Ultrasensitive Quantitation of Circulating Tumor DNA

循环肿瘤 DNA 的超灵敏定量

• 批准号: 9126456
• 负责人: Aaron M Newman
• 金额: $ 17.1万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-13 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9126456
• 关键词: Address; Aftercare; American; Benchmarking; Biochemical; Bioinformatics; Biological; Biological Markers; Biopsy; Blood Circulation; Cancer Detection; Cancer Etiology; Cancer Patient; Carcinoma; Cessation of life; Classification; Computational Molecular Biology; DNA; Detection; Detection of Minimal Residual Disease; Diagnosis; Disease; Early Diagnosis; Early identification; Exercise; Foundations; Genomic Segment; Genomic approach; Genotype; Goals; Health; Hematologic Neoplasms; Hematopoietic Neoplasms; Histology; Human; Hybrids; IGH@ gene cluster; Image; Immunoglobulins; In Vitro; Laboratory Research; Malignant Neoplasms; Medicine; Methods; Minority; Molecular; Molecular Biology; Monitor; Mutate; Mutation; Nature; Non-Small-Cell Lung Carcinoma; Patient-Focused Outcomes; Patients; Phase; Plasma; Published Comment; Recovery; Recurrence; Reporter; Research; Residual Neoplasm; Residual Tumors; Sampling; Screening for cancer; Sensitivity and Specificity; Solid; Solid Neoplasm; Somatic Mutation; Source; Specificity; Staging; Statistical Algorithm; Statistical Models; Techniques; Testing; Training; Tumor Volume; Tumor-Derived; V(D)J Recombination; Validation; Work; advanced disease; base; burden of illness; cancer biomarkers; career; cost; deep sequencing; design; genome analysis; improved; knowledge base; large cell Diffuse non-Hodgkin' s lymphoma; liquid biopsy; mortality; novel; novel strategies; predicting response; research study; response; screening; treatment response; tumor; tumor DNA

 DESCRIPTION (provided by applicant): Cancer will be responsible for an estimated 585,720 American deaths in 2014 alone, highlighting the urgent need for improved disease detection and monitoring methods. Circulating tumor DNA (ctDNA) has the potential to revolutionize the identification and monitoring of cancer, but its detection in the blood plasma of most patients has remained costly and challenging. I recently helped develop an economical method (called CAPP- Seq) that combines ultra-deep sequencing and novel bioinformatics methods to achieve highly sensitive and specific noninvasive assessment of ctDNA with broad patient coverage. With this foundation, I hypothesize that ctDNA is a widely applicable biomarker for (1) sensitive and specific detection of residual disease, (2) monitoring of response to therapy, (3) and biopsy-free cancer screening and genotyping. To address this hypothesis, during the K99 and R00 phases, I propose to further develop and refine the computational and molecular biology framework of CAPP-Seq to lower its ctDNA detection limit by an order of magnitude. This will require introducing and validating novel statistical models and algorithms for genome analysis, and will involve wet laboratory research to both optimize the recovery of ctDNA molecules from plasma and eliminate sources of DNA error. During the training phase, I will further evaluate ctDNA detection levels at diagnosis in early stage patients with non-small cell lung cancer (NSCLC), the number one cause of cancer-related mortality, and will extend CAPP-Seq to diffuse large B-cell lymphoma (DLBCL), the commonest hematological malignancy. These two cancers are contrasted by the relative disparity of patient outcomes, an important consideration for disease surveillance, and will be studied as representatives of carcinomas and hematologic malignancies, respectively. Finally, during the independent phase, I will work with my group to devise statistical and genomic approaches for biopsy-free detection, genotyping, and classification of tumors that will be evaluated on plasma samples from diverse cancer patients, initially those with advanced disease as proof-of-principle, but ultimately on early-stage patients This project, if successful, will accelerate the early detection and monitoring of cancer.

 描述（由申请人提供）：仅 2014 年，癌症就导致了 585,720 名美国人死亡，这凸显了改进疾病检测和监测方法的迫切需要，循环肿瘤 DNA (ctDNA) 有可能彻底改变癌症的识别和监测。但在大多数患者的血浆中进行检测仍然成本高昂且具有挑战性，我最近帮助开发了一种经济的方法（称为 CAPP-Seq），该方法结合了超深度测序和新颖的生物信息学方法。在此基础上，我认为 ctDNA 是一种广泛适用的生物标志物，可用于 (1) 灵敏且特异性地检测残留疾病，(2) 监测治疗反应。 3) 和免活检癌症筛查和基因分型为了解决这一假设，在 K99 和 R00 阶段，我建议进一步开发和完善 CAPP-Seq 的计算和分子生物学框架，以将其 ctDNA 检测限降低一个数量级。震级。这将需要引入和验证用于基因组分析的新型统计模型和算法，并将涉及湿实验室研究，以优化血浆中 ctDNA 分子的回收并消除 DNA 错误来源。在训练阶段，我将进一步评估 ctDNA 检测水平。诊断早期非小细胞肺癌（NSCLC）患者，这是癌症相关死亡的第一大原因，并将将 CAPP-Seq 扩展到弥漫性大 B 细胞淋巴瘤（DLBCL），这是最常见的两种血液恶性肿瘤。癌症与患者结果的相对差异形成对比，这是疾病监测的重要考虑因素，并将分别作为癌症和血液恶性肿瘤的代表进行研究。最后，在独立阶段，我将与我的团队合作设计统计和基因组学。用于肿瘤的免活检检测、基因分型和分类的方法，这些方法将在来自不同癌症患者的血浆样本上进行评估，最初是那些患有晚期疾病的患者作为原理证明，但最终是在早期患者上这个项目如果成功，将要加速癌症的早期发现和监测。