Emerging Technologies Applied to the Discovery of Human Tumor Viruses

感染导致了全球约20%的人类癌症。已知的致癌传染源列表， 然而，令人惊讶的是，在过去的十年里，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，可能会错过新的发现。 特工的家人使用这些技术的阴性研究并不能排除肿瘤病毒的存在 并且可能错过先前未知的代理。 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， 发现使用在二氧化硅数字转录减法（SDG）。我们在这里展示了一种实用的方法来执行 短转录物标签的全转录组计算机扣除，允许区分人类和 非人类序列一旦发现候选肿瘤病毒序列，就可以将其用作 病毒基因组步移和表征。 为了证明这种方法的可行性，我们对感染了HSP 70的肿瘤细胞系进行了初步研究。 潜伏的KSHV病毒快速和独特地鉴定了5种KSHV从头转录物，占0.44%， 总细胞转录组。该技术通过加标KSHV感染的细胞系进行定量重现 RNA转化为未感染的人类肿瘤组织RNA。我们还确定了实际的截止水平， 大多数人的多态性来自病毒SAGE标签，最后，我们在3号试验台上进行了试验性试验， 鳞状细胞结膜癌（SCCC）肿瘤，一种免疫缺陷相关的恶性肿瘤。计算机模拟 减去108，000个SAGE标签产生46个候选序列，包括12个高概率标签， 被评估为可能的SCCC代理序列。我们发现这项技术令人惊讶地 免疫RNA降解，使其可用于稀有或档案材料，其中部分RNA 发生了退化。 我们寻求第二阶段R33资金，对4个SCCC样本进行测试，将我们的试点研究扩展到一个全面的 在每百万人5-10个转录本的水平上分析SCCC。这将使我们能够识别或排除 很可能是肿瘤病毒导致了这种免疫缺陷相关的癌症这也完成了开发 技术，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

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