Quantitative systems biology of glioblastoma cells and their interactions with the neuronal and immunological milieu

摘要--总体 MIT/DFCI胶质母细胞瘤系统生物学中心的主要关注点是了解 神经元、免疫细胞和肿瘤细胞在这一致命肿瘤中的交叉点。对……缺乏回应 免疫治疗策略尽管在许多GBM中有显著的免疫细胞渗透，但突出了免疫- GBM微环境的抑制性以及更清楚地了解 肿瘤/免疫界面的动态相互作用。同样，肿瘤细胞和神经之间的相互作用 肿瘤微环境中的细胞已经成为肿瘤进展和侵袭的驱动力， 来自神经元的电信号为肿瘤细胞提供生长和迁移刺激，而肿瘤细胞导致 局部神经元中的异常电信号。这一提议的中心假设是，开发一种 从系统水平理解肿瘤细胞、神经元和免疫细胞之间的动态相互作用 提供对胶质瘤肿瘤生物学的前所未有的见解并促进新疗法的开发 消除肿瘤侵袭、提高细胞毒治疗疗效和增加肿瘤清除的策略 肿瘤由先天和获得性免疫系统造成的负担。计划中的分析将使建立一个 基底膜肿瘤肿瘤-神经-免疫相互作用的综合计算模型。该模型将基于 在体外、体内和体外模型系统的基础上，然后在数十名人类患者中进行验证。 每个患者体内不同肿瘤区域的影像登记活检将被分析以检验预测。 这一模型与人类肿瘤的“基本事实”相抵触。MIT/DFCI中心的最终目标是 胶质母细胞瘤的系统生物学是利用系统生物学和计算机技术改善患者的护理 识别特定干扰关键肿瘤细胞微环境的治疗策略的建模 互动。

ABSTRACT – OVERALL The primary focus of the MIT/DFCI Center for Systems Biology of Glioblastoma is to understand the intersections between neurons, immune cells, and tumor cells in this deadly tumor. The lack of response to immunotherapy strategies despite prominent infiltrates of immune cells in many GBM highlights the immuno- suppressive nature of the GBM microenvironment and the importance of more clearly understanding the dynamic interactions at the tumor/immune interface. Similarly, interactions between tumor cells and neural cells in the tumor microenvironment have emerged as driving forces in tumor progression and invasion, with electrical signals from neurons providing growth and migration stimuli to tumor cells, while tumor cells lead to aberrant electrical signaling in local neurons. The central hypothesis of this proposal is that developing a systems-level understanding of the dynamic interactions between tumor cells, neurons and immune cells will provide unprecedented insights into glioma tumor biology and foster development of novel therapeutic strategies to abrogate tumor invasion, enhance the efficacy of cytotoxic therapies, and increase clearance of tumor burden by the innate and adaptive immune system. The planned analyses will enable building an integrated computational model of tumor-neural-immune interactions for GBM tumors. The model will be based on a foundation of in vitro, in vivo, and ex vivo model systems, and then validated in dozens of human patients. Image-registered biopsies from different tumor regions within each patient will be analyzed to test predictions of this model against the ‘ground truth’ of human tumors. The ultimate goal of the MIT/DFCI Center for Systems Biology of Glioblastoma is to improve patient care by using systems biology and computational modeling to identify therapeutic strategies to specifically disrupt critical tumor cell – microenvironment interactions.