Genetic determinants of gene expression phenotypes in aggressive prostate cancer

侵袭性前列腺癌基因表达表型的遗传决定因素

• 批准号: 8327764
• 负责人: Liang Wang
• 金额: $ 61万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-02 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8327764
• 关键词: Accounting; Alleles; Bioinformatics; Candidate Disease Gene; Case Study; Cell Cycle Regulation; Cessation of life; Clinical; Complex; DNA Sequence; Data; Data Set; Disease; Disease Progression; Disease susceptibility; Frequencies; Gene Expression; Gene Expression Profiling; Genes; Genetic; Genetic Determinism; Genetic Variation; Genome; Genotype; Goals; Individual; Linkage Disequilibrium; Malignant neoplasm of prostate; Maps; Methodology; Minor; Molecular Profiling; Pathway Analysis; Patients; Phenotype; Play; Prevention strategy; Prostate; Quantitative Trait Loci; Regulation; Research Design; Role; SNP genotyping; Shapes; System; Systems Analysis; Testing; Tissues; Variant; Weight; base; genetic variant; genome wide association study; innovation; lymphoblastoid cell line; novel; outcome forecast; trait; tumor

DESCRIPTION (provided by applicant): The regulatory variation is believed to play an important role in shaping phenotypic differences among individuals and thus is also very likely to influence disease susceptibility and progression. In this study, we propose to take advantage of the expression QTL mapping and co-expressed gene network analysis to identify and characterize candidate genes and genetic variants that are responsible for aggressive phenotype of prostate cancer. Our hypothesis is that most genetic variants responsible for an aggressive phenotype of prostate cancer have regulatory effect on candidate gene expression and complete understanding of regulatory SNPs can only be achieved by examining primary tissue (here, prostate). To test this hypothesis, we will use a case-case study design and apply an innovative yet feasible approach by integrating DNA sequence variation and gene expression with clinical trait information. The four Specific Aims are: 1. Identify novel aggressiveness-related candidate SNPs by utilizing an expression genetics-based eQTL mapping approach; 2, Identify novel aggressiveness-related candidate SNPs by utilizing an integrative systems genetics-based network analysis approach; 3. For the novel candidate SNPs identified in Aims 1 and 2, perform additional association-based studies to confirm their association with an aggressiveness-related phenotype for prostate cancer; and 4. Identify candidate causal-SNPs by fine mapping, recognizing that the candidate eSNPs identified in Aim 3 will most likely be in linkage disequilibrium with the causal-SNPs. Understanding genetic mechanisms underlying the aggressive phenotype will have significant impact on prevention strategies, prognosis and potentially targeted therapy.

描述（由申请人提供）： 人们认为，调节性变异在塑造个体之间的表型差异中起着重要作用，因此也很可能会影响疾病的敏感性和进展。在这项研究中，我们建议利用表达QTL映射和共表达的基因网络分析，以识别和表征负责前列腺癌积极表型的候选基因和遗传变异。我们的假设是，大多数负责前列腺癌积极表型的遗传变异对候选基因表达具有调节作用，并且只能通过检查原代组织（这里，前列腺）来实现对调节性SNP的完全了解。为了检验这一假设，我们将使用病例研究设计设计，并通过将DNA序列变异和基因表达与临床性状信息整合在一起，应用创新但可行的方法。四个具体目的是：1。通过利用基于表达遗传学的EQTL映射方法来确定与侵略性相关的新型候选SNP。 2，通过利用基于集成系统遗传学的网络分析方法来确定与攻击性相关的新型候选SNP； 3。对于在目标1和2中鉴定出的新型候选SNP，进行了其他基于关联的研究，以确认其与前列腺癌与侵略性相关的表型的关联；和4。通过精细的映射确定候选因果-SNP，认识到AIM 3中鉴定的候选ESNP很可能与因果SNP的联系不平衡。了解侵略性表型背后的遗传机制将对预防策略，预后和潜在靶向治疗产生重大影响。