(PQD5) Predicting Anti-Cancer Efficacy through Tumor Profiling

描述(由申请人提供)：阻碍我们理解黑色素瘤和其他人类癌症治疗难治性的一个实验问题是缺乏有效和可靠的疗效测试模型。从历史上看，有希望的抗癌化合物在体外进行了临床前疗效测试，然后在人体测试之前在小鼠的异种移植模型中进行了测试。在异种移植系统中，人类癌细胞系生长在免疫受损小鼠的皮肤下，然后对携带异种移植的动物进行预定的治疗。这些模型不是生理学的，在预测治疗成功方面记录不佳。最近的变化使在癌症的基因工程小鼠模型(GEMM)中测试潜在的癌症治疗成为可能，这为异种移植模型提供了几个优势。在北卡罗来纳大学小鼠第一阶段单元(MP1U)进行的研究表明，在GEMM中进行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。在这项提案中，我们将使用我们认证的GEMM研究几种计划在黑色素瘤患者身上进行人体试验的新型抗癌药物的治疗效果。我们将选择目前正在进行人体临床试验的方案进行测试，包括抗免疫系统靶向疗法，这些疗法无法在异种移植模型中进行测试。通过使用几个经过精心挑选和验证的黑色素瘤GEM模型，具有不同的“驱动”基因，我们将识别与特定治疗剂的反应相关的躯体事件。反应和难治性肿瘤将使用RNA和DNA的基因组分析进行测试，以提供对治疗反应的进一步了解。然后，我们将把这些药物在GEMM中的预测疗效与12个正在进行或计划中的人类临床试验的结果进行比较，以实证地确定这些小鼠“共同临床”试验对患有黑色素瘤的人类患者的疗效。

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.