T cell mechanisms of immunotherapy response in pancreatic ductal adenocarcinoma

项目摘要 免疫检查点抑制剂（ICI）在约20%的癌症患者中提供了持久的临床反应， 对于缺乏肿瘤内T细胞的非免疫原性癌症，这种方法在很大程度上无效。大多数肿瘤都有体细胞- 编码肿瘤特异性的突变蛋白质而不在正常细胞上表达的突变蛋白质（称为新抗- gens）。具有最高突变负荷的癌症，如黑色素瘤，更可能对单一药物产生反应 ICIs。然而，大多数癌症，包括胰腺导管腺癌（PDAC），具有较低的突变负荷， 导致更少的T细胞渗透肿瘤。先前的研究表明，同种异体GM-CSF- 的疫苗增强了T细胞向人胰腺癌中的渗透。最近的Panc 02细胞研究， 表达约60种与人PDAC相似的新抗原，表明PancVAX，一种新抗原靶向疫苗， 当与免疫调节剂配对时，清除了携带Panc 02的小鼠中的肿瘤。这些数据表明，癌症 靶向肿瘤新抗原的疫苗诱导新表位特异性T细胞，其可被ICI进一步激活， 导致肿瘤排斥。目前，这种治疗对T细胞表达状态的影响和潜在的- 治疗反应的机制仍不明确。反应T的综合表征 细胞将是理解反应机制和提供组合疗法的基本原理的关键。在 在这项提议中，我们将检验这样一种假设，即当与新抗原靶向疫苗一起使用时， 具有不同的协同作用模式，不同的治疗组合导致不同的 与免疫治疗反应相关的T细胞库的变化。为了解决这个问题，我提出两个建议。 具体目标。目的1：研究免疫治疗过程中T细胞转录水平的变化。我会 首先研究PancVAX在添加和不添加ICI的情况下对单细胞水平基因表达的影响 在Panc 02小鼠模型中。然后，我将确定驱动抗肿瘤反应差异的生物过程， 治疗臂之间。我将使用流式细胞术实验性地验证这些差异。目标2：发展 描绘T细胞克隆进化的轨迹构建方法。我们将把这种方法应用于T细胞受体 对用疫苗和ICI治疗的PDAC的人类临床试验的数据进行测序，以确定 与肿瘤消退或抵抗相关的T细胞库。这些目标的成功实现将为我们提供 未来PDAC患者的联合免疫治疗方法，并提供新的开源计算 软件来表征T细胞群，可以应用于不同的癌症类型。我将获得的技能 当我完成这项研究时，将为我作为一名跨学科科学家的职业生涯做好准备， 免疫景观为精准免疫疗法提供信息。

Project Summary Immune checkpoint inhibitors (ICIs) provide durable clinical responses in about 20% of cancer patients, but have been largely ineffective for non-immunogenic cancers that lack intratumoral T cells. Most tumors have somatic mu- tations that encode for mutant proteins that are tumor-specific and not expressed on normal cells (termed neoanti- gens). Cancers, such as melanoma, with the highest mutational burdens are more likely to respond to single agent ICIs. However, most cancers, including pancreatic ductal adenocarcinoma (PDAC), have lower mutational loads, resulting in fewer T cells infiltrating the tumor. Studies have previously demonstrated that an allogeneic GM-CSF- based vaccine enhances T cell infiltration into human pancreatic cancer. Recent work with Panc02 cells, which express around 60 neoantigens similar to human PDAC, showed that PancVAX, a neoantigen-targeted vaccine, when paired with immune modulators cleared tumors in Panc02-bearing mice. This data suggests that cancer vaccines targeting tumor neoantigens induce neoepitope-specific T cells, which can be further activated by ICIs, leading to tumor rejection. Currently the impact of such treatment on T cell expression states and the underly- ing mechanism of therapeutic response remains poorly defined. Comprehensive characterization of responding T cells will be critical in understanding mechanisms of response and providing rationale for combinatorial therapy. In this proposal we will test the hypothesis that when used alongside neoantigen-targeted vaccines, individual ICIs have distinct as well as synergistic modes of action and that different treatment combinations result in distinct changes in the T cell repertoire related to immunotherapy response. To address this hypothesis, I propose two specific aims. Aim 1: To characterize the transcriptional changes in T cells during immunotherapy treatment. I will first investigate the effect of PancVAX, with and without addition of ICIs, on gene expression at a single-cell level in the Panc02 mouse model. Then I will determine biological processes driving differences in anti-tumor response between treatment arms. I will experimenally validate these differences using flow cytometry. Aim 2: To develop trajectory building methods depicting the clonal evolution of T cells. We will apply this method to T cell receptor sequencing data from human clinical trials of PDAC treated with vaccine and ICI to identify key changes within the T cell repertoire associated with tumor regression or resistance. Successful completion of these aims will inform future combination immunotherapy approaches in PDAC patients and provide new open-source computational software to characterize T cell populations that can be applied to diverse cancer types. The skills I will acquire as I complete this research will prepare me for a career as an interdisciplinary scientist, characterizing the tumor immune landscape to inform precision immunotherapy.