Emerging Technologies Applied to the Discovery of Human Tumor Viruses

描述（由申请人提供）：感染导致全球约20%的人类癌症。然而，已知的致癌感染因子的名单令人惊讶地短，并且在过去十年中没有发现新的人类肿瘤病毒。目前的肿瘤病毒发现方法并不全面，可能会错过发现新的代理家族。使用这些技术的阴性研究不能排除肿瘤病毒的存在，并且可能会遗漏以前未知的药物。我们建议修改长序列基因表达分析（SAGE）作为一种无偏的手段，用于病毒发现使用在二氧化硅数字转录本减法（SDG）。我们在这里展示了一种实用的方法来执行短转录本标签的全转录组计算机减法，允许人类和非人类序列之间的歧视。一旦发现候选肿瘤病毒序列，它就可以用作病毒基因组步移和表征的起点。为了证明这种方法的可行性，我们进行了初步研究的潜伏KSHV病毒感染的肿瘤细胞系上的病毒。快速和独特地鉴定了5个KSHV从头转录物，占总细胞转录组的0.44%。通过将KSHV感染的细胞系RNA掺入未感染的人肿瘤组织RNA中，定量再现了该技术。我们还确定了实际的截止水平，区分大多数人的多态性病毒SAGE标签，使用PCR。最后，我们对3例鳞状细胞结膜癌（SCCC）肿瘤（一种与免疫缺陷相关的恶性肿瘤）进行了初步研究。108，000个SAGE标签的计算机减法产生了46个候选序列，包括12个被评估为可能的SCCC试剂序列的高概率标签。我们表明，这种技术是令人惊讶的免疫RNA降解，使它可以用于稀有或档案材料，其中部分RNA降解发生。我们寻求第二阶段R33资金，对4个SCCC样本进行分析，将我们的试点研究扩展到每百万人5-10个转录本水平的SCCC全面分析。这将使我们能够识别或排除可能导致这种免疫缺陷相关癌症的肿瘤病毒。这也完成了对肿瘤免疫学技术的开发，使我们能够充分优化其应用于其他疑似感染性肿瘤的性能 评估：

DESCRIPTION (provided by applicant): Infection contributes to ~20% of human cancers worldwide. The list of known carcinogenic infectious agents, however, is surprisingly short and no new human tumor viruses have been discovered over the past decade. Current tumor virus discovery methods are not comprehensive and are likely to miss discovery of new families of agents. Negative studies using these techniques do not rule out the presence of a tumor virus and may miss a previously unknown agent. We propose modifying long Serial Analysis of Gene Expression (SAGE) as an unbiased means for virus discovery using in silica digital transcript subtraction (DTS). We show here a practical method to perform transcriptome-wide in silico subtraction of short transcript tags, allowing discrimination between human and nonhuman sequences. Once a candidate tumor virus sequence is found, it can be used as a start point for viral genome walking and characterization. To demonstrate the feasibility of this method, we performed pilot studies of DTS on a tumor cell line infected with latent KSHV virus. DTS rapidly and uniquely identified 5 KSHV transcripts de novo comprising 0.44% of the total cell transcriptome. The technique was quantitatively reproduced by spiking KSHV-infected cell line RNA into uninfected human tumor tissue RNA. We also identified practical cut-off levels that distinguish most human polymorphisms from viral SAGE tags using DTS. Finally, we performed pilot DTS on 3 squamous cell conjunctival carcinoma (SCCC) tumors, an immunodeficiency-related malignancy. In silico subtraction of 108,000 SAGE tags generated 46 candidate sequences, including 12 high probability tags that are being evaluated as possible SCCC agent sequences. We show that this technique is surprisingly immune to RNA degradation so that it can be used on rare or archival materials in which partial RNA degradation has occurred. We seek phase II R33 funding to perform DTS on 4 SCCC samples, extending our pilot studies into a full analysis of SCCC at the 5-10 transcripts per million level. This will allow us to either identify or exclude a likely tumor virus causing this immunodeficiency-related cancer. This also completes development of DTS technology, allowing us to fully optimize its performance for application to other suspected infectious tumors ASSESSMENT: