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）：已知肿瘤样本中的细胞是异质的，这是由于非恶性组织的污染或存在多个亚克隆，每个亚克隆携带不同的体细胞突变。迄今为止鉴定的大多数体细胞突变聚集在少数“癌症基因”的功能位点中（突变热点），这些基因在细胞增殖和存活的信号传导途径中起关键作用。癌症基因的体细胞突变改变了它们的致癌潜力或影响对治疗的敏感性。目前可用的能够检测罕见体细胞突变的测定并不全面。它们通常集中在几个常见的突变基因座上，并且由于成本或技术原因而不在临床环境中实施。因此，目前的技术需要一种测定法，其可以可靠地检测和准确地测量仅存在于异质性肿瘤中的一部分细胞中的多种体细胞突变的患病率。这种测定将促进转化研究以研究疾病进展和治疗期间肿瘤亚克隆的选择。此外，临床医生可以使用该测定来改善肿瘤表征和临床试验期间的治疗选择。我们建议利用靶向高通量测序的新兴技术来开发能够检测存在于e1%肿瘤细胞中的体细胞突变的具有成本效益的测定。具体来说，我们将在每个肿瘤中进行约100 kb的超深度靶向测序（UDT-Seq），检测位于46个癌症基因中的518个突变热点。所选择的突变热点覆盖COSMIC数据库中所有条目的约87%。我们将与RainDance Technologies合作开发一种简化的样品制备方法，以确保在临床中直接实施。该样品制备使用嵌合PCR引物在一个步骤中整合靶向PCR和文库制备。因此，扩增的靶向热点（200 bp长）将在Illumina基因组分析仪（GAII）上以非常高的覆盖度（~20，000 x）直接测序。然后，我们将使用校准样品精确地对测序误差进行建模，以从测序噪声中过滤出真实的突变。我们的具体目标是：1）通过分析含有精确比例的已知SNP的合并DNA样品和掺有少量来自癌细胞的突变DNA的DNA样品来校准UDT-Seq测定。为此，我们将开发一个统计测序错误模型来检测深度序列中的罕见突变。2)评价UDT-Seq检测法检测冷冻和福尔马林固定石蜡包埋实体瘤中罕见体细胞突变的准确性。如果UDT-Seq检测开发的这个试验阶段的定量里程碑得到满足，我们将申请R33资金，以进一步开发并使该检测广泛提供给临床肿瘤学家，通过CLIA实验室进行自己的转化研究。