3D imaging of the murine neurovasculature with μMRI and validation with μCT and optical microscopy.

<p>(a) Photograph of a freshly excised mouse brain showing blue Microfil® perfused vessels (arrows). (b) X-ray radiograph of the same brain in which radio-opaque microfilled vessels are clearly visible. Arrows indicate major vessels that are also visible in (a). (c) Slice through the 3D R₂* map of the same brain. The Microfil-brain tissue interface is characterized by elevated R2* (hot colors) values. Note that background voxels are assigned R2* of zero. (d) ∼1.2 mm slab from another intact brain, in which μMRI-derived vasculature (gold) is overlaid on that acquired using μCT (purple). One can clearly visualize the vascular architecture and the agreement between μMRI and μCT. (e) Bright-field images (2×) of ROIs corresponding to colored squares in (d). Images are from a 1 mm thick, unstained brain section. Dark microfilled vessels provide corroboration of the μMRI data in (d). Arrows indicate major vessels that are also visible in (d). μCT data were resampled to match the μMRI spatial resolution, and the fractional vascular volume (FV) computed within 8×8×1 subvolumes for each dataset. The correlation between the μMRI and μCT-derived FVs for the 1 mm thick slice is plotted in (f). A similar analysis was conducted for the <i>whole</i> brain, wherein the FV was computed within 8×8×8 subvolumes for each dataset. The correlation between the μMRI and μCT-derived FVs for the <i>whole</i> brain is plotted in (g) and demonstrate good agreement between μMRI and μCT-derived vasculature. The red lines in (f) and (g) are the best linear fit to the data, and blue lines indicate the 95% confidence limits about the mean.</p

Ultra-high resolution 3D μMRI and “zonal” analyses of the neurovasculature.

<p>(a) 3D rendering of the neurovasculature in a non-invasive, 9L tumor bearing mouse brain acquired using ultra-high resolution (30 µm×30 µm×30 µm) μMRI. The vasculature has been color coded into three different “zones”: normal vessels (blue), tumor vessels (red) and vessels at the tumor-brain interface or transition zone (green). The transition-zone or tumor-brain tissue interface is crucial to understanding both, brain tumor angiogenesis and invasion. The radius and length of every individual vessel segment was measured in each zone. (b) Box plot of the average vessel length in each zone, wherein the width of each box includes 75% of the measured lengths and the median length is indicated by a horizontal line in each box. In addition, the radius of every vessel segment is plotted for each zone, with the color and size of each symbol proportional to the vessel radius. The normal zone exhibited significantly longer vessel segments compare to the transition (p = 0.002) and tumor zones (p<0.001), respectively. At this tumor stage, vessel radii were similar between the tumor and normal zones. These data demonstrate our ability to characterize the neurovasculature in physiologically relevant “zones”, and could provide new insight into the relationship between brain tumor angiogenesis and invasion. (c) T₂-weighted μMRI slice through a 9L brain tumor (gold rendering) bearing brain. (d) 3D overlay of the neurovasculature acquired using ultra-high resolution μMRI. (e) 3D DTI image showing reorganization of the fibers of the anterior commissure (<i>ac</i>) and internal capsule (<i>ic</i>) around the tumor. (f) Overlay of (d) and (e) illustrating simultaneous changes in vascular and white matter structures.</p

Multi-scale MRI of a 9L brain tumor model.

<p>(a) In vivo T₂-weighted MRI at the ‘systemic’ scale (∼150 µm); ex vivo μMRI at two ‘intermediate’ scales: (b) ∼60 µm, and (c) ∼30 µm. (d) Ultra-high resolution vascular μMRI image in which vessels have been segmented into tumor vessels (gold) and normal vessels (red). One can clearly visualize the abnormal tumor vessel architecture and changes in vessel morphology at the tumor-host tissue interface (arrows).</p

Simultaneous imaging of brain tumor angiogenesis and invasion with μMRI.

<p>(a) FA map of a patient-derived, invasive primary glioma model. (b) Zoomed view of the hatched region in (a) showing two ROIs in the corpus callosum for which the FA was analyzed. (c) Histograms of the FA from the ROIs in (b), wherein one can see that the FAs from ROI-1 are shifted toward lower values than those from ROI-2. (d) Histology (H&E) from the same region as in (b) in which one can see the white matter tract (WM) being infiltrated by a tuft of tumor cells (I). The tumor margin (T) is also visible in (d). (e) Visualization of the DTI tensors as 3D ellipsoid glyphs for one μMRI slice, wherein each ellipsoid is scaled according the values of the three principal eigen-vectors and color coded according to the FA. The invasive primary tumor (hatched outline) is identifiable by its lower FA in contrast to the contralateral brain. (f) Visualization of the 3D vasculature for the whole brain. Tumor vasculature (hatched outline) is dense and chaotic relative to that of the contralateral brain. (g) The image in (e) overlaid with that in (f) allows us to simultaneously assess the interaction between brain tumor angiogenesis and the effects of tumor invasion on the integrity of white matter tracts. The tumor ROI is highlighted by a hatched outline.</p

Bridging macroscale and microscale MRI.

<p>(a) In vivo macrovascular CBV (ΔR₂*) map. (b) Co-registered <i>ex vivo</i> fractional blood volume (FV) map obtained from μMRI. The tumor ROI is highlighted by hatched lines in each panel and FV ranges from 0 to 1. (c) Histograms showing the relative distribution of the ΔR₂* between tumor and contralateral ROIs. (d) Histograms showing the relative distribution of the FV between tumor and contralateral ROIs. Tumor blood volume is elevated relative to the contralateral brain across these “multi-scale” data. (e) 2D histograms of the macrovascular CBV measured <i>in vivo</i> versus the fractional blood volume assessed <i>ex vivo</i>. These data further demonstrate the utility of multi-scale imaging of brain tumor vascularization.</p

Segmentation of the Vasculature from μMRI Data.

<p>Image processing steps involved in the extraction of the 3D vasculature from the raw GE μMRI data for a 9L tumor (arrow in all panels) bearing mouse brain: (a) <i>Ex vivo</i> T₂*-weighted image corresponding to the 1^st TE; (b) Blood vessels (red) segmented out using the “tubeness” filter overlaid on the raw data in (a). (c) Binarized vasculature obtained by thresholding the tubeness data in (b) followed by removal of isolated voxels. (d) Volume rendering of the μMRI-derived vasculature, color-coded by average vessel radius.</p

Levels of secreted cytokines in the conditioned medium of transfected and non-transfected cells.

<p>Conditioned medium from cells transfected with either SM20 or WT15 and non-transfected cells were collected and assayed for cytokines expression as detailed in Materials and Methods. Data represent the average of three to four independent transfection experiments. Error bars represent the standard deviation of the data.</p

Intracellular aptamers inhibit uPA activity.

<p><b>(A)</b> Intracellular uPA or (<b>B</b>) PAI-1 protein levels in cellular extracts of transfected and non-transfected MDA-MB-231 cells were analyzed by Western blot using an antibody to either uPA (A) or PAI-1 (<b>B</b>). (<b>A</b>) Top panel (short exposure) and the lower panel (longer exposure). Total protein concentration was determined and 21 μg protein was added at each experimental condition. The upper band corresponds to the PAI-1/uPA complex (<b>A-B</b>). (<b>C</b>) Intracellular uPA activity was determined in cellular extracts using a chromogenic assay in non-transfected cells (0) and cells transfected with 100 pmol RNA aptamers. Each experiment was performed at least three times with comparable results. **p<0.01, *p<0.05.</p

Expression of RNA aptamers in HUVECs.

<p>(<b>A</b>) Total RNA was isolated from transfected (+) and non-transfected (-) cells, then RT-PCR analysis were performed. Expression of the aptamer, PAI-1, and β-actin is shown. N.B. The SM20 was assay was run separately and then added to the figure. (<b>B</b>) HUVECs transfected with aptamers (Sel2, SM20, and WT15) or non-transfected cells were added to vitronectin coated plates and incubated for 1 hour at 37°C. The non-adherent cells were removed and the adherent cells were assessed by an MTT assay analysis. The percent of adherent cells were normalized to the percent of cells adhering in the absence of aptamers. All reactions were done in triplicates and repeated at least twice times; error bars represent the standard deviation of the data. *p<0.05.</p

Effects of RNA aptamers on migration and invasion of MDA-MB-231 cells.

<p>MDA-MB-231 cells transfected with Sel2 (<b>A</b>), SM20 (<b>B</b>), and WT15 (<b>C</b>) were added to transwell inserts. For migration assays, the cells were added to uncoated transwell inserts and allowed to migrate for 18–24 hours at 37°C. For invasion assays, the cells were added to transwell inserts coated with Matrigel. The cells were allowed to invade for 24 hours at 37°C. Chemo attractants were added to the lower well. Results shown represent the average +S.D. from three independent assays that were performed in duplicate. All data were normalized to migration or invasion in non-transfected cells, which was set at 100%. *<i>p</i><0.05 compared with PAI-1 alone. Each data point was performed in triplicates and the experiments were repeated at least three times with similar results. *p<0.05, **p<0.01.</p