An integrated acoustofluidic droplet-sorting platform for classification of lymphocyte activity and functional phenotyping at single cell level

摘要 许多病理性疾病如感染和癌症的结果是由相互作用决定的 疾病细胞与各种免疫细胞亚群的关系，这两种免疫细胞亚群在表型和功能上都是多样的。 对化疗和免疫治疗药物的诱导抗性仍然是现代免疫治疗的主要挑战之一。 药此外，存在显著的患者间和甚至患者内的变异性，以响应良好- 由于药物治疗方案尚未建立，因此很难预测患者对应用治疗的反应。单细胞 分析技术在揭示并最终利用患者特异性细胞免疫应答方面具有巨大的潜力。 这些信息有助于设计更个性化的治疗方案。因此，快速发展 用于评估靶-免疫细胞相互作用的筛选系统，所述靶-免疫细胞相互作用由免疫原性调节 治疗，将允许临床医生预测患者对治疗的反应，简化治疗方案， 并以患者特异性方式提高免疫策略的功效。在此，我们建议 开发基于微流体液滴的集成平台，该平台允许定量分析 免疫反应（响应与非响应和快速与缓慢动力学）和随后的分选， 用于分子（转录组学）表征的功能不同子集的恢复。我们建议 集成大规模液滴微流控阵列与双声流控分选器， 通量（> 18，000事件/秒）和可控性（四通道分选），这是任何微流体液滴分选仪都不具备的 能够实现。总的来说，分选器和液滴对接阵列将允许选择， 在不同细胞中富集和可视化含有效应免疫细胞和靶细胞的感兴趣的液滴 比率，从而允许动态分析细胞-细胞相互作用以鉴定预测性表型分类器。的 然后通过全局转录组学分析和无偏系统生物学方法分析分选的细胞 以确定关键分子特征和功能异质性之间的相关性。该多功能 分析平台将进一步实现在单细胞水平上筛选和验证靶向治疗， 将所述包封的效应细胞/靶细胞经由药物组合物依次暴露于第一代和第二代药物。 集成的液滴合并结。这种方法将大大加强对候选药物的鉴别 在治疗性给药之前，以帮助疾病和患者特异性治疗决策。我们将 验证我们的平台通过功能分类淋巴瘤自然杀伤（NK）细胞的相互作用，在存在 批准的抗CD 20免疫疗法，以（1）确定实现高度免疫所需的最佳免疫活性， 对抗CD 20免疫疗法的有效反应;和（2）获得对发展的重要见解 抗CD 20治疗的癌症。我们设想这个平台最终将被用于各种 单细胞分析应用，对生物医学、药学研究具有重要价值 社区.

Abstract The outcome of many pathological diseases such as infection and cancer is determined by the interaction of diseased cells with various immune cell subsets, both of which are phenotypically and functionally diverse. Induced resistance to chemo- and immuno-therapeutic drugs remain one of the main challenges in modern medicine. Moreover, there exists significant inter-patient and even intra-patient variability in response to well- established drug regimens, making it difficult to predict a patient's response to applied treatments. Single-cell analysis techniques have great potential in revealing, and ultimately utilizing, patient-specific cellular information to devise a more personalized approach to therapeutic regimens. Thus, developing a rapid screening system for assessing target-immune cell interactions, which are modulated by immunogenic treatments, will allow clinicians to predict the patient's response to a treatment, streamline treatment protocols and improve the efficacy of immunotherapeutic strategies in patient-specific manner. Here, we propose to develop an integrated microfluidic droplet based platform that permits quantitative analysis of the efficiency of immune reactions (responsive vs. non-responsive and fast vs. slow kinetics) and subsequent sorting and recovery of functionally distinct subsets for molecular (transcriptomic) characterization. We propose to integrate large-scale droplet microfluidic arrays with dual acoustofluidic sorters that achieve a level of throughput (>18,000 events/sec) and controllability (four-channel sorting) that no microfluidic droplet sorter has been able to achieve. Collectively, the sorters and the droplet docking arrays will allow for selection, enrichment and visualization of droplets of interest containing effector immune and target cells at different cell ratios, thereby allowing dynamic analysis of cell-cell interaction to identify predictive phenotypic classifiers. The sorted cells will then be analyzed by global transcriptomic profiling and unbiased systems biology approaches to identify the correlation between key molecular signatures and functional heterogeneity. This multifunctional analytical platform will further enable screening and validation of targeted therapies at single-cell level by sequentially exposing the encapsulated effector/target cells to first and second generation drugs via an integrated droplet merging junction. This approach will greatly enhance the identification of drug candidates prior to therapeutic administration to assist in disease - and patient-specific treatment decisions. We will validate our platform by functionally classifying lymphoma-Natural Killer (NK) cell interaction in the presence of approved anti-CD20 immunotherapy to (1) determine optimal immune activity required to achieve highly effective response to anti-CD20 immunotherapy; and (2) obtain critical insights into the development of resistance to anti-CD20 therapy in cancer. We envision this platform ultimately being employed in a variety of single-cell analysis applications and being of high value to the biomedical, and pharmaceutical research communities.