MusIC: A multi-scale technology for integrating dynamic cellular function and molecular profiles

我们的目标是开发并严格验证一种将蜂窝 功能/活性及其深层分子特征，单细胞分辨率，高通量。 免疫疗法已经成为治疗人类癌症的一种非常有效的方法，并通过 利用免疫系统的力量及其识别和消除癌细胞的能力。 免疫疗法具有明显的优势，包括：(1)持久的反应；(2)明确的机制 与传统方法相比，该方法具有更高的特异性和更少的靶标效应。与抗体一起 免疫疗法，基因工程T细胞重定向免疫反应最近收到了食物 和药品管理局(FDA)的批准。基于输注体外扩增T细胞的过继细胞疗法(ACT) 携带T细胞受体(TCR)或嵌合抗原受体(CAR)的细胞已经表现出戏剧性的 和持久的反应，即使在经过大量预治疗的患者中也是如此。尽管取得了这些初步的临床成功，患者 人们的反应千差万别。最近的相关数据表明，制造的T细胞产品中的可变性可能 成为临床成功的主要决定因素。由于细胞输液产品是不同种类的混合物 细胞，绘制种群的复杂性需要识别功能和分子图谱的能力 单元格分辨率的单元格。对于能够映射这种复杂性的技术是必不可少的 在T细胞功能方面，并能够在单细胞分辨率下将功能与分子图谱联系起来。我们建议 多尺度智能融合(MUSIC)的开发与验证音乐将提供多尺度 从分子到亚细胞动力学再到细胞间相互作用生物学的数据跨越数千个相同的细胞 细胞的数量。鉴于用于ACT的细胞组成的异质性，它是用于 音乐的发展和验证。我们的研究团队在单细胞技术方面拥有专业知识 开发和免疫治疗、机器学习、图像分析和数据建模。我们预料到 这一建议的成功实施将使音乐作为学习平台的有效性得到验证 多尺度细胞生物学。反过来，这将导致T细胞输注产品的更可靠的生物制造， 设计更强大的免疫细胞可以对免疫治疗产生广泛的影响。

Our objective is develop and rigorously validate a transformative technology that integrates cellular functions/activities with their deep molecular signatures at single-cell resolution, in high-throughput. Immunotherapy has emerged as a highly effective approach for the treatment of human cancer, and works by harnessing the power of the immune system and its ability to recognize and eliminate cancer cells. Immunotherapy has distinct advantages, including: (i) sustained and durable responses; (ii) defined mechanisms of action; and (iii) higher specificity and fewer-off target effects than traditional approaches. Along with antibody immunotherapy, genetically engineering T cells for redirecting immune responses has recently received Food and Drug Administration (FDA) approval. Adoptive cell therapy (ACT), based on infusing in vitro expanded T cells bearing either T-cell receptors (TCR), or chimeric antigen receptors (CAR), have demonstrated dramatic and durable responses, even in heavily pretreated patients. Despite these initial clinical successes, patient responses vary widely. Recent correlative data indicate that variability in the manufactured T cell products may be the primary determinant of clinical success. Since cellular infusion products are a heterogeneous mixture of cells, mapping the complexity of the population requires the ability to identify the function and molecular profiles of cells at single-cell resolution. There is an essential need for technologies that are able to map this complexity in T-cell functionality and being able to link function to molecular profiles at single-cell resolution. We propose the development and validation of Multiscale Intelligent Convergence (MusIC). MusIC will provide multi-scale data from molecules to subcellular dynamics to cell-cell interaction biology on the same cells across thousands of cells. Given the heterogeneity in the composition of cells being used for ACT, it serves as the ideal system for the development and validation of MusIC. Our team of investigators has expertise in single-cell technology development and immunotherapy, machine learning, and image analysis and data modeling. We anticipate that the successful implementation of this proposal will enable the validation of MusIC as a platform for studying multi-scale cell biology. This in turn, will lead to the more reliable biomanufacturing of T-cell infusion products, and the engineering of more potent immune cells can have a broad impact on immunotherapy.