Project 1: High Grade Cancers: Capitalizing on PARPness in Ovarian Carcinoma

项目 1:高级别癌症:利用 PARPness 治疗卵巢癌

基本信息

  • 批准号:
    10251114
  • 负责人:
  • 金额:
    $ 34.41万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-09-22 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

Project 1 SUMMARY/ABSTRACT Unfortunately, there are few “druggable” alterations in high-grade serous ovarian cancer (HGSOC). Thus, exploration of therapeutic liabilities engendered by defects in homologous recombination (HR), the second most common aberration in ovarian cancer after TP53 mutation, has taken a dominant role. HR defects caused by germline and somatic BRCA1/2 aberrations, as well as aberrations in other pathway members, lead to synthetic lethality in combination with inhibition of poly (ADP-ribose) polymerase–1 (PARP). However, crucial gaps in knowledge exist that hinder our long-term goal of optimal implementation of PARP inhibitors (PARPi) including: 1) the identification of patients most likely to benefit from PARPi (i.e., “PARPness”) and 2) the development of rational combination therapies able to prevent or overcome resistance to PARPi. In our prior SPORE project, we developed and implemented DNA, RNA and protein assays designed to predict benefit from PARPi as well as identified new members of the HR pathway, providing approaches to expand the population of patients likely to benefit from PARPi. In this SPORE proposal, we will complete our ongoing multi-arm combination trial with PARPi and phosphatidylinositol 3 kinase (PI3K) inhibitors and implement a resensitization trial in PARP resistant patients of Wee1 inhibition compared to PARP plus Wee1i. Using these trials, based on strong preliminary data from cell line, PDX and animal models, we will refine the utility of biomarkers to predict response and resistance to PARPi in HGSOC. We will further develop the preclinical and clinical data to justify a series of rational combination trials in this SPORE. Our overarching hypothesis is that the identification of a “PARPness” molecular profile will expand the utility of PARPi in HGSOC. As a corollary, optimal outcomes will only manifest by rational combination therapy with PARPi. Thus, we will perform a systematic analysis of cell lines, animal models and patient samples, combined with our combinatorial adaptive resistance therapy platform and ultra-deep shRNA and CRISPR/CAS screens to targetable molecules to systematically identify rational combinations with PARPi therapy. To accomplish our long term goals and to test our overarching hypothesis, we propose two specific aims: Specific Aim 1: To identify and refine biomarkers of benefit from PARPi in ovarian cancer and Specific Aim 2: To establish a preclinical framework to identify and prioritize rational combination therapies in ovarian cancer. The successful implementation of the proposed studies will contribute to: 1) development of personalized treatment of women with advanced and recurrent ovarian cancer based on molecular profiles, 2) an expanded definition of patients likely to benefit from PARP inhibitors, 3) identification of resistance mechanisms to PARP inhibitors, and 4) rational combination therapies that will increase the spectrum of patients likely to benefit and also prevent the emergence of resistance. Successful implementation of this project will not only improve clinical outcomes but will direct development of future clinical trials to advance the field.
项目1概要/摘要 不幸的是,在高级别浆液性卵巢癌(HGSOC)中几乎没有“药物”改变。因此,在本发明中, 探索由同源重组(HR)缺陷引起的治疗责任,第二, 在卵巢癌中最常见的畸变后,TP 53突变,已占主导地位。人力资源缺陷导致 生殖系和体细胞BRCA 1/2畸变,以及其他途径成员的畸变,导致 合成致死性与聚(ADP-核糖)聚合酶-1(PARP)抑制的组合。然而,至关重要的是, 知识上的差距阻碍了我们实现PARP抑制剂最佳应用的长期目标 (PARPi)包括:1)识别最可能从PARPi受益的患者(即,“PARP性”)和(2) 开发能够预防或克服PARPi耐药性的合理联合疗法。 在我们之前的SPORE项目中,我们开发并实施了DNA、RNA和蛋白质检测,旨在预测 受益于PARPi以及确定的人力资源途径的新成员,提供了扩大 可能受益于PARPi的患者人群。在这个SPORE提案中,我们将完成我们正在进行的 PARPi和磷脂酰肌醇3激酶(PI 3 K)抑制剂的多组联合试验, 与PARP加Wee 1 i相比,在PARP耐药患者中进行了Wee 1抑制的脱敏试验。使用这些 试验,基于来自细胞系,PDX和动物模型的强有力的初步数据,我们将改进 用于预测HGSOC中对PARPi的响应和抗性的生物标志物。我们将进一步开发临床前和 临床数据来证明本SPORE中的一系列合理组合试验的合理性。 我们的首要假设是,“PARP性”分子谱的鉴定将扩大 HGSOC中的PARPi。作为一个必然的结果,最佳的结果将只体现在合理的联合治疗, PARPi。因此,我们将对细胞系、动物模型和患者样本进行系统分析, 通过我们的组合适应性耐药治疗平台和超深shRNA和CRISPR/CAS筛选, 以系统地鉴定与PARPi疗法的合理组合。完成我们 为了检验我们的总体假设,我们提出了两个具体目标:具体目标1: 鉴定和改进PARPi在卵巢癌中获益生物标志物和具体目标2:建立 一个临床前框架,以确定和优先考虑合理的卵巢癌联合治疗。 建议研究的成功实施将有助于:1)开发个性化的 基于分子特征的晚期和复发性卵巢癌女性的治疗,2)扩大 定义可能从PARP抑制剂中获益的患者,3)确定PARP耐药机制 抑制剂,和4)合理的联合治疗,这将增加可能受益的患者谱, 也防止了阻力的出现。该项目的成功实施不仅将改善 临床结果,但将指导未来临床试验的发展,以推动该领域的发展。

项目成果

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GORDON B. MILLS其他文献

GORDON B. MILLS的其他文献

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{{ truncateString('GORDON B. MILLS', 18)}}的其他基金

Project 1: High Grade Cancers: Capitalizing on PARPness in Ovarian Carcinoma
项目 1:高级别癌症:利用 PARPness 治疗卵巢癌
  • 批准号:
    10005294
  • 财政年份:
    2017
  • 资助金额:
    $ 34.41万
  • 项目类别:
Biological annotation of TCGA data
TCGA数据的生物学注释
  • 批准号:
    9060264
  • 财政年份:
    2012
  • 资助金额:
    $ 34.41万
  • 项目类别:
Role of Rab25 and its Effectors in Breast Cancer Bioengenerics
Rab25 及其效应子在乳腺癌生物工程中的作用
  • 批准号:
    7962741
  • 财政年份:
    2010
  • 资助金额:
    $ 34.41万
  • 项目类别:
Modeling response to P13K Targeted Therapies
对 P13K 靶向治疗的反应进行建模
  • 批准号:
    8181915
  • 财政年份:
    2010
  • 资助金额:
    $ 34.41万
  • 项目类别:
P4 - Pers. Therapy for High-Grade Ovarian Cancer: Targeting PI3Kness & BRCAne
P4-个人。
  • 批准号:
    7961946
  • 财政年份:
    2010
  • 资助金额:
    $ 34.41万
  • 项目类别:
Modeling response to P13K Target Therapies
对 P13K 靶向治疗的反应进行建模
  • 批准号:
    8181894
  • 财政年份:
    2010
  • 资助金额:
    $ 34.41万
  • 项目类别:
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)
综合分析管道
  • 批准号:
    7788997
  • 财政年份:
    2009
  • 资助金额:
    $ 34.41万
  • 项目类别:
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)
综合分析管道
  • 批准号:
    7942759
  • 财政年份:
    2009
  • 资助金额:
    $ 34.41万
  • 项目类别:
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)
综合分析管道
  • 批准号:
    8123272
  • 财政年份:
    2009
  • 资助金额:
    $ 34.41万
  • 项目类别:
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)
综合分析管道
  • 批准号:
    8327267
  • 财政年份:
    2009
  • 资助金额:
    $ 34.41万
  • 项目类别:

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