A Comprehensive Protocol for Tissue of Origin Prediction in Circulating Cell-Free DNA

循环游离 DNA 组织起源预测的综合方案

• 批准号: 10373970
• 负责人: Christa Caggiano
• 金额: $ 3.86万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10373970
• 关键词: ALS patients; Address; Age; Aging; Algorithms; Amyotrophic Lateral Sclerosis; Apoptosis; Autoimmune Diseases; Biological Markers; Blood; Blood Cells; Blood Circulation; Cell Death; Cell Survival; Cells; Clinical; Clinical Trials; Complementary DNA; DNA; DNA Methylation; DNA Sequence; Data; Degenerative Disorder; Development; Diagnosis; Disease; Disease Progression; Drug usage; Epigenetic Process; Growth; Health; Human body; Individual; Lead; Length; Malignant Neoplasms; Measures; Methods; Methylation; Monitor; Motor Neurons; Necrosis; Organ Transplantation; Patients; Performance; Physicians; Protocols documentation; Public Health; Reproducibility; Research; Sampling; Severity of illness; Signal Transduction; Site; Skeletal Muscle; Statistical Methods; Supervision; Symptoms; Technology; Tissues; Work; algorithm development; base; biomarker discovery; bisulfite sequencing; cell free DNA; clinical application; cohort; cost; design; disease diagnosis; drug development; drug discovery; improved; muscle degeneration; potential biomarker; tissue degeneration; tissue trauma; treatment response; whole genome

PROJECT ABSTRACT Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising non- invasive biomarker for cell death. Recent studies have demonstrated that cfDNA levels are correlated with cancer, tissue trauma, autoimmune disease, and organ transplants, indicating the potential clinical utility of cfDNA. CfDNA, however, can originate from any number of tissues throughout the body, and some of the cfDNA present in an individual at a given moment is likely originating from healthy cell turnover. To better understand tissue degeneration, especially in the context of disease, a reliable estimate of the tissue of origin of cfDNA is needed. Identifying the tissue of origin of cfDNA will have direct impact on disease diagnosis and monitoring, and in quantitative biomarker discovery. Pre-existing methods for tissue of origin decomposition are inadequate for cfDNA. Firstly, cDNA is only present in a small amount in the blood. Current decomposition methods generally rely on array-based platforms that require an onerous amount of patient blood, which may not be clinically applicable. An alternative is whole genome bisulfite sequencing data, which requires lower input cfDNA, but is noisy. This data is not addressed with previous methods. Finally, accurately decomposing cfDNA mixtures requires a robust understanding of all possible tissue types that could potentially contribute to the mixture. This robust reference, however, is nearly impossible to assemble, as there are hundreds of distinct tissue types, and because the methylation state for a CpG in a tissue can vary. This could lead to biases in the decomposition results of previous methods. In this proposal, we aim to address the limitations of previous methods by developing a comprehensive workflow for cfDNA tissue-of-origin prediction. We will develop a statistical method for predicting the tissue of origin of cfDNA, allowing for low read count data and unknown tissue types (Aim 1). We hypothesize that this will reduce bias in decomposition estimates and allow our method to be more widely used than previous methods. Additionally, we propose developing a capture protocol that will enrich for cfDNA fragments that are informative of tissue or disease status. This protocol will be designed to use with only small amounts of input cfDNA (Aim 2). We hypothesize that a capture panel approach will vastly reduce sequencing costs and, thus, increase the clinical utility of our approach. Lastly, we propose applying our method to a large cohort of ALS patients and age matched controls (Aim 3). If successful, this biomarker will have substantial impact on the treatment of and drug development for ALS and other degenerative diseases.

项目摘要 血液中的循环游离 DNA (cfDNA) 源自垂死细胞，是一种很有前途的非 细胞死亡的侵入性生物标志物。最近的研究表明，cfDNA 水平与 癌症、组织创伤、自身免疫性疾病和器官移植，表明了其潜在的临床用途 cfDNA。然而，CfDNA 可以源自全身任意数量的组织，并且某些 cfDNA 个体在特定时刻的存在可能源自健康的细胞更新。为了更好地理解 组织变性，特别是在疾病背景下，对 cfDNA 起源组织的可靠估计是 需要。鉴定cfDNA的组织来源将对疾病诊断和监测产生直接影响， 以及定量生物标志物发现。 现有的组织来源分解方法不足以用于 cfDNA。首先，cDNA只是 少量存在于血液中。目前的分解方法一般依赖于基于数组的平台 需要大量的患者血液，这可能不适用于临床。替代方案是完整的 基因组亚硫酸氢盐测序数据，需要较低的 cfDNA 输入，但噪声较大。此数据未处理 与以前的方法。最后，准确分解 cfDNA 混合物需要对所有 可能对混合物有贡献的可能组织类型。然而，这个强有力的参考几乎是 不可能组装，因为有数百种不同的组织类型，并且因为甲基化状态 组织中的 CpG 可能会有所不同。这可能会导致先前方法的分解结果出现偏差。 在这个提案中，我们的目标是通过开发一个全面的方法来解决以前方法的局限性。 cfDNA 组织来源预测的工作流程。我们将开发一种统计方法来预测组织 cfDNA 的起源，允许低读取计数数据和未知的组织类型（目标 1）。我们假设这 将减少分解估计中的偏差，并使我们的方法比以前的方法得到更广泛的使用。 此外，我们建议开发一种捕获协议，以丰富具有信息性的 cfDNA 片段 组织或疾病状态。该协议将设计为仅使用少量输入 cfDNA（目标 2）。我们假设捕获面板方法将大大降低测序成本，从而提高 我们的方法的临床实用性。最后，我们建议将我们的方法应用于一大群 ALS 患者和年龄 匹配的对照（目标 3）。如果成功，该生物标志物将对以下疾病的治疗产生重大影响： 以及针对 ALS 和其他退行性疾病的药物开发。