Imaging Guided Genomics of Malignant Transformation

恶性转化的影像引导基因组学

基本信息

项目摘要

DESCRIPTION (provided by applicant): This project will use novel quantitative imaging methods to guide biopsies to biologically distinct regions of brain tumors for targeted exome and transcriptome analysis. Our goal is to identify naturally evolving and treatment-induced mutations that drive malignant transformation (MT) of low grade glioma (LGG) to high grade glioma (HGG). MT is associated with very poor survival, but the mechanisms underlying MT are unknown, and it is not known how chemotherapy following resection of LGG might alter the natural course of tumor evolution. Our substantial preliminary data from exome and RNA sequencing (RNA-seq) suggests that evolution of mutations can differ dramatically in temozolomide (TMZ) treated and non-treated patients, and that this commonly used chemotherapeutic agent itself may induce recurring transformation-promoting driver mutations that converge on common signaling pathways. In contrast to traditional genomic studies, imaging guided genomics could enrich the detection of mutations that drive MT by linking mutations to regions of aggressive tumor growth in vivo. Here we propose to interrogate the genetic underpinnings of MT in TMZ-treated and untreated patients with two complementary approaches. In aim 1, we will use exome and RNA-seq to compare exon mutations and expression profiles among four tumor biopsies from each patient, two with and two without characteristics of MT as predicted by novel physiologic/metabolic imaging parameters and subsequently confirmed by tissue analyses. This will provide a focused assessment of MT from a single surgical time point. In aim 2, we will use longitudinally collected samples from the same individual before and after transition from LGG to HGG. We will compare the mutation and expression profiles within this second set of subjects who have (i) LGG tissue available retrospectively and (ii) image guided tissue samples that were obtained as part of this grant and that demonstrate transformation to HGG. These paired samples will allow a direct assessment of evolution of mutations in individual patients over time. The integration of genomics with advanced imaging, validation of mutation frequency in large, independent set of tumors, experimental assays of candidates, and up-to-date computational analyses are expected to enrich for the identification of mutations that drive MT and to distinguish naturally evolving from TMZ-induced mutations. These studies could therefore impact patient management by identifying LGG patients for which chemotherapy should be contraindicated, and by identifying common and targetable mutations associated with MT.
描述(由申请人提供):该项目将使用新颖的定量成像方法引导活检到脑肿瘤的生物学不同区域,以进行靶向外显子组和转录组分析。我们的目标是识别自然进化和治疗诱导的突变,这些突变可驱动低级别胶质瘤 (LGG) 向高级别胶质瘤 (HGG) 的恶性转化 (MT)。 MT 与极差的生存率相关,但 MT 的机制尚不清楚,也不知道 LGG 切除后的化疗如何改变肿瘤进化的自然过程。我们来自外显子组和 RNA 测序 (RNA-seq) 的大量初步数据表明,在替莫唑胺 (TMZ) 治疗和未治疗的患者中,突变的进化可能存在显着差异,并且这种常用的化疗药物本身可能会诱导重复出现的促进转化的驱动突变,这些突变会集中在常见的信号通路上。与传统的基因组研究相比,成像引导的基因组学可以通过将突变与体内侵袭性肿瘤生长的区域联系起来,丰富驱动 MT 的突变的检测。在这里,我们建议用两种互补的方法来探究接受 TMZ 治疗和未治疗的患者 MT 的遗传基础。在目标 1 中,我们将使用外显子组和 RNA-seq 来比较每位患者的四个肿瘤活检中的外显子突变和表达谱,其中两个具有和两个不具有 MT 特征,如通过新的生理/代谢成像参数预测并随后通过组织分析证实。这将从单个手术时间点对 MT 进行集中评估。在目标 2 中,我们将使用从 LGG 转换为 HGG 之前和之后从同一个体纵向收集的样本。我们将比较第二组受试者中的突变和表达谱,这些受试者具有 (i) 回顾性可用的 LGG 组织和 (ii) 作为本次资助的一部分获得的图像引导组织样本,并证明其已转化为 HGG。这些配对样本将允许直接评估个体患者的突变随时间的演变。基因组学与先进成像的整合、大型独立肿瘤组中突变频率的验证、候选物的实验分析以及最新的计算分析预计将丰富驱动 MT 的突变的识别,并区分自然进化和 TMZ 诱导的突变。因此,这些研究可以通过确定禁忌化疗的 LGG 患者以及确定与 MT 相关的常见和可靶向突变来影响患者管理。

项目成果

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Joseph F Costello其他文献

A first look at entire human methylomes
对整个人类甲基化组的初步观察
  • DOI:
    10.1038/nbt1209-1130
  • 发表时间:
    2009-12-01
  • 期刊:
  • 影响因子:
    41.700
  • 作者:
    Joseph F Costello;Martin Krzywinski;Marco A Marra
  • 通讯作者:
    Marco A Marra
Comparative epigenomics of leukemia
白血病的比较表观基因组学
  • DOI:
    10.1038/ng0305-211
  • 发表时间:
    2005-03-01
  • 期刊:
  • 影响因子:
    29.000
  • 作者:
    Joseph F Costello
  • 通讯作者:
    Joseph F Costello

Joseph F Costello的其他文献

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{{ truncateString('Joseph F Costello', 18)}}的其他基金

3-D spatial approach to discover genomic effectors of immunosuppression during malignant transformation
3-D 空间方法发现恶性转化过程中免疫抑制的基因组效应子
  • 批准号:
    10434045
  • 财政年份:
    2020
  • 资助金额:
    $ 63.49万
  • 项目类别:
3-D spatial approach to discover genomic effectors of immunosuppression during malignant transformation
3-D 空间方法发现恶性转化过程中免疫抑制的基因组效应子
  • 批准号:
    10066668
  • 财政年份:
    2020
  • 资助金额:
    $ 63.49万
  • 项目类别:
3-D spatial approach to discover genomic effectors of immunosuppression during malignant transformation
3-D 空间方法发现恶性转化过程中免疫抑制的基因组效应器
  • 批准号:
    10651651
  • 财政年份:
    2020
  • 资助金额:
    $ 63.49万
  • 项目类别:
3-D spatial approach to discover genomic effectors of immunosuppression during malignant transformation
3-D 空间方法发现恶性转化过程中免疫抑制的基因组效应器
  • 批准号:
    10183206
  • 财政年份:
    2020
  • 资助金额:
    $ 63.49万
  • 项目类别:
Global Analyses of the Placental Epigenome in Preeclampsia
先兆子痫胎盘表观基因组的整体分析
  • 批准号:
    9369783
  • 财政年份:
    2017
  • 资助金额:
    $ 63.49万
  • 项目类别:
Global Analyses of the Placental Epigenome in Preeclampsia
先兆子痫胎盘表观基因组的整体分析
  • 批准号:
    9920738
  • 财政年份:
    2017
  • 资助金额:
    $ 63.49万
  • 项目类别:
Antigens for Molecularly Targeted Vaccines for Progressive Glioma
进行性神经胶质瘤分子靶向疫苗的抗原
  • 批准号:
    9087366
  • 财政年份:
    2015
  • 资助金额:
    $ 63.49万
  • 项目类别:
Antigens for Molecularly Targeted Vaccines for Progressive Glioma
进行性神经胶质瘤分子靶向疫苗的抗原
  • 批准号:
    8968177
  • 财政年份:
    2015
  • 资助金额:
    $ 63.49万
  • 项目类别:
Imaging Guided Genomics of Malignant Transformation
恶性转化的影像引导基因组学
  • 批准号:
    8830326
  • 财政年份:
    2013
  • 资助金额:
    $ 63.49万
  • 项目类别:
Imaging Guided Genomics of Malignant Transformation
恶性转化的影像引导基因组学
  • 批准号:
    8649030
  • 财政年份:
    2013
  • 资助金额:
    $ 63.49万
  • 项目类别:

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基于使用酵母敲除菌株收集的新生物测定系统的药物发现
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