Nano and biomolecular engineered technologies for neoantigen-specific T cell capture and characterization

项目摘要 许多癌症免疫疗法集中于工程化或活化肿瘤抗原特异性CD 8 + T细胞， 其次是CD 4 + T细胞。特别是，新抗原特异性T细胞是有吸引力的，因为它们可以杀死 高特异性的癌细胞。1一般方法从识别识别新抗原的T细胞开始 在肿瘤内广泛表达，分离T细胞并确定它们的T细胞受体（TCR）序列。 然后，这些TCR可以被转染到患者T细胞中，可能还需要额外的基因工程2来促进T细胞的增殖。 更持久的抗肿瘤作用，并扩展为输液产品用于患者治疗。3事实上， 这种方法最近进入了临床，其中一项试验（NCT 03970382）来自NCI的发明， 由本提案的PI领导的CCNE U 54资助。4，5然而，仍然有一些基本的和 与推进新抗原特异性TCR工程化疗法相关的技术挑战。一是 新抗原特异性TCR的发现依赖于算法的指导，如NET MHCpan 4.1，以预测 抗原/MHC呈递（基于结合和其他考虑），以及许多由 截断突变，如突变型KRAS或突变型TP 53，被预测为不太可能，但已被报道为 临床有效靶点6，7，8第二，新抗原特异性CD 4 + T细胞及其II类限制性新抗原， 虽然被认为对免疫疗法诱导的抗肿瘤反应很重要，但9，10仍然是一个很大程度上未开发的领域。 治疗资源，II类抗原/MHC结合的预测算法11、12开发较少。第三 挑战在于分析患者血液中的新抗原特异性T细胞通常需要20 M以上 外周血单核细胞（PBMC），因此不是特别有效。在这里，我们提出了三个具体目标 旨在解决这些悬而未决的问题。技术解决方案的核心是以下方面的组合： 工程化纳米颗粒（NP）和生物分子工程化构建体，其设计用于高效和选择性地 干细胞新抗原特异性CD 4+和CD 8 + T细胞群体的捕获、分析和验证。显著 为所有3个目标提供了初步数据，其中一些目标使用了我们工作产生的COVID-19患者数据 在目前的流行病。13，14这项工作的结果将是一个功能强大的工具集，专为最小偏差的 搜索针对躯干新抗原的CD 4+和CD 8 + T细胞群（独立于患者HLA 单倍型），设计用于快速验证和表征那些新抗原特异性T细胞的工具集， 克隆型，以及I类和II类干细胞新抗原和T细胞受体基因特异性的公共数据库 对那些新抗原的反应

Project summary Much of cancer immunotherapy is focused on engineering or activating tumor-antigen specific CD8+ T cells and, to a lesser extent, CD4+ T cells. In particular, neoantigen-specific T cells are attractive because they can kill cancer cells with high specificity. 1 A general approach starts with identifying T cells that recognize neoantigens broadly expressed within the tumor, isolating the T cells and determining their T cell receptor (TCR) sequences. These TCRs can then be transfected into patient T cells, perhaps with additional genetic engineering2 to promote more durable anti-tumor effects, and expanded into an infusion product for patient treatment. 3 In fact, this approach has recently entered the clinic, with one trial (NCT03970382) drawing from inventions from an NCI- funded CCNE U54 grant led by the PI of this proposal. 4,5 However, there are still a number of fundamental and technological challenges associated with advancing neoantigen-specific TCR-engineered therapies. First, the discovery of neoantigen-specific TCRs relies on guidance from algorithms, such as NET MHCpan 4.1, to predict antigen/MHC presentation (based upon binding and other considerations), and many neoantigens arising from truncal mutations, such as mutant KRAS or mutant TP53, are predicted as unlikely, yet have been reported as clinically effective targets. 6,7,8 Second, neoantigen-specific CD4+ T cells and their class II restricted neoantigens, while identified as important for immunotherapy-induced anti-tumor responses, 9,10 remain a largely untapped therapeutic resource, with prediction algorithms 11,12 for Class II antigen/MHC binding less developed. A third challenge is that analysis of a patient blood for neoantigen-specific T cells typically requires upwards of 20M peripheral blood mononuclear cells (PBMCs), and so isn't particularly efficient. Here we propose 3 specific Aims designed to address these outstanding issues. At the heart of the technology solutions are combinations of engineered nanoparticles (NPs) and biomolecular engineered constructs designed for efficient and selective capture, analysis, and validation of truncal neoantigen-specific CD4+ and CD8+ T cell populations. Significant preliminary data is presented for all 3 Aims, some of which uses COVID-19 patient data generated by our work during the current pandemic. 13,14 The result of this work will be a powerful toolset designed for a minimally-biased search for CD4+ and CD8+ T cell populations against truncal neoantigens (independent of patient HLA haplotype), a toolset designed for the rapid validation and characterization of those neoantigen-specific T cell clonotypes, and a public data base of Class I and Class II truncal neoantigens and T cell receptor genes specific to those neoantigens.