need exists for an assay that can reliably detect and accurately measure the prevalence of multiple somatic mutations present only in a fraction of the cells in a heterogeneous tumor. Such an assay would facilitate translational research to study the selection of tumor sub-clones during disease progression and treatment. Additionally the assay could be used by clinicians to improve tumor characterization and selection of therapy choices during clinical trials. We propose to leverage the emerging technology of targeted high-throughput sequencing to develop a cost- effective assay capable of detecting somatic mutations that are present in e1% of tumor cells. Specifically we will perform ultra-deep targeted sequencing (UDT-Seq) of ~100 kb in each tumor assaying 518 mutational hotspots located in 46 cancer genes. The selected mutational hotspots cover ~87% of all entries in the COSMIC database. We will develop a streamlined sample preparation in collaboration with RainDance Technologies to ensure a straightforward implementation in the clinic. This sample preparation integrates the targeting PCR and the library preparation in one step using chimeric PCR primers. The amplified targeted hotspots (200bp long) will be thus directly sequenced on the Illumina Genome Analyzer (GAII) at a very high coverage (~20,000x). We will then precisely model the sequencing error using calibration samples to filter true mutations from the sequencing noise. Our specific aims are: 1) To calibrate the UDT-Seq assay by analyzing both pooled DNA samples containing precise ratios of known SNPs and DNA samples spiked with low amounts of mutated DNA from cancer cells. For this, we will develop a statistical sequencing error model to detect rare mutations in deep sequence. 2) To evaluate the accuracy of the UDT- Seq assay to detect rare somatic mutations in both frozen and formalin fixed paraffin embedded solid tumors. If the quantitative milestones set for this pilot phase of the UDT-Seq assay development are met, we will apply for R33 funding to further develop and make this assay broadly available to clinical oncologists for their own translational research through a CLIA laboratory.

描述（由申请人提供）：已知肿瘤样品中的细胞是由于非恶性组织的污染或存在多个亚clones的污染，每种细胞是异质的，每种都带有不同的体细胞突变。迄今为止确定的大多数体细胞突变是在几个“癌症基因”的功能部位聚集（突变热点），在增殖和存活的细胞信号传导途径中具有关键作用。癌症基因的体细胞突变改变了其致癌潜力或影响对治疗的敏感性。目前能够检测到罕见的体细胞突变的可用测定并不全面。它们通常专注于一些通常突变的基因座，并且由于成本或技术原因而在临床环境中不实施。因此，对于可以可靠地检测并准确测量仅在异质性肿瘤中的细胞中仅存在的多个体细胞突变的患病率的测定的当前技术需求。这样的测定将促进转化研究，以研究疾病进展和治疗过程中肿瘤亚cl骨的选择。此外，临床医生可以使用该测定法改善临床试验期间的肿瘤表征和选择的治疗选择。我们建议利用有针对性的高通量测序的新兴技术来开发能够检测E1％肿瘤细胞中存在的体细胞突变的成本有效测定。具体而言，我们将在每个肿瘤分析的518个突变热点中，对位于46个癌症基因的518个突变热点进行超深的靶向测序（UDT-SEQ）。所选的突变热点覆盖了宇宙数据库中所有条目的87％。我们将与Raindance Technologies合作开发简化的样品制备，以确保诊所中的直接实施。该样品制备使用嵌合PCR引物一步一步地整合了靶向PCR和库制备。因此，放大的靶向热点（200bp长）将在Illumina基因组分析仪（GAII）上直接测序，以非常高的覆盖率（〜20,000x）进行。然后，我们将使用校准样品精确地对测序误差进行建模，以从测序噪声中滤除真实的突变。我们的具体目的是：1）通过分析两个合并的DNA样品来校准UDT-Seq分析，这些样品包含已知SNP的精确比例和含量低的癌细胞突变DNA的DNA样品的精确比率。为此，我们将开发一个统计测序误差模型，以检测深层序列的稀有突变。 2）评估UDT-SEQ分析的准确性，以检测冷冻和福尔马林固定石蜡嵌入的实体瘤中罕见的体细胞突变。如果满足了UDT-Seq分析开发的此试点阶段的定量里程碑，我们将申请R33资金，以进一步开发并使该测定法可以通过CLIA实验室为自己的翻译研究广泛地使用。