An infrastructure for cancer virus discovery from next-generation sequencing data

描述（由申请人提供）：我们的目标是建立一个基础设施，使用我们开发的基于序列的计算减法方法，从下一代测序数据中发现与人类癌症相关的新型病毒。该拟议项目响应ARRA研究和研究基础设施大机会RFA关于“在癌症基因组试验计划的生殖系和体细胞变化的大规模研究中识别潜在的病毒特征”。大规模基因组计划，包括癌症基因组图谱（TCGA）以及与癌症的生殖系遗传相关性的研究，现在正朝着在cDNA水平（“RNA-seq”）和DNA水平（特别是全基因组测序（“WGS”））上应用超高通量下一代测序方法的方向发展。该研究的重点是对用于病毒发现的大型下一代测序数据集进行计算分析。具体来说，我们计划建立一个基础设施，应用基于序列的计算减法，一种由PI和合作研究者共同开发的方法，以评估这些大规模癌症基因组计划生成的数据库中是否存在新型非人类核酸序列。这种方法始于病毒诱导的癌症含有人和病毒核酸的假设，并且从癌症衍生的序列中减去人基因组将留下残留的候选非人和潜在的病毒序列。首先，我们将建立一个基于计算减法的数据分析和候选病原体序列发现的软件管道。其次，我们将把这个管道应用于来自TCGA和其他大规模数据集的下一代测序数据的输入。第三，我们将通过实验测试我们已经确定的非人类序列，以验证它们在癌症中的存在。第四，我们将使用验证数据来循环并提高计算管道的质量。从长远来看，我们预计，我们可以建立一个可持续的管道，可以支持无论是作为一个学术或工业的努力。鉴定与人类癌症相关的新感染因子将具有直接的预防、诊断和治疗意义。我们在这个为期两年的项目试点中开发的基础设施将通过分析不断增加的下一代癌症测序数据，为未来发现其他癌症相关病原体奠定基础。 公共卫生相关性：病毒是人类癌症的主要原因之一。发现这些病毒可以导致公共卫生的重大改善，因为病毒引起的癌症可以通过接种疫苗来预防。近年来，B型肝炎疫苗接种导致肝癌发病率大幅下降，而人乳头瘤病毒疫苗接种已被证明可降低宫颈癌的发病率。基因组分析和测序技术正在被用于发现人类癌症的原因，如癌症基因组图谱或TCGA。这些技术也可能导致新病毒的发现。因此，美国国家癌症研究所正在投资2009年美国复苏和再投资法案的资金，以支持在癌症基因组计划（如TCGA）的数据中发现新病毒。我们的建议是响应国家癌症研究所的要求，题为“在癌症基因组试点计划的生殖系和体细胞变化的大规模研究中识别潜在的病毒特征”。我们已经开发出一种强大的计算方法，可以将癌症或癌症患者的DNA和RNA序列与正常人类基因组进行比较。癌症或癌症患者特有的序列可能代表新的致癌病毒。在该计划中，我们将构建一个稳定的软件基础设施来执行这种序列比较，将该基础设施应用于大规模癌症基因组计划的数据，测试候选序列是否可能代表病毒，然后继续改进软件基础设施。这一努力将使整个癌症研究界能够发现病毒。

DESCRIPTION (provided by applicant): Our goal is to build an infrastructure to discover novel viruses associated with human cancer from next-generation sequencing data, using a sequence-based computational subtraction approach that we developed. This proposed project responds to the ARRA Research and Research Infrastructure Grand Opportunities RFA on "Identifying Potential Viral Signatures in Large Scale Studies of Germline and Somatic Changes in Cancer Genomes Pilot Program". Large-scale genome projects, including The Cancer Genome Atlas (TCGA) as well as studies of germ-line genetic correlations with cancer, are now moving towards the application of ultra-high- throughput next-generation sequencing approaches, both on the cDNA level ("RNA-seq") and the DNA level, especially whole genome sequencing ("WGS"). The study is focused on the computational analysis of large next-generation sequencing data sets for virus discovery. Specifically, we plan to build an infrastructure to apply sequence-based computational subtraction, a method developed by the PI and co-investigator jointly, to evaluate the presence of novel non-human nucleic acid sequences in databases generated by these large-scale cancer genome projects. This approach starts with the assumption that virally-induced cancers contain both human and viral nucleic acids, and that subtraction of the human genome from cancer-derived sequences will leave residual candidate non-human and potentially viral sequences. First, we will build a software pipeline for computational subtraction-based data analysis and candidate pathogen sequence discovery. Second, we will apply this pipeline to the incoming flood of next-generation sequencing data from TCGA and other large-scale data sets. Third, we will experimentally test non-human sequences that we have identified for their presence in validation cohorts for the cancers in which they were discovered. Fourth, we will use the validation data to circle back and improve the quality of our computational pipeline. In the long run, we anticipate that we can build a sustainable pipeline that could be supported either as an academic or industrial effort. Identification of a novel infectious agent associated with human cancer would have immediate preventive, diagnostic and therapeutic significance. The infrastructure that we develop in this two-year project pilot will lay the groundwork for discovering additional cancer-associated pathogens in the future, by analyzing the ever-increasing quantities of next-generation cancer sequencing data. PUBLIC HEALTH RELEVANCE: Viruses are among the major causes of human cancer. Discovering these viruses can lead to major improvements in public health, because virally induced cancers can be prevented by vaccination. In recent years, hepatitis B vaccination has led to a dramatic decrease in the occurrence of liver cancer, and human papillomavirus vaccination has been shown to decrease the rates of cervical carcinoma. Genome analysis and sequencing technologies are being used to discover the causes of human cancer, in projects such as The Cancer Genome Atlas, or TCGA. These technologies can also lead to the discovery of new viruses. Therefore the National Cancer Institute is investing funds from the American Recovery and Reinvestment Act of 2009 to support the discovery of new viruses in data from cancer genome projects such as TCGA. Our proposal is responsive to the National Cancer Institute request, entitled "Identifying Potential Viral Signatures in Large Scale Studies of Germline and Somatic Changes in Cancer Genomes Pilot Program". We have developed a powerful computational approach to compare DNA and RNA sequences from cancer, or from cancer patients, to the normal human genome. Sequences that are unique to cancers, or to cancer patients, may represent novel cancer- causing viruses. In this plan, we will build a stable software infrastructure to perform this sequence comparison, apply this infrastructure to data from large-scale cancer genome projects, test candidate sequences for whether they are likely to represent viruses, and then continue to improve the software infrastructure. This effort will enable discovery of viruses by the entire cancer research community.