Gene traps and in vivo microinjection: a cancer drug discovery platform

基因陷阱和体内显微注射：癌症药物发现平台

• 批准号: 8523625
• 负责人: Richard Klinghoffer
• 金额: $ 14.47万
• 依托单位: PRESAGE BIOSCIENCES, INC.
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8523625
• 关键词: Address; Advanced Malignant Neoplasm; Animal Cancer Model; Antineoplastic Agents; Area; Biological Assay; Biology; Cancer Patient; Cell Death; Cell model; Cells; Chemistry; Clinic; Clinical; Clinical Trials; Collaborations; Coupling; Data; Decision Making; Development; Disease; Drug Combinations; Drug Targeting; Drug resistance; Environment; Exposure to; Failure; Fred Hutchinson Cancer Research Center; Gene Expression Regulation; Genes; Goals; Hand; Health; Image; In Vitro; Industry; Injection of therapeutic agent; Investments; Journals; Knowledge; Lead; Left; Life; Light; Luciferases; Maintenance; Malignant Neoplasms; Market Research; Marketing; Medicine; Methodology; Microinjections; Modeling; Molecular Target; Mus; Mutation; Needles; New York; Oncogenes; Oncogenic; Outcome; Output; Paper; Pathway interactions; Patients; Peer Review; Personal Satisfaction; Pharmaceutical Chemistry; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Process; Property; Proteins; Publishing; Regimen; Reliance; Reporter; Resistance; Resources; Scientist; Serum; Signal Pathway; Signal Transduction; Staging; System; Technology; Testing; Time; Translating; Triage; Trust; Validation; Work; anticancer research; base; cancer cell; cancer initiation; clinical efficacy; combat; cost effective; drug development; drug discovery; drug efficacy; efficacy testing; experience; functional genomics; improved; in vivo; in vivo Model; inhibitor/antagonist; interest; light emission; neoplastic cell; novel; oncogene addiction; oncology; programs; public health relevance; success; therapy development; tool; tumor; tumor xenograft; vector

DESCRIPTION (provided by applicant): With few exceptions, extensive characterization of signal pathway alterations in cancer, and advances in our capacity to identify potent modulators of distinct molecular targets, has not translated into breakthrough drugs. In a recent New York Times article (Nov. 14, 2009), Mervyn Turner, Chief Strategy Officer for Merck was quoted: "We invest far too long in bad ideas." "It is really important to stop that at an earlier stage in the cycle". This is particularly evident in cancer drug development where over 90% of new anti-cancer drugs fail in the clinic. Our experiences in this area lead us to believe that one reason fo this problem is the lack of an efficient, clinically predictive platform for validating hypotheses nd making program advancement decisions at the earliest stages of the drug development process. Current in vivo models are resource intensive and rate limiting. Furthermore, current in vivo drug efficacy testing requires substantial investment in chemistry to optimize compounds for systemic delivery. Thus the majority of early drug development is heavily dependent on in vitro tumor cell models most of which are grown under conditions, such as in serum, which do not represent the native tumor environment. It is well accepted that these models do not reliably predict clinical efficacy. A second fundamental issue is that almost all tumors acquire resistance to single agent targeted therapies by rewiring signaling networks to reestablish effective oncogenic output. Proactive and rapid identification of alternative druggable pathway nodes would enable a shift in focus from developing drugs that target specific molecules to devising strategies to shut down oncogenic networks. To address these issues, we are developing an end-to-end platform that enables comprehensive functional interrogation of cancer pathways of interest to drug developers, compatible with rapid validation of findings in vivo co-clinical model at the earliest stages of cancer drug development. In Aim 1, we will employ a gene trap vector to generate tumor models that emit light only upon specific inhibition of key oncogenic pathway nodes. In Aim 2, we will use our porous needle array technology to demonstrate capacity to test, compare, and validate multiple agents, in the context of a single tumor grown in vivo, for anti-pathway and anti-tumor efficacy. Drs. Klinghoffer and Olson (Presage Biosciences Inc., and the Fred Hutchinson Cancer Research Center), who developed the porous needle array technology, have joined forces with Dr. Finney (Xactagen LLC), whose optimized gene trap vector system permits capture of pathway modulation via endogenous gene regulation with sensitivity amenable to in vivo analysis. Successful coupling of the porous needle array with high fidelity, high sensitivity gene trap derived oncogene pathway reporters will facilitate a paradigm shift from the current heavy reliance on standard in vitro based models early in the drug discovery process to more predictive and disease relevant in vivo models. Our platform will improve rational advancement of drug development projects, and in doing so, will increase the clinical success rate of new treatments that improve the health of cancer patients.

描述（由申请人提供）：除了少数例外，癌症中信号通路改变的广泛表征以及我们鉴定不同分子靶点的有效调节剂的能力的进展尚未转化为突破性药物。在最近的一篇纽约时报文章（2009年11月14日）中，默克公司首席战略官默文·特纳被引用说：“我们在坏主意上投资太久了。“在周期的早期阶段停止这种做法非常重要。这在癌症药物开发中尤其明显，超过90%的新抗癌药物在临床上失败。我们在这一领域的经验使我们相信，这个问题的一个原因是缺乏一个有效的，临床预测的平台来验证假设，并在药物开发过程的最早阶段做出项目推进决策。目前的体内模型是资源密集型和速率限制型的。此外，目前的体内药物功效测试需要在化学方面进行大量投资，以优化用于全身递送的化合物。因此，大多数早期药物开发严重依赖于体外肿瘤细胞模型，其中大多数在不代表天然肿瘤环境的条件下生长，例如在血清中。普遍认为这些模型不能可靠地预测临床疗效。第二个基本问题是，几乎所有的肿瘤都通过重新连接信号网络以重建有效的致癌输出来获得对单一药物靶向治疗的抗性。主动和快速识别替代药物途径节点将使重点从开发靶向特定分子的药物转移到设计关闭致癌网络的策略。为了解决这些问题，我们正在开发一个端到端的平台，该平台能够对药物开发人员感兴趣的癌症途径进行全面的功能性询问，与癌症药物开发早期阶段体内协同临床模型中发现的快速验证兼容。在目标1中，我们将采用基因陷阱载体来产生仅在特异性抑制关键致癌通路节点时发光的肿瘤模型。在目标2中，我们将使用我们的多孔针阵列技术来证明在体内生长的单个肿瘤的背景下测试、比较和验证多种药物的抗途径和抗肿瘤功效的能力。Klinghoffer和Olson博士（Presage Biosciences Inc.，和Fred哈钦森癌症研究中心），他们开发了多孔针阵列技术，已经与Finney博士（Xactagen LLC）联手，其优化的基因捕获载体系统允许通过内源性基因调控捕获途径调节，灵敏度适合于体内分析。多孔针阵列与高保真度、高灵敏度基因陷阱衍生的致癌基因途径报告物的成功偶联将促进从目前在药物发现过程早期严重依赖于基于标准体外模型到更具预测性和疾病相关性的体内模型的范式转变。我们的平台将促进药物开发项目的合理推进，从而提高改善癌症患者健康的新疗法的临床成功率。