Biodata Management of Genomics Data from Cancer Cell Lines and Tumors

癌细胞系和肿瘤基因组数据的生物数据管理

• 批准号: 7745591
• 负责人: Daniel R Rhodes
• 金额: $ 15.14万
• 依托单位: COMPENDIA BIOSCIENCE, INC.
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7745591
• 关键词: Address; Antineoplastic Agents; Bioinformatics; Biological Markers; Biological Sciences; Biotechnology; Cancer Etiology; Cancer Gene Mutation; Cancer cell line; Cataloging; Catalogs; Cell Line; Characteristics; Clinical; Clinical Trials; Collection; Communities; Complex; Cosmic; DNA; DNA Microarray Chip; DNA copy number; Data; Data Element; Data Set; Databases; Development; Disease; Environment; Explosion; Fill-It; Gene Expression; Gene Expression Profile; Gene Mutation; Genes; Genetic; Genomics; Goals; Hereditary Disease; Individual; Industry; Institutes; Investments; Knowledge; Libraries; Licensing; Ligands; Link; Malignant Neoplasms; Maps; Medicine; Metadata; Methods; Microarray Analysis; Molecular; Molecular Profiling; Mutation; Nomenclature; Pathway interactions; Patient Selection; Patients; Pattern; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Phenotype; Population; Positioning Attribute; Preclinical Drug Development; Process; Public Health; Refractory; Research; Resources; Risk; Sampling; Services; Solutions; Source; Specimen; Staging; Technology; Testing; Translating; United States; Work; base; cancer genomics; cancer therapy; cancer type; data integration; design; drug development; drug sensitivity; flexibility; genome-wide; improved; innovation; mortality; novel; novel strategies; novel therapeutics; patient population; pre-clinical; public health relevance; receptor; research study; response; technological innovation; tumor; tumor progression

DESCRIPTION (provided by applicant): It is now clear that response to targeted therapies in cancer is dictated by the molecular characteristics of an individual patient's tumor. The industry is increasingly looking to genomics-based analyses to link drug response phenotypes to underlying genetic mutations and multiplex molecular signatures. Such analyses are hindered by three fundamental challenges. First, cancer comprises a diverse collection of potentially hundreds of distinct molecular diseases and most preclinical experiments are not of the appropriate scale to represent this diversity. Second, most analyses are limited in their scope of genomic associations, focusing on only one out of several possible characterizations (e.g. mutations, gene expression, DNA copy number). Finally, most analyses are missing the last crucial step, which is to map multiplex genetic biomarkers of drug response to clinical tumor populations. Compendia Bioscience seeks to address these fundamental challenges and provide an oncogenomics drug profiling solution that: assesses a broad panel of cancer cell lines for response to a given compound; defines sensitive and refractory cell line populations; performs detailed genomics correlation analysis spanning gene expression DNA copy number and mutations; develops and refines multiplex genetic biomarker(s) of response; and analyzes response biomarker(s) across nearly 30,000 highly curated clinical cancer specimens to identify patient populations and subpopulations likely to respond. The solution builds upon the functionality and resources previously established in Oncomine, a comprehensive gene expression database that collects, standardizes, and analyzes publicly available gene expression data. This will be accomplished by extending the flexibility of Oncomine to capture new metadata on existing studies: by overcoming technical obstacles associated with incorporating new data types; and by utilizing the full range of available data in logical ways to support drug development workflows. The Specific Aims of this Phase I proposal are to: 1. Catalog and annotate publicly available gene mutation data for 300+ cancer cell line panel. 2. Process and integrate DNA copy number data for 300+ cancer cell line panel. 3. Develop method to call amplifications and deletions from DNA copy number data and integrate with mutation data. Altogether the aims of this proposal significantly contribute to proving the feasibility of the overall approach: by assembling critical data elements for a large cell line panel and then directly comparing concordance between cell line data and tumor data. PUBLIC HEALTH RELEVANCE: Despite enormous investments in genomics technology aimed at improving the drug development pipeline, cancer remains a leading cause of mortality in the United States. This proposal seeks to advance preclinical drug development efforts by maximizing the value of experimentally robust, well-characterized cell lines, and using the results of those studies to inform patient selection in clinical trials of novel therapeutic compounds. This will improve public health by making it easier for drug development companies to identify patient populations likely to benefit from novel compounds, and to successfully advance those compounds through clinical trials and to the marketplace.

描述（由申请人提供）：现在清楚的是，对癌症靶向治疗的反应由个体患者肿瘤的分子特征决定。该行业越来越多地寻求基于基因组学的分析，以将药物反应表型与潜在的基因突变和多重分子特征联系起来。这种分析受到三个基本挑战的阻碍。首先，癌症包括潜在的数百种不同分子疾病的多样性集合，并且大多数临床前实验不具有代表这种多样性的适当规模。其次，大多数分析都局限于基因组关联的范围，只关注几种可能的特征之一（例如突变，基因表达，DNA拷贝数）。最后，大多数分析都缺少最后一个关键步骤，即绘制临床肿瘤人群药物反应的多重遗传生物标志物。Compendia Bioscience致力于解决这些基本挑战，并提供一种癌基因组学药物分析解决方案，该解决方案：评估一组广泛的癌细胞系对给定化合物的反应;定义敏感和难治细胞系群体;进行详细的基因组学相关性分析，涵盖基因表达DNA拷贝数和突变;开发和完善多重遗传生物标志物的反应;并分析近30，000个高度策划的临床癌症样本中的响应生物标志物，以识别可能响应的患者群体和亚群。该解决方案建立在Oncomine中先前建立的功能和资源之上，Oncomine是一个全面的基因表达数据库，可以收集，分析和分析公开的基因表达数据。这将通过以下方式实现：扩展Oncomine的灵活性，以获取现有研究的新元数据;克服与纳入新数据类型相关的技术障碍;以及以合乎逻辑的方式利用所有可用数据来支持药物开发工作流程。第一阶段提案的具体目标是：1.对300多个癌细胞系组的公开基因突变数据进行编目和注释。2.处理并整合300+癌细胞系组的DNA拷贝数数据。3.开发从DNA拷贝数数据中调用扩增和缺失的方法，并与突变数据整合。总而言之，该提案的目的显着有助于证明整体方法的可行性：通过为大型细胞系小组组装关键数据元素，然后直接比较细胞系数据和肿瘤数据之间的一致性。公共卫生关系：尽管在基因组学技术方面进行了大量投资，旨在改善药物开发渠道，但癌症仍然是美国死亡率的主要原因。该提案旨在通过最大限度地提高实验稳健，充分表征的细胞系的价值来推进临床前药物开发工作，并利用这些研究的结果为新型治疗化合物的临床试验中的患者选择提供信息。这将通过使药物开发公司更容易识别可能从新化合物中受益的患者群体，并通过临床试验成功地将这些化合物推向市场，从而改善公共健康。