Project 1 - Precision disparity modeling of cervical cancer survival using genomic and social determinants

项目 1 - 使用基因组和社会决定因素对宫颈癌生存进行精确差异建模

• 批准号: 9146145
• 负责人: J SUNIL RAO
• 金额: $ 38.99万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-19 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9146145
• 关键词: Accounting; Address; Age; Atlases; Attenuated; Automobile Driving; Awareness; Behavioral; Biological; Biology; Cancer Burden; Censuses; Cervical; Cervix Neoplasms; Clinical; Cohort Studies; Communities; Complex; Computer software; DNA Methylation; Data; Data Set; Development; Diagnosis; Diet; Discipline; Disease; Disease Outcome; Environmental Risk Factor; Ethnic Origin; Etiology; Future; Genomics; Grant; Health; Individual; Intervention; Malignant Neoplasms; Malignant neoplasm of cervix uteri; Maps; Methodology; Methods; Modeling; National Research Council; Nature; Outcome; Pathway interactions; Patients; Pattern; Play; Population; Predisposition; Programming Languages; Proxy; Race; Research; Risk; Risk Factors; Role; Sample Size; Socioeconomic Status; Somatic Mutation; Staging; Structure; Techniques; Testing; Text; The Cancer Genome Atlas; Time; United States; Universities; Vulnerable Populations; Woman; base; burden of illness; cancer genome; cancer health disparity; cancer risk; cancer survival; demographics; disease phenotype; epigenomics; ethnic minority population; experience; genomic biomarker; health disparity; improved; interdisciplinary approach; medically underserved; methylome; mortality; novel; outcome forecast; parity; population health; precision medicine; racial and ethnic; racial difference; racial disparity; residence; social; social genomics; user friendly software; user-friendly

ABSTRACT The National Research Council defines precision medicine as, “the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology and/or prognosis of the diseases that they may develop, or in their specific treatment.” The underlying principle of this emerging discipline is to better capture and address key variability in health outcomes, giving emphasis to the role of genomic and epigenomic factors in disease etiology, onset, and progression. In the current proposal, we extend this principle to cancer health disparity. Our approach, termed “precision disparities” aims to better understand why certain population sub-groups persistently contribute to excess cancer risk. To accomplish this aim, we will examine multilevel risk factors, including genomic and epigenomic alterations, often not accounted for in most disparities-focused inquiry, as well as, explore the complex interaction between such alterations and socio-environmental risk conditions, associated with observed variability in cancer outcomes. For the current proposal, we will focus on cervical cancer survival. In the United States, this outcome is characterized by significant disparity. Blacks are more likely to die of this largely preventable disease, largely due to advanced stage of disease at diagnosis. However, there are some known biological differences in the cervical tumors of Black versus white women with disease that merit further inquiry, particularly in relation to modifiable behavioral and environmental determinants. Therefore, we propose: 1) to explore how DNA methylation and other multilevel risk factors moderate the influence of race on cervical cancer survival; 2) to identify patterns of disparity that are not race-based, but are driven by other underlying structure in the data; 3) to examine potential shared determinants, or drivers, across multiple disease phenotypes characterized by health disparity and, 4) to develop user-friendly software that will enable further disparities research. We will test such aims using the publically available Cancer Genome Atlas (TCGA), as well as BioVu and the Southern Community Cohort Study (SCCS) from Vanderbilt University. The latter two include patient socio-demographics ,clinical indicators, diet proxies, somatic mutation profiles, and community context, among other variables. The first three aims require the development of novel statistical methodologies, described in further detail in our grant text.

摘要 国家研究理事会将精准医学定义为“将个体分类为 这些亚群在对特定疾病的易感性、疾病的生物学和/或预后方面存在差异。 他们可能发展的疾病，或在他们的具体治疗。这一新兴趋势的基本原则 纪律是为了更好地捕捉和解决健康结果的关键可变性，强调的作用， 基因组和表观基因组因素在疾病病因学、发病和进展中的作用。在目前的提案中，我们 将这一原则扩展到癌症健康差异。我们的方法被称为“精确差异”，旨在更好地 了解为什么某些人口亚组持续导致癌症风险过高。为了实现这一 目的是，我们将检查多层次的风险因素，包括基因组和表观基因组改变，往往没有考虑到 因为在大多数以生物学为中心的研究中， 和社会环境风险状况，与观察到的癌症结果的变异性相关。为 目前的建议，我们将集中在子宫颈癌生存。在美国，这种结果的特点是 巨大的差距。黑人更有可能死于这种基本上可以预防的疾病，这主要是由于 诊断时疾病处于晚期。然而，在宫颈癌中存在一些已知的生物学差异， 黑人与白色妇女的肿瘤，值得进一步调查，特别是与可改变的 行为和环境决定因素。因此，我们建议：1）探索DNA甲基化和 其他多层次的危险因素缓和了种族对宫颈癌生存率的影响; 2）识别 不以种族为基础，但由数据中的其他基础结构驱动的差异; 3）检查 在以健康差异为特征的多种疾病表型中，潜在的共同决定因素或驱动因素 （4）开发便于用户使用的软件，以便于进一步的差异研究。我们将测试这些目标 使用可在医学上获得的癌症基因组图谱（TCGA），以及BioVu和南方社区， 范德比尔特大学的队列研究（SCCS）。后两者包括患者社会人口统计学、临床 指标，饮食代理，体细胞突变谱和社区背景，以及其他变量。第一 有三个目标要求开发新的统计方法，在我们的赠款中有更详细的描述 短信了