首页> 美国卫生研究院文献>Neuro-Oncology >TMOD-13. MAXIMIZING THE POWER OF PATIENT TUMOR-DERIVED ORTHOTOPIC XENOGRAFT (PDOX) MODELS OF PEDIATRIC BRAIN TUMORS TO PREDICT DRUG RESPONSES IN HUMANS
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TMOD-13. MAXIMIZING THE POWER OF PATIENT TUMOR-DERIVED ORTHOTOPIC XENOGRAFT (PDOX) MODELS OF PEDIATRIC BRAIN TUMORS TO PREDICT DRUG RESPONSES IN HUMANS

机译:TMOD-13。最大化患者的肿瘤源性正交异种移植(PDOX)模型预测人类药物反应的能力

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摘要

Brain tumors are the leading cause of cancer-related death in children. A major challenge in the development of new therapies is the failure of many model systems to accurately predict drug responses patients. We identified two major weakness common to the majority of available models of pediatric brain tumors. First, while patients receive multi-modal therapy, pre-clinical testing typically involves the comparison of single agent therapy to placebo or other single agents. Two, while the majority of early phase clinical trials are carried out in relapsed, frequently heavily pre-treated patients; pre-clinical models almost exclusively represent untreated disease. To begin to address these issues, our lab has leveraged our large panel (>80) orthotopic xenograft mouse models of brain tumors which have undergone extensive molecular characterization. We designed treatment schedules based on original patient treatment data for 8 pediatric glioblastoma models and 9 medulloblastoma models and treated them accordingly. We are able to demonstrate the feasibility of combining radiation and multi-agent cytotoxic chemotherapy our mouse models. Furthermore, our results correlate with what has been seen in large scale human clinical trials with glioblastoma and DIPG models showing little benefit from standard treatments while medulloblastoma models show a significant increase in survival time. Going forward, these survival data will provide a more appropriate basis for the comparison of novel compounds allowing for increased efficiency in translating promising new treatments. Furthermore by harvesting the tumors which progressed after being exposed to patient based therapies, we have generated a resource that will allow for the establishment of more accurate models of brain tumor relapse in the future.
机译:脑肿瘤是儿童癌症相关死亡的主要原因。开发新疗法的主要挑战是许多模型系统无法准确预测患者的药物反应。我们确定了两个主要的小儿脑肿瘤可用模型共有的两个主要缺点。首先,当患者接受多模式治疗时,临床前测试通常涉及将单药治疗与安慰剂或其他单药进行比较。二是大多数早期临床试验是在复发且经常接受大量治疗的患者中进行的;临床前模型几乎专门代表未治疗的疾病。为了开始解决这些问题,我们的实验室利用了经过大规模分子鉴定的大型(> 80)原位异种移植脑肿瘤小鼠模型。我们基于原始的患者治疗数据设计了8种小儿胶质母细胞瘤模型和9种髓母细胞瘤模型的治疗方案,并进行了相应的治疗。我们能够证明在小鼠模型中结合放射线疗法和多剂细胞毒性化学疗法的可行性。此外,我们的结果与在胶质母细胞瘤和DIPG模型的大规模人类临床试验中看到的结果相关,这些试验显示标准治疗获益不大,而髓母细胞瘤模型则显示生存时间显着增加。展望未来,这些生存数据将为比较新型化合物提供更合适的基础,从而提高翻译有希望的新疗法的效率。此外,通过收集在接受基于患者的疗法后进展的肿瘤,我们获得了可用于将来建立更准确的脑肿瘤复发模型的资源。

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