Browsing by Author "Rockne, Russell C."

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    Delivery strategies for cell-based therapies in the brain: overcoming multiple barriers
    Turk, Olivia M.; Woodall, Ryan C.; Gutova, Margarita; Brown, Christine E.; Rockne, Russell C.; Munson, Jennifer M. (Springer, 2021-10-30)
    Cell-based therapies to the brain are promising for the treatment of multiple brain disorders including neurodegeneration and cancers. In order to access the brain parenchyma, there are multiple physiological barriers that must be overcome depending on the route of delivery. Specifically, the blood–brain barrier has been a major difficulty in drug delivery for decades, and it still presents a challenge for the delivery of therapeutic cells. Other barriers, including the blood-cerebrospinal fluid barrier and lymphatic-brain barrier, are less explored, but may offer specific challenges or opportunities for therapeutic delivery. Here we discuss the barriers to the brain and the strategies currently in place to deliver cell-based therapies, including engineered T cells, dendritic cells, and stem cells, to treat diseases. With a particular focus on cancers, we also highlight the current ongoing clinical trials that use cell-based therapies to treat disease, many of which show promise at treating some of the deadliest illnesses. Graphical abstract: [Figure not available: see fulltext.].
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    Effect of Interstitial Fluid Flow and Radiotherapy on Glioblastoma Invasiveness and Progression
    Atay, Naciye Nur (Virginia Tech, 2024-06-27)
    Glioblastoma (GBM) is the most aggressive and malignant glioma. It accounts for 48.6% of all primary, malignant gliomas with a median survival of 15 months. Infiltration into the surrounding parenchyma is a hallmark of GBM. Radiotherapy is used to address the invasion; however, recent studies have implicated that radiation contributes to increased invasiveness of glioma. Although the effect of radiation on cells has been studied extensively, its effect on the transport of fluid is not well characterized. Transport in the brain which has significant roles in physiology, GBM pathophysiology, and GBM treatment. Thus, understanding the effect of radiation on transport within the lesion and surrounding interstitium will be beneficial in characterizing the effects of radiotherapy in GBM patients. This dissertation seeks to explore the relationship between radiation, transport, and movement of glioma cells and includes the following: 1) Characterizing in vitro motility metrics of glioma stem cell lines in and relating them to in vivo invasion. 2) Studying the effect of radiation on motility, flow-mediated invasion, extracellular matrix components, and transport within the lesion and interstitium. 3) Assessing transport in clinical images and relating transport parameters to progression of GBM. 4) Developing a novel pipeline for applying vector field topology to the study of interstitial fluid flow in glioma. Surprisingly, we found that motility metrics in vitro have a negative correlation trend with in vivo invasion. Next, we found that radiation causes a transient increase in advective flow, and a more sustained decrease in diffusivity in a murine glioma model. Tenascin C was found to correlate significantly with invasion and diffusivity, indicating that it might be a link between radiation, transport, and invasion. Furthermore, interstitial fluid flow was calculated and assessed in clinical images. This showed that interstitial fluid flow velocity magnitude in the tumor correlates with overall survival in GBM patients. Lastly, vector field topology was introduced as a novel method of studying transport that provides more detailed information to identify potential drivers of transport within a flow field. Altogether, this work presents novel insight into the effects of radiation on invasion and transport in GBM. Hopefully, this work can provide a foundation to build upon in efforts of improving treatment planning and clinical outcomes for GBM patients.
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    MRI analysis to map interstitial flow in the brain tumor microenvironment
    Kingsmore, Kathryn M.; Vaccari, Andrea; Abler, Daniel; Cui, Sophia X.; Epstein, Frederick H.; Rockne, Russell C.; Acton, Scott T.; Munson, Jennifer M. (AIP Publishing, 2018-06-26)
    Glioblastoma (GBM), a highly aggressive form of brain tumor, is a disease marked by extensive invasion into the surrounding brain. Interstitial fluid flow (IFF), or the movement of fluid within the spaces between cells, has been linked to increased invasion of GBM cells. Better characterization of IFF could elucidate underlying mechanisms driving this invasion in vivo. Here, we develop a technique to noninvasively measure interstitial flow velocities in the glioma microenvironment of mice using dynamic contrast-enhanced magnetic resonance imaging (MRI), a common clinical technique. Using our in vitro model as a phantom “tumor” system and in silico models of velocity vector fields, we show we can measure average velocities and accurately reconstruct velocity directions. With our combined MR and analysis method, we show that velocity magnitudes are similar across four human GBM cell line xenograft models and the direction of fluid flow is heterogeneous within and around the tumors, and not always in the outward direction. These values were not linked to the tumor size. Finally, we compare our flow velocity magnitudes and the direction of flow to a classical marker of vessel leakage and bulk fluid drainage, Evans blue. With these data, we validate its use as a marker of high and low IFF rates and IFF in the outward direction from the tumor border in implanted glioma models. These methods show, for the first time, the nature of interstitial fluid flow in models of glioma using a technique that is translatable to clinical and preclinical models currently using contrast-enhanced MRI.
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    Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients
    Chatterjee, Krishnashis; Atay, Naciye; Abler, Daniel; Bhargava, Saloni; Sahoo, Prativa; Rockne, Russell C.; Munson, Jennifer M. (MDPI, 2021-02-04)
    Background: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. Methods: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. Results: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. Conclusions: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.