DNA Methylation Markers, Genes and Breast Cancer Risk

DNA 甲基化标记、基因和乳腺癌风险

• 批准号: 10590610
• 负责人: Jirong Long
• 金额: $ 65.65万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10590610
• 关键词: ABCC1 gene; African; African ancestry; Asia; Asian; Asian ancestry; Bioinformatics; Biological; Biological Assay; Biological Process; Breast; Breast Cancer Genetics; Breast Cancer Prevention; Breast Cancer Risk Factor; Breast Cancer cell line; Breast Cancer gene; Breast Epithelial Cells; Cancer Biology; Cell physiology; Clustered Regularly Interspaced Short Palindromic Repeats; DNA Methylation; Data; Development; Diagnostic; Disease susceptibility; ERBB2 gene; Epigenetic Process; Estrogen Receptors; European; European ancestry; Freezing; Gene Expression; Genes; Genetic; Genetic Diseases; Genetic Models; Genetic study; Genomics; Genotype; Goals; In Vitro; Malignant Neoplasms; Mammary Gland Parenchyma; Maps; Methylation; Modeling; Modification; Participant; Pathogenesis; Pathway interactions; Pilot Projects; Play; Positioning Attribute; Prevention; Race; Regulation; Research; Resources; Risk Assessment; Role; Sampling; Series; Site; Susceptibility Gene; System; Testing; Tissue Banks; Tissue Sample; Tissues; Translating; Variant; Woman; carcinogenesis; causal variant; cost; cost efficient; density; disorder prevention; epigenetic regulation; experience; experimental study; functional genomics; genetic variant; genome wide association study; genome wide methylation; genomic data; genomic locus; improved; innovation; instrument; malignant breast neoplasm; methylation biomarker; methylation pattern; methylome; multi-racial; multiple omics; novel; predictive modeling; racial population; risk stratification; transcriptome; transcriptomics; translational genetics

PROJECT SUMMARY Genome-wide association studies (GWAS) have identified common variants in ~200 genetic loci associated with breast cancer risk. However, it is difficult to translate these findings to disease prevention and treatment because causal genes and underlying mechanisms in these loci are largely unknown. Increasing evidence suggests that epigenetic regulation may be on the causal pathway between genetic variants and diseases. DNA methylation, one of the most frequent and important epigenetic modifications, plays a crucial role in cancer development. However, it is almost impossible to collect pre-diagnostic breast tissues to profile the methylome from a large number of participants. Herein, we propose a novel -omics approach: a methylation- wide association study (MeWAS) using genetic instruments. In Aim 1, we will build race-specific prediction models using genome wide methylation and genetic data in fresh-frozen breast samples from 600 cancer-free women of African-, Asian- and European- ancestry (200 per race). These models will then be applied to the GWAS data from three large consortia, including ~123,000 cases and ~106,000 controls of European, ~25,000 cases and ~25,000 controls of Asian-, ~20,000 cases and ~20,000 controls of African- ancestry to impute methylation levels. The genetically predicted methylation levels will be tested in association with breast cancer overall and by estrogen receptor and HER2 status. In Aim 2, we will perform a series of integrative functional analyses to evaluate the functions of promising methylation sites and the potential target genes regulated by these methylation sites. In Aim 3, we will select the top 20 methylation sites and their target genes for in vitro functional assays to assess their influence on major cell functions related to cancer biology. Given the strong pilot data, unique resources from three large genetic consortia, and our team's extensive expertise and experience, we are uniquely positioned to conduct this project. The findings will greatly improve our understanding of the genetic and biological basis of breast cancer pathogenesis and facilitate the translation of genetic findings to prevention and treatment.

项目摘要 全基因组关联研究（GWAS）已经确定了约200个遗传位点的常见变异， 有患乳腺癌的风险然而，很难将这些发现转化为疾病预防和治疗 因为这些基因座中的致病基因和潜在机制在很大程度上是未知的。越来越多的证据 表明表观遗传调控可能是遗传变异和疾病之间的因果途径。 DNA甲基化是最常见和最重要的表观遗传修饰之一， 癌症发展然而，几乎不可能收集诊断前的乳腺组织来描绘乳腺癌的特征。 来自大量参与者的甲基化组。在此，我们提出了一种新的组学方法：甲基化- 广泛关联研究（MeWAS）使用遗传工具。在目标1中，我们将建立特定种族的预测 使用来自600名无癌症患者的新鲜冷冻乳腺样本中的全基因组甲基化和遗传数据的模型 非洲、亚洲和欧洲血统的妇女（每个种族200人）。然后将这些模型应用于 GWAS数据来自三个大型联盟，包括欧洲的~ 123，000例病例和~ 106，000例对照， 亚洲血统~ 25，000例和~ 20，000例对照，非洲血统~ 20，000例和~ 20，000例对照， 甲基化水平。基因预测的甲基化水平将与乳腺癌相关 总体以及雌激素受体和HER 2状态。在目标2中，我们将执行一系列综合功能 分析，以评估有希望的甲基化位点的功能和潜在的靶基因调控， 这些甲基化位点。在目标3中，我们将选择前20个甲基化位点及其靶基因进行体外研究。 功能测定以评估它们对与癌症生物学相关的主要细胞功能的影响。考虑到强劲的 试点数据，来自三个大型遗传财团的独特资源，以及我们团队广泛的专业知识， 经验，我们有独特的优势来执行这个项目。这些发现将大大改善我们的 了解乳腺癌发病机制的遗传和生物学基础，并促进翻译 遗传学研究成果用于预防和治疗。