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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:
10674212
负责人:
Matthew Frank Buas
金额:
$6.16万
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 2024-02-29

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中文摘要
翻译
项目总结/摘要 食管腺癌是一种罕见但致命的癌症,中位生存期<1年。全基因 关联研究(GWAS)估计EAC及其相关疾病的风险有相当大的遗传成分(25-35%), Barrett食管(Barrett's esophagus)近20个新的遗传风险位点已被发现,但大多数 遗传性仍然无法解释。“缺失遗传性”阻碍了GWAS阐明分子生物学的能力 疾病风险的潜在途径,并确定新的干预目标。在本建议中,我们力求 克服BE/EAC样本量的固有限制,并通过整合 先进的基于网络的方法和组织特异性调节组资源, 发现框架几条证据表明BE/EAC生物学中的转录调控网络 并鼓励使用基于网络的方法来探索这种癌症未被发现的遗传基础。 这些发现包括BE/EAC组织中关键的胚胎转录调节因子的重新激活; EAC肿瘤中转录因子(TF)基因的基因组改变;以及全基因组显著的GWAS 信号与编码食管/前肠TF的基因非常接近。根据这些观察, 流行的观点认为,与疾病相关的遗传变异在功能上集中在一组有限的核心生物学特征上, 通路,我们假设嵌入在发育转录网络中的遗传信号代表了 BE/EAC的“缺失遗传性”的重要来源。使用定制的疾病相关参考网络 覆盖GWAS衍生的节点权重,我们将筛选基因水平和增强子/启动子水平的遗传 先前的全基因组扫描遗漏了相关性。我们的多学科MPI团队借鉴了强大的轨道 在BE/EAC遗传学方面的记录,利用最大的可用GWAS数据集和广泛的组学 数据来自GTEx、RoadMap/ENCODE和启动子捕获HiC。在目标1中,我们将鉴定共表达基因 使用来自RNA-seq的转录调控网络, 数据区.通过互信息和图形套索方法组装的共表达网络应用于 330个胃食管交界处组织的转录组将用来自基因水平的权重填充。 GWAS测试,并使用分层Hotnet(HHN)进行分析。在目标2中,我们将鉴定连接的启动子, 使用来自3D染色质相互作用谱的调控图谱,使用具有浓缩的GWAS信号的增强子。 将加载使用正常食管中的启动子捕获HiC数据构建的增强子-靶标参考网络 使用自定义SNP集测试的权重,并通过HHN进行评估。我们提议的研究将有助于 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中 通过持续的合作,以确定BE/EAC的新预防/治疗目标为目标。
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
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