Searching Environmental Metagenomes for Novel Infectious Cancer Agents (PQ12)

描述(由申请人提供)：这是一个探索性的应用程序，旨在开发新的计算方法来识别导致癌症的感染性病原体。为了实现这一点，我们将合并来自两种不同方法的数据：基因表达谱和元基因组学。全世界约20%的癌症与病毒、细菌和寄生虫等感染性因素有关。这个数字很可能被低估了。 而且更多的癌症是由等待发现的媒介引起的。发现潜在致癌微生物的一种有效方法是虚拟减法，即在肿瘤基因组序列或基因表达谱中搜索非人类序列。然后，通过搜索公共核酸和蛋白质数据库，并识别类似的序列，然后将其与已知的病毒、细菌或其他生物体相关联，在这些非人类序列中识别潜在的致癌物质。这种方法的一个主要局限性是缺乏数据库中大多数生物体，特别是微生物的序列。元基因组学是一种方法，在这种方法中，对所有微生物的特定生物群进行采样，然后进行深度测序。然后，通过将获得的序列读数与公共数据库中存储的序列进行比较来识别单个物种。包括我们自己在内的许多实验室的研究表明，在元基因组调查中获得的大多数序列与现有数据库中的任何序列都不匹配，这表明它们来自以前未确定特征的制剂。例如，我们的研究表明，目前已知的3000种左右的病毒在自然界中所占的比例不到0.01%。同样，绝大多数细菌物种都在等待发现和定性。我们建议搜索基因表达谱数据以确定这些新的元基因组序列中是否有任何在肿瘤中表达。我们还将开发计算工具，使我们能够分离出未确定特征的病毒、细菌或其他生物体，并研究它们与癌症的关系。新的潜在致癌感染源的识别将对癌症的诊断和治疗产生直接影响。 与公共卫生相关：为了设计针对不同癌症的诊断和治疗方法，我们必须知道是什么导致了这些癌症。这个项目的目的是发现引起或促成癌症的感染性因素。因此，这些药物的鉴定和表征将为癌症的诊断和治疗带来新的方法。

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.