Development of a novel platform for label-free monitoring of CAR-T cell interactions in vivo

嵌合抗原受体(CAR)-T细胞疗法产生了戏剧性的、持久的反应，特别是对 标准治疗难以治愈的B细胞恶性肿瘤患者。大量的临床试验是重点 关于改进治疗范围更广的恶性血液病的方法和应用 实体瘤。然而，这种靶向治疗也与高复发率和发生 严重的毒性很难预测。因此，优化和监控响应的改进工具有 这是急需的。我们的最终目标是开发一种简单、定量和非侵入性的护理点设备 以所需频率动态监测体内CAR-T细胞相互作用。这项提议的目标是 以演示该方法的原则证明及其对人类研究的翻译潜力。我们的方法 依赖于使用内源性和外源性光学来源的体内流式细胞术(IVFC)评估 对比及其优化方法在体内外检测CAR-T/B细胞相互作用中的应用建议数 该方法依赖于内源性光散射和荧光(无标记或LF)信号的共聚焦检测 相互作用的流动的CAR-T/B细胞。以前的研究支持相互作用的CAR-T/B的假说 细胞可能会产生独特的光学特征。我们预计先进的信号处理技术的应用 这些方法将使我们能够在具有挑战性的体外血液流动环境中优化对这些信号的检测 在活体内。荧光蛋白(FP)表达人CAR-T和B细胞的初步测量 全血将允许我们开发、实施和评估硬件和软件方面的增强，以实现 准确评估相互作用的CAR-T和B细胞的LF-IVFC。(目标1.1)。翻译的潜力将是 对接受CAR-T细胞治疗的患者在不同时间点分离的血液样本进行检测 第一个月的治疗。我们希望使用LF-来检测相互作用的CAR-T和B细胞数量的变化。 IVFC和这一预期将被基于抗体的流式细胞术测量(AIM 1.2)所证实。 最后，我们将在体内进行基于LF和FP的IVFC测量，使用注入人B的小鼠 淋巴母细胞和CAR-T细胞在已知浓度下可引起相对循环水平的变化 这些细胞。我们的目标将是证明LF-IVFC测量可以在足够高的情况下进行 准确检测一个月内相互作用的CAR-T和B细胞数量的动态变化。我们预计 要生成一组强大的数据，以推动低频静脉内营养监测的开发和应用 与CAR-T/B细胞相互作用，对接受CAR-T细胞治疗的患者进行动态、非侵入性监测。这样的一个 该设备可以利用组合时间来获取关于个体患者响应的信息 分辨率和灵敏度/特异度是目前无法实现的。我们预计这样的数据将产生一个 新的患者监测模式，以优化响应并识别可能需要更及时的患者 旨在优化结果的干预措施。

Chimeric antigen receptor (CAR)-T cell therapy has resulted in dramatic, durable responses, especially for patients with B cell malignancies that are refractory to standard treatment. Numerous clinical trials are focused on improvements of the approach and applications for a much broader range of hematologic malignancies and solid tumors. However, this targeted therapy is also associated with high relapse rates and the development of severe toxicities that are challenging to predict. Thus, improved tools to optimize and monitor response are critically needed. Our ultimate goal is to develop a simple, quantitative, and non-invasive point-of-care device to monitor CAR-T cell interactions in vivo dynamically with the needed frequency. The objective of this proposal is to demonstrate proof-of-principle of the approach and its translational potential for human studies. Our approach relies on in vivo flow cytometry (IVFC) assessments using endogenous and exogenous sources of optical contrast and its optimization and use to detect CAR-T/B cell interactions in vitro and in vivo. The proposed method relies on the confocal detection of endogenous light scattering and fluorescence (label-free or LF) signals of flowing CAR-T/B cells that are interacting. Previous studies support the hypothesis that interacting CAR-T/B cells will likely yield unique optical signatures. We anticipate that utilization of advanced signal processing approaches will enable us to optimize detection of these signals in the challenging milieu of flowing blood in vitro and in vivo. Initial measurements with fluorescent protein (FP)-expressing human CAR-T and B cells spiked in whole blood will allow us to develop, implement, and assess enhancements in hardware and software to realize accurate LF-IVFC assessments of interacting CAR-T and B cells. (Aim 1.1). The translational potential will be tested on blood samples isolated from patients undergoing CAR-T cell therapy at different time points over the first month of therapy. We expect to detect variations in the numbers of interacting CAR-T and B cells using LF- IVFC and this expectation will be corroborated with antibody-based flow cytometry measurements (Aim 1.2). Finally, we will perform in vivo LF and FP-based IVFC measurements using mice infused with human B lymphoblasts and CAR-T cells at concentrations known to induce variations in the relative circulating levels of these cells. Our goal will be to demonstrate that LF-IVFC measurements can be performed with high enough accuracy to detect dynamic changes in the numbers of interacting CAR-T and B cells over a month. We expect to generate a robust set of data that will motivate development and application of LF-IVFC monitoring of interacting CAR-T/B cells for dynamic, non-invasive monitoring of patients receiving CAR-T cell therapy. Such a device may enable acquisition of information regarding individual patient responses with a combined time resolution and sensitivity/specificity that is not possible to achieve currently. We anticipate such data will yield a novel paradigm for patient monitoring to optimize response and identify patients that may need more timely interventions to optimize outcomes.