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）： 人们认为调节变异在塑造个体之间的表型差异方面发挥着重要作用，因此也很可能影响疾病的易感性和进展。在这项研究中，我们建议利用表达QTL作图和共表达基因网络分析来识别和表征导致前列腺癌侵袭性表型的候选基因和遗传变异。我们的假设是，大多数导致前列腺癌侵袭性表型的遗传变异对候选基因表达具有调节作用，并且只有通过检查原发组织（此处为前列腺）才能完全了解调节性 SNP。为了检验这一假设，我们将采用案例研究设计，并通过将 DNA 序列变异和基因表达与临床特征信息相结合，应用创新且可行的方法。四个具体目标是： 1. 利用基于表达遗传学的 eQTL 作图方法识别新的攻击性相关候选 SNP； 2、利用基于综合系统遗传学的网络分析方法识别新的攻击性相关候选SNP； 3. 对于目标 1 和 2 中确定的新候选 SNP，进行额外的基于关联的研究，以确认它们与前列腺癌侵袭性相关表型的关联； 4. 通过精细作图识别候选因果 SNP，认识到目标 3 中识别的候选 eSNP 最有可能与因果 SNP 连锁不平衡。了解侵袭性表型背后的遗传机制将对预防策略、预后和潜在的靶向治疗产生重大影响。