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Tools for detecting biologically important sequence variation in cancer

用于检测癌症中具有重要生物学意义的序列变异的工具

基本信息

批准号：
8333965
负责人：
Rachel Karchin
金额：
$ 11.37万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-16 至 2014-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8333965
关键词：
Algorithms Animal Model Antineoplastic Agents Architecture Atlases Binding Biochemical Bioinformatics Biological Biological Assay Biometry Cancer Center Cell Line Cell model Cell physiology Classification Code Codon Nucleotides Collaborations Common Data Element Communities DNA Resequencing Data Databases Detection Development Diagnosis Disease Drug Delivery Systems Exons Foundations Funding Future Genes Genetic Variation Genomics Goals Grant Human Imagery Individual Investigation Knowledge Letters Link Malignant Neoplasms Maps Medical Research NCI Center for Cancer Research Oncogenes Oncogenic Online Systems Pathway Analysis Pathway interactions Pilot Projects Point Mutation Positioning Attribute Predisposition Primary Neoplasm Property Proteins Publishing Research Infrastructure Research Personnel Resources Role Sampling Sequence Analysis Software Engineering Software Tools Source Staging System Technology Testing Time Translations Tumor Suppressor Proteins Tumor-Derived Variant Work biomedical informatics cancer genome cancer genomics cancer type computerized tools cost design drug development exome experience genome sequencing improved interest novel outcome forecast software development tool tumor tumor progression user-friendly web based interface

项目摘要

DESCRIPTION (provided by applicant): The detection of biologically important sequence variation is a major goal of modern cancer genomics. In an effort to focus resequencing investigations on high-value regions, many researchers have chosen to focus on the exome (protein-coding exons), which is expected to be enriched for functional variation. In the near future, comprehensive resequencing of an individual's exome may cost less than $1000, substantially less than whole-genome sequencing. We anticipate that these developments will yield an enormous amount of exonic sequence variation in cancer genomes that will provide leads to new cancer genes and drug targets. Most of this variation is likely to be effectively neutral, thus the cancer genomics community will have to identify and prioritize those variants that warrant further studies in assay systems, e.g. cell lines and model organisms. At this time, there are no publicly available resources that enable researchers who are not bioinformatics experts to explore the biological importance of sequence variants discovered in their investigations. There is a pressing need for tools that enable transparent, researcher-driven exploration of variation, by mapping variants onto proteins and pathways and presenting results in a way that is accessible to the average researcher. Development of such resources will allow rapid translation of genomic investigations into tangible progress in medical research. We propose here to develop a novel computational application tailored to the needs of researchers who are discovering variation in the exomes of cancers. Our work will produce a high- throughput annotation pipeline, with associated web-based analysis and visualization tools. This resource will enable users to interpret and prioritize tumor-derived sequence changes and help them think about how to design functional tests for variants of interest. We will demonstrate the utility of the application by collaborating with researchers from the Johns Hopkins Sidney Kimmel Cancer Research Center, who are sequencing the exomes of eleven cancer types during the two years for which we request funding (approximately 23 primary tumors per cancer type). The application will be used in collaboration with this team of researchers, led by Drs. Bert Vogelstein, Ken Kinzler, and Victor Velculescu to identify genes responsible for susceptibility to and progression of these cancers (Support Letter attached). This work will lay the foundation for a broader application of the tools to exomic variation data in additional cancers, such as those being studied by NCI's Cancer Genome Atlas project and TARGET.

描述（由申请人提供）：生物学上重要的序列变异的检测是现代癌症基因组学的主要目标。为了将重测序研究重点放在高价值区域，许多研究人员选择将重点放在外显子组（蛋白质编码外显子）上，预计该外显子组将富集功能变异。在不久的将来，对个体外显子组进行全面重测序的成本可能会低于 1000 美元，大大低于全基因组测序。我们预计这些进展将在癌症基因组中产生大量的外显子序列变异，从而为新的癌症基因和药物靶标提供线索。大多数变异可能实际上是中性的，因此癌症基因组学界必须识别并优先考虑那些需要在分析系统中进行进一步研究的变异，例如细胞系和模式生物。目前，还没有公开的资源可以让非生物信息学专家的研究人员探索其研究中发现的序列变异的生物学重要性。迫切需要一种工具，通过将变异映射到蛋白质和途径上，并以普通研究人员可以理解的方式呈现结果，从而实现透明的、由研究人员驱动的变异探索。此类资源的开发将使基因组研究快速转化为医学研究的切实进展。我们在此建议开发一种新颖的计算应用程序，以满足发现癌症外显子组变异的研究人员的需求。我们的工作将产生一个高吞吐量的注释管道，以及相关的基于网络的分析和可视化工具。该资源将使用户能够解释和优先考虑肿瘤衍生的序列变化，并帮助他们思考如何为感兴趣的变体设计功能测试。我们将通过与约翰霍普金斯大学 Sidney Kimmel 癌症研究中心的研究人员合作来展示该应用程序的实用性，他们在我们申请资助的两年内对 11 种癌症类型的外显子组进行测序（每种癌症类型大约 23 个原发性肿瘤）。该应用程序将与由博士领导的研究团队合作使用。 Bert Vogelstein、Ken Kinzler 和 Victor Velculescu 鉴定了与这些癌症的易感性和进展相关的基因（附有支持信）。这项工作将为这些工具更广泛地应用于其他癌症的外显子组变异数据奠定基础，例如 NCI 癌症基因组图谱项目和 TARGET 正在研究的癌症。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

CRAVAT: cancer-related analysis of variants toolkit.

DOI：
10.1093/bioinformatics/btt017
发表时间：
2013-03-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
0
作者：
Douville C;Carter H;Kim R;Niknafs N;Diekhans M;Stenson PD;Cooper DN;Ryan M;Karchin R
通讯作者：
Karchin R

Identifying Mendelian disease genes with the variant effect scoring tool.