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: 8155075
• 负责人: Olivier Harismendy
• 金额: $ 12.86万
• 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/8155075
• 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. PUBLIC HEALTH RELEVANCE: We propose to develop an assay to analyze somatic mutations in rare subclones of solid-tumors. This assay will feature microfluidic-based sample preparation method and high throughput DNA sequencing. It would be the most comprehensive assay to identify rare somatic mutational hotspots in a clinical setting and clinical oncologists will potentially use this assay to identify new biomarkers for disease progression or predictive of drug response, for a more personalized treatment of cancer.

描述(申请人提供)：已知肿瘤样本中的细胞是异质性的，这是由于来自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。到目前为止发现的大多数体细胞突变都聚集在少数癌症基因的功能部位(突变热点)，这些基因在细胞增殖和存活的信号通路中发挥关键作用。癌症基因的体细胞突变改变了它们的致癌潜力或影响了对治疗的敏感性。目前，能够检测罕见体细胞突变的分析方法并不全面。它们通常集中在几个常见的突变基因座上，由于成本或技术原因而没有在临床环境中实施。因此，目前的技术需要一种能够可靠地检测和准确测量在异质肿瘤中只存在于一小部分细胞中的多个体细胞突变的流行程度的检测方法。这样的分析将促进转化研究，以研究疾病进展和治疗过程中肿瘤亚克隆的选择。此外，在临床试验期间，临床医生可以使用该分析来改善肿瘤的特征和治疗选择。我们建议利用新兴的靶向高通量测序技术来开发一种成本效益高的分析方法，能够检测存在于E1%的肿瘤细胞中的体细胞突变。具体地说，我们将在每个肿瘤中进行~100kb的超深度靶向测序(UDT-Seq)，分析位于46个癌症基因的518个突变热点。选定的突变热点覆盖了COSMIC数据库中所有条目的87%。我们将与RainDance Technologies合作开发一种简化的样品制备方法，以确保在临床上直接实施。该样品制备方法将靶向PCR和文库制备结合在一起，使用嵌合的聚合酶链式反应引物。因此，扩增的目标热点(200bp长)将在Illumina Genome Analyzer(GAII)上以非常高的覆盖率(~20,000倍)直接测序。然后，我们将使用校准样本对测序错误进行精确建模，以从测序噪声中筛选出真正的突变。我们的具体目标是：1)通过分析包含已知SNPs的精确比例的混合DNA样本和添加了来自癌细胞的低数量突变DNA的DNA样本，来校准UDT-Seq分析。为此，我们将开发一个统计测序错误模型来检测深层序列中的罕见突变。2)评价UDT-Seq法在冰冻和福尔马林固定石蜡包埋实体瘤中检测罕见体细胞突变的准确性。如果为UDT-Seq分析开发的这一试点阶段设定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分析广泛地提供给临床肿瘤学家，供他们通过CLIA实验室进行自己的翻译研究。 公共卫生相关性：我们建议开发一种分析实体肿瘤罕见亚克隆的体细胞突变的方法。该分析将以基于微流控的样品制备方法和高通量DNA测序为特色。这将是在临床环境中识别罕见的体细胞突变热点的最全面的测试，临床肿瘤学家可能会使用这种测试来识别新的疾病进展或预测药物反应的生物标记物，以便更个性化地治疗癌症。