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

项目总结/摘要 实体器官移植受者是研究致癌性病毒感染与肿瘤发生之间联系的理想人群。 感染和癌症，因为需要深度免疫抑制来防止同种异体移植排斥反应， 增加了他们患上感染和癌症等临床并发症的风险。我们的长期目标是 以移植为模型系统，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， 循环无细胞DNA的测序和详细的免疫分析可用于早期癌症检测， 确定恶性转化之前病毒组的变化，并量化总体 免疫抑制我们将通过三个具体目标来验证我们的假设：（1）评估循环肿瘤DNA 用于移植后恶性肿瘤的早期检测，重点关注移植后淋巴增生性 疾病（PTLD）。我们将评估CAPP-Seq的性能，这是一种用于早期癌症的超灵敏检测方法。 在斯坦福大学现有的2000多名心脏和肺移植受者中， 6个合作网站。我们将对PTLD患者进行研究，以（a）确定出现的体细胞病变的动力学， （B）通过以下方式定义用于癌症风险的准确早期预测的窗口： 循环肿瘤DNA，以及（c）将这些发现与嗜瘤病毒扩增和免疫系统 镇压将在移植后肺和结直肠癌患者中进行类似的探索性分析。 癌的(2)分析无细胞DNA中的肿瘤病毒并评估整合位点作为癌症风险 预测器为了区分恶性转化前的嗜瘤病毒组的特征，我们将丰富 肿瘤病毒无细胞DNA，使人类能够通过深度测序识别病毒基因融合，并将 确定读段覆盖度是否与基因组整合或游离DNA一致。然后我们会侧写 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。（三） 量化免疫抑制、病毒感染和癌症发展之间的关系。我们将 在移植后的规定时间点进行新的免疫分析， 伴随急性排斥反应机会性感染和癌症的发展。具体而言，我们将测量循环 Anellovirus负载，将从RNA-seq推断免疫细胞亚群，并将对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剂的关系，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 与癌症风险和早期检测相关的分子特征可能会导致预防，监测， 治疗恶性疾病。我们的创新方法，我们将采用我们开发的新方法， 研究一个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 和早期发现癌症作为改善临床结果的手段。

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.