3-D spatial approach to discover genomic effectors of immunosuppression during malignant transformation

项目总结/摘要 IDH突变型低级别胶质瘤（LGG）向侵袭性高级别肿瘤的恶性转化（MT）是一种恶性肿瘤。 具有重大临床意义的事件，最终导致大多数LGG患者死亡。我们发现 IDH的突变促进了免疫抑制的微环境，其特征在于减少了 在LGG中STAT 1调节的趋化因子的产生和低CD 8 + T细胞浸润。在恶性转化 在肿瘤中，我们发现了IDH 1突变等位基因的意外缺失，这可能会导致抵消性变化 免疫抑制的微环境，特别是在MT。经历治疗诱导的LGG 超突变（HM），另一种MT途径，产生更高质量的新抗原。总体而言， 相对于患者匹配的LGG，我们发现T细胞克隆的数量增加， 增加参与细胞毒性T细胞吸引和效应子功能的基因的表达。基于这些 数据，我们假设IDH突变型LGG的免疫抑制在MT后减少，由遗传驱动， 主要在恶性转化期间获得的改变。为了解决这个问题，我们将 量化MT期间突变IDH 1驱动的免疫抑制的空间和时间变化（Aim 1）。我们有 设计了一种新的三维（3-D），肿瘤范围的方法，我们将获得10个空间映射 每个肿瘤的样本代表肿瘤的最大解剖结构。整个队列将包括30个恶性 转化和30例非恶性转化的复发性肿瘤，我们已经储存了这些患者的样本。 与之匹配的IDH 1突变型LGG基因我们将使用高灵敏度的T细胞库测定，通过流式细胞术， 飞行时间（CyTOF）、基于RNAseq的去卷积和多重免疫组织化学来绘制 免疫景观的三维，并确定在何种程度上突变IDH 1介导的免疫抑制 在MT期间减少。在目标2中，我们将确定MT过程中获得的遗传改变如何影响突变体， IDH 1介导的免疫抑制。我们将对收集的样本进行深度全外显子组测序， 目的1建立MT过程中肿瘤内基因组三维图谱。我们将测试MT的本地影响- 相关的遗传改变，包括高突变肿瘤中的高质量新抗原， 突变IDH 1等位基因或其他遗传事件对免疫抑制的影响。了解哪些遗传事件 有助于免疫抑制的变化对于选择可以协同的靶向治疗至关重要 用免疫疗法来预防或延缓MT为了开始开发基于T细胞的疗法，我们将捕获 新表位特异性T细胞，优先考虑那些存在于肿瘤范围内的T细胞，并确定新表位特异性T细胞的表达。 它们靶向的新表位/HLA和相应的T细胞受体（TCR）α-和β-的氨基酸序列。 β-链。然后，我们将测试克隆的TCR的相对靶特异性和针对新抗原的活性。 阳性患者特异性肿瘤细胞。肿瘤大范围内的三维免疫基因组景观 对于设计针对整个肿瘤的个性化治疗至关重要。

PROJECT SUMMARY/ABSTRACT Malignant transformation (MT) of IDH-mutant low grade glioma (LGG) to aggressive high grade tumors is an event of major clinical significance, eventually leading to death in the majority of LGG patients. We discovered that mutations in IDH promote an immunosuppressed microenvironment characterized by decreased production of STAT1-regulated chemokines and low CD8+ T cell infiltration in LGG. In malignantly transformed tumors, we identified the unexpected deletion of the IDH1 mutant allele that may drive counteracting changes to the immunosuppressed microenvironment specifically during MT. LGG that undergo treatment-induced hypermutation (HM), another route to MT, produce more high quality neoantigens. Overall in malignantly transformed tumors relative to patient-matched LGG, we found increasing numbers of T cell clones and increasing expression of genes involved in cytotoxic T cell attraction and effector function. Based on these data, we hypothesize that immunosuppression in IDH mutant LGG is reduced upon MT, driven by genetic alterations that are acquired primarily during malignant transformation. To address this hypothesis, we will quantify spatial and temporal changes in mutant IDH1-driven immunosuppression during MT (Aim 1). We have devised a novel 3-dimensional (3-D), tumor-wide approach in which we will acquire 10 spatially mapped samples per tumor representing maximal anatomy of the tumor. The full cohort will include 30 malignantly tranformed and 30 non-malignantly transformed recurrences from patients for which we have banked samples of the matching initial IDH1-mutant LGG. We will use a high-sensitivity T cell repertoire assay, cytometry by Time of Flight (CyTOF), RNAseq based deconvolution, and multiplex immunohistochemistry to map the immunologic landscape in 3-D, and determine the extent to which mutant IDH1-mediated immunosuppression is reduced during MT. In Aim 2, we will determine how genetic alterations acquired during MT affect mutant IDH1-mediated immunosuppression. We will perform deep whole exome sequencing on samples collected in Aim 1 to map the intratumoral genomic landscape in 3-D during MT. We will test for the local influence of MT- associated genetic alterations, including high quality neoantigens in hypermutated tumors, deletion of the mutant IDH1 allele, or other genetic events on immunosuppression. Understanding which genetic events contribute to changes in immunosuppression is critical for selecting targeted therapies that could synergize with immunotherapies to prevent or delay MT. To begin to develop T cell based therapies, we will capture neoepitope-specific T cells, prioritizing those that are present tumor-wide, and determine the neoepitopes/HLAs they target and the amino acid sequences for corresponding T Cell Receptor (TCR) α- and β-chains. We will then test the cloned TCR for relative target specificity and activity against neoantigen- positive patient-specific tumor cells. The 3-D immuno-genomic landscapes across wide swaths of the tumor will be essential to the design of personalized therapies that have activity against the whole tumor.