Understanding brain extracellular matrix in the tumor microenvironment

癫痫是脑肿瘤常见的严重神经系统症状，高达80%的患者在癫痫发作时 至少有一次癫痫发作。复发性癫痫，称为脑瘤相关性癫痫(BTRE)，发生在一半的脑肿瘤中 患者，往往难以进行医疗管理。控制不良的癫痫是导致 脑肿瘤患者的长期残疾，并因药物毒性而使疗程复杂化，丧失 驾驶特权，生活质量下降。此外，一个新兴的研究神经细胞的工作机构 对胶质瘤生长的调控表明，癫痫样活动促进了肿瘤的增殖和侵袭。 成功的阻止患者癫痫发作的干预措施将大大降低神经系统的发病率，并可能停止 肿瘤进展。然而，目前治疗BTRE的一线药物左旋西坦是一种突触释放 抑制剂，在一半的患者中未能抑制癫痫发作。我们治疗BTRE方法的根本转变 是非常需要的。 最近对肿瘤相关性癫痫发病机制的研究发现了大脑的新作用 肿瘤微环境(TME)，包括肿瘤-间质和肿瘤-神经元的相互作用，导致双向， 重塑TME分子结构的协同努力，导致神经元功能障碍 以及失去抑制、反复发作和肿瘤进展的前馈循环。尤其是， 神经周围神经网络(PNN)已被证明被胶质瘤降解，导致抑制的失调。 相邻皮质中的中间神经元。TME是一种新的、潜在的治疗BTRE的靶点； 然而，肿瘤微环境与临床癫痫发作之间的分子和细胞机制 患者的定义仍然不明确。 为了更好地了解脑瘤患者的癫痫发作，这个项目将进行数字空间 谱分析(DSP)，一个多路、空间链接的RNA转录本和蛋白质表达的自动化系统 脑肿瘤标本定量和Viitom10x单核RNA测序评价PNN TME中的结构和组成。然后，该项目将应用机器学习方法来分析这些 高维数据，以确定与癫痫临床病史有关的PNN特征。这一目标将 验证患者肿瘤相关的PNN降解与严重的神经病学相关的假设 症状。它还将导致用于评估的新的组织学和计算技术的重大发展 可广泛应用于其他类似复杂的生物医学数据集的PNN结构和功能。 完成这些目标将有助于项目负责人和研究团队更好地了解Brain 病理影响患者的PNNS，为人类研究产生新的生物资源和技术 PNN，并提供证据支持保存或恢复PNN作为一种新的、更有效的战略 BTRE的治疗。

Seizures are a common, severe neurologic symptom of brain tumors with up to 80% of patients experiencing at least one seizure. Recurrent seizures, termed brain-tumor-related epilepsy (BTRE), develop in half of brain tumor patients and are often refractory to medical management. Poorly controlled epilepsy is the leading risk-factor for long-term disability in brain tumor patients and complicates the course of treatment due to drug toxicities, loss of driving privileges, and decreased quality of life. Further, an emerging body of work investigating neuronal regulation of glioma growth suggests that epileptiform activity promotes tumor proliferation and invasion. Successful intervention to stop seizures in patients would profoundly reduce neurologic morbidity and may halt tumor progression. However, current first-line therapy for BTRE, the drug Leviteracetam, a synaptic release inhibitor, fails to suppress seizures in half of patients. A fundamental shift in our approach to treatment of BTRE is greatly needed. Recent studies on the pathogenesis of tumor-related epilepsy have uncovered novel roles for the brain tumor microenvironment (TME), including tumor-stromal and tumor-neuron interactions that result in bidirectional, synergistic efforts to re-sculpt the molecular structure of the TME, resulting in neuronal dysfunction and a feed-forward loop of loss of inhibition, repeated seizures, and tumor progression. In particular, the perineuronal net (PNN) has been shown to be degraded by gliomas, resulting in dysregulation of inhibitory interneurons in the adjacent cortex. The TME is a novel and potentially powerful therapeutic target in BTRE; however, the molecular and cellular mechanisms connecting tumor microenvironment to clinical seizures in patients remain undefined. To better understand seizure onset in patients with brain tumors, this project will perform digital spatial profiling (DSP), an automated system for multiplexed, spatially-linked RNA transcript and protein expression quantification, and Visium 10x Single-nuclei RNA sequencing on brain tumor specimens to evaluate PNN structure and composition in the TME. The project will then apply machine-learning approaches to analyze these high-dimensional data in order to identify PNN features that relate to a clinical history of seizures. This aim will test the hypothesis that tumor-related PNN degradation in patients is associated with severe neurologic symptoms. It will also result in major development of novel histologic and computational techniques for evaluation of PNN structure and function that can be broadly applied to other, similarly complex biomedical datasets. Completion of these aims will help the Project Leader and research team to better understand how brain pathologies affect PNNs in patients, generate new biological resources and technologies for the study of human PNNs, and provide evidence to support preserving or restoring the PNN as a novel, more effective strategy for treatment of BTRE.