Predictive Markers to Personalize Medicine for Malignant Glioma

恶性胶质瘤个性化医疗的预测标记

基本信息

项目摘要

There is a gap in in the availability of predictive biomarkers that are necessary to personalize treatment for patients with GBM. A challenge has been to separate prognostic makers (those that predict the natural history of the disease) from predictive (those that predict response to a particular treatment). l/Vfe hypothesize that effective biomarkers of treatment response must be decoupled from prognostic influences. Furthermore, to maximize clinical utility, these biomarkers must be developed as high-throughput, validated diagnostics applicable to small quantities of formalin-fixed, paraffin-embedded (FFPE) tissue. The specific aims of Project 3 are: 1) Develop a novel clinical diagnostic to classify patients suitable for FFPE tissue and incorporating the most robust molecular prognostic markers. 2) Develop a predictive marker of response to anti-angiogenic therapy. 3) Develop a predictive marker of response to immunomodulation. In the initial MDACC Brain SPORE funding, we developed a 9-gene FFPE biomarker that distinguished favorable from unfavorable patient prognosis. The assay was validated, commercialized, and incorporated as a prospective stratification factor in a phase III trial evaluating the anti-angiogenesis inhibitor bevacizumab [Radiation Therapy Oncology Group (RTOG) 0825]. To further improve survival discrimination, we expanded the 9-gene signature to a more robust 19-gene. In addition, we identified an additional epigenetic prognostic signature, the glioma CpG-island methlylator phenotype (G-CIMP). Using >300 cases from M.D. Anderson Cancer Center (MDACC) we developed a unified four risk group system called the molecular-clinical, prognosticator (MCP) that combines clinicopathologic factors with gene expression, genetic, and epigenetic factors. The analytic approach in constructing the MCP and its improved prognostic classification will allow us to better develop predictive makers independent of prognostic influences. Based on our success in the initial SPORE funding period and leveraging our expertise in biomarker development and our close involvement with the RTOG we know propose renewal of this project.
在预测性生物标志物的可用性方面存在差距,这些生物标志物是个性化治疗所必需的。 GBM患者一个挑战是将预测因子(那些预测自然事件的因子) 疾病的历史)从预测(预测对特定治疗的反应)。l/Vfe 假设治疗反应有效生物标志物必须与预后无关, 影响。此外,为了使临床效用最大化,这些生物标志物必须被开发为高通量的, 经验证的诊断适用于少量福尔马林固定、石蜡包埋的 (FFPE)组织。项目3的具体目标是: 1)开发一种新的临床诊断方法,对适合FFPE组织的患者进行分类,并结合 最可靠的分子预后标记物。 2)开发抗血管生成治疗反应的预测性标志物。 3)开发免疫调节反应的预测性标志物。 在最初的MDACC脑孢子基金中,我们开发了一种9基因FFPE生物标志物, 从不利的患者预后中获益。该检测方法经过验证,商业化,并纳入 作为评价抗血管生成抑制剂的III期试验中的前瞻性分层因素 贝伐珠单抗[放射治疗肿瘤组(RTOG)0825]。为了进一步提高生存率 为了区分,我们将9个基因的签名扩展到更稳健的19个基因。此外,我们还发现了一个 另外的表观遗传预后标志,胶质瘤CpG岛甲基化表型(G-CIMP)。使用 >300例来自M.D.安德森癌症中心(MDACC),我们制定了一个统一的四个风险组系统 将临床病理因素与基因结合起来的分子临床预测因子(MCP 表达、遗传和表观遗传因素。构建MCP的分析方法及其应用 改进的预后分类将使我们能够更好地开发独立于 预后影响基于我们在初始SPORE融资期的成功,并利用我们的 生物标志物开发方面的专业知识以及我们与RTOG的密切合作,我们知道, 这个项目的。

项目成果

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KENNETH D ALDAPE其他文献

KENNETH D ALDAPE的其他文献

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{{ truncateString('KENNETH D ALDAPE', 18)}}的其他基金

TOWARDS A REFINED MOLECULAR RECURSIVE PARTITIONING ANALYSIS MODEL FOR GLIOBLASTOM
建立精细的胶质母细胞分子递归分区分析模型
  • 批准号:
    7944134
  • 财政年份:
    2009
  • 资助金额:
    $ 23.99万
  • 项目类别:
TOWARDS A REFINED MOLECULAR RECURSIVE PARTITIONING ANALYSIS MODEL FOR GLIOBLASTOM
建立精细的胶质母细胞分子递归分区分析模型
  • 批准号:
    7853814
  • 财政年份:
    2009
  • 资助金额:
    $ 23.99万
  • 项目类别:
Predictive Markers to Personalize Medicine for Malignant Glioma
恶性胶质瘤个性化医疗的预测标记
  • 批准号:
    8588569
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Pathology and Biorepository Core
病理学和生物样本库核心
  • 批准号:
    8588575
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Pathology and Biorepository Core
病理学和生物样本库核心
  • 批准号:
    8753981
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Pathology and Biorepository Core
病理学和生物样本库核心
  • 批准号:
    9128427
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
CB: Pathology and Tissue Procurement Core
CB:病理学和组织采购核心
  • 批准号:
    7450239
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Predictive Markers to Personalize Medicine for Malignant Glioma
恶性胶质瘤个性化医疗的预测标记
  • 批准号:
    8918452
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Prediction of Chemoradiation response in Glioblastoma to individualize Therapy
预测胶质母细胞瘤的放化疗反应以进行个体化治疗
  • 批准号:
    7450205
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:
Predictive Markers to Personalize Medicine for Malignant Glioma
恶性胶质瘤个性化医疗的预测标记
  • 批准号:
    9128424
  • 财政年份:
    2008
  • 资助金额:
    $ 23.99万
  • 项目类别:

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