Overcoming Tumor Resistance to Chemotherapy with Multiscale Diffuse and Nonlinear Imaging

项目摘要/摘要 2016年，美国估计新诊断出25万例女性乳腺癌病例，导致 估计有4万人死亡。几乎所有的乳腺癌死亡都是由于肿瘤对全身系统的渐进性抵抗造成的。 治疗，然后是转移。预测乳腺癌的化疗耐药是一项重大的临床挑战 因为通常监测的参数的变化，包括肿瘤体积或葡萄糖类似物摄取， 已被证明不能很好地预测耐药性，而且往往只有在耐药性发生后才表现出来。这个 准确预测化疗耐药发生的能力将使医生能够根据证据 及时改变治疗方法，这可以极大地改善患者的预后。新的临床前研究 在适当的空间和时间尺度上跟踪阻力的成像技术可以提供 临床化疗耐药的有效管理的关键见解。F99阶段的目标是 开发一种名为漫反射和非线性成像(DNI)的新成像技术，它将两种不同的 在从cm到μm的空间尺度上对比机制以监测体内的耐药性。DNI利用乘法 用于广泛绘制肿瘤代谢图的散射光子，以及实现分子的多光子相互作用， 具有3D细胞分辨率的结构和代谢肿瘤成像。这些技术将结合在一起，以 共同注册的集成临床前成像系统，提供前所未有的肿瘤评估 在一系列空间尺度和对比机制上的异质性。DNI将整合外源和 分子靶向显像剂与内源性显像源获得更完整的显像剂 体内肿瘤状态的图片。第一个目标是将血管组织的非线性切片与 临床前乳腺肿瘤通过窗腔的弥散成像的氧合图谱。第二 目的是通过DNI监测治疗的临床前乳腺来确定化疗耐药的光学特征 肿瘤。最后，第三个目标是将光学阻力指标与肿瘤血管组织的异质性联系起来。 K00阶段的目标是研究治疗的时间安排和空间分布如何影响到 抵抗。这需要跟踪不同的克隆种群及其复杂的动态和竞争 药物与肿瘤的相互作用。抗性和异质性的遗传和表型标记将被标记为 经过改造的纳米光学探测器。这些将实现纵向和同时的多路复用和成像 复杂的克隆相互作用，以及临床前和临床肿瘤个体体内克隆动力学的捕获。 然后将开发一种光学技术来使用光释放技术来控制时空治疗 参数和克隆巢间药物分布的跟踪研究药物-肿瘤相互作用对肿瘤生长的影响 长期抵抗。设计一种用光控制的一体化光学肿瘤学研究平台 治疗，绘制药物分布图，并通过不同的对比剂机制成像结果 不同的空间和时间尺度，将为有效治疗耐药肿瘤提供新的见解。

PROJECT SUMMARY/ABSTRACT In 2016, an estimated 250,000 new cases of female breast cancer were diagnosed in the U.S., causing an estimated 40,000 deaths. Almost all breast cancer deaths are due to tumor progressive resistance to systemic therapies, followed by metastasis. Anticipating breast cancer chemoresistance is a significant clinical challenge because the changes in commonly monitored parameters, including tumor volume or glucose-analog uptake, have been shown to be poor predictors of resistance and often manifest only after resistance has occurred. The ability to accurately predict the onset of chemoresistance would allow physicians to make evidence based treatment changes in a timely manner, which could substantially improve patient outcomes. New preclinical imaging techniques designed to track resistance over the appropriate spatial and temporal scales could provide key insights into the effective management of chemoresistance in the clinic. The goal of the F99 phase is to develop a novel imaging technique called Diffuse and Nonlinear Imaging (DNI) that combines two different contrast mechanisms over spatial scales ranging from cm to μm to monitor resistance in vivo. DNI utilizes multiply scattered photons for widefield mapping of tumor metabolism, and multiphoton interactions to achieve molecular, structural, and metabolic tumor imaging with cellular resolution in 3D. These techniques will be combined to make an integrated preclinical imaging system that is co-registered, providing unprecedented evaluation of tumor heterogeneity over a range of spatial scales and contrast mechanisms. DNI will integrate exogenous and molecularly targeted imaging agents with endogenous sources of imaging contrast to obtain a more complete picture of the in vivo tumor state. The first aim is to co-register nonlinear sectioning of vascular organization with oxygenation maps from diffuse imaging of preclinical mammary tumors through a window chamber. The second aim is to identify optical signatures of chemoresistance via DNI monitoring of treated preclinical mammary tumors. Lastly, the third aim is to link optical resistance metrics to heterogeneity in tumor vascular organization. The goal of the K00 phase is to study how the scheduling and spatial distribution of treatment affect the time-to- resistance. This entails tracking distinct clonal populations, and their complex dynamics and competition during drug-tumor interactions. Genetic and phenotypic markers of resistance and heterogeneity will be labeled with engineered nano-optical probes. These will enable longitudinal and simultaneous multiplexing and imaging of complex clonal interactions, and capturing of individual clonal dynamics in vivo in preclinical and clinical tumors. An optical technique will then be developed to use photorelease technology to control spatiotemporal treatment parameters and track drug distribution among clonal nests to study the effects of drug-tumor interactions on long-term resistance. Engineering an all-in-one investigative optical oncology platform that uses light to control treatment, map drug distribution, and image the resulting effects with various contrast mechanisms across different spatial and time scales, will provide novel insights into the effective treatment of resistant tumors.