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Transcriptomic and Proteomic Approaches to Discovering Viral Causes for Human Hem

Transcriptomic and Proteomic Approaches to Discovering Viral Causes for Human Hem
转录组学和蛋白质组学方法发现人类血汗病的病毒原因
批准号:
8534746
负责人:
YUAN CHANG
金额:
$31.68万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2016-06-30

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项目成果

YUAN CHANG的其他基金

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中文摘要
翻译
描述(由申请人提供):全世界五分之一的癌症病例是由感染引起的(国际癌症研究机构,2002年),但只有七种病毒被确定能导致人类癌症。我们实验室发现并鉴定了其中两种病原体,KS疱疹病毒(KSHV/HHV8)和默克尔细胞多瘤病毒(MCV),这两种病毒都是通过高度定向的基因组搜索发现的。这些发现开创了癌症生物学的新领域,并为改进由这些病毒引起的癌症的诊断、治疗和预防提供了新的基础。癌症遗传学的传统方法几乎完全集中在体细胞突变上,大规模的测序研究可能会错过可能导致一些人类肿瘤的病毒的发现。在过去的四年里,一组由七种新的人类多瘤病毒(包括已知的引起默克尔细胞癌(MCC)的MCV)被发现,它们编码T抗原癌蛋白,是可靠的候选肿瘤病毒。虽然大多数成年人都是慢性感染这些病毒,但通过癌症基因组解剖项目测序研究没有发现任何病毒。NCI主任的挑衅性问题倡议#12源于我们最近与MCV相关的MCC研究,该研究表明,MCV是一种常见的共生性皮肤感染,在病毒基因组发生特定突变后引发肿瘤。这是一种新的致癌机制,除非以有序的方式进行高度定向的非人类病毒序列搜索,否则不一定能通过癌细胞基因组测序项目找到它。为了识别人类癌症病毒,我们开发了数字转录组消减(DTS),这是一种依赖于高保真序列数据库的深度测序方法,并提供关于肿瘤细胞转录的定量数据。尽管标准的深度测序已经被其他人用来搜索病毒,但成功的分析高度依赖于特定的技术技能和假设。2008年,我们使用DTS在MCC中发现了MCV mRNA序列,使随后的全病毒基因组测序和验证性研究成为可能。在这项应用中,我们通过直接和无偏见的方法,最大限度地提高在血液系统恶性肿瘤中识别新型癌症病毒(ES)的可能性。我们的定向方法将调查一大批恶性血液病患者是否存在新的人类多瘤病毒。利用从MCV生物学中获得的信息,我们将确定是否存在肿瘤特异性病毒突变模式,以区分因果病毒感染和偶发病毒感染。我们不偏不倚的方法将使用DTS来检查高度精选的EBV阴性移植后淋巴增殖性疾病(EN-PTLD)的黄金标准病例,以确定是否存在新的病毒转录本。将对EN-PTLD肿瘤进行高Phred等效测序,达到每百万转录本1(TPM)水平,以识别新的病毒转录本。这些数据将与EBV阳性PTLD和CD19外周B细胞上的DTS进行比较,以1)确认病毒转录检测,2)确定EBV阴性和EBV阳性疾病之间的差异细胞基因表达模式。我们还将启动与太平洋西北国家实验室的探索性合作,利用整个EN-PTLD组织样本的无监督LC-MS/MS蛋白质组学开发下一代肿瘤病毒发现技术。对从相同组织样本获得的DTS(转录本)和LC-MS/MS(肽)数据的比较,将允许更精确地减去人类序列数据,以识别存在于肿瘤中的新病毒。随着这些目标的完成,我们预计能够回答六种新的人类多瘤病毒中是否有一种与血液淋巴恶性肿瘤有关,我们将确定EN-PTLD是否携带一种新的病毒。这种系统化的方法提供了发现新的人类癌症病毒的最高可能性,我们将开发新的技术方法,可以广泛用于未来对人类癌症感染的研究。
英文摘要
DESCRIPTION (provided by applicant): One in 5 cancer cases worldwide is caused by infection (International Agency for Research on Cancer, 2002) and yet only seven viruses have been established to cause human cancers. Our laboratory discovered and characterized two of these agents, KS herpesvirus (KSHV/HHV8) and Merkel cell polyomavirus (MCV), both of which were discovered through highly-directed genomic searches. These findings initiated new fields in cancer biology and provided new bases for improved diagnosis, treatment and prevention of cancers caused by these viruses. Traditional approaches to cancer genetics have focused almost exclusively on somatic cell mutations and large scale sequencing studies are likely to miss discovery of viruses that might be causing some human tumors. Over the past four years, a group of seven new human polyomaviruses (including MCV, known to cause Merkel cell carcinoma (MCC)) were discovered that encode T antigen oncoproteins and are credible candidate tumor viruses. Although most adults are chronically infected with these viruses, none were found through cancer genome anatomy project sequencing studies. The NCI Director's Provocative Question Initiative #12 arises from our recent MCV-related MCC studies showing that MCV, a common commensal skin infection, initiates tumors after specific mutations to the viral genome. This is a new mechanism for carcinogenesis that will not necessarily be found through cancer cell genome sequencing projects unless a highly directed search for nonhuman viral sequences is performed in a orderly fashion. To identify human cancer viruses, we developed digital transcriptome subtraction (DTS), a deep sequencing approach that depends on generation of high-fidelity sequence databases and provides quantitative data on tumor cell transcription. Although standard deep sequencing has been used by others to search for viruses, successful analysis is highly-dependent on specific technical skills and assumptions. In 2008, we used DTS to discover MCV mRNA sequences in MCC, allowing subsequent full viral genome sequencing and confirmatory studies. In this application, we maximize the likelihood for identifying a novel cancer virus (es) in hematologic malignancies through both directed and unbiased approaches. Our directed approach will survey a large panel of hematologic malignancies for presence of the new human polyomaviruses. Using information gained from the biology of MCV, we will determine whether tumor-specific viral mutation patterns are present that differentiate causal from incidental viral infections. Our unbiased approach will use DTS to examine highly-selected gold-standard cases of EBV-negative post-transplant lymphoproliferative disorder (EN-PTLD) for presence of novel viral transcripts. High PHRED-equivalent sequencing of EN-PTLD tumors to <1 transcript per million (TPM) level will be performed to identify novel viral transcripts. These data will be compared to DTS on EBV-positive PTLD and CD19+ peripheral B cells to 1) confirm virus transcript detection and 2) determine differential cellular gene expression patterns between EBV-negative and EBV- positive disease. We will also initiate an exploratory collaboration with the Pacific Northwest National Laboratory to develop the next generation of tumor virus discovery technology using unsupervised LC- MS/MS proteomics of whole EN-PTLD tissue samples. Comparisons of DTS (transcript) and LC-MS/MS (peptide) data, obtained from the same tissue samples, will allow a more precise subtraction of human sequence data to identify novel viruses present in tumors. With the completion of these aims, we anticipate being able to answer whether one of the six new human polyomaviruses contributes to hematolymphoid malignancies and we will determine whether or not EN- PTLD harbors a novel virus. This systematic approach provides the highest probability to find a new human cancer virus and we will develop new technologic approaches that can be widely used in future searches for infections in human cancer.
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Transcriptomic and Proteomic Approaches to Discovering Viral Causes for Human Hem
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