Quantitative analysis of pharmacological mechanism by intravital imaging

该提案来自一个跨学科团队，该团队具有成像，系统生物学和 临床研究（Weissleder，Sorger，Mitchison和Danuser）。其响应RFA-CA-11 - 005， 并建议在小鼠中创建和验证定量癌症药理学平台， 使用单细胞水平的活体成像。当前的目标是确定个人 肿瘤中的癌细胞对单剂和双剂治疗的体内应答， 药物在肿瘤细胞中的摄取和分布（药物动力学，PK），以及多种 在不同的时间尺度上发挥作用的下游反应（药效学，PD）。我们 重点将放在navitoclax（ABT 263; Bcl-2和Bcl-Xl的研究拮抗剂）的使用上 和吉西他滨（一种成熟的S期特异性细胞毒性药物），无论是单独使用还是在 组合.目标1将开发和验证用于测量药物前肿瘤的活细胞生物传感器 通过活体内亚细胞分辨在小鼠异种移植肿瘤中的状态和药物反应 显像AIM2将开发基于新型生物正交的可注射显像剂 将用于荧光或18F标记药物的化学物质。这些代理将在 使用aim 1的生物传感器进行验证。目标3将侧重于开发计算 从活体图像中提取定量数据的方法，以及创建数据的方法， 驱动的多尺度（PK/PD;单细胞动力学和机制/分子）数学模型 阐明了单一疗法和联合疗法之间的治疗相关差异。 总的来说，我们的目标是获得对药物作用的理解，即：a）定量（在 可能在时间和空间上变化的数据的处理）; B）概率性的（考虑小区到小区的 和肿瘤间变异性）; c）分子水平的机制; d）后基因组 （分析具有已知遗传差异的多种细胞系和患者样品）; （假设药物反应的决定因素是多因素的）; f）数学上 复杂的（关于质量作用、集总参数和随机建模）;以及g） 医学相关（通过分析目前正在临床研究中的联合治疗， 通过开发可翻译的测量方法）。该项目的成功将导致 单细胞癌症药理学的综合平台。该平台不仅将为 克服将临床前结果转化为临床环境的主要障碍， 但将为合理和预测性的联合治疗提供知识基础。同样，它 将提高我们开发能够抑制新的和现有目标的有效药物的能力， 也可更广泛地用于其他新兴抗癌药物的开发。

This proposal is from an inter-disciplinary team with expertise in imaging, systems biology and clinical research (Weissleder, Sorger, Mitchison and Danuser). It responds to RFA-CA-11-005, and proposes to create and validate a platform for quantitative cancer pharmacology in mice using live imaging at the single-cell level. The immediate goal is to determine how individual cancer cells in tumors respond to single and dual-agent therapy in vivo by measuring both the uptake and distribution of drugs in tumor cells (pharmaco-kinetics, PK), as well as the multiple downstream responses that play out over different time-scales (pharmaco-dynamics, PD). Our focus will be on the use of navitoclax (ABT263; an investigational antagonist of Bcl-2 and Bcl-Xl) and gemcitabine (a well established, S-phase-specific cytotoxic drug), both individually and in combination. Aim 1 will develop and validate live-cell biosensors for measuring pre-drug tumor states and drug responses in mouse xenograft tumors by sub-cellular resolution intravital imaging. Aim 2 will develop injectable imaging agents based on novel bioorthogonal chemistries that will be used to label drugs fluorescently or with 18F. These agents will then be validated using the biosensors from aim 1. Aim 3 will focus on the development of computational methods for extracting quantitative data from intravital images, and on the creation of data- driven, multi-scale (PK/PD; single cell kinetics and mechanistic/molecular) mathematical models that elucidate therapeutically relevant differences between mono and combination therapy. Overall, our goal is to gain an understanding of drug action that is: a) quantitative (in the treatment of data that may vary in time and space); b) probabilistic (accounting for cell-to-cell and tumor-to-tumor variability); c) mechanistic at the molecular level; d) post-genomic (analyzing diverse cell lines and patient samples with known genetic differences); e) integrative (assuming that determinants of drug response are multi-factorial); f) mathematically sophisticated (with respect to mass-action, lumped parameter and stochastic modeling); and g) medically relevant (by analyzing a combination therapy currently under clinical investigation and by developing translatable measurement methods). Success of the project will result in an integrated platform for single-cell cancer pharmacology. This platform will not only serve to overcome prevailing impediments to the translation of preclinical results into a clinical setting, but will provide the knowledge base for rational and predictive combination therapy. Likewise, it will improve our ability to develop effective drugs capable of inhibiting new and existing targets, and could also be more broadly used in the development of other emerging anti-cancer drugs.