Project 2 - Modulation of Anti-Tumor Immunity by Inhibitory Receptors

项目总结 细胞表面抑制受体(IRS)PD1和LAG3控制细胞信号和关键细胞内源性效应因子 T细胞的功能和分化。然而，这些IR也表达在耗尽的肿瘤内T细胞上，限制了 疾病清除。IRS是维持免疫控制的关键，但也是有效的主要障碍 抗肿瘤免疫。PD1和LAG3在多种疾病中具有协同作用，包括癌症，以及许多CD8+和 CD4+肿瘤浸润性淋巴细胞(TIL)表达PD1/LAG3。事实上，我们证明了肿瘤免疫疗法 靶向PD1/LAG3可以诱导小鼠肿瘤几乎完全缓解，现在的临床证据支持 单(抗PD1)或双(抗PD1/LAG3)IR阻断的益处。这个项目将检验中心假说 PD1和LAG3协同加强肿瘤诱导的耐受性，使用重叠和组合 在CD4+和CD8+效应T细胞中独特的细胞内在和外在功能“。由于宽容的力量在 肿瘤微环境(TME)，小鼠模型是研究IR机制的优秀系统 与自身免疫(项目1)和慢性病毒环境(项目3)中的过程进行比较。我们将追求三个目标： 目的1：PD1和LAG3在限制初始CD8+T细胞中的相对和协同作用是什么 细胞抗肿瘤效应反应？我们假设PD1和LAG3通过限制种群动态、分化、代谢，而不是启动而是暂时地加强向CD8+T细胞耗竭的进程 健康和多功能“。我们将使用Quad AT系统，共同转移肿瘤特异性CD8+T细胞， 是野生型或缺乏PD1和/或LAG3，以便在同一微环境中进行功能和转录分析。 目的2：PD1和LAG3在限制初始CD4+T细胞转化中的相对和协同作用是什么 抗肿瘤效应反应？我们推测PD1/LAG3对CD4+Tconv细胞具有协同作用 通过对CD8+T细胞功能和容量的不同调节来帮助“。我们将审问他的角色 使用我们的新的CreERT2株来删除CD4+T细胞中的等位基因，而不是CD8+T细胞中的等位基因 特雷格斯。 目的3：PD1/LAG3对抗肿瘤T细胞记忆和维持的持久性有何影响 全身免疫力的问题？我们假设“PD1和/或LAG3通过以下方式限制抗肿瘤免疫的持久性 影响Tex重振和Tconv细胞记忆的发育和维持，使其回忆反应迟钝 以及限制系统免疫力。我们将问两个问题：(A)PD1/LAG3的损失对TeX和 他们的复兴？(B)PD1/LAG3对维持T细胞抗肿瘤记忆和回忆有何影响 有什么反应？ PPG互动：项目2将与项目1合作，比较PD1/LAG3丢失对CD4+的影响 自身免疫与肿瘤环境中的T细胞功能；与项目3比较CD8+T细胞耗竭 通过肿瘤或慢性病毒感染；与核心A交换数据，核心B获得小鼠，核心C获得 转录分析和CRISPR/sgRNA序列，核心D用于免疫组织学分析。

PROJECT SUMMARY Cell surface inhibitory receptors (IRs) PD1 and LAG3 control cellular signaling and critical cell intrinsic effector T cell function and differentiation. Yet, these IRs are also expressed on exhausted intratumoral T cells, limiting disease clearance. IRs are critical to maintain immune control, but also represent a major barrier to effective anti-tumor immunity. PD1 and LAG3 are synergistic in multiple diseases, including cancers, and many CD8+ and CD4+ tumor-infiltrating lymphocytes (TILs) express PD1/LAG3. Indeed, we showed that tumor immunotherapy targeting PD1/LAG3 can induce almost complete remission of tumors in mice, and clinical evidence now supports the benefit of single (anti-PD1) or dual (anti-PD1/LAG3) IR blockade. This project will test the central hypothesis that “PD1 and LAG3 synergize to enforce tumor-induced tolerance using a combination of overlapping and unique cell intrinsic and extrinsic functions in CD4+ and CD8+ effector T cells”. Due to potency of tolerance in the tumor microenvironment (TME), mouse models represent an outstanding system to study IR mechanisms to compare with processes in autoimmune (Project 1) and chronic viral settings (Project 3). We will pursue 3 Aims: AIM 1: What are the relative and synergistic contributions of PD1 and LAG3 in limiting the initial CD8+ T cell anti-tumor effector response? We hypothesize that “PD1 and LAG3 do not initiate but temporally reenforce progression toward CD8+ T cell exhaustion by limiting population dynamics, differentiation, metabolic health, and polyfunctionality”. We will use a Quad AT system that co-transfers tumor-specific CD8+ T cells that are wild-type or lack PD1 and/or LAG3 for functional and transcriptional analysis in the same microenvironment. AIM 2: What are the relative and synergistic contributions of PD1 and LAG3 in limiting initial CD4+ Tconv anti-tumor effector response? We hypothesize that “PD1/LAG3 have synergistic effects on CD4+ Tconv cells by differentially modulating their function and capacity for CD8+ T cell help”. We will interrogate the role of PD1/LAG3 on CD4+ T cells using our novel CreERT2 line to delete alleles in CD4+ Tconv but not CD8+ T cells or Tregs. AIM 3: What is the impact of PD1/LAG3 on the durability of anti-tumor T cell memory and maintenance of systemic immunity? We hypothesize that “PD1 and/or LAG3 limit durability of anti-tumor immunity by impacting Tex reinvigoration and Tconv cell memory development and maintenance, blunting their recall response and limiting systemic immunity”. We will ask 2 questions: (A) What is the impact of PD1/LAG3 loss on Tex and their reinvigoration? (B) What is the impact of PD1/LAG3 on maintenance of T cell anti-tumor memory and recall response? PPG Interactions: Project 2 will collaborate with Project 1 to compare the impact of PD1/LAG3 loss on CD4+ T cell function in autoimmune versus tumoral settings; with Project 3 to compare CD8+ T cell exhaustion induced by tumors or chronic viral infections; and with Core A to exchange data, Core B to obtain mice, Core C for transcriptional analysis and CRISPR/sgRNA sequences, and Core D for immunohistological analysis.