Understanding the cellular and functional changes in the immune tumor microenvironment of glioblastoma during progression and treatments.

项目摘要 胶质母细胞瘤（GBM）是一种无法治愈的原发性恶性脑癌，其特征是高度的恶性胶质瘤。 患者间和肿瘤内基因组和细胞异质性，短暂的中位生存期（约15个月），和 缺乏有效的治疗。即使是检查点阻断免疫疗法的成功， 许多癌症没有转化为GBM。GBM肿瘤免疫微环境（TIME）是一种高度依赖性的免疫系统。 免疫抑制，主要由常驻和浸润性髓样细胞（占肿瘤质量的30-40%） 与罕见的T细胞相比（<5%）。尽管最近的单细胞RNA测序（scRNAseq）研究 提供了GBM肿瘤细胞的细胞组成和演变的广泛表征，解剖了 GBM的免疫组成的多样性、功能和区域定位仍然不完全。有 还普遍缺乏关于GBM进展期间肿瘤内免疫细胞进化的知识， 以及在整个标准护理（SOC）疗法（电离辐射/放射疗法）治疗期间， 替莫唑胺/地塞米松IR/TMZ/DEX）。实现科学和临床影响的主要挑战 GBM仍然存在，包括深入了解癌细胞和免疫系统之间的相互作用。 在SOC和免疫疗法治疗的背景下的微环境。这样的知识很难获得 使用新鲜切除的患者样本。该提案的主要假设是， 治疗方式引起的GBM肿瘤细胞和免疫细胞的变化可以通过使用 遗传上精确的小鼠模型来解析和重定向人类患者数据集的分析。一种机械的 了解临床前治疗对免疫和致瘤细胞群体动态的影响 小鼠模型与人类患者数据集的分析相结合将产生变革性的进步 在外地我们将利用存档的患者样本、GBM小鼠模型和GLASS联盟数据集 使用scRNA序列和空间分析技术揭示SOC相关的细胞和分子进化变化， 转录组学我们还将揭示决定对检查站封锁的敏感性和抵抗力的因素 疗法通过整合详细的小鼠和人类数据，我们将确定未被识别的治疗领域， 这将有助于消除脆弱性，并为开发新的治疗方法铺平道路。

Project Summary Glioblastoma (GBM) is an incurable primary malignant brain cancer characterized by a high degree of interpatient and intratumoral genomic and cellular heterogeneity, a brief median survival (~15 months), and absence of an effective treatment. Even the successes of checkpoint blockade immunotherapies observed in many cancers have not translated to GBM. The GBM tumor immune microenvironment (TIME) is highly immunosuppressive and is dominated by resident and infiltrating myeloid cells (30-40% of the tumor mass) compared to rare T cells (<5%). Although recent single-cell RNA-sequencing (scRNAseq) studies have provided broad characterization of the cellular makeup and evolution of GBM tumor cells, dissecting the diversity, function and regional localization of the immune composition of GBM remains incomplete. There is also a widespread lack of knowledge on the evolution of intratumoral immune cells during GBM progression, and throughout treatment with standard of care (SOC) therapies (ionizing radiation/ temozolomide/dexamethasone IR/TMZ/DEX). Major challenges to achieving scientific and clinical impact in GBM remain, including an in-depth understanding of the interactions between cancer cells and the immune microenvironment in the context of SOC and immunotherapy treatments. Such knowledge is difficult to obtain using freshly excised patient samples. The main hypothesis of the proposal is that critical and clinically relevant changes in GBM neoplastic and immune cells brought about by treatment modalities can be revealed using genetically accurate mouse models to parse and redirect analyses of human patient datasets. A mechanistic understanding of the effects of therapies on immune and tumorigenic cell population dynamics in pre-clinical mouse models in combination with analysis of human patient datasets will yield transformative advancements in the field. We will leverage archival patient samples, mouse models of GBM and GLASS consortium datasets to uncover SOC-related cellular and molecular evolutionary changes using scRNA seq and spatial transcriptomics. We will also unveil factors determining sensitivity and resistance to checkpoint blockade therapy. By integrating detailed mouse and human data, we will identify areas of unrecognized therapeutic vulnerabilities and pave the way for the development of new treatment approaches.