A Noninvasive Integrated Genomic Approach for Early Cancer Detection and Risk Stratification after Transplantation

用于早期癌症检测和移植后风险分层的无创综合基因组方法

基本信息

批准号：
9882972
负责人：
Ash Arash Alizadeh
金额：
$ 60.7万
依托单位：
STANFORD UNIVERSITY
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：
2019-03-01 至 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9882972
关键词：
Acute Address Antibodies Antibody Repertoire Antigen Receptors B-Lymphocytes Biological Assay Biological Models Cancer Control Cells Chest Chronic Clinical Colorectal Cancer DNA DNA sequencing Detection Development Disease Early Diagnosis Event Foundations Frequencies Gene Fusion General Population Genetic Fingerprintings Genome Genomic approach Goals Graft Rejection Heart-Lung Transplantation Human Human Herpesvirus 4 Human Papillomavirus Immune Immune system Immunocompromised Host Immunologics Immunosuppression Impairment Incidence Infection Infectious Agent Inflammation International Kinetics Knowledge Lead Link Lymphocyte Lymphoproliferative Disorders Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Measures Methods Molecular Molecular Profiling Monitor Mutation Newly Diagnosed Non-Invasive Cancer Detection Oncogenic Oncornaviruses Opportunistic Infections Organ Transplantation Outcome Patients Performance Peripheral Plasma Population Prevention Primary Neoplasm Prospective cohort Public Health Research Risk Risk stratification Sampling Satellite Viruses Screening for cancer Site Solid Somatic Mutation Squamous cell carcinoma Technology Testing Therapeutic immunosuppression Time Tissues Transplant Recipients Transplantation Tumor Subtype Universities Variant Viral Viral Cancer Virus Virus Diseases Work allograft rejection base cancer diagnosis cancer prevention cancer risk carcinogenesis case control cell free DNA clinical risk cohort deep sequencing design early detection biomarkers experimental study high risk immune function improved infection risk innovation integration site mathematical model novel novel marker pathogen patient population post-transplant prevent risk minimization screening single cell analysis transcriptome sequencing transplant centers tumor tumor DNA virome virus identification

项目摘要

PROJECT SUMMARY/ABSTRACT Solid organ transplant recipients are an ideal population in which to study the link between oncogenic viral infections and cancer due to the deep immunosuppression required to prevent allograft rejection, which increases their risk of developing clinical complications such as infections and cancer. Our long-term goal is to study the relations among immunosuppression, infections, and cancer using transplantation as a model system. Our central hypothesis is that novel biomarkers of cancer risk such as detection of circulating tumor DNA, sequencing of circulating cell-free DNA, and detailed immune profiling can be used for early cancer detection, to identify changes in the virome that precede malignant transformation, and to quantify overall immunosuppression. We will test our hypothesis via three specific aims: (1) To evaluate circulating tumor DNA for early detection of post-transplant malignancies, focusing on post-transplant lymphoproliferative disorders (PTLDs). We will evaluate the performance of CAPP-Seq, an ultra-sensitive assay for early cancer detection, in existing cohorts of over 2000 heart and lung transplant recipients followed at Stanford University and 6 collaborating sites. We will study patients with PTLDs to (a) determine the kinetics of emerging somatic variants preceding tumor development, (b) define the window for accurate early prediction of cancer risk via circulating tumor DNA, and (c) relate these findings to oncotropic viral expansion and immune system suppression. Similar exploratory analyses will be performed in patients with post-transplant lung and colorectal cancers. (2) To profile oncoviruses in cell-free DNA and evaluate integration sites as cancer risk predictors. To distinguish features in the oncotropic virome preceding malignant transformation, we will enrich oncoviral cell-free DNA to enable identification of human:virus gene fusion by deep sequencing, and will determine whether read coverage is consistent with genome integration or with free DNA. We will then profile DNA from primary tumors and cell-free DNA, and will compare integration site coverage in tumor subtypes. (3) To quantify associations among immunosuppression, viral infection and cancer development. We will perform novel immune profiling assays at defined time points following transplantation and will correlate results with development of acute rejection, opportunistic infections, and cancer. Specifically, we will measure circulating Anellovirus load, will infer immune cell subsets from RNA-seq, and will sequence the B-cell antibody heavy chain. We will determine how these results relate to administered immunosuppression, and will build mathematical models to predict risk of clinical complications. This contribution is significant because knowledge of the molecular signatures associated with cancer risk and early detection may lead to novel ways to prevent, monitor, and treat malignant disease. Our innovative approach, in which we will employ novel methods developed by our group to study a very high-risk transplant patient cohort, will lay the foundation for studies aimed at prevention and early detection of cancer as a means of improving clinical outcomes.

项目概要/摘要实体器官移植受者是研究致癌病毒之间联系的理想人群由于防止同种异体移植排斥所需的深度免疫抑制，导致感染和癌症增加了他们发生感染和癌症等临床并发症的风险。我们的长期目标是使用移植作为模型系统研究免疫抑制、感染和癌症之间的关系。我们的中心假设是癌症风险的新型生物标志物，例如循环肿瘤 DNA 的检测，循环游离 DNA 的测序和详细的免疫分析可用于早期癌症检测，识别恶性转化之前病毒组的变化，并量化整体免疫抑制。我们将通过三个具体目标来检验我们的假设：(1) 评估循环肿瘤 DNA 用于早期检测移植后恶性肿瘤，重点关注移植后淋巴增殖性疾病疾病（PTLD）。我们将评估 CAPP-Seq 的性能，这是一种针对早期癌症的超灵敏检测方法斯坦福大学现有的 2000 多名心脏和肺移植接受者队列中进行了检测以及 6 个合作网站。我们将研究患有 PTLD 的患者，以 (a) 确定新兴躯体疾病的动力学肿瘤发展之前的变异，(b) 通过以下方式定义准确早期预测癌症风险的窗口循环肿瘤 DNA，以及 (c) 将这些发现与促瘤病毒扩增和免疫系统联系起来抑制。类似的探索性分析将在肺和结直肠移植后的患者中进行癌症。 (2) 分析游离 DNA 中的肿瘤病毒并评估整合位点的癌症风险预测因子。为了区分恶性转化之前的促瘤病毒组的特征，我们将丰富肿瘤病毒无细胞DNA，能够通过深度测序鉴定人：病毒基因融合，并将确定读数覆盖率是否与基因组整合或游离 DNA 一致。然后我们将简介来自原发性肿瘤的 DNA 和无细胞 DNA，并将比较肿瘤亚型中的整合位点覆盖率。 (3) 量化免疫抑制、病毒感染和癌症发展之间的关联。我们将在移植后的规定时间点进行新颖的免疫分析测定并将结果关联起来随着急性排斥反应、机会性感染和癌症的发展。具体来说，我们将测量循环指环病毒加载，将从 RNA-seq 推断免疫细胞亚群，并对 B 细胞抗体重链进行测序。我们将确定这些结果与免疫抑制的关系，并建立数学模型预测临床并发症风险的模型。这一贡献意义重大，因为了解与癌症风险和早期检测相关的分子特征可能会带来预防、监测、并治疗恶性疾病。我们的创新方法，我们将采用我们开发的新颖方法小组研究非常高风险的移植患者队列，将为旨在预防的研究奠定基础以及早期发现癌症作为改善临床结果的一种手段。