Project 1: Deciphering the Dynamic Evolution of the Tumor-Neural Interface
项目1:破译肿瘤-神经界面的动态演化
基本信息
- 批准号:10729275
- 负责人:
- 金额:$ 47.3万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-15 至 2028-08-31
- 项目状态:未结题
- 来源:
- 关键词:AMPA ReceptorsAffectAftercareAnimalsAntiepileptic AgentsBiological ProcessBlood VesselsBrainBrain NeoplasmsCell CommunicationCellsClassificationClinical TrialsClone CellsCommunicationCommunitiesCompetenceComputer ModelsDataDedicationsDevelopmentElectrophysiology (science)ExcisionExhibitsExtracellular MatrixFavorable Clinical OutcomeGlioblastomaGliomaGlutamatesHeterogeneityHigh Frequency OscillationImmunologicsIndividualInvadedLevetiracetamLocationLogistic RegressionsMagnetic Resonance ImagingMalignant - descriptorMalignant GliomaMapsMeasurementMeasuresMetabolicMetabolic PathwayMicroscopicMitochondriaModelingMolecularMultiomic DataNatureNeuroepithelial, Perineurial, and Schwann Cell NeoplasmNeuronsOperative Surgical ProceduresOxidative PhosphorylationPathway interactionsPatientsPhenotypeProliferatingRadiation therapyRecurrenceResectedResistanceResolutionResourcesRouteSamplingSignal PathwaySignal TransductionSliceSpecimenSynapsesSystemSystems BiologyTestingTherapeuticTimeTissuesTreatment EfficacyTumor MarkersTumor PromotionWorkcancer proteomicscell growthcell motilitycell typechemotherapyclinically relevantcohortdata integrationdeep learningdesigndynamical evolutionexperimental studyin vivoinhibitorinnovationmultiple omicsneoplastic cellneuronal tumornovelpatient derived xenograft modelpharmacologicpre-clinicalprogenitorrandom forestresponsesingle-cell RNA sequencingstandard of caretherapeutic developmenttherapy resistanttumortumor metabolismtumor progressiontumorigenesiswhite matter
项目摘要
ABSTRACT – PROJECT 1
The central premise of our CSBC MIT/DFCI Center for Systems Biology in Glioblastoma is that high-content
systems-level measurements at molecular, microscopic, and macroscopic scales with spatial resolution will
enable the development of computational models to map and predict tumor dynamics leveraging data integration
and deconvolution for computational modeling of the glioblastoma-microenvironment. The establishment of this
novel GBM model will support the identification of critical signaling and metabolic pathways and networks
regulating tumor progression and therapeutic resistance, while providing biomarkers of tumor state and efficacy
for therapeutic developement. Project 1 will focus on elucidating networks coordinating the tumor-neuronal
interface. Recent results uncovered the ability of subpopulations of glioblastoma cells to organize in brain tumor
cell networks that include the formation of glutamatergic synapses formed between individual glioblastoma cells
and neural cells from the normal brain. The establishment of synaptic connectivity was proposed to promote
tumor cell movement along white matter, therefore implying that the mutually connected glioma cells may drive
invasion of the normal brain, which is the primary mechanism of progression and aggressiveness of malignant
glioma that ultimately renders these tumors incurable. We will now leverage key preclinical resources established
by our labs, including an integrated computational-experimental framework, annotated GBM patient-derived
xenografts (PDXs) for ex vivo and in vivo mechanistic experiments to derive a model of glioma-neuron
interactions that drive the malignant nature of glioblastoma and how perturbation of this signaling network affects
tumor proliferation, invasion, and therapeutic resistance. In Aim 1, we will use our innovative multi-omics platform
with ex vivo slice culture models to investigate the ability of neurons to support tumor cell growth and invasion
and affect cell state and develop and implement computational modeling strategies to model the dynamic
evolution of different cell types and tumor cell clones over time and in response to stimulation. Aim 2 will allow
further parametrization of the computational model with data acquired from in vivo orthotopic models tested
for the effect of anti-epileptic drugs on tumor proliferation and invasion in the context of standard of care treatment
with radiotherapy and recurrence. In Aim 3, we will analyze the impact of anti-epileptic therapeutics on the
glioma-brain network in clinical trial tissue specimens with our multi-omics platform, allowing to test and
optimize the model accuracy with clinically relevant data.
摘要-项目1
我们的CSBC MIT/DFCI胶质母细胞瘤系统生物学中心的中心前提是,
具有空间分辨率的分子、微观和宏观尺度的系统级测量将
使计算模型的开发能够利用数据集成来映射和预测肿瘤动力学
以及用于胶质母细胞瘤微环境的计算建模的去卷积。设立这一
一个新的GBM模型将支持关键信号和代谢途径和网络的识别
调节肿瘤进展和治疗抗性,同时提供肿瘤状态和功效的生物标志物
用于治疗发展。项目1将集中于阐明协调肿瘤-神经元
接口.最近的结果揭示了胶质母细胞瘤细胞亚群在脑肿瘤中组织的能力
包括单个胶质母细胞瘤细胞之间形成的突触的形成的细胞网络
和正常大脑的神经细胞。突触连接的建立被提出来促进
肿瘤细胞沿着白色物质运动,因此暗示相互连接的胶质瘤细胞可能驱动
正常脑的侵袭,这是恶性肿瘤进展和侵袭性的主要机制。
最终导致这些肿瘤无法治愈的神经胶质瘤。我们现在将利用已建立的关键临床前资源
我们的实验室,包括一个综合的计算实验框架,注释GBM患者衍生
异种移植物(PDX)用于离体和体内机制实验以获得神经胶质瘤-神经元模型
驱动胶质母细胞瘤恶性性质的相互作用以及这种信号网络的扰动如何影响
肿瘤增殖、侵袭和治疗抗性。在目标1中,我们将使用创新的多组学平台
用离体切片培养模型研究神经元支持肿瘤细胞生长和侵袭的能力
并影响细胞状态,开发和实施计算建模策略,
不同细胞类型和肿瘤细胞克隆随时间的演变和对刺激的响应。目标2将允许
利用从测试的体内原位模型获得的数据进一步参数化计算模型
在标准治疗的背景下,抗癫痫药物对肿瘤增殖和侵袭的影响
放疗和复发。在目标3中,我们将分析抗癫痫治疗对癫痫发作的影响。
神经胶质瘤-脑网络在临床试验组织标本与我们的多组学平台,允许测试和
利用临床相关数据优化模型精度。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nathalie YR Agar其他文献
Nathalie YR Agar的其他文献
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{{ truncateString('Nathalie YR Agar', 18)}}的其他基金
Defining mechanisms to promote antitumor immunity by modulating one-carbon metabolism
定义通过调节一碳代谢促进抗肿瘤免疫的机制
- 批准号:
10565099 - 财政年份:2023
- 资助金额:
$ 47.3万 - 项目类别:
Dynamics of Cellular Brain Metabolism Using Mass Spectrometry Imaging
使用质谱成像研究细胞脑代谢动力学
- 批准号:
10556434 - 财政年份:2022
- 资助金额:
$ 47.3万 - 项目类别:
Dynamics of cellular brain metabolism using mass spectrometry imaging
使用质谱成像研究细胞脑代谢动力学
- 批准号:
10418219 - 财政年份:2022
- 资助金额:
$ 47.3万 - 项目类别:
Real-Time Stereotactic Mass Spectrometry Tissue Analysis for Intraoperative Neuro
术中神经的实时立体定向质谱组织分析
- 批准号:
7981836 - 财政年份:2010
- 资助金额:
$ 47.3万 - 项目类别:
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