Maximum efficiency sequencing using nuclease-based mutation enrichment and digital barcodes
使用基于核酸酶的突变富集和数字条形码进行最高效率测序
基本信息
- 批准号:9355330
- 负责人:
- 金额:$ 45.67万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-08-01 至 2020-07-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAllelesBiological MarkersCancer EtiologyCancer PatientClinicalComputational TechniqueDNADNA Sequence AlterationDetectionDevelopmentExonsFingerprintFutureGenesGenomic DNAGenomicsHeterogeneityLengthLiquid substanceLow PrevalenceLungMalignant NeoplasmsMalignant neoplasm of lungMethodologyMethodsMolecularMolecular ProfilingMutateMutationNamesNeoplasm MetastasisNoiseOligonucleotidesOncogenesOperative Surgical ProceduresPatientsPharmacotherapyPlasmaPreparationPublic HealthRecurrenceRoleSamplingScreening for cancerSensitivity and SpecificitySiteSomatic MutationSpeedSteamTechnologyTestingTimeTranslatingTumor Suppressor Genesbasecancer diagnosiscancer therapychemoradiationcirculating DNAclinical applicationclinical practicecohortcostcost effectivedeep sequencingdigitalfield studyfollow-upindividual patientinnovationliquid biopsymutantmutation screeningnext generation sequencingnovelnucleaseoutcome forecastpersonalized decisionpersonalized medicineplatform-independentpreventresponsescreeningsequencing platformsingle moleculetreatment choicetumortumor heterogeneity
项目摘要
Project Summary
Low-level tumor somatic DNA mutations can have profound implications for development of metastasis,
prognosis, choice of treatment, follow-up or early cancer detection strategies. Unless they are effectively
detected, these low-level mutations can misinform patient management decisions or become missed
opportunities for personalized medicine. Next generation sequencing (NGS) technologies can effectively reveal
prevalent somatic mutations, yet they 'lose steam' when it comes to detecting low-level DNA mutations in
tumors with clonal heterogeneity, or in bodily fluids, and their integration with clinical practice is problematic.
For mutations at allelic ratio of ~2-5% or less, NGS generates excessive false positives (‘noise’) independent
of sequencing depth and hinders personalized clinical decisions based on mutational profiling. Recent
adaptations of NGS to detect rare mutations using random barcoding strategies may overcome the noise but
invariably diminish its high throughput capability and increase costs.
We recently developed NaMe-PrO, a simple and powerful technology to eliminate wild-type sequences
from large numbers of targets in genomic DNA. NaME-PrO utilizes a nuclease guided by probes to thousands
of DNA targets, to render WT sequences non-amplifiable thereby allowing mutation–containing sequences to
amplify and be sequenced as if they were clonal mutations. This R33 proposes to develop quantitative NaME-
PrO (qNaME-PrO), which combines NaME-PrO with a novel use of molecular barcoding, to provide strict
enumeration of original mutation abundance for all mutant sequences following their enrichment. Thereby
converting rare mutations to high abundance mutations, boosting confidence in their detection and
circumventing the need for repeated and wasteful sequence reads during NGS. The method creates the
potential for massively parallel mutation enrichment prior to sequencing and engenders a new paradigm
whereby rare mutations do not require deep sequencing for their detection. The R33 (Aims 1&2) will optimize
and develop qNaME-PrO panels to cover all known mutation hotspots and full length exons in tumor
suppressor genes and oncogenes relevant to lung cancer. In Aim 3 the method will be field-tested in a
compilation of longitudinally collected plasma samples from patients undergoing radio-chemo-therapy.
Being able to extract ‘the mutated portion of a large genomic target’ from a mixed clinical sample prior
to downstream analysis will translate to a major boost in the speed, accuracy and cost of sequencing low-
prevalence mutations in heterogeneous tumors and bodily fluids and will accelerate clinical application of NGS
for cancer diagnosis, prognosis and management. Therefore relevance to Public Health is high.
项目概要
低水平的肿瘤体细胞 DNA 突变可能对转移的发展产生深远的影响,
预后、治疗选择、随访或早期癌症检测策略,除非它们是有效的。
如果检测到,这些低水平突变可能会误导患者管理决策或被遗漏
下一代测序(NGS)技术可以有效揭示个性化医疗的机会。
普遍的体细胞突变,但在检测低水平 DNA 突变时,它们“失去了动力”
具有克隆异质性或体液中的肿瘤,其与临床实践的结合是有问题的。
对于等位基因比率约为 2-5% 或更低的突变,NGS 会产生过多的假阳性(“噪音”),与此无关
测序深度并阻碍基于突变分析的个性化临床决策。
使用随机条形码策略对 NGS 进行改造以检测罕见突变可能会克服噪音,但
总是会降低其高吞吐量并增加成本。
我们最近开发了 NaMe-PrO,这是一种简单而强大的技术,可以消除野生型序列
NaME-PrO 利用由探针引导的核酸酶从基因组 DNA 中的大量目标中分离出数千个目标。
DNA 靶标,使 WT 序列不可扩增,从而允许包含突变的序列
像克隆突变一样进行扩增和测序。该 R33 建议开发定量 NaME-。
PrO (qNaME-PrO) 将 NaME-PrO 与分子条形码的新颖用途相结合,提供严格的
从而对富集后的所有突变序列的原始突变丰度进行计数。
将罕见突变转化为高丰度突变,增强对其检测和检测的信心
该方法避免了 NGS 期间重复和浪费的序列读取的需要。
在测序之前进行大规模并行突变富集的潜力并产生新的范例
因此,罕见突变不需要深度测序来进行检测,R33(目标 1 和 2)将进行优化。
并开发 qNaME-PrO panel 以涵盖肿瘤中所有已知的突变热点和全长外显子
在目标 3 中,该方法将在与肺癌相关的抑制基因和癌基因中进行现场测试。
从接受放化疗的患者身上纵向收集的血浆样本的汇编。
能够事先从混合临床样本中提取“大型基因组靶标的突变部分”
下游分析将大大提高测序的速度、准确性和成本
异质性肿瘤和体液中的流行突变将加速NGS的临床应用
因此,与公共健康的相关性很高。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(1)
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G. Mike Makrigiorgos其他文献
G. Mike Makrigiorgos的其他文献
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{{ truncateString('G. Mike Makrigiorgos', 18)}}的其他基金
Comprehensive minimal residual disease tracking in cancer
癌症的全面微小残留病追踪
- 批准号:
9920128 - 财政年份:2018
- 资助金额:
$ 45.67万 - 项目类别:
Prognostic potential of low-level mutations in meylodysplastic syndrome
骨髓增生异常综合征低水平突变的预后潜力
- 批准号:
8787719 - 财政年份:2014
- 资助金额:
$ 45.67万 - 项目类别:
Temperature-Tolerant COLD-PCR enables mutation-enriched targeted re-sequencing
耐温 COLD-PCR 可实现突变富集的靶向重测序
- 批准号:
8591934 - 财政年份:2013
- 资助金额:
$ 45.67万 - 项目类别:
High-throughput technology that enables sequencing depth for colorectal CA
高通量技术可实现结直肠 CA 深度测序
- 批准号:
8333344 - 财政年份:2011
- 资助金额:
$ 45.67万 - 项目类别:
High-throughput technology that enables sequencing depth for colorectal CA
高通量技术可实现结直肠 CA 深度测序
- 批准号:
8153972 - 财政年份:2011
- 资助金额:
$ 45.67万 - 项目类别:
Technology for sensitive and reliable mutational profiling in pancreatic cancer
胰腺癌敏感且可靠的突变分析技术
- 批准号:
7795122 - 财政年份:2009
- 资助金额:
$ 45.67万 - 项目类别:
Technology for sensitive and reliable mutational profiling in pancreatic cancer
胰腺癌敏感且可靠的突变分析技术
- 批准号:
7626951 - 财政年份:2009
- 资助金额:
$ 45.67万 - 项目类别:
Technology for sensitive and reliable mutational profiling in pancreatic cancer
胰腺癌敏感且可靠的突变分析技术
- 批准号:
8022903 - 财政年份:2009
- 资助金额:
$ 45.67万 - 项目类别:
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