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 th...