Computational analysis of cancer cytogenetic data

癌症细胞遗传学数据的计算分析

• 批准号: 6650546
• 负责人: PING LIANG
• 金额: $ 9.08万
• 依托单位: ROSWELL PARK CANCER INSTITUTE CORP
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2005-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6650546
• 关键词: chromosome aberrations; computer data analysis; computer program /software; cytogenetics; human data; information systems; mathematics; neoplasm /cancer; neoplasm /cancer genetics; neoplastic process

DESCRIPTION (provided by applicant): Characterization of non-random recurrent chromosomal aberrations have proven to be a useful instrument for identification of genes related to cancers and other genetic diseases and for improving diagnosis and prognosis of certain types of cancer. Current studies on characterization of cytogenetic signatures have been limited to the use of data available as individual clinical cases or as small-scale epidemiologic surveys with a primary focus on individual abnormalities and breakpoints using manual approaches. Due to the limitation on data size and the simplicity of methods, more complex patterns and critical breakpoints have not been revealed. Comprehensive cytogenetic data analyzed with new strategies and methodologies are needed to identify novel cytogenetic signatures for human cancer. The proposed project involves analysis of the unprecedented comprehensive cancer etiologic/cytogenetic data deposited in the Mitelman Database of Chromosomal Aberrations in Cancers using computational approaches. By first establishing a computational algorithm with the capability to decode karyotype data to reveal all cytogenetic changes implied by the simplified cytogenetics nomenclature, and by taking advantage of the first digitally compiled comprehensive data of cancer chromosomal aberrations, the project aims: 1) to attempt to establish cytogenetic signatures for cancers without previously known cytogenetic characteristics; 2) to identify new cytogenetic signatures for cancers with established patterns; and 3) to study relationships among different cancers and general patterns for all human chromosomal aberrations. The data resulting from this project should shed light on the molecular basis of poorly understood cancers, the multistage process of tumorigenesis, and relationships among different cancers, and it may provide a global picture of all cancers at the cytogenetic level.

描述（由申请人提供）： 非随机复发性染色体畸变的表征已被证明是识别与癌症和其他遗传疾病相关的基因以及改善某些类型癌症的诊断和预后的有用工具。目前关于细胞遗传学特征表征的研究仅限于使用可作为个体临床病例或小规模流行病学调查的数据，主要关注使用手动方法的个体异常和断点。由于数据量的限制和方法的简单性，更复杂的模式和临界断点尚未被揭示。需要用新的策略和方法分析全面的细胞遗传学数据，以确定人类癌症的新细胞遗传学特征。 拟议的项目涉及使用计算方法分析Mitelman癌症染色体畸变数据库中储存的前所未有的全面癌症病因学/细胞遗传学数据。通过首先建立一种能够解码核型数据的计算算法，以揭示简化细胞遗传学命名法所暗示的所有细胞遗传学变化，并通过利用第一个数字编译的癌症染色体畸变的综合数据，该项目旨在：1）尝试建立先前不具有已知细胞遗传学特征的癌症的细胞遗传学特征; 2）鉴定具有已建立模式的癌症的新的细胞遗传学特征;和3）研究不同癌症之间的关系和所有人类染色体畸变的一般模式。该项目产生的数据应有助于阐明对癌症知之甚少的分子基础、肿瘤发生的多阶段过程以及不同癌症之间的关系，并可能在细胞遗传学水平上提供所有癌症的全球图景。