Searching Environmental Metagenomes for Novel Infectious Cancer Agents (PQ12)

寻找环境宏基因组寻找新型传染性癌症病原体（PQ12）

• 批准号: 8382024
• 负责人: JAMES M PIPAS
• 金额: $ 19.9万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8382024
• 关键词: Algorithms; Bacteria; Base Sequence; Cancer Etiology; Carcinogens; Cells; Data; Data Set; Databases; Deposition; Diagnosis; Diagnostic; Elements; Epidemiology; Etiology; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genetic Predisposition to Disease; Genome; Genomics; Human; Individual; Infectious Agent; Laboratories; Lead; Malignant Neoplasms; Mammals; Metagenomics; Methods; Microbe; Molecular; Molecular Profiling; Nature; Normal tissue morphology; Nucleic Acids; Nucleic acid sequencing; Oral; Organism; Parasites; Population; Protein Databases; Publishing; RNA; Reading; Sampling; Science; Screening procedure; Sequence Analysis; Sewage; Soil; Surveys; Transcript; Tumor Tissue; Ursidae Family; Viral; Viral Genome; Virion; Virus; cancer therapy; computerized tools; design; metagenome; metagenomic sequencing; microorganism; novel; stem; tumor; tumorigenesis; tumorigenic; virtual

DESCRIPTION (provided by applicant): This is an exploratory application aimed at developing novel computational approaches for identifying infectious agents that contribute to cancer. To achieve this we will merge data from two distinct approaches: gene expression profiling and metagenomics. Approximately 20% of all cancers worldwide are associated with infectious agents including viruses, bacteria and parasites. It is likely that this number is an underestimate and that many more cancers are caused by agents that await discovery. One powerful approach to uncovering potential cancer-causing microorganisms is virtual subtraction in which tumor genomic sequences or gene expression profiles are searched for non-human sequences. Potential cancer causing agents are then identified among these nonhuman sequences by searching public nucleic acid and protein databases and identifying similar sequences that can then be associated with a known virus, bacteria or other organism. A major limitation of this approach is the lack of representation of sequences from most organisms, especially microorganisms, in the databases. Metagenomics is an approach in which specific biomes are sampled for all microorganisms followed by deep sequencing. Individual species are then identified by comparing the sequence reads obtained with sequences deposited in public databases. Studies from a number of laboratories including our own have shown that most sequences obtained in metagenomic surveys do not match anything in existing databases suggesting they are derived from previously uncharacterized agents. For example, our studies suggest that the 3,000 or so currently known viruses represent less than 0.01% of viruses in nature. Similarly the vast majority of bacterial species await discovery and characterization. We propose to search gene expression profile data to determine if any of these novel metagenomic sequences are expressed in tumors. We will also develop the computational tools that will allow uncharacterized viruses, bacteria or other organisms that we identify to be isolated and their association with cancer studied. The identification of new potential tumorigenic infectious agents will have a direct impact on the diagnosis and treatment of cancer. PUBLIC HEALTH RELEVANCE: In order to design diagnostics and therapies for different cancers we must know what is causing them. This project is aimed at discovering infectious agents that cause or contribute to the cause of cancer. The identification and characterization of these agents will thus lead to new methods for the diagnosis and treatment of cancer.

描述（由申请人提供）：这是一种探索性应用程序，旨在开发新的计算方法，用于识别有助于癌症的传染药。为了实现这一目标，我们将从两种不同的方法中合并数据：基因表达分析和宏基因组学。全球所有癌症中约有20％与包括病毒，细菌和寄生虫在内的传染剂有关。这个数字可能是一个低估的 而且，更多的癌症是由等待发现的代理引起的。一种强大的方法来发现潜在的引起癌症的微生物，是虚拟减法，其中搜索肿瘤基因组序列或基因表达谱以寻找非人类序列。然后，通过搜索公共核酸和蛋白质数据库，在这些非人类序列中鉴定出潜在的癌症，并确定可以与已知病毒，细菌或其他生物体相关的相似序列。这种方法的一个主要局限性是数据库中大多数生物（尤其是微生物）的序列缺乏代表。宏基因组学是一种对所有微生物进行采样特定生物素的方法，然后进行深度测序。然后，通过比较在公共数据库中存放的序列获得的序列读取来识别单个物种。来自包括我们自己在内的许多实验室的研究表明，在宏基因组调查中获得的大多数序列与现有数据库中的任何内容都不匹配，这表明它们是从先前未表征的剂中得出的。例如，我们的研究表明，目前已知的3,000个左右的病毒占自然界病毒的少于0.01％。同样，绝大多数细菌物种都在等待发现和特征。我们建议搜索基因表达谱数据，以确定这些新型的宏基因组序列是否在肿瘤中表达。我们还将开发计算工具，这些工具将允许我们鉴定出可以隔离的病毒，细菌或其他生物，并与研究的癌症相关。鉴定新的潜在肿瘤感染剂将对癌症的诊断和治疗产生直接影响。 公共卫生相关性：为了为不同的癌症设计诊断和疗法，我们必须知道导致它们的原因。该项目的目的是发现导致或促成癌症原因的传染药。因此，这些药物的鉴定和表征将导致诊断和治疗癌症的新方法。