Diversity Supplement Ifediora: Image-based models of tumor-immune dynamics in glioblastoma

摘要 多形性胶质母细胞瘤（GBM）是所有胶质瘤中最常见的，中位生存期为14-18 几个月，尽管积极的治疗方案。然而，神经胶质瘤是一种 不仅仅是癌细胞事实上，许多研究表明，胶质瘤可以 以促进肿瘤存活和繁殖的方式改变大脑微环境。内 这个脑肿瘤微环境是多种细胞类型。利益集团之一 是胶质瘤相关的小胶质细胞和巨噬细胞（GAMM），其是神经胶质瘤的重要组成部分。 大脑中的免疫细胞因此，免疫疗法正在成为一种有前途的方法， 治疗癌症;然而，我们无法确定早期反应或预测谁会有反应。 虽然活组织检查是最可靠的方法来评估免疫景观内 肿瘤，我们在空间和时间上都受到我们可以获得的活检数量的限制， 特别是对于脑肿瘤患者。肿瘤免疫景观的异质性 患者建议，将需要一种针对患者的方法来准确评估每种 患者的个体肿瘤免疫环境及其演变。作为家长的一部分 格兰特，我们将使用非侵入性成像，图像引导活检，计算建模， 人工智能桥接空间和时间尺度并预测神经胶质瘤的丰度 相关的小胶质细胞/巨噬细胞（GAMM），包括每个磁共振图像 (MRI)在voxel级别。使用放射组学将MRI与生物异质性联系起来 方法提供了一个机会，使我们对肿瘤免疫的理解个体化， 环境同样在最近几年，研究已经调查了药物治疗如何能够 激活GAMM以呈现免疫反应性表型。对于这一拟议的补充，我们将 表征响应于诱导的免疫原性细胞死亡的髓样胶质瘤细胞相互作用 化疗药物托泊替康引起的这将通过MRI定位活检以及 体外共培养系统，提供了额外的治疗相关背景， 研究细胞反应和信号传导。这项研究将利用单细胞RNA测序， 识别免疫细胞的激活状态，并将为我们提供小胶质细胞的另一个方面， 和巨噬细胞生物学，可以纳入在父母补助金产生的模型。

Abstract Glioblastoma Multiforme (GBM) is the most common of all gliomas with a median survival 14-18 months, despite aggressive treatment regimens. However, glioma is a disease that encompasses more than just cancer cells. In fact, many studies have shown that glioma can alter the brain microenvironment in ways that promote tumor survival and propagation. Within this brain tumor microenvironment is a diversity of cell types. One of particular group of interest is glioma associated microglia and macrophages (GAMMs), an important component of the immune cells in the brain. As a result, immunotherapy is emerging as a promising method to treat cancer; however, we are not able to identify early response or predict who will respond. While biopsies are the most reliable way to assess the immunological landscape within the tumor, we are limited both spatially and temporally in the number of biopsies we can obtain, particularly for brain tumor patients. The heterogeneity of the tumor-immune landscape across patients suggests that a patient-specific approach will be required to accurately assess each patient’s individual tumor-immune environment and the evolution thereof. As part of the Parent Grant, we will use non-invasive imaging, image-guided biopsies, computational modeling, and artificial intelligence to bridge spatial and temporal scales and predict the abundance of glioma associated microglia/macrophages (GAMMs) comprising each magnetic resonance image (MRI) at the voxel level. Linking the MRI to the biological heterogeneity using radiomics approaches provides an opportunity to individualize our understanding of the tumor-immune environment. Also in recent years, research has looked into how drug treatment is able to activate GAMMs to take on immunoreactive phenotypes. For this proposed supplement we will characterize myeloid – glioma cell interactions in response to immunogenic cell death induced by the chemotherapy drug topotecan. This will be done using MRI localized biopsies as well as in vitro co-culture systems, providing an additional therapeutically relevant context in which to study cellular response and signaling. The study will make use of single cell RNA sequencing to identify activational states of immune cells, and will provide us with another aspect of microglia and macrophage biology that can be incorporated into the model generated in the Parent Grant.