Novel Computation Methods for the Analysis of Cell-Free DNA Sequence Data

用于分析无细胞 DNA 序列数据的新计算方法

基本信息

批准号：
10004012
负责人：
Steven M. Dubinett
金额：
$ 55.22万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10004012
关键词：
Address Algorithmic Software Area Attention Autoimmune Diseases Bioinformatics Biopsy Blood Blood Circulation Blood specimen Cancer Detection Cancer Patient Cardiovascular Diseases Caring Cells Clinical Clinical Trials Collection Computer software Computing Methodologies Copy Number Polymorphism DNA DNA Methylation DNA Sequence DNA analysis DNA sequencing Data Dendritic Cells Detection Development Diagnosis Diagnostic Disease Disease Management Epigenetic Process Face Human Immunotherapy Individual Information Retrieval Knowledge Discovery Leukocytes Malignant Neoplasms Malignant neoplasm of liver Malignant neoplasm of lung Measures Medicine Methods Methylation Monitor Mutation Nature Non-Invasive Cancer Detection Nucleotides Organ Transplantation Patient Monitoring Patients Prenatal Diagnosis Procedures Property Regimen Resolution Sampling Signal Transduction Software Tools Solid Neoplasm Surrogate Markers Technology Time Tissues Transplantation Trauma Tumor Tissue Tumor-Derived Validation Variant base bioinformatics tool bisulfite sequencing cancer type cell free DNA clinical application cohort computational suite computerized tools design disease diagnosis epigenomics exome sequencing fetal genomic profiles immunotherapy clinical trials improved innovation liquid biopsy methylome neoplastic cell next generation sequencing novel open source organ transplant rejection prenatal prognostic public health relevance repository tool treatment response tumor variant detection whole genome

项目摘要

Project Summary Non-invasive detection of cell-free DNA(cfDNA) promises to impact clinical regimens of a wide range of diseases, e.g. prenatal conditions, cancer, transplantation, autoimmune disease, trauma, and cardiovascular disease. While this field is emerging as one of the most promising and exciting areas of medicine, few bioinformatics tools are available to facilitate the information extraction from cfDNA sequencing data, although cfDNA data possesses many unique properties. In this proposal, we aim to generate a suite of computational methods facilitating the analysis and interpretation of cfDNA sequencing data, and demonstrate its utilities in cancer detection and characterization. Specifically, we will develop computational methods for the following applocations: (1) Ultra-sensitively detect and locate multiple types of cancer using cfDNA methylome; (2) Detect Copy Number Variation (CNV) in cfDNA sequencing data; (3) Annotate Single Nucleotide Variations (SNV) in cfDNA sequencing data. These computational tools will be validated with cfDNA samples collected from a cohort of lung cancer patients participating in an immunotherapy clinical trial, a repository of blood samples from patients with different types of cancer, and a cohort of liver cancer patients. Although we use cancer as the main context for developing these applications, many of the methods can be adapted to other diseases, e.g. prenatal diagnosis and organ transplant monitoring. We expect that the above open-source tools will significantly facilitate cfDNA- based disease diagnosis and monitoring. 1

项目概要游离 DNA (cfDNA) 的非侵入性检测有望影响多种疾病的临床治疗方案疾病，例如产前疾病、癌症、移植、自身免疫性疾病、创伤和心血管疾病。虽然这一领域正在成为最有前途和最令人兴奋的医学领域之一，但很少有人生物信息学工具可用于促进从 cfDNA 测序数据中提取信息，尽管 cfDNA 数据拥有许多独特的属性。在这个提案中，我们的目标是生成一套计算促进 cfDNA 测序数据分析和解释的方法，并展示其在癌症检测和表征。具体来说，我们将开发以下计算方法应用：（1）利用cfDNA甲基化组超灵敏地检测和定位多种类型的癌症； (2) 检测 cfDNA 测序数据中的拷贝数变异 (CNV)； (3) 注释单核苷酸变异（SNV） cfDNA 测序数据。这些计算工具将通过从队列中收集的 cfDNA 样本进行验证参与免疫治疗临床试验的肺癌患者，这是患者血液样本的存储库患有不同类型的癌症，以及一组肝癌患者。虽然我们以癌症为主要背景为了开发这些应用，许多方法可以适用于其他疾病，例如产前诊断和器官移植监测。我们预计上述开源工具将显着促进 cfDNA- 基于疾病的诊断和监测。 1