EAGER: Biomanufacturing: Engineering genetic classifiers to increase the homogeneity of CAR T cells with central memory phenotype

1645169-Won利用癌症患者自身的T细胞进行基因工程来对抗癌症，已经成为一种很有前途的癌症治疗策略，特别是针对血液肿瘤。虽然前景看好，但还需要改进，以使这些工程T细胞能够有效地治疗其他癌症。T细胞的某些亚群在治疗肿瘤方面比其他亚群更好。分离纯抗癌T细胞亚群的强大制造工艺最终将导致更有效和更统一的临床产品。然而，提纯T细胞亚群的标准方法需要高度复杂的机器，很难扩大规模，而且成本高昂。因此，一种不需要这些机器生产纯化T细胞亚群的制造工艺将大大提高肿瘤靶向T细胞生产的效率和降低成本。该项目的目标是开发新的遗传分类器，选择所需的T细胞亚群，而不需要机器辅助的纯化步骤。研究人员将构建一系列日益复杂的遗传分类器，以选择强大的抗癌T细胞亚群，并开发包含肿瘤靶向受体和遗传分类器的基因传递平台。教育活动将包括培训和接待一支参加国际基因工程机器竞赛的学生团队，开发一个关于T细胞工程和制造的项目，并为本科生和研究生开发关于T细胞生物制造的课程材料。表达肿瘤靶向嵌合抗原受体(CAR)的基因工程T细胞已显示出惊人的抗肿瘤功效，可对抗B细胞恶性肿瘤。需要进一步的改进才能使CAR T细胞有效地治疗其他癌症。具有中央记忆表型的CAR T细胞是最有效的肿瘤根除T细胞亚群之一。一个强大的制造过程来产生同质的中央记忆CAR T细胞，最终将导致更有效和更统一的临床产品。然而，纯化T细胞亚群的标准方法需要临床细胞分选机和磁分离器在GMP条件下操作，这很难放大，而且成本高昂。因此，一种不需要机器辅助细胞分离就能生产出纯化的T细胞亚群的制造工艺将大大提高CAR T细胞的生产效率并降低成本。为了在不进行细胞分离的情况下丰富T细胞亚群，将开发一种新的基于microRNA(MiRNA)的遗传分类器来选择中央记忆T细胞(Medics)。分类器将根据中药miRNA签名来表达抗生素耐药基因。添加抗生素将消除除目标T细胞外的所有细胞。这些分类器将与CARS一起被引入同一基因载体中的T细胞。基于miRNA的分类器非常适合这一应用，因为miRNA结合位点很小，这使得紧凑的电路设计有助于高效的基因传递。此外，已经为许多不同的人类T细胞亚群分析了miRNA签名，从而大大简化了电路设计工作。该项目将建立一系列用于选择中央记忆CAR T细胞的miRNA分类器，并将开发一个慢病毒平台，其中包含一个结构性CAR表达盒和一个控制抗生素耐药性基因表达的miRNA分类器。

1645169 - WongThe genetic engineering of cancer patients' own T cells to fight cancers has become a promising cancer treatment strategy, especially against blood tumors. While promising, improvement is needed to enable these engineered T cells to effectively treat other cancers. Some subsets of T cells are better than others at treating tumors. A robust manufacturing process to isolate pure anti-cancer T cell subsets will ultimately lead to a more effective and uniform clinical product. However, the standard approach for purifying T cell subsets, which requires highly complex machines, is difficult and expensive to scale up. Therefore, a manufacturing process that does not require these machines to yield purified T cell subsets would greatly improve the efficiency and reduce the cost of tumor-targeting T cell production. The goal of this project is to develop novel genetic classifiers that select desired T cell subsets that will not require machine-assisted purification steps. The researchers will build a series of increasingly sophisticated genetic classifiers for selecting potent anti-cancer T cell subsets and develop a gene delivery platform that contains a tumor targeting receptor and genetic classifier. Educational activities will include training and hosting a team of students to compete in the International Genetically Engineered Machines competition, developing a project on T cell engineering and manufacturing, and developing course materials on T cell biomanufacturing for undergraduate and postgraduate students.Genetically engineered T cells expressing tumor-targeting chimeric antigen receptors (CAR) have demonstrated surprising anti-tumor efficacy against B cell malignancies. Further improvement is needed to enable CAR T cells to effectively treat other cancers. CAR T cells with the central memory phenotype are one of the most potent tumor-eradicating T cell subsets. A robust manufacturing process to generate homogeneous central memory CAR T cells will ultimately lead to a more effective and uniform clinical product. However, the standard approach for purifying T cell subsets require clinical cell sorters and magnetic separators operating under GMP conditions, which is difficult and expensive to scale up. Therefore, a manufacturing process that can yield purified T cell subsets without machine-assisted cell separation will greatly improve the efficiency and reduce the cost of the CAR T cells production. To enrich T cell subsets without cell sorting, a novel microRNA (miRNA)-based genetic classifiers will be developed to select for central memory T cells (TCM). The classifiers will express antibiotic resistance gene dependent on the TCM miRNA signature. The addition of antibiotics will eliminate all cells except for the T cells of interest. These classifiers will be introduced into the T cells along with CARs in the same gene delivery vehicle. A miRNA-based classifier is ideally suited for this application because miRNA binding sites are small, which allows compact circuit design that facilitates efficient gene delivery. In addition, miRNA signatures have been profiled for many different human T cell subsets, thus greatly simplifying the circuit design efforts. The project will build a series of miRNA classifiers for selecting central memory CAR T cells, and will develop a lentivirus platform that contains a constitutive CAR expression cassette and a miRNA classifier controlling the expression of an antibiotic resistance gene.