Traditional methods of imaging cell migration in the tumor microenvironment include serial sections of xenografts and standard histologic stains. Current molecular imaging techniques suffer from low resolution and difficulty in imaging through the skull. Here we show how computer algorithms can be used to reconstruct images from tissue sections obtained from mouse xenograft models of human glioma and can be rendered into three-dimensional images offering exquisite anatomic detail of tumor cell dispersal. Our findings identify human LN-229 and rodent CNS-1 glioma cells as valid systems to study the highly dispersive nature of glioma tumor cells along blood vessels and white matter tracts in vivo. This novel cryo-imaging technique provides a valuable tool to evaluate therapeutic interventions targeted at limiting tumor cell invasion and dispersal. Cancer Res; 71(17); 5932–40. ©2011 AACR.
Glioblastoma multiforme (GBM) is a devastating disease characterized by necrotic primary tumor centers with robust neovascularization (1) surrounded by pseudopalisades of migrating cells (2). In fact, infiltration of tumor cells as far away as 4 cm from the primary tumor has been observed (3). Migrating or dispersing GBM cells follow characteristic pathways along secondary structures including perivascular, perifascicular, perineural, and neuronophagic, subpial or “surface,” and intrafascicular growth (4). Perivascular growth is the most common individual form observed, whereas the most common combination of structures observed in a single tumor is perivascular, neuronophagic, and subpial growth (4). The type and location of the dispersed cells are likely influenced by the location of the primary neoplasm itself. Given that migration of tumor cells seems to be a primary feature of GBM neoplasia, a better understanding of the regulation of this migration is in order.
The current cellular theory of GBM dispersal into the surrounding tissue involves cellular detachment from the primary tumor, attachment to and degradation of the extracellular matrix, and finally migration (5). A number of molecules have been implicated in regulating these processes in in vitro experiments, including receptor tyrosine kinases and phosphatases, cell adhesion molecules, and proteases (5, 6).
To identify the molecular regulation of GBM cell infiltration in vivo, accurate models of GBM dispersal need to be developed. To date, the best animal models that recapitulate the main features of GBM are spontaneous brain tumors observed in dogs (7). Spontaneous, transgenic, xenograft, and syngeneic tumor models in rodents have also been characterized histologically (7–9). From these studies, various cell lines have been identified that mimic elements of human GBM pathology. For instance, human tumor-derived U-87 MG cells injected intracranially into C57/B6 mice are highly angiogenic (7), whereas rat tumor-derived CNS-1 cells injected into Lewis rats mimic the pseudopallisading and hemorrhaging of GBM tumors in addition to being infiltrative (7, 9).
In this article, we describe the analysis of mouse orthotopic xenograft tumors by using a novel 3-dimensional (3D) imaging technique developed in the laboratory of Dr. David Wilson at Case Western Reserve University. The Case Cryo-Imaging System acquires high-resolution anatomic color and cellular and molecular fluorescent images and then 3-dimensionally reconstructs a tissue or an entire organism, such as a mouse. Cryo-imaging is unique among all in vivo and microscopic techniques in that it allows micron-level resolution and information-rich contrast over large 3D fields of view. We used the system to analyze the 3D extent of cell migration and dispersal from orthotopic glioma tumors along blood vessels and white matter tracts within the brain.
We recently described the development of algorithms to reconstruct the 3D architecture of blood vessels and tumor cell dispersal within the mouse brain (Qutaish and colleagues, submitted manuscript). We used these algorithms to characterize how commonly used human (Gli36Δ5, U-87 MG, LN-229) and rodent (CNS-1) glioma cell lines disperse in the mouse brain. In this article, we provide a complete 3D analysis of the dispersal and migration of these 4 tumor cell lines on blood vessels and white matter tracts. Our studies suggest that LN-229 and CNS-1 are effective cell lines to use to study the dispersive nature of tumor cells along both blood vessels and white matter tracts whereas Gli36Δ5 cells are not dispersive in vivo and instead stay associated with the primary tumor. U-87 MG cells showed limited dispersal only along blood vessels. Our data suggest that either the human LN-229 cell line or the rat CNS-1 cell line in mouse xenograft models of glioma are the most appropriate for future studies investigating the molecular regulation of tumor cell dispersal along particular anatomic structures within the brain. These xenograft systems evaluated with the Case Cryo-Imaging System will allow for future testing of therapeutics aimed at blocking GBM tumor cell dispersal.
Materials and Methods
Orthotopic xenograft intracranial tumors
Human LN-229 and U-87 MG glioma cells were obtained from American Type Culture Collection. CNS-1 rodent glioma cells were obtained from Mariano S. Viapiano (10). Human Gli36Δ5 glioma cells constitutively overexpress the vIII mutant forms of the EGFR gene (11) and were obtained from E.A. Chiocca. The CNS-1 and Gli36Δ5 cell lines were authenticated by Research Animal Diagnostic Laboratory at the University of Missouri (Columbia, MO) for interspecies and mycoplasma contamination by PCR analysis. Five- to 8-week-old NIH athymic nude mice (20–25 g each) were housed in the Athymic Animal Core Facility at Case Western Reserve University according to institutional policies. All animal protocols were approved by the Institutional Animal Care and Use Committee.
Gli36Δ5, U-87 MG, CNS-1, or LN-229-GFP cell lines were infected with green fluorescent protein (GFP) encoding lentivirus, harvested for intracranial implantation by trypsinization, and concentrated to 1 × 105 cells/μL PBS. Mice were anesthetized by intraperitoneal administration of 50 mg/kg ketamine/xylazine and fitted into a stereotaxic rodent frame (David Kopf Instruments). Cells were implanted at AP = +0.5 and ML = −2.0 from bregma at a rate of 1 μL/min in the right striatum at a depth of −3 mm from dura. For examination of dispersal along white matter tracts, cells were implanted at a depth of −2 mm from dura for tumor formation in close vicinity to the corpus callosum. A total of 50,000 to 200,000 cells were implanted per mouse.
Mice were sacrificed 7 to 38 days after implantation on the basis of tumor burden. Dissected brains were embedded in Tissue-Tek optimum cutting temperature (OCT) compound (Sakura Finetek U.S.A., Inc.), frozen in a dry ice/ethanol slurry and transferred to the stage of the cryo-imaging device.
Cryo-imaging of tissue samples
Three brains implanted per cell type with either LN-229, CNS-1, U-87 MG, or Gli36Δ5-GFP were analyzed. Frozen brains were alternately sectioned and imaged using the cryo-imaging system at a section thickness of 15 to 40 μm and a resolution of 11 × 11 × 15 or 15.6 × 15.6 × 40 μm. The cryo-imaging system consists of a mouse-sized stage on a motorized cryostat with special features for imaging, a modified bright-field/fluorescence microscope, and a robotic xyz imaging system positioner, all of which are fully automated. The system images fluorescent agents or cells at a very high resolution and sensitivity. Bright-field and fluorescence images were acquired for each of the brains with a low-light digital camera (Retiga Exi), GFP fluorescence filters (exciter HQ470/40x, dichroic Q495LP, emitter HQ500LP; Chroma), and an epi-illumination fluorescent light source (XCite 120PC; EXFO).
Image processing algorithms for visualization of tumor cells and vasculature
We recently developed methods for segmentation and visualization of the vasculature, main tumor mass, and dispersing cells (Qutaish and colleagues, submitted manuscript). To segment the main tumor mass, we used a recently developed 3D seeded region growing algorithm (Qutaish and colleagues, submitted manuscript). Results were reviewed in individual slice images and manually edited if necessary. To segment dispersed tumor cells and clusters, we applied a high-pass filter and thresholded the result, excluding the binary volume consisting of the main tumor. To create a 3D volume of the brain vasculature, bright-field images from each brain specimen were processed using algorithms developed for vessel edge detection and volume rendering (Qutaish and colleagues, submitted manuscript). These algorithms resulted in a 3D reconstruction of the brain vasculature. The lower limit for the blood vessel detection algorithm was approximately 30 μm diameter vessels. Three-dimensional pseudo-colored volumes were created that included the main tumor (green), dispersing cells (yellow), and vasculature (red). The location of dispersed cells was visually inspected by rotation of the composite 3D volume within Amira (Visage Imaging Inc.) to confirm a distinct nonfluorescent region separating dispersing cells from the main tumor and to identify cells in close proximity to blood vessels.
Dispersal on white matter
The corpus callosum white matter was manually segmented using bright-field cryo-images and Amira Software. The segmented region was reconstructed as a 3D volume that was merged with the 3D tumor and dispersed cell volumes. The white matter was pseudo-colored gray, and the dispersed cells in contact with the white matter were pseudo-colored magenta, whereas all other dispersing cells were pseudo-colored yellow.
Orthotopic xenograft models of glioma cells in rodents are useful for assessing tumor growth characteristics and response to therapeutics. Gli36Δ5 is a human glioma cell line that grows rapidly to form a large tumor within 2 weeks (11). However, the tumors become encapsulated and cell dispersal from Gli36Δ5 tumors was never observed, as shown in 2-dimensional (2D) histologic sections (Fig. 1A and B). Xenografts of U-87 MG human glioma cells also grow rapidly as closely associated cells with defined margins (Fig. 1C and D). The LN-229 human glioma cell line exhibits slower growth characteristics, and examination of orthotopic xenografts in histologic sections revealed that LN-229 cells disperse from the main tumor at 4 to 6 weeks postimplantation (Fig. 1E and F). The CNS-1 glioma cell line was developed in the inbred Lewis rat, and it exhibits very rapid growth (10). Within 1 week following implantation, these tumors were highly vascularized, the cells of the tumor were loosely associated, and individual cells had dispersed from the entire perimeter of the main tumor (Fig. 1G and H). By 10 days of growth in vivo, the dispersed cells were observed throughout the entire frontal lobe of the hemisphere surrounding the main tumor (data not shown).
Perivascular growth is the most common form of glioma dispersal (4). To examine whether these cell lines dispersed along blood vessels, histologic sections of GFP-expressing tumor xenografts of U-87 MG (Fig. 2A–D), LN-229 (Fig. 2E–H), and CNS-1 (Fig. 2I–L) cells were immunolabeled with the endothelial cell–specific antibody CD-31. U-87 MG tumor cells dispersed along blood vessels in close proximity to the main tumor (Fig. 2A–D); however, the extent of dispersal was minimal. In contrast, LN-229 (Fig. 2E–H) and CNS-1 (Fig. 2I–K) cell dispersal occurred primarily along blood vessels.
The 2D histologic sections provided a high-resolution snapshot of a single plane through the tumor of interest. However, 3D reconstruction of histology images is time-consuming and prone to tissue shrinkage and errors in image alignment. To overcome these obstacles the Case Cryo-Imaging System was used to analyze tumor cell dispersal from orthotopic xenografts of the 4 glioma cell lines in 3D at high resolution. The technique utilized bright-field images of the block face for overall brain anatomy and fluorescent images to detect the GFP-expressing glioma cells (Qutaish and colleagues, submitted manuscript). Three-dimensional volumes were created for the vasculature (pseudo-colored red), white matter (pseudo-colored gray), and the main tumor mass (pseudo-colored green). Glioma cells that were no longer physically connected in any dimension to the main tumor were pseudo-colored yellow to indicate tumor cell dispersal. Multiple xenograft specimens of each cell line were analyzed using this technique, and representative examples are shown. The comparison with standard histology images highlights the tumor biology that can be visualized using this novel technique.
Gli36Δ5 cells are non-dispersive
The growth of Gli36Δ5 xenografts was rapid, resulting in a large encapsulated mass by 2 weeks after implantation (arrow in Fig. 3A). Three-dimensional cryo-image analysis of Gli36Δ5 tumors showed that the average tumor volume was 40.57 mm3 (n = 3). Tumor growth resulted in the compression of surrounding brain structures (Fig. 3A). In addition, 3D reconstruction of the brain vasculature indicated that although the tumors were highly vascularized, cell dispersal was never observed (Fig. 3B and C), which supported previous observations in 2D histologic sections (Fig. 1A and B).
U-87 MG cells are marginally dispersive along blood vessels
In U-87 MG xenografts, tumor cells dispersed along blood vessels in close proximity to the main tumor. This dispersal pattern was observed in both 2D histologic sections (Fig. 2A–D), and 3D tumor reconstructions from cryo-image analysis (Fig. 3E and F). Analysis of the 3D tumors indicated that the average dispersed cell volume was 0.0028 mm3 and average tumor volume was 1.86 mm3 (n = 3). Therefore, the dispersed cells represented only 0.15% of the total tumor cell population. However, the cells dispersed up to 300 μm from the main tumor (Supplementary Fig. S1). Although U-87 MG tumors exhibit somewhat limited dispersal, they may be good models to analyze effects of chemotherapeutics on reduction of tumor load or migration on blood vessels.
LN-229 is a dispersive human glioma cell line
The LN-229 xenografts grew at a slower rate than Gli36Δ5 or U-87 MG to form an average tumor load of 2.76 mm3 (n = 3) after 4 to 6 weeks. Two-dimensional histologic analysis revealed cell dispersal along the length of the tumor (Fig. 1F), often in association with blood vessels (Fig. 2E–H). Analysis of 3D cryo-image volumes illustrated that LN-229 cells frequently disperse as connected strands for several hundred microns along blood vessels (Fig. 4C and D). It is unclear whether these vessels were pre-existing or due to tumor-mediated angiogenesis. Small populations of cells released all along the main tumor to migrate through the brain parenchyma (Fig. 4B and F) and (Qutaish and colleagues, submitted manuscript). These cells may also be dispersing along blood vessels that are below the limits of detection with our analysis algorithms (<30 μm diameter). Overall, the average dispersed cell volume was 0.035 mm3, which represents 1.26% of the total tumor cell population. LN-229 cells were observed to reach the lateral ventricle from the main tumor in some cases, resulting in spread to distant regions of the brain via passive movement in the cerebrospinal fluid (data not shown). In those instances, the cells became imbedded in and spread along the meninges covering the brain.
The rat glioma cell line CNS-1 is highly dispersive in vivo
The CNS-1 cell line spread aggressively to infiltrate distant regions of the brain from the tumor within 7 to 10 days post-implantation. The main tumor consisted of loosely associated, pseudopallisading cells (Fig. 1G and H), with features of hemorrhage and necrosis (arrow in Fig. 5A and E). Because of the rapid dispersal of CNS-1 cells, the volume of the main tumor at 7 days was only 1.49 mm3 (n = 3). However, the dispersed cell volume was 0.18 mm3, which represents 10.6% of the total tumor cell population detected by 3D cryo-image analysis. CNS-1 cells migrated extensively along blood vessels, as shown in the 3D reconstructions from 7-day tumors (Fig. 5D and H). In addition, CNS-1 cells readily dispersed through the brain parenchyma (Fig. 1H). Supplementary Video 1 shows an example of CNS-1 cell dispersal around the entire perimeter of the main tumor. Dispersed cells are clustered on blood vessels in close proximity to the tumor edge as well as streaming along vessels at a distance.
We analyzed the dispersal distance of CNS-1, LN-229, and U-87 MG cells using a 3D morphologic distance algorithm that detects the presence of voxels containing fluorescent cells in a series of dilations from the tumor edge outward (Qutaish and colleagues, submitted manuscript). The voxel size was 11 × 11 × 15, approximately the size of a single cell. The first 2 dilations closest to the tumor were discarded to reduce nonspecific error. The results from this analysis indicate that LN-229 and CNS-1 xenografts generate thousands of dispersive cells (Supplementary Fig. S1), which represent a 13- to 28-fold increase in total number of dispersed cells when compared with the U-87 MG xenografts. The maximum distance traveled by LN-229 cells was 562 μm away from the tumor edge, whereas CNS-1 cells dispersed more than 3 mm from the tumor (Supplementary Fig. S1).
LN-229 and CNS-1 cell dispersal along white matter tracts
One of the pathways used by human glioma cells for dispersal is intrafascicular growth on white matter. We analyzed the ability of the 4 cell lines to use white matter for dispersal. Neither Gli36Δ5 nor U-87 MG cells dispersed on the corpus callosum, a large white matter structure in close proximity to the main tumors. U-87 MG cells within the main tumor were observed to realign along the longitudinal axis of the corpus callosum (Fig. 6A and B). In all 3 xenografts examined by 3D cryo-image analysis, the U-87 MG tumor bulged out onto the corpus callosum (arrow in Fig. 6G). Thus, these cells seem to respond to cues on the surface of the myelinated fibers. However, individual U-87 MG tumor cells did not disperse on the white matter (Fig. 6G).
LN-229 and CNS-1 cell lines dispersed along the corpus callosum as single cells or small cell clusters, as shown in histologic sections (Fig. 6C–F). Individual cells were observed to exit the main tumor to disperse directly onto the white matter, evidenced in the 3D tumor volumes by the magenta cells at the tumor–white matter transition zone (Fig. 6H and I). Supplementary Video 2 provides a detailed view of cell dispersal on white matter from a CNS-1 tumor. Together, these results provide further support that both LN-229 and CNS-1 cell lines are dispersive in the brain, showing dispersal characteristics comparable with humans, and thus may be good model systems for testing therapeutic efficacy.
Angiogenesis is correlated with tumor growth and dispersal rate
Angiogenesis is a hallmark feature of tumor growth. To determine whether differences in angiogenesis existed between the 4 glioma cell lines, we used the 3D cryo-image blood vessel reconstruction volumes to quantitate blood vessel density within each tumor. The most significant increase in blood vessel density occurred in tumors with the fastest growth rate such as Gli36Δ5 and U-87 MG as well as in the most extensively dispersing cells, CNS-1 (Supplementary Table S1).
The most useful animal models of human disease exhibit characteristics that are highly representative of those observed in humans. In this article, we characterized the in vivo growth and dispersal of 4 different glioma cell lines by using orthotopic xenografts in athymic nude mice. The cryo-imaging and 3D reconstruction methods described here provide extraordinary insight into tumor growth characteristics within the complex architecture of the brain at single-cell resolution that is a significant advancement over standard methods such as histologic sections. Our results also indicate that the best cell lines for studying migration and dispersal in the context of GBM are the LN-229 and CNS-1 cell lines.
Of note, the 4 cell lines we evaluated in this article showed a gradation of migration within the brain. Gli36Δ5 cells do not migrate, U-87 MG cells disperse marginally only along blood vessels, LN-229 cells migrate significantly along blood vessels and white matter tracts, and CNS-1 cells are the most migratory along both these secondary structures. Given that GBM tumor cells show a great range of distances and substrates for dispersal (1, 4), it would be ideal to have a range of cell lines to evaluate migration in vivo. Our findings that U-87 MG cells are not highly dispersive in vivo are supported by other recent data (12) and suggest that despite its popularity as a GBM tumor model in vitro, U-87 MG cells are not the best in vivo model.
Dispersal of LN-229 and CNS-1 cells along blood vessels suggests that the cells respond to migration-promoting cues present on the surface of blood vessels. A number of migration-promoting molecules have been identified in dispersive GBM cells in vivo. Stromal cell–derived factor 1α (SDF-1α) and its receptor CXCR4 (13), Na+/H+ exchanger regulatory factor 1 (NHERF-1; ref. 14), ephrin B2, ephrin B3, and the EphB2 receptor (15–17) mRNA and/or protein are all elevated in dispersive GBM cells versus core GBM tumor cells. Additional molecules, such as the cleaved extracellular fragment of the receptor tyrosine phosphatase PTPμ (18), the type I receptor of the TNF superfamily TNFRSF19/TROY (19), Neuropilin 1 and its ligand Sema3A (20), and the vitronectin receptor Necl5 (21), are also elevated in GBM tumor tissue, although not necessarily in dispersive cells. Only SDF-1 expression has specifically been localized to GBM secondary structures, whereas its receptor CXCR4 is expressed on migrating glioblastoma cells themselves (13).
All of the aforementioned molecules regulate GBM cell migration in vitro, as shown in Matrigel invasion or 2D migration assays (13–17, 19, 20, 22, 23) or 3D matrix spheroid assays (14, 21). Ex vivo models evaluating human GBM cell migration on rodent brain slices have also been employed to investigate the function of specific molecules in GBM dispersal (15–17, 19, 22). In addition to the different in vitro and ex vivo assays carried out, a wide variety of GBM cell lines were evaluated in these studies, including, but not limited to, A172 (20, 21), U-87 MG (13, 15–17, 19, 20, 23), T98G (14, 15, 19), and SNB19 cells (15, 19). The reason for selecting these different cell lines differs, but most often it is based on the expression level of a gene or protein of interest.
Both cellular and molecular differences exist between the tumor cells found within the main GBM tumor or “core” and those cells that have migrated away from the core or “edge” (24). Given this fact, it is important for us to develop means of studying dispersal as a separate event from the primary tumor growth and survival. The methodology that we present here and in Qutaish and colleagues (submitted manuscript) allows for the evaluation of migrating and dispersing cells in vivo at single-cell resolution. Tumor models such as the ones described here will be increasingly important to achieve the goal of understanding cell dispersal at a molecular level and evaluation of therapeutics targeting GBM dispersal.
Disclosure of Potential Conflicts of Interest
D.L. Wilson has a financial interest in BioInVision Inc., which intends to commercialize cryo-imaging.
This research was supported by the following NIH grants: R01-NS051520 (S.M. Brady-Kalnay), R01-NS063971 (S.M. Brady-Kalnay, J.P. Basilion, and D.L. Wilson), R42-CA124270 (D. Wilson), and P30-CA043703. This work was also supported by grants from the Ohio Wright Center/BRTT, The Biomedical Structure, Functional and Molecular Imaging Enterprise (D. Wilson), as well as the Case Center for Imaging Research.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The authors thank Cathy Doller and Scott Becka for expert technical support with histology, Dr. Scott Howell for help with the movies, and Dr. Andrew Sloan for helpful comments on the manuscript.
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).
- Received May 5, 2011.
- Revision received June 28, 2011.
- Accepted July 4, 2011.
- ©2011 American Association for Cancer Research.