Investigating the mechanisms of driver genes associated with ancestry and aggressiveness in prostate cancer

研究与前列腺癌的血统和侵袭性相关的驱动基因的机制

基本信息

  • 批准号:
    10403592
  • 负责人:
  • 金额:
    $ 58.61万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-05-10 至 2026-04-30
  • 项目状态:
    未结题

项目摘要

Summary African American (AA) men have the highest incidence and mortality rate from prostate cancer in the United States. We recently showed that AA men with low-risk prostate cancer have a two-fold increased risk of death compared to men of other racial groups. While the causes of this stark disparity are multifactorial, we hypothesize that low-risk prostate cancer in AA men harbor unique genomic alterations that give rise to more aggressive prostate cancer. Towards this end, we have performed an initial meta-analysis of existing sequencing studies and found candidate driver genes associated with ancestry. However, the ability to determine the effect of these candidates on prostate cancer biology is limited due to the lack of biological cell models from different ancestral backgrounds. In Aim 1, we will find additional molecular alterations associated with grade using whole exome sequencing of prostate cancer cases from 300 AA men and 200 men from a European background using a collection of archived specimens from Boston Medical Center and UCSF. In Aim 2, we will characterize the transcriptomic and proteomic states of different prostate epithelial cell populations by performing single-cell RNA- seq and mass spectrometry of organoids derived from AA and EA men. In Aim 3, we will develop new prostate cell models from AA patients using a conditional reprogramming method. We will then perturb ancestry- and grade-associated driver genes using CRISPR/Cas9 genome editing and determine whether the functional effects of these genes are augmented in different ancestral backgrounds. At the conclusion of these studies we will have expanded our understanding of the molecular pathways are associated with aggressiveness in different ancestral backgrounds. We will also generate a large resource of prostate cell models from AA men for the scientific community to investigate prostate cancer disparities. This project will generate substantial knowledge of the mechanisms that underlie prostate cancer disparities that could ultimately lead to improved treatment of AA men with prostate cancer and the reduction of cancer health disparities.
概括 非裔美国人(AA)男性的发病率和死亡率最高 国家。我们最近表明,患有低风险前列腺癌的AA男性死亡风险增加了两倍 与其他种族群体的男人相比。虽然这种鲜明差异的原因是多因素,但我们 假设AA男性中低风险的前列腺癌具有独特的基因组改变,这会引起更多 侵略性前列腺癌。为此,我们对现有测序进行了初步的荟萃分析 研究并发现与祖先相关的候选驱动基因。但是,确定效果的能力 由于缺乏不同的生物细胞模型 祖先背景。在AIM 1中,我们会发现使用整个等级相关的其他分子变化 使用来自300名AA男性和200名来自欧洲背景的200名男性的前列腺癌病例的外显子组测序 来自波士顿医疗中心和UCSF的存档标本集。在AIM 2中,我们将表征 通过执行单细胞RNA-的转录组和蛋白质组学状态 源自AA和EA的类器官的SEQ和质谱法。在AIM 3中,我们将开发新的前列腺 使用条件重编程方法来自AA患者的细胞模型。然后,我们将扰动祖先 - 和 使用CRISPR/CAS9基因组编辑与等级相关的驱动基因并确定功能效应是否效应 这些基因在不同的祖先背景中得到了增强。在这些研究的结论下,我们将 扩展了我们对分子途径的理解与不同的侵略性有关 祖先背景。我们还将从AA男士那里生成大量的前列腺细胞模型 研究前列腺癌差异的科学界。该项目将产生大量知识 前列腺癌差异的基础的机制最终导致对治疗的治疗 患有前列腺癌的男性和癌症健康差异的减少。

项目成果

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Joshua D Campbell其他文献

Joshua D Campbell的其他文献

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{{ truncateString('Joshua D Campbell', 18)}}的其他基金

Investigating the mechanisms of driver genes associated with ancestry and aggressiveness in prostate cancer
研究与前列腺癌的血统和侵袭性相关的驱动基因的机制
  • 批准号:
    10615833
  • 财政年份:
    2021
  • 资助金额:
    $ 58.61万
  • 项目类别:
Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasets
利用贝叶斯建模改进大规模数据集中的突变特征推断
  • 批准号:
    10684720
  • 财政年份:
    2021
  • 资助金额:
    $ 58.61万
  • 项目类别:
Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasets
利用贝叶斯建模改进大规模数据集中的突变特征推断
  • 批准号:
    10490301
  • 财政年份:
    2021
  • 资助金额:
    $ 58.61万
  • 项目类别:
Investigating the mechanisms of driver genes associated with ancestry and aggressiveness in prostate cancer
研究与前列腺癌的血统和侵袭性相关的驱动基因的机制
  • 批准号:
    10198345
  • 财政年份:
    2021
  • 资助金额:
    $ 58.61万
  • 项目类别:
Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasets
利用贝叶斯建模改进大规模数据集中的突变特征推断
  • 批准号:
    10305242
  • 财政年份:
    2021
  • 资助金额:
    $ 58.61万
  • 项目类别:
Integrative clustering of cells and samples using multi-modal single-cell data
使用多模态单细胞数据对细胞和样本进行综合聚类
  • 批准号:
    10215623
  • 财政年份:
    2019
  • 资助金额:
    $ 58.61万
  • 项目类别:
Integrative clustering of cells and samples using multi-modal single-cell data
使用多模态单细胞数据对细胞和样本进行综合聚类
  • 批准号:
    9981822
  • 财政年份:
    2019
  • 资助金额:
    $ 58.61万
  • 项目类别:

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  • 批准号:
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  • 财政年份:
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