(PQD5) Predicting Anti-Cancer Efficacy through Tumor Profiling

描述（由申请人提供）：阻碍我们了解黑色素瘤和其他人类癌症治疗难治性的能力的一个实验问题是缺乏经过验证且可靠的功效测试模型。从历史上看，有前途的抗癌化合物已经在体外测试了临床前疗效，然后在人体测试之前在小鼠“异种移植”模型中进行了测试。在异种移植系统中，人癌细胞系在免疫功能低下的小鼠的皮肤下生长，然后用预期的疗法治疗携带异种移植物的动物。这些模型不是生理性的，并且在预测治疗成功方面的记录很差。最近的变化使得有可能在癌症的基因工程小鼠模型（GEMM）中测试潜在的癌症疗法，这为异种移植模型提供了几个优势。在MEDIO小鼠I期单位（MP1U）进行的研究表明，GEMM中的测试可以更好地复制人体药代动力学和疗效预测，这些研究的结果可以为临床试验提供及时的数据。在本提案中，我们将研究几种新型抗癌药物的治疗效果，这些药物将在黑色素瘤患者中进行人体试验，使用我们认证的GEMM。我们将选择目前正在人体临床试验中测试的方案进行测试，包括抗免疫系统靶向治疗，这些治疗无法在异种移植模型中进行测试。通过使用几个精心选择和验证的GEM模型的黑色素瘤窝藏不同的“驱动”遗传学，我们将确定与特定的治疗药物的反应相关的体细胞事件。将使用RNA和DNA的基因组分析来测试反应性和难治性肿瘤，以提供对治疗反应的进一步理解。然后，我们将这些药物在GEMM中的预测疗效与12项正在进行或计划进行的人类临床试验的结果进行比较，以经验性地确定这些小鼠“协同临床”试验预测人类黑色素瘤患者疗效的能力。

DESCRIPTION (provided by applicant): An experimental issue hampering our ability to understand the therapeutic refractoriness of melanoma and other human cancers has been a lack of validated and faithful models for efficacy testing. Historically, promising anti-cancer compounds have been tested for preclinical efficacy in vitro and then in mouse 'xenograft' models prior to human testing. In xenograft systems, human cancer cell lines are grown under the skin of immunocompromised mice, and then xenograft-bearing animals are treated with intended therapies. These models are not physiologic, and have a poor track record of predicting therapeutic success. Recent changes have made it possible to test would-be cancer therapies in genetically engineered murine models (GEMMs) of cancer, which provide several advantages to xenograft models. Studies conducted in the UNC Mouse Phase I Unit (MP1U) have shown that testing in GEMMs can better replicate human pharmacokinetics and efficacy prediction, and results from these studies can provide timely data for clinical trials. In this proposal we will study the therapeutic efficacy of several novel anti-cancer drugs slated for human trials in patients with melanoma, using our credentialed GEMMs. We will chose for testing, regimens that are currently being testing in human clinical trials, including anti-immune system targeted therapeutics, which are not able to be tested in xenograft models. Through the use of several well selected and validated GEM models of melanoma harboring different 'driver' genetics, we will identify somatic events associated with response to specific therapeutic agents. Responding and refractory tumors will be tested using genomic analysis of RNA and DNA to provide a further understanding of therapeutic response. We will then compare the predicted efficacy of these agents in GEMMs to results from 12 ongoing or planned human clinical trials, to empirically determine the ability of these murine 'co-clinical' trials to predit efficacy in human patients with melanoma.