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Leveraging tissue-specific regulatory maps and network-assisted analysis to identify novel genetic risk loci for esophageal adenocarcinoma

Leveraging tissue-specific regulatory maps and network-assisted analysis to identify novel genetic risk loci for esophageal adenocarcinoma
利用组织特异性调控图和网络辅助分析来识别食管腺癌的新遗传风险位点
批准号:
10437324
负责人:
Matthew Frank Buas
金额:
$2.64万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-03-03 至 2022-06-30

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中文摘要
翻译
项目摘要/摘要 食管腺癌(EAC)是一种罕见但致命的癌症,中位生存期为1年。全基因组 协会研究(Gwas)估计,EAC及其相关疾病的风险有相当大的可遗传成分(25-35%)。 前驱,巴雷特食道(BE)。目前已发现近20个新的遗传风险基因座,但大多数 遗传性仍未得到解释。“遗漏遗传性”阻碍了GWAs阐明分子的能力 疾病风险的潜在途径,并确定新的干预目标。在这项建议中,我们寻求 克服BE/EAC样本大小的固有限制并通过整合确定新的易感基因座 先进的基于网络的方法和组织特异性调节组资源转化为生物动机 发现框架。BE/EAC生物学中涉及转录调控网络的几条证据 并鼓励使用基于网络的方法来探索这种癌症尚未发现的基因基础。 这些发现包括在BE/EAC组织中重新激活关键的胚胎转录调节因子;体细胞 EAC肿瘤中转录因子(TF)基因的基因组改变和全基因组意义的GWAs 与编码食道/前肠因子的基因非常接近的信号。在这些观察的基础上,以及 流行的观点认为,与疾病相关的基因变异在功能上汇聚在一组有限的核心生物学上 途径,我们假设嵌入在发育转录网络中的遗传信号代表 BE/EAC“缺失遗传性”的一个重要来源。使用定制的疾病相关参考网络 覆盖了GWAS派生的节点权重,我们将筛选基因水平和增强子/启动子水平的基因 之前的全基因组扫描遗漏了关联。我们的多学科MPI团队走上了一条强大的轨道 在BE/EAC遗传学方面的记录,利用对最大可用GWAS数据集的访问,以及广泛的组学 来自GTEx、路线图/编码和启动子捕获HIC的数据。在目标1中,我们将鉴定共表达的基因 利用来自RNA-seq的转录调控网络,丰富了与风险相关的遗传变异 配置文件。通过互信息和图形套索方法组装的共表达网络应用于 330个胃-食道交界处组织的转录本将从基因水平填充权重 用分层HotNet(HHN)进行分析。在目标2中,我们将确定关联的启动子和 使用来自3D染色质相互作用谱的调节图谱,使用浓缩的GWAS信号的增强剂。 使用正常食道中的启动子-捕获-hic数据构建的增强子-靶参考网络将被加载 权重来自定制的基于SNP集的测试,并通过HHN进行评估。我们建议的研究将有助于 阐明EAC及其唯一已知前体(BE)的遗传结构。候选风险基因和 增强子/启动子将被推进到目前正在进行的已知基因座的功能验证研究 通过正在进行的合作,目标是为BE/EAC确定新的预防/治疗目标。
英文摘要
PROJECT SUMMARY / ABSTRACT Esophageal adenocarcinoma (EAC) is a rare yet lethal cancer with median survival <1 year. Genome-wide association studies (GWAS) have estimated a substantial heritable component of risk (25-35%) for EAC and its precursor, Barrett’s esophagus (BE). Nearly 20 novel genetic risk loci have been discovered, but most heritability remains unexplained. ‘Missing heritability’ hinders the power of GWAS to illuminate molecular pathways underlying disease risk and identify novel targets for intervention. In this proposal, we seek to overcome inherent limits on sample sizes for BE/EAC and identify novel susceptibility loci by integrating advanced network-based methods and tissue-specific regulome resources into a biologically-motivated discovery framework. Several lines of evidence implicate transcriptional regulatory networks in BE/EAC biology and motivate use of network-based approaches to probe undiscovered genetic underpinnings of this cancer. These findings include reactivation of key embryonic transcriptional regulators in BE/EAC tissues; somatic genomic alterations in transcription factor (TF) genes in EAC tumors; and genome-wide-significant GWAS signals in close proximity to genes encoding esophageal/foregut TFs. Building on these observations, and the prevailing view that disease-linked genetic variation functionally converges on a limited set of core biological pathways, we hypothesize that genetic signals embedded in developmental transcriptional networks represent an important source of ‘missing heritability’ for BE/EAC. Using customized disease-relevant reference networks overlaid with GWAS-derived node weights, we will screen for gene-level and enhancer/promoter-level genetic associations missed by prior genome-wide scans. Our multi-disciplinary MPI team draws on a strong track record in BE/EAC genetics, leveraging access to the largest available GWAS datasets, and extensive omics data from GTEx, RoadMap/ENCODE, and promoter-capture HiC. In Aim 1, we will identify co-expressed genes enriched in risk-associated genetic variation, using transcriptional regulatory networks derived from RNA-seq profiles. Co-expression networks assembled via mutual information and graphical lasso methods applied to transcriptomes of 330 gastro-esophageal junction tissues will be populated with weights from gene-level GWAS tests, and analyzed using Hierarchical Hotnet (HHN). In Aim 2, we will identify linked promoters and enhancers with concentrated GWAS signal using regulatory maps from 3D chromatin interaction profiles. Enhancer-target reference networks built using promoter-capture-HiC data in normal esophagus will be loaded with weights from custom SNP-set-based tests and evaluated via HHN. Our proposed research will help elucidate the genetic architecture of EAC and its only known precursor (BE). Candidate risk genes and enhancers/promoters will be advanced to functional validation studies currently underway for known loci through an ongoing collaboration, with the goal of defining new preventive/therapeutic targets for BE/EAC.
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会议论文
Genetics, Epigenetics, and Risk Prediction for Esophageal Adenocarcinoma
  • 批准号:
    10703461
  • 项目类别:
  • 资助金额:
    $71.02万
  • 财政年份:
    2022
  • 负责人:
    Matthew Frank Buas
  • 依托单位:
Leveraging tissue-specific regulatory maps and network-assisted analysis to identify novel genetic risk loci for esophageal adenocarcinoma
  • 批准号:
    10674212
  • 项目类别:
  • 资助金额:
    $6.16万
  • 财政年份:
    2022
  • 负责人:
    Matthew Frank Buas
  • 依托单位:
Leveraging tissue-specific regulatory maps and network-assisted analysis to identify novel genetic risk loci for esophageal adenocarcinoma
  • 批准号:
    10583526
  • 项目类别:
  • 资助金额:
    $9.08万
  • 财政年份:
    2022
  • 负责人:
    Matthew Frank Buas
  • 依托单位:
Genetic susceptibility to Barrett's esophagus: From GWAS to biology
  • 批准号:
    10674348
  • 项目类别:
  • 资助金额:
    $80.18万
  • 财政年份:
    2021
  • 负责人:
    Matthew Frank Buas
  • 依托单位:
海外基金