(PQD5) Mass Profiling Melanoma Responses to Improve Therapy Choices and Prognosis

项目摘要/摘要 这项提议解决了D组的挑衅性问题(PQD5)：由于目前预测 新药候选在人体上的疗效或毒性往往是不准确的，我们能否开发新的方法来 测试潜在的治疗药物，以产生更好的反应预测？ 我们将解决在预测治疗反应以预测肿瘤复发方面的严重缺陷 并改善患者的预后，这通常是基于肿瘤的异质性。我们将实现这一目标 通过开发和应用一种新的单细胞响应测量技术，称为高通量 筛选活细胞干涉仪(HTS-LCI)，以量化单细胞生物量在时间上的变化 以及在接触毒品期间。通过10,000个随时间变化的生物量分布，我们将快速描述一个 肿瘤对治疗的异质性动力学反应，以便提供一个定量的统计分类器。 我们的建议是变革性的，对所有类型的癌症都有广泛的影响，但在这里我们重点关注 转移性黑色素瘤(主要是III-IV期)，因为1)它是一种发病率不断上升的常见癌症，2)是 通常是迅速致死的，3)关于靶向治疗和耐药性的了解很多。具体来说，MAPK 激活BRAF丝氨酸/苏氨酸激酶途径的突变存在于约50%的黑色素瘤中。 重要的是，具有良好特性的BRAF抑制物(BRAFi)敏感和耐药细胞系和新鲜患者 黑色素瘤样本很容易用于临床前的原则验证研究。 个性化医学的方法依赖于静态生物标记物、基因组和表观遗传学参数 改进治疗选择和预测预后，但它们都未能纳入治疗反应，这是一种 关键的遗漏。经过验证的、个性化的肿瘤细胞反应图谱可能对 治疗效果、癌症快速诊断、预后和肿瘤复发预测。要做到这一点 目标我们提出了一种新的方法，包括三个创新部分，包括1)设计HTS- LCI以实时量化肿瘤细胞生物量变化对治疗药物的响应；2)使用配对 BRAFi敏感和耐药的患者来源的转移性黑色素瘤细胞系已被广泛 由我们的合作者进行基因组、表观基因组和表达谱分析；以及3)利用我们的 通过与Jonsson Complete合作，立即访问未确认身份的患者样本 癌症中心临床医生及其正在进行的早期临床试验。我们建议的具体目标是： 目的1：建立BRAFi敏感和耐药的成对黑色素瘤细胞系统计分类器。 目的2：设计HTS-LCI，用于36孔板形式的多药物生长速率分析。 目的：评价HTS-LCI快速检测BRAFi敏感和抗性品系的价值。 目的：应用HTS-LCI平台对新鲜黑色素瘤患者样本进行生物量分析。

PROJECT SUMMARY/ABSTRACT This proposal addresses the Group D Provocative Question (PQD5): Since current methods to predict the efficacy or toxicity of new drug candidates in humans are often inaccurate, can we develop new methods to test potential therapeutic agents that yield better predictions of response? We will address critical shortcomings in predicting therapeutic responses to anticipate tumor recurrence and improve patient outcome, which is usually based on tumor heterogeneity. We will accomplish this goal by developing and applying a novel single-cell response measuring technology, termed a High-Throughput Screening Live Cell Interferometer (HTS-LCI), to quantify single-cell biomass changes temporally, before and during drug exposure. With 10,000s of time-dependent biomass profiles, we will rapidly characterize a tumor's heterogeneous kinetic response to therapy in order to provide a quantitative statistical classifier. Our proposal is transformative with broad implications for all types of cancer, but here we focus on metastatic melanoma (mainly stage III-IV) because 1) it is a common cancer with increasing incidence, 2) is often rapidly fatal, and 3) much is known about targeted therapy and resistance. Specifically, MAPK pathway-activating BRAF serine/threonine kinase mutations are present in ~50% of melanomas. Importantly, well-characterized BRAF-inhibitor (BRAFi) sensitive and resistant cell lines and fresh patient melanoma samples are readily available for proof-of-principle preclinical studies. Approaches in personalized medicine rely on static biomarker, genomic, and epigenetic parameters to refine therapy choice and predict prognosis, but they all fail to incorporate therapeutic response, which is a critical omission. Validated, individualized tumor cell response profiling could have enormous impact on therapeutic efficacy, rapid cancer diagnosis, prognosis, and prediction of tumor recurrence. To reach this goal we propose a new approach with three innovative components that include 1) engineering the HTS- LCI to quantify tumor cell biomass changes in response therapeutic agents, in real time; 2) using paired BRAFi sensitive and resistant patient-derived metastatic melanoma cell lines that have been extensively characterized for genomic, epigenomic, and expression profiling by our collaborators; and 3) utilizing our immediate access to de-identified patient samples through collaboration with Jonsson Comprehensive Cancer Center clinicians and their ongoing early phase clinical trials. The Specific Aims of our proposal are: Aim 1: To generate a BRAFi sensitive and resistant paired melanoma cell line statistical classifier. Aim 2: To engineer the HTS-LCI for multi-drug growth rate profiling in a 36-well plate format. Aim 3: To evaluate the HTS-LCI for rapid response detection of BRAFi sensitive and resistant lines. Aim 4: To apply the HTS-LCI platform for biomass profiling of fresh melanoma patient samples.