Graft Engineering of Allogeneic Hematopoietic Stem Cell Products with Molecular Cascades

建议书摘要 根据有无识别具有不同功能的造血细胞亚群 细胞表面标记物。某些亚群被认为是移植物抗宿主病的媒介。 异基因造血干细胞移植(AHSCT)中的GVHD。最先进的努力 将这些副作用降至最低，并已应用于临床，依靠扩展的三步免疫磁学 顺序正选择分离方案(用于保护干细胞免于消除，基于 CD34表达)，负选择(基于CD45RA表达的原始TN细胞的消除)，以及 随后将阳性选择的干细胞返回移植物，然后将其引入患者体内。这个 然而，工程移植物也会耗尽B细胞、NK细胞和Treg细胞，这些细胞是控制霍乱的关键。 感染并发症、移植物抗宿主病的调节和复发控制，从而影响术后长期生存 移植。快速高效的单步正面或负面选择，可最大限度地减少对 走出自然生态位的细胞也会改善细胞健康，可能会带来更好的临床结果。高 精确的单步程序也将为我们提供一个严格和可靠的研究 特定细胞亚群的高质量制剂在疾病动物模型中的影响。 我们最近开发了基于与靶向结合的寡核苷酸的分子计算级联 部分(如抗体、抗体片段和适配子)。这些是靶向部分的混合物， 携带分子计算元素并产生一种结果，即单个细胞亚群上的特定标记， 基于对所有目标部分的考虑。因此，例如，三步分离会是什么？ 将流式细胞术中的三色荧光表征浓缩为一步 分离程序或单一颜色的流式细胞术。这些计算寡核苷酸的混合物 因此，具有靶向部分的偶联物特别适合于单步“混合分离”细胞标记 用于磁选的协议。我们的级联可以基于细胞表面的存在来阻止隔离 或者它们可以放大来自低表达水平的表面标记的信号。 在这个项目中，我们将问两个主要问题：(1)在指标为收益率的情况下，实际限制是什么， 当应用于细胞亚群的分离时，分子计算级联的细胞的纯度和健康 临床应用？以及，(2)我们必须保存或保存的最小细胞亚群是多少？ 消除，以最大限度地减少各种形式的GVHD的诱发。在三个目标中，我们将解决翻译和 移植物工程和使用日益复杂的移植物诱导移植物抗宿主病的机制问题 协议。我们将用不同水平的标记来表征细胞群体对幼稚、中央 记忆，以及GVHD小鼠模型中的Treg细胞，同时评估 与标准方法相比，日益复杂的分子计算级联。

Proposal Summary Subpopulations of hematopoietic cells with different functions are identified based on the presence or absence of cell surface markers. Certain subpopulations are hypothesized to mediate forms of graft-vs-host disease (GVHD) in allogeneic hematopoietic stem cell transplantations (aHSCT). The most advanced efforts to minimize these side effects, and to have reached clinics, rely on an extended three step immunomagnetic separation protocol with sequential positive selection (for protection of stem cells from elimination based on CD34 expression), negative selection (elimination of naïve TN-cells based on CD45RA expression), and subsequent return of positively selected stem cells to the graft that is then introduced into patients. The engineered graft, however, is also depleted of B-, NK-, and Treg-cells, which are essential for control of infectious complications, modulation of GVHD, and relapse control, thus impacting long-term survival after transplantation. Rapid and efficient single-step positive or negative selections that would minimize handling of cells out of their natural niches would also improve cell health likely leading to better clinical outcomes. Highl precision single-step procedures would also provide us with a powerful tool for rigorous and reliable studies of the impact of high quality preparations of specific subpopulations of cells in animal models of disease. We have recently developed molecular computing cascades based on oligonucleotides conjugated to targeting moieties (such as antibodies, their fragments, and aptamers). These are mixtures of targeting moieties that carry molecular computing elements and produce one outcome, a specific label on a single cell subpopulation, based on taking into account all targeting moieties. Thus, what would be, for example, a three-step separation protocol or a three-colored-fluorescence characterization in flow cytometry is condensed into a single step isolation procedure or a single color in flow cytometry. These computing mixtures of oligonucleotide conjugates with targeting moieties are thus uniquely suited for single-step `mix-and-separate' cell labelling protocols for magnetic separations. Our cascades can block isolation based on the presence of a cell surface marker or they can amplify signal coming from surface markers with low expression levels. In this project we will ask two principal questions: (1) What are the practical limitations, with metrics being yield, purity, and health of cells, of molecular computing cascades when applied to isolation of cell-subpopulations for clinical applications? And, (2) What are the minimal subpopulation of cells that we have to either preserve or eliminate to minimize induction of various forms of GVHD. In three Aims we will address translational and mechanistic questions regarding graft engineering and the induction of GVHD using increasingly complex protocols. We will characterize the impact of cell populations with different levels of markers for naïve, central memory, and Treg cells in a mouse model of GVHD, while at the same time assessing translational potential of increasingly complex molecular computing cascades, in comparison to standard methods.