We thank the Steeg Lab, at the National Cancer Institute for the generous donation of MDA-MB-231-BR-GFP cells. Confocal microscopy was performed at the University of Michigan Biointerfaces Institute (BI). Flow cytometry was performed at the University of Michigan Flow Cytometry Core. Viral vectors were created by the University of Michigan Vector Core. We also thank Kelley Kidwell for guidance in statistical analysis of these data.
FUNDING:
C.R.O. was partially supported by an NIH T-32 Training Fellowship (T32CA009676) and 1R21CA245597-01. T.M.W. was partially supported by 1R21CA245597-01 and the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002240. Funding for materials and characterization was provided by National Cancer Institute of the National Institutes of Health under award number 1R21CA245597-01, P30CA046592, 5T32CA009676-23, CA196018, AI116482, METAvivor Foundation, and the Breast Cancer Research Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health

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There are no disclosures to declare.

We have developed and presented a new method that adapts tools often utilized in clinical imaging analyses for measurement of extravasation and migration of cancer cells through an endothelial barrier into brain tissue. We pose this approach can be useful for both in vivo and in vitro measurements; we have demonstrated its use on a 3D microfluidic system recapitulating brain vasculature. Cancer cell measurements including distance extravasated, percent extravasated by volume, sphericity, and volume are quantified using t...

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type1,2. A principal question that arises when studying cancer metastasis is how sub clones migrate from the humoral environment of the bloodstream into an organ such as the brain3,4. This question has led to many variations of migration, invasion, and extravasation assays. All these methods share the critical step of counting or measuring properties of cells that move from one location to another in response to a stimulus. Most migration assays readily available are used to study two-dimensional (2D) migration of cancer cells. These have elucidated a wealth of knowledge; however, they do not recapitulate the three-dimensional nature of the in vivo system that other methods can provide5. Therefore, it is necessary to study the tumor micro-environment (TME) in three-dimensional (3D) systems, but the analysis approaches available for 3D structures are limited and often inconsistent.
One of the most popular 3D tools is a Boyden chamber that consists of a membrane suspended at the bottom of a well, separating two distinct regions. Boyden introduced the assay to study leukocyte chemotaxis4. The bottom regions may be varied by chemistry or other means6,7 to induce cells in the upper region to migrate to the lower region. The most common approach to quantifying the number of cells that have migrated is to release the cells from the bottom of the membrane using a buffer solution, lyse them, and then count them based on the quantity of DNA content in the solution7. This indirect approach is prone to operator error due to technique variability and the procedure destroys information about the cancer phenotype and the micro-environment. Variations of the Boyden chamber assay involve fixation of migratory cells that remain on the membrane, but only provides a count of cells that are no longer viable for continued study6,8,9.
Due to limitations of the Boyden chamber and the growth of innovations in the microfluidic community, migration assay chips have been developed which observe the motion of cells in response to a stimulus in one direction rather than three10,11,12. These migration assays facilitate control over factors such as flow or single cell separation13,14 that enable better interpretation of the results; however, their 2D format inevitably loses some dynamic information. Recent studies have focused on extravasation (i.e., the movement of cells from circulation into a tissue, such as the blood brain barrier) in a 3D environment14,15. The extravasation distance into tissue and probing behavior that occurs at the cellular barrier/membrane is more refined than measurements gleaned using either the Boyden chamber or a 2D microfluidic migration device16. Thus, devices that enable appropriate imaging and analysis of 3D extravasation are critical to capture these sophisticated measurements but are lacking in the literature.
Independent of migration assays, robust imaging techniques have been developed for magnetic resonance imaging (MRI) and tomography that are able to identify and accurately reconstruct tissue in 3D space17,18. These techniques acquire images in z-stacks and segment portions of the image based on the properties of the tissue and then convert the segmented images into three-dimensional meshes19,20,21. This allows physicians to visualize in 3D individual organs, bones, and vessels to aid in surgical planning or aid in diagnosis of cancer or heart disease22,23. Here, we will show that these approaches can be adapted for use on microscopic specimens and 3D extravasation devices.
To this end, we developed the innovative confocal tomography technique, presented herein, which affords flexibility to study the extravasation of tumor cells across a membrane by adapting existing tomography tools. This approach enables the study of the full gamut of cancer cell behaviors as they interact with a cellular barrier, such as an endothelial cell layer. Cancer cells exhibit probing behaviors; some may invade but remain close to the membrane, while others traverse the barrier readily. This technique is capable of yielding information about the phenotype of the cell in all dimensions24. Using this approach to study the TME is both relatively inexpensive, easy to interpret, and reproducible, when compared to more complex in vivo murine models. The presented methodology should provide a strong basis for the study of many types of tumors and micro-environments by adapting the stromal region.
We describe and demonstrate the use of a 3D microfluidic blood brain niche (&#181;mBBN) platform (Figure 1) where critical elements of the barrier and niche (brain microvascular endothelial cells and astrocytes) can be cultured for an extended period (approximately up to 9 days), fluorescently imaged by confocal microscopy, and the images reconstructed using our confocal tomography technique (Figure 2); all aimed to understand the development of micro-metastasis and changes to the tumor micro-environment in a repeatable and quantitative manner. The blood brain barrier interface with the brain niche is composed of brain microvascular endothelial cells that are strengthened by basement membrane, astrocyte feet, and pericytes25. We selectively focused on the astrocyte and endothelial components given their importance in the formation and regulation of the blood brain barrier. We demonstrate how to fabricate, seed, image, and analyze the cancer cells and tumor micro-environment cellular and humoral components, using this platform. Finally, we show how machine learning can be used to identify the intrinsic phenotypic differences of cancer cells that are capable of transit through a model &#181;mBBN and to assign them an objective index of brain metastatic potential24. The data sets generated by this method can be used to answer basic and translational questions about metastasis, therapeutic strategies, and the role of the TME in both.

<table><tbody><tr><td>0.25% Trypsin-EDTA with phenol red</td><td>Thermo Fisher Scientific</td><td>25200056</td><td></td></tr><tr><td>1.5 mm biopsy punch with plunger</td><td>Integra LifeSciences Corporation</td><td>33-31A-P/25</td><td></td></tr><tr><td>10x MEM</td><td>Thermo Fisher Scientific</td><td>11430030</td><td></td></tr><tr><td>150 mm petri dishes</td><td>Fisher Scientific</td><td>FB0875714</td><td></td></tr><tr><td>1x DPBS, without Ca and Mg</td><td>Thermo Fisher Scientific</td><td>14190144</td><td></td></tr><tr><td>200uL pipette tip</td><td>Fisher Scientific</td><td>02-707-411</td><td></td></tr><tr><td>4 inch silicon wafer</td><td>University Wafer</td><td>452</td><td></td></tr><tr><td>48 mm wide packing tape</td><td>Fisher Scientific</td><td>19-072-097</td><td></td></tr><tr><td>50 x 75 mm glass slide</td><td>Fisher Scientific</td><td>12-550C</td><td></td></tr><tr><td>A1 confocal microscope</td><td>Nikon</td><td></td><td></td></tr><tr><td>acetone</td><td>Fisher Scientific</td><td>A9-20</td><td></td></tr><tr><td>antibiotic/antimycotic (penicillin/streptomycin/amphotericin)</td><td>Gibco</td><td>15240062</td><td></td></tr><tr><td>box cutter blade</td><td>Fisher Scientific</td><td>NC1721575</td><td></td></tr><tr><td>dissection scissors</td><td>Fisher Scientific</td><td>08-951-5</td><td></td></tr><tr><td>DMEM with 4.5 g/L glucose</td><td>Thermo Fisher Scientific</td><td>11960-044</td><td></td></tr><tr><td>double sided tape</td><td>Fisher Scientific</td><td>NC0879005</td><td></td></tr><tr><td>EGM-2</td><td>Lonza</td><td>CC-3162</td><td></td></tr><tr><td>Fetal Bovine Serum, Heat inactivated</td><td>Corning</td><td>MT35011CV</td><td></td></tr><tr><td>Fiji software</td><td>ImageJ</td><td></td><td></td></tr><tr><td>glass vial</td><td>Fisher Scientific</td><td>03-341-25D</td><td></td></tr><tr><td>glutamax</td><td>Thermo Fisher Scientific</td><td>35050061</td><td></td></tr><tr><td>hCMEC/D3</td><td>EMD Millipore</td><td>SCC066</td><td></td></tr><tr><td>Jupyter notebook</td><td>Anaconda</td><td></td><td></td></tr><tr><td>L-glutamine</td><td>Thermo Fisher Scientific</td><td>25030081</td><td></td></tr><tr><td>Matrigel - growth factor reduced with phenol red</td><td>Corning</td><td>CB-40230A</td><td></td></tr><tr><td>MDA-MB-231</td><td>ATCC</td><td>HTB-26</td><td></td></tr><tr><td>MDA-MB-231-BR-GFP</td><td>Dr. Patricia Steeg, NIH</td><td></td><td></td></tr><tr><td>N-2 growth supplement</td><td>Thermo Fisher Scientific</td><td>17502048</td><td></td></tr><tr><td>normal human astrocytes (NHA)</td><td>Lonza</td><td>CC-2565</td><td></td></tr><tr><td>Orange software</td><td>University of Ljubljana</td><td></td><td></td></tr><tr><td>Pasteur pipette</td><td>Fisher Scientific</td><td>13-711-9AM</td><td></td></tr><tr><td>Photolithography masks</td><td>Photosciences Incorporated</td><td></td><td></td></tr><tr><td>pLL3.7-dsRed</td><td>University of Michigan Vector Core</td><td></td><td></td></tr><tr><td>pLL-EV-GFP</td><td>University of Michigan Vector Core</td><td></td><td></td></tr><tr><td>pLOX-TERT-iresTK</td><td>Addgene</td><td>12245</td><td></td></tr><tr><td>pMD2.G</td><td>Addgene</td><td>12259</td><td></td></tr><tr><td>polycarbonate membrane, 5um pore size</td><td>Millipore</td><td>TMTP04700</td><td></td></tr><tr><td>psPAX2</td><td>Addgene</td><td>12260</td><td></td></tr><tr><td>PureCol, 3 mg/mL</td><td>Advanced Biomatrix</td><td>5005</td><td>Type I bovine collagen</td></tr><tr><td>sodium bicarbonate</td><td>Thermo Fisher Scientific</td><td>25080094</td><td></td></tr><tr><td>sodium pyruvate</td><td>Thermo Fisher Scientific</td><td>11360070</td><td></td></tr><tr><td>Solo cup</td><td>Fisher Scientific</td><td>NC1416545</td><td></td></tr><tr><td>SU-8 2075</td><td>MicroChem Corporation</td><td>Y111074 0500L1GL</td><td></td></tr><tr><td>SU8 developer</td><td>MicroChem Corporation</td><td>Y020100 4000L1PE</td><td></td></tr><tr><td>Sylgard 184</td><td>Ellsworth Adhesive Company</td><td>NC0162601</td><td></td></tr><tr><td>Toluene</td><td>Sigma-Aldrich</td><td>179965-1L</td><td></td></tr><tr><td>Tricholoro perfluoro octyl silane</td><td>Sigma-Aldrich</td><td>448931-10G</td><td></td></tr></tbody></table>

quantifying the brain metastatic tumor micro-environment using an organ-on-a chip 3d model, machine learning, and confocal tomography

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translational knowledge need to be addressed. Major challenges include a paucity of reproducible preclinical models and associated tools. Three-dimensional models of brain metastasis can yield the relevant molecular and phenotypic data used to address these needs when combined with dedicated analysis tools. Moreover, compared to murine models, organ-on-a-chip models of patient tumor cells traversing the blood brain barrier into the brain microenvironment generate results rapidly and are more interpretable with quantitative methods, thus amenable to high throughput testing. Here we describe and demonstrate the use of a novel 3D microfluidic blood brain niche (&#181;mBBN) platform where multiple elements of the niche can be cultured for an extended period (several days), fluorescently imaged by confocal microscopy, and the images reconstructed using an innovative confocal tomography technique; all aimed to understand the development of micro-metastasis and changes to the tumor micro-environment (TME) in a repeatable and quantitative manner. We demonstrate how to fabricate, seed, image, and analyze the cancer cells and TME cellular and humoral components, using this platform. Moreover, we show how artificial intelligence (AI) is used to identify the intrinsic phenotypic differences of cancer cells that are capable of transit through a model &#181;mBBN and to assign them an objective index of brain metastatic potential. The data sets generated by this method can be used to answer basic and translational questions about metastasis, the efficacy of therapeutic strategies, and the role of the TME in both.

Using this technique, we analyzed cell types labeled with different fluorescent proteins or dyes. We demonstrate the use of this approach with a &#181;mBBN chip formulated with hCMEC/D3-DsRed and non-fluorescent astrocytes. The brain microvascular endothelial cells were seeded onto a porous membrane (5 &#181;m track etched pores) and placed in an incubator34 at 37 &#176;C under 5% CO2. After three days the confluency of the endothelial layer was confirmed via microscopy and then cancer ...

Watch this Scientific Journal Video about Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography at JoVE.com

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Here, we present a protocol for preparing and culturing a blood brain barrier metastatic tumor micro-environment and then quantifying its state using confocal imaging and artificial intelligence (machine learning).

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, ...

quantifying-brain-metastatic-tumor-micro-environment-using-an-organ

Research

JoVE Journal

Cancer Research

7.2K Views.  University of Michigan Ann Arbor. Confocale tomografie werd ontwikkeld om het volledige gamma van kankercelgedrag te verkrijgen, omdat ze interageren met de cellulaire barrière en niche. Deze methode biedt een basis voor het bestuderen van uitzaaiingen als ze zich voordoen. Deze aanpak is handig voor het kwantificeren van levend celgedrag.Confocale tomografie, in combinatie met machine learning, is nuttig voor een verscheidenheid van organ-on-a-chip platforms. Het analyseren van primaire of terugkerende tumor of circu...

Video: Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

MAME Models for 4D Live-cell Imaging of Tumor: Microenvironment Interactions that Impact Malignant Progression

We have developed 3D coculture models, which we term MAME (mammary architecture and microenvironment engineering), and used them for live-cell imaging in real-time of cell:cell interactions. Our overall goal was to develop models that recapitulate the architecture of preinvasive breast lesions to study their progression to an invasive phenotype. Specifically, we developed models to analyze interactions among pre-malignant breast epithelial cell variants and other cell types of the tumor microenvironment that have been implicated in enhancing or reducing the progression of preinvasive breast epithelial cells to invasive ductal carcinomas. Other cell types studied to date are myoepithelial cells, fibroblasts, macrophages and blood and lymphatic microvascular endothelial cells. In addition to the MAME models, which are designed to recapitulate the cellular interactions within the breast during cancer progression, we have developed comparable models for the progression of prostate cancers. 
Here we illustrate the procedures for establishing the 3D cocultures along with the use of live-cell imaging and a functional proteolysis assay to follow the transition of cocultures of breast ductal carcinoma in situ (DCIS) cells and fibroblasts to an invasive phenotype over time, in this case over twenty-three days in culture. The MAME cocultures consist of multiple layers. Fibroblasts are embedded in the bottom layer of type I collagen. On that is placed a layer of reconstituted basement membrane (rBM) on which DCIS cells are seeded. A final top layer of 2% rBM is included and replenished with every change of media. To image proteolysis associated with the progression to an invasive phenotype, we use dye-quenched (DQ) fluorescent matrix proteins (DQ-collagen I mixed with the layer of collagen I and DQ-collagen IV mixed with the middle layer of rBM) and observe live cultures using confocal microscopy. Optical sections are captured, processed and reconstructed in 3D with Volocity visualization software. Over the course of 23 days in MAME cocultures, the DCIS cells proliferate and coalesce into large invasive structures. Fibroblasts migrate and become incorporated into these invasive structures. Fluorescent proteolytic fragments of the collagens are found in association with the surface of DCIS structures, intracellularly, and also dispersed throughout the surrounding matrix. Drugs that target proteolytic, chemokine/cytokine and kinase pathways or modifications in the cellular composition of the cocultures can reduce the invasiveness, suggesting that MAME models can be used as preclinical screens for novel therapeutic approaches.

We have developed 3D coculture models for live-cell imaging in real-time of interactions among breast tumor cells and other cells in their microenvironment that impact progression to an invasive phenotype. These models can serve as preclinical screens for drugs to target paracrine-induced proteolytic, chemokine/cytokine and kinase pathways implicated in invasiveness.

We have developed 3D coculture models, which we term MAME (mammary architecture and microenvironment engineering), and used them for live-cell imaging in ...

Medicine

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less aggressive breast tumors, the 5-year survival rate of TNBC patients is 77% due to their characteristic drug-resistant phenotype and metastatic burden. Toward this end, murine models have been established aimed at identifying novel therapeutic strategies limiting TNBC tumor growth and metastatic spread. This work describes a practical guide for the TNBC orthotopic model where MDA-MB-231 breast cancer cells suspended in a basement membrane matrix are implanted in the fourth mammary fat pad, which closely mimics the cancer cell behavior in humans. Measurement of tumors by caliper, lung metastasis assessment via in vivo and ex vivo imaging, and molecular detection are discussed. This model provides an excellent platform to study therapeutic efficacy and is especially suitable for the study of the interaction between the primary tumor and distal metastatic sites.

This work presets an advanced protocol to accurately assess tumor loading by detection of green fluorescent protein and bioluminescence signals as well as the integration of quantitative molecular detection technique.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less ...

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Metastatic spread of cancer is an unfortunate consequence of disease progression, aggressive cancer subtypes, and/or late diagnosis. Brain metastases are particularly devastating, difficult to treat, and confer a poor prognosis. While the precise incidence of brain metastases in the United States remains hard to estimate, it is likely to increase as extracranial therapies continue to become more efficacious in treating cancer. Thus, it is necessary to identify and develop novel therapeutic approaches to treat metastasis at this site. To this end, intracranial injection of cancer cells has become a well-established method in which to model brain metastasis. Previously, the inability to directly measure tumor growth has been a technical hindrance to this model; however, increasing availability and quality of small animal imaging modalities, such as magnetic resonance imaging (MRI), are vastly improving the ability to monitor tumor growth over time and infer changes within the brain during the experimental period. Herein, intracranial injection of murine mammary tumor cells into immunocompetent mice followed by MRI is demonstrated. The presented injection approach utilizes isoflurane anesthesia and a stereotactic setup with a digitally controlled, automated drill and needle injection to enhance precision, and reduce technical error. MRI is measured over time using a 9.4 Tesla instrument in The Ohio State University James Comprehensive Cancer Center Small Animal Imaging Shared Resource. Tumor volume measurements are demonstrated at each time point through use of ImageJ. Overall, this intracranial injection approach allows for precise injection, day-to-day monitoring, and accurate tumor volume measurements, which combined greatly enhance the utility of this model system to test novel hypotheses on the drivers of brain metastases.

Intracranial brain metastasis modeling is complicated by an inability to monitor tumor size and response to treatment with precise and timely methods. The presented methodology couples intracranial tumor injection with magnetic resonance imaging analysis, which when combined, cultivates precise and consistent injections, enhanced animal monitoring, and accurate tumor volume measurements.

Metastatic spread of cancer is an unfortunate consequence of disease progression, aggressive cancer subtypes, and/or late diagnosis. Brain metastases are ...

Modeling Brain Metastasis Via Tail-Vein Injection of Inflammatory Breast Cancer Cells

Metastatic spread to the brain is a common and devastating manifestation of many types of cancer. In the United States alone, about 200,000 patients are diagnosed with brain metastases each year. Significant progress has been made in improving survival outcomes for patients with primary breast cancer and systemic malignancies; however, the dismal prognosis for patients with clinical brain metastases highlights the urgent need to develop novel therapeutic agents and strategies against this deadly disease. The lack of suitable experimental models has been one of the major hurdles impeding advancement of our understanding of brain metastasis biology and treatment. Herein, we describe a xenograft mouse model of brain metastasis generated via tail-vein injection of an endogenously HER2-amplified cell line derived from inflammatory breast cancer (IBC), a rare and aggressive form of breast cancer. Cells were labeled with firefly luciferase and green fluorescence protein to monitor brain metastasis, and quantified metastatic burden by bioluminescence imaging, fluorescent stereomicroscopy, and histologic evaluation. Mice robustly and consistently develop brain metastases, allowing investigation of key mediators in the metastatic process and the development of preclinical testing of new treatment strategies.

We describe a xenograft mouse model of breast cancer brain metastasis generated via tail-vein injection of an endogenously HER2-amplified inflammatory breast cancer cell line.

Metastatic spread to the brain is a common and devastating manifestation of many types of cancer. In the United States alone, about 200,000 patients are ...

Coculture System with an Organotypic Brain Slice and 3D Spheroid of Carcinoma Cells

Patients with cerebral metastasis of carcinomas have a poor prognosis. However, the process at the metastatic site has barely been investigated, in particular the role of the resident (stromal) cells. Studies in primary carcinomas demonstrate the influence of the microenvironment on metastasis, even on prognosis1,2. Especially the tumor associated macrophages (TAM) support migration, invasion and proliferation3. Interestingly, the major target sites of metastasis possess tissue-specific macrophages, such as Kupffer cells in the liver or microglia in the CNS. Moreover, the metastatic sites also possess other tissue-specific cells, like astrocytes. Recently, astrocytes were demonstrated to foster proliferation and persistence of cancer cells4,5. Therefore, functions of these tissue-specific cell types seem to be very important in the process of brain metastasis6,7.
Despite these observations, however, up to now there is no suitable in vivo/in vitro model available to directly visualize glial reactions during cerebral metastasis formation, in particular by bright field microscopy. Recent in vivo live imaging of carcinoma cells demonstrated their cerebral colonization behavior8. However, this method is very laborious, costly and technically complex. In addition, these kinds of animal experiments are restricted to small series and come with a substantial stress for the animals (by implantation of the glass plate, injection of tumor cells, repetitive anaesthesia and long-term fixation). Furthermore, in vivo imaging is thus far limited to the visualization of the carcinoma cells, whereas interactions with resident cells have not yet been illustrated. Finally, investigations of human carcinoma cells within immunocompetent animals are impossible8.
For these reasons, we established a coculture system consisting of an organotypic mouse brain slice and epithelial cells embedded in matrigel (3D cell sphere). The 3D carcinoma cell spheres were placed directly next to the brain slice edge in order to investigate the invasion of the neighboring brain tissue. This enables us to visualize morphological changes and interactions between the glial cells and carcinoma cells by fluorescence and even by bright field microscopy. After the coculture experiment, the brain tissue or the 3D cell spheroids can be collected and used for further molecular analyses (e.g. qRT-PCR, IHC, or immunoblot) as well as for investigations by confocal microscopy. This method can be applied to monitor the events within a living brain tissue for days without deleterious effects to the brain slices. The model also allows selective suppression and replacement of resident cells by cells from a donor tissue to determine the distinct impact of a given genotype. Finally, the coculture model is a practicable alternative to in vivo approaches when testing targeted pharmacological manipulations.

The organotypic brain slice coculture with carcinoma cells enables visualizing morphological changes by fluorescence as well as bright field (video) microscopy during the process of carcinoma cell invasion of brain tissue. This model system also allows for cell exchange and replenishment approaches and offers a wide variety of manipulations and analyses.

Patients with cerebral metastasis of carcinomas have a poor prognosis. However, the process at the metastatic site has barely been investigated, in ...

Ultrasound Imaging-guided Intracardiac Injection to Develop a Mouse Model of Breast Cancer Brain Metastases Followed by Longitudinal MRI

Breast cancer brain metastasis, occurring in 30% of breast cancer patients at stage IV, is associated with high mortality. The median survival is only 6 months. It is critical to have suitable animal models to mimic the hemodynamic spread of the metastatic cells in the clinical scenario. Here, we are introducing the use of small animal ultrasound imaging to guide an accurate injection of brain tropical breast cancer cells into the left ventricle of athymic nude mice. Longitudinal MRI is used to assessing intracranial initiation and growth of brain metastases. Ultrasound-guided intracardiac injection ensures not only an accurate injection and hereby a higher successful rate but also significantly decreased mortality rate, as compared to our previous manual procedure. In vivo high resolution MRI allows the visualization of hyperintense multifocal lesions, as small as 310 &#181;m in diameter on T2-weighted images at 3 weeks post injection. Follow-up MRI reveals intracranial tumor growth and increased number of metastases that distribute throughout the whole brain.

A breast cancer brain metastasis mouse model is established with ultrasound imaging-guided intracardiac injection of MDA-MB231/Br-GFP cells. Development of multifocal intracranial metastases has been monitored longitudinally using high-resolution 9.4 T MRI.

Breast cancer brain metastasis, occurring in 30% of breast cancer patients at stage IV, is associated with high mortality. The median survival is only 6 ...

Modeling Brain Metastasis by Internal Carotid Artery Injection of Cancer Cells

Brain metastasis is a cause of severe morbidity and mortality in cancer patients. Critical aspects of metastatic diseases, such as the complex neural microenvironment and stromal cell interaction, cannot be entirely replicated with in vitro assays; thus, animal models are critical for investigating and understanding the effects of therapeutic intervention. However, most brain tumor xenografting methods do not produce brain metastases consistently in terms of the time frame and tumor burden. Brain metastasis models generated by intracardiac injection of cancer cells can result in unintended extracranial tumor burden and lead to non-brain metastatic morbidity and mortality. Although intracranial injection of cancer cells can limit extracranial tumor formation, it has several caveats, such as the injected cells frequently form a singular tumor mass at the injection site, high leptomeningeal involvement, and damage to brain vasculature during needle penetration. This protocol describes a mouse model of brain metastasis generated by internal carotid artery injection. This method produces intracranial tumors consistently without the involvement of other organs, enabling the evaluation of therapeutic agents for brain metastasis.

Brain metastasis is a cause of severe morbidity and mortality in cancer patients. Most brain metastasis mouse models are complicated by systemic metastases confounding analysis of mortality and therapeutic intervention outcomes. Presented here is a protocol for internal carotid injection of cancer cells that produces consistent intracranial tumors with minimal systemic tumors.

Brain metastasis is a cause of severe morbidity and mortality in cancer patients. Critical aspects of metastatic diseases, such as the complex neural ...

Preparing a Microfluidics-Based Vascularized Human Micro-Tumor Model

Establishing a Physiologic Human Vascularized Micro-Tumor Model for Cancer Research

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical cancer research and therapeutic development.&#160;To overcome this problem, we have developed the vascularized microtumor (VMT), or tumor chip, a microphysiological system that realistically models the complex human tumor microenvironment. The VMT forms de novo within a microfluidic platform by co-culture of multiple human cell types under dynamic, physiological flow conditions. This tissue-engineered micro-tumor construct incorporates a living perfused vascular network that supports the growing tumor mass just as newly formed vessels do in vivo. Importantly, drugs and immune cells must cross the endothelial layer to reach the tumor, modeling in vivo physiological barriers to therapeutic delivery and efficacy. Since the VMT platform is optically transparent, high-resolution imaging of dynamic processes such as immune cell extravasation and metastasis can be achieved with direct visualization of fluorescently labeled cells within the tissue. Further, the VMT retains in vivo tumor heterogeneity, gene expression signatures, and drug responses. Virtually any tumor type can be adapted to the platform, and primary cells from fresh surgical tissues grow and respond to drug treatment in the VMT, paving the way toward truly personalized medicine. Here, the methods for establishing the VMT and utilizing it for oncology research are outlined. This innovative approach opens new possibilities for studying tumors and drug responses, providing researchers with a powerful tool to advance cancer research.

Author Spotlight: Creating Human Vascularized Micro-Tumors as Models for Translational Cancer Research 

This protocol presents a physiologically relevant tumor-on-a-chip model to perform high-throughput basic and translational human cancer research, advancing drug screening, disease modeling, and personalized medicine approaches with a description of loading, maintenance, and evaluation procedures.

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical ...

A Brain Tumor/Organotypic Slice Co-culture System for Studying Tumor Microenvironment and Targeted Drug Therapies

Brain tumors are a major cause of cancer-related morbidity and mortality. Developing new therapeutics for these cancers is difficult, as many of these tumors are not easily grown in standard culture conditions. Neurosphere cultures under serum-free conditions and orthotopic xenografts have expanded the range of tumors that can be maintained. However, many types of brain tumors remain difficult to propagate or study. This is particularly true for pediatric brain tumors such as pilocytic astrocytomas and medulloblastomas. This protocol describes a system that allows primary human brain tumors to be grown in culture. This quantitative assay can be used to investigate the effect of microenvironment on tumor growth, and to test new drug therapies. This protocol describes a system where fluorescently labeled brain tumor cells are grown on an organotypic brain slice from a juvenile mouse. The response of tumor cells to drug treatments can be studied in this assay, by analyzing changes in the number of cells on the slice over time. In addition, this system can address the nature of the microenvironment that normally fosters growth of brain tumors. This brain tumor organotypic slice co-culture assay provides a propitious system for testing new drugs on human tumor cells within a brain microenvironment.

Many types of human brain tumors are localized to specific regions within the brain and are difficult to grow in culture. This protocol addresses the role of tumor microenvironment and investigates new drug treatments by analyzing fluorescent primary brain tumor cells growing in an organotypic mouse brain slice. &#160;

Brain tumors are a major cause of cancer-related morbidity and mortality. Developing new therapeutics for these cancers is difficult, as many of these ...

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise invisible processes. Advanced cell assays closely mimicking in vivo scenery are establishing themselves as novel ways to visualize and measure the bidirectional tumor-host interplay influencing the progression of cancer. Here we describe two versatile protocols to recreate highly controllable 2D and 3D co-cultures in microdevices, mimicking the complexity of the tumor microenvironment (TME), under natural and therapy-induced immunosurveillance. In section 1, an experimental setting is provided to monitor crosstalk between adherent tumor cells and floating immune populations, by bright field time-lapse microscopy. As an applicative scenario, we analyze the effects of anti-cancer treatments, such as the so-called immunogenic cancer cell death inducers on the recruitment and activation of immune cells. In section 2, 3D tumor-immune microenvironments are assembled in a competitive layout. Differential immune infiltration is monitored by fluorescence snapshots up to 72 h, to evaluate combination therapeutic strategies. In both settings, image processing steps are illustrated to extract a plethora of immune cell parameters (e.g., immune cell migration and interaction, response to therapeutic agents). These simple and powerful methods can be further tailored to simulate the complexity of the TME encompassing the heterogeneity and plasticity of cancer, stromal and immune cells subtypes, as well as their reciprocal interactions as drivers of cancer evolution. The compliance of these rapidly evolving technologies with live-cell high-content imaging can lead to the generation of large informative datasets, bringing forth new challenges. Indeed, the triangle &#39;&#39;co-cultures/microscopy/advanced data analysis&#34; sets the path towards a precise problem parametrization that may assist tailor-made therapeutic protocols. We expect that future integration of cancer-immune on-a-chip with artificial intelligence for high-throughput processing will synergize a large step forward in leveraging the capabilities as predictive and preclinical tools for precision and personalized oncology.

In the age of immunotherapy and single-cell genomic profiling, cancer biology requires novel in vitro and computational tools for investigating the tumor-immune interface in a proper spatiotemporal context. We describe protocols to exploit tumor-immune microfluidic co-cultures in 2D and 3D settings, compatible with dynamic, multiparametric monitoring of cellular functions.

Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise ...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

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