Towards a spatial view of Ras signaling and immune cell function in NF-1 mutant glioblastoma

项目总结/摘要 胶质母细胞瘤（GBM）是成人中最致命的恶性脑肿瘤， 自2005年以来没有变化，中位总生存期仅为14.6个月。尽管几 基于突变景观和基因表达的GBM亚组已经被鉴定，它们没有 治疗意义在GBM的这些亚组中，具有神经纤维蛋白1（NF 1）突变的肿瘤和 与NF 1野生型（WT）GBM相比，缺失具有最差的总体存活率。NF 1基因突变 在几种情况下显示出显著的生物学效应，例如， 与免疫抑制肿瘤微环境（TME）相关。因此，我建议识别NF 1- GBM的相关特征可能是该亚组有效治疗靶向的关键。尽管 在肿瘤学领域迫切需要治疗靶点的发现，一般来说， 方法，大多数研究只使用单一的组学技术，未能同时研究这两种方法。 癌细胞的基因组学和TME的功能状态，相互影响的特征。 鉴于这些缺点，我将测试细胞中存在NF 1特异性拓扑模式的假设， 表型和RAS通路活性的研究。这有可能识别新的 该GBM亚群的治疗靶点，同时为通用治疗靶点发现提供框架 使用集成多重免疫荧光（mpIF），一种用于原位单细胞分析的方法， 转录组学（ST）。我策划了一个84例GBM患者（42例NF 1改变和42例NF 1 WT）的队列， 基于靶向小组的基因组测序，我将在相邻的福尔马林固定石蜡上进行mpIF和ST， 这些病人的肿瘤。在目标1中，我将优化细胞表型的计算模型 分配mpIF数据，并使用mpIF和ST的空间共聚类来加强推断。然后我将 将此模型应用于我的GBM队列中收集的mpIF和ST数据，以定义TME的空间拓扑 相对于NF 1的改变。在目标2中，我将定义RAS通路活性的空间拓扑结构，这还没有被证实。 在GBM和NF 1的背景下，在单细胞水平上进行探索。然后，我将RAS通路活性与 使用空间聚类将癌细胞与TME的功能状态相关联。我的总体目标是整合mpIF和 ST数据，并制定标准化的统计工作流程，用于分析这些数据，以确定新的治疗方法 NF 1改变GBM的靶点，也为未来的癌症靶点发现研究提供了蓝图。

PROJECT SUMMARY/ABSTRACT The standard of care for glioblastoma (GBM), the most lethal malignant brain tumor in adults, has remained unchanged since 2005 and only achieves a median overall survival of 14.6 months. Although several subgroups of GBM based on mutational landscape and gene expression have been identified, they have no therapeutic implications. Among these subgroups of GBM, tumors with neurofibromin 1 (NF1) mutations and deletions have the worst overall survival compared to NF1 wild-type (WT) GBM. NF1 alterations have been shown to have significant biological effects in several contexts, NF1 loss in GBM has, for example, been associated with an immunosuppressive tumor microenvironment (TME). Thus, I propose that identifying NF1- associated features of GBM may hold the key for effective therapeutic targeting of this subgroup. Despite the urgent need for therapeutic target discovery in the field of oncology, in general, there are no standardized approaches, and most studies only use a single omics technology, failing to simultaneously study both the genomics of cancer cells and the functional status of the TME, features that influence one another. Given these shortcomings, I will test the hypothesis that there are NF1-specific topological patterns in cell phenotypes and RAS pathway activity in NF1 altered GBM tumors. This has the potential to identify novel therapeutic targets for this GBM subset while providing a framework for universal therapeutic target discovery using integrated multiplexed immunofluorescence (mpIF), a method for in situ single-cell profiling, and spatial transcriptomics (ST). I have curated a cohort of 84 GBM patients (42 NF1 altered and 42 NF1 WT) with targeted panel-based genome sequencing, and I will perform mpIF and ST on adjacent formalin-fixed paraffin- embedded tumors from these patients. In Aim 1, I will optimize a computational model for cell phenotype assignment in mpIF data and use spatial co-clustering of mpIF and ST to strengthen inferences. I will then apply this model to mpIF and ST data collected on my GBM cohort to define the spatial topology of the TME relative to NF1 alteration. In Aim 2, I will define the spatial topology of RAS pathway activity, which has yet to be explored at the single-cell level in GBM and in the context of NF1. I will then relate RAS pathway activity in cancer cells to the functional state of the TME using spatial clustering. My overall goal is to integrate mpIF and ST data and develop a standardized statistical workflow for analysis of these data to identify novel therapeutic targets for NF1 altered GBM and also present a blueprint for future cancer target discovery research.