Image-based Systems Biology of Vascular Co-option in Brain Tumors

摘要： 最近的临床和临床前证据表明，胶质瘤可以在最初生长，侵袭，逃避抗血管生成治疗， 并最终通过劫持或“吸收”大脑原有的血管而复发。血管联合是一种 非血管生成性胶质瘤生长机制，其中，选择肿瘤细胞导致星形胶质细胞失去与 血管，即引起神经胶质血管解偶联（GVU），并改变脑血流动力学。此外，在积极的高- 对于恶性胶质瘤（例如胶质母细胞瘤或GBM），血管共选择促进癌细胞迁移和侵入 健康的脑组织然而，随着胶质瘤的生存期，血管共选择的演变，导致GVU和血流动力学 由于缺乏微血管分辨率生命周期和多模态/多尺度， 成像方法。此外，由于缺乏造影剂， 增强和缺乏常规MRI（例如T2/FLAIR）方法的特异性。因此，我们的目标是使用 基于图像的系统生物学方法，以阐明在其生命周期内的共视胶质瘤的血流动力学， 开发一个功能磁共振成像生物标志物的co-option诱导GVU。在令人信服的初步数据的指导下，我们将追求三个 具体目的：（1）表征患者源性胶质瘤异种移植物（PDX）在其生命周期中的血管共选择， 多尺度成像;（2）建立血管共选择引起的全脑血流动力学变化的基于图像的模型 （3）确定rs-fMRI是否可以检测患者来源的胶质瘤异种移植物中血管共选择诱导的GVU。 在Aim 1下，我们提出了一种范式转变方法，采用微型显微镜进行微血管分辨率（~5 µm） 在患者源性胶质瘤的生命周期中，共选择诱导的血流动力学变化的多对比度体内成像 异种移植我们将用多模态/多尺度全脑数据补充这些微血管尺度测量 来自同一动物的离体CT/MRI/光片显微镜（LSM），以关联结构/功能/细胞变化 血管微环境（VME）在Aim 2下，我们将这些数据应用于一个诱导合作选择的模型中。 血流动力学失调，以模拟脑范围的变化，可作为合作的fMRI生物标志物， 胶质瘤在目标3下，我们将确定静息状态fMRI（rs-fMRI）是否可以检测到共同选择PDX中的GVU，并区分 它来自非共视胶质瘤生长。我们的方法是创新的，因为它融合了微型化的尖端技术， 显微镜、多尺度/多模态成像和基于图像的系统生物学。所提出的研究是有意义的 因为这些研究将建立：（i）癌症系统生物学的免费下载、共同注册的多尺度数据 研究人员;（ii）一个血流动力学模型的共选择胶质瘤;（iii）一种新的生物标志物的胶质瘤共选择与潜在的 改变病人的管理和刺激治疗的发展，以阻止抗血管生成的阻力。我们 还期望这种方法适用于依赖于血管共选择的其他CNS疾病（例如脑转移瘤）。

ABSTRACT: Recent clinical and preclinical evidence has shown that gliomas can initially grow, invade, evade antiangiogenic therapies and eventually recur by hijacking or “co-opting” the brain’s preexisting blood vessels. Vascular co-option is a nonangiogenic glioma growth mechanism in which, co-opting tumor cells cause astrocytes to lose intimate contact with blood vessels, i.e. cause gliovascular uncoupling (GVU), and alter cerebral hemodynamics. Additionally, in aggressive high- grade gliomas (e.g. glioblastoma or GBM), vessel co-option facilitates the migration and invasion of cancer cells into healthy brain tissue. Yet, the evolution of vessel co-option over the glioma’s life-time, resultant GVU and hemodynamic changes remain poorly understood due to a lack of microvascular-resolution lifecycle and multimodality/multiscale imaging approaches. Moreover, co-optive glioma growth is radiologically undetectable due to an absence of contrast enhancement and the lack of specificity of conventional MRI (e.g. T2/FLAIR) approaches. Therefore, our goal is to use an image-based systems biology approach to elucidate the hemodynamics of co-optive glioma over its lifecycle and develop an fMRI biomarker of co-option induced GVU. Guided by compelling preliminary data, we will pursue three Specific Aims: (1) Characterize vessel co-option in a patient-derived glioma xenograft (PDX) over its lifecycle with multiscale imaging; (2) Develop an image-based model of brain-wide hemodynamic changes induced by vessel co-option in glioma; and (3) Determine if rs-fMRI can detect vessel co-option induced GVU in a patient-derived glioma xenograft. Under Aim1, we propose a paradigm-shifting approach that employs a miniscope for microvessel resolution (~5 µm) multicontrast in vivo imaging of co-option induced hemodynamic changes over the lifecycle of a patient-derived glioma xenograft. We will complement these microvascular-scale measurements with multimodality/multiscale whole-brain data from ex vivo CT/MRI/light sheet microscopy (LSM) in the same animal to corelate structural/functional/cellular changes in the vascular microenvironment (VME). Under Aim2, we employ these data in a model of co-option induced hemodynamic dysregulation to simulate brain-wide changes that could be exploited as fMRI biomarkers of co-optive glioma. Under Aim3, we will determine if resting-state fMRI (rs-fMRI) can detect GVU in a co-optive PDX and differentiate it from non-co-optive glioma growth. Our approach is innovative because it blends cutting-edge advances in miniaturized microscopy, multiscale/multimodality imaging and image-based systems biology. The proposed research is significant because these studies will establish: (i) freely downloadable, co-registered multiscale data for cancer systems biology investigators; (ii) a hemodynamic model for co-optive glioma; (iii) a novel biomarker of glioma co-option with the potential to transform patient management and stimulate the development of therapies to thwart antiangiogenic resistance. We also expect this approach to be adaptable to other CNS diseases dependent on vessel co-option (e.g. brain metastases).