Polymorphisms in Inflammation Genes and Bladder Cancer Risk

描述（由申请人提供）： 这项拟定研究将建立在来自一项正在进行的膀胱癌研究“膀胱癌遗传易感性：分子流行病学方法”（RO 1 CA 74880，PI：Xifeng Wu）的广泛流行病学数据库和标本库的基础上。父母资助涉及一个多学科的研究小组，应用分子流行病学方法来确定膀胱癌发生易感性的个体间差异，重点是参与保护基因组不稳定性的基因，如DNA修复，细胞周期和端粒维持。越来越多的人认识到炎症在许多癌症的病因学中起重要作用，包括膀胱癌（BC）。我们最近发现IL-6启动子SNP（G-174 C）与BC风险和进展相关。在本申请中，我们将检验BC受炎症相关基因中常见的低多态性调节的假设，这些基因相互作用和/或环境因素。我们将采取基于途径的基因分型方法，并应用新的统计工具来解决这一假设。有3个具体目标：具体目标1：确定炎症相关基因中易患BC的候选多态性。我们计划对1000例白人病例和1000例年龄、性别和种族相匹配的对照者进行炎症基因潜在功能多态性（44个基因中的85个多态性）的基因分型。具体目标二：对特定目标1中确定的前8个候选基因的标签SNP进行基因分型（使用显著性水平0.1）。这将使我们对特定基因在BC病因学中所起的作用有一个完整的了解。我们将实施基于单体型的分析，以确定使用基于SNP的方法可能遗漏的任何其他变体。具体目标3：应用分层模型来完善风险评估，并应用新的机器学习工具来识别影响BC风险的任何基因-环境和基因-基因相互作用。这些分析将检查SNP的主要影响和基因-基因相互作用，基因-环境相互作用，并开发和验证算法，这些算法将根据个人暴露模式和遗传风险特征识别BC风险最高的个体。该应用程序将使我们能够全面了解炎症相关基因的功能多态性对BC风险的影响。

DESCRIPTION (provided by applicant): This proposed study will build upon the extensive epidemiologic database and specimen repository derived from an ongoing bladder cancer study entitled "Genetic Susceptibility to Bladder Cancer: A Molecular Epidemiologic Approach" (RO1 CA74880, PI: Xifeng Wu). The parent grant involved a multidisciplinary group of researchers applying a molecular epidemiologic approach to identify inter-individual differences in susceptibility to bladder carcinogenesis, with a focus on genes involved in protecting against genomic instability, such as DNA repair, cell cycle, and telomere maintenance. It is increasing recognized that inflammation plays an important role in the etiology of many cancers, including bladder cancer (BC). We have recently shown that an IL-6 promoter SNP (G-174C) is associated with BC risk and progression. In this application, we will test the hypothesis that BC is modulated by common, low penetrance polymorphisms in inflammation related genes, interacting with each other and/or environmental factors. We will take a pathway based genotyping approach and apply novel statistical tools to address the hypothesis. There are 3 specific aims: Specific Aim 1: To identify candidate polymorphisms in inflammation related genes that predispose individuals to BC. We plan to perform genotyping of a comprehensive list of potential functional polymorphisms in inflammation genes (85 polymorphisms in 44 genes) on 1000 Caucasian cases and 1000 controls matched on age, gender, and ethnicity. Specific Aim 2: To perform genotyping on tagging SNPs for the top 8 candidate genes that were identified in Specific Aim 1 (using a significance level of 0.1) identified in Specific Aim 1. This will give us a complete picture of the role that the specific gene plays in BC etiology. We will implement haplotype-based analyses to identify any additional variants that might have been missed using individual SNP-based approaches. Specific Aim 3: To apply hierarchical models to refine risk assessment and to apply novel machine-learning tools to identify any gene-environment and gene- gene interactions influencing risk for BC. These analyses will examine SNP main effects and gene-gene interactions, gene-environment interaction and develop and validate algorithms, which will identify individuals at highest risk for BC, given their personal exposure patterns and their genetic risk profiles. The application will allow us to have a comprehensive picture of the effects of functional polymorphisms in inflammation related genes on BC risk.