This research is supported by funding from CBCF (to ZW).

1. Preparing the Cells for Live Imaging
<ol>
	<li>Cell culture and seeding
	<ol>
		<li>Use MCF-7 breast cancer cells selected for resistance to docetaxel (MCF-7TXT) and their non-resistant parental cell line (MCF-7CC). The detailed selection process and the characterization of these selected cell lines were described previously24.</li>
		<li>Grow all cells in 10 cm culture dishes at 37 &#176;C in a medium composed 90% of Dulbecco&#39;s modified Eagle&#39;s medium (DMEM) and 10% of fetal bovine serum (FBS) and supplemented with non-essential amino acids. Maintain the medium in a 5% CO2 atmosphere. Maintain MCF-7TXT cells at 5 nM docetaxel.</li>
		<li>Seed cells on coverslips for live imaging. Sterilize 24 mm poly-L-lysine-coated glass coverslips by rinsing them with 70% alcohol and then exposing them to UV overnight. Place the coverslips into a 6-well culture plate of 35 mm. Place one coverslip in each well.</li>
		<li>Remove the medium from the 10-cm culture dish and wash the cells with PBS. Add 0.5 mL of trypsin-EDTA to the dish to detach the cells from the dish. Add 5 mL of culture medium to the dish to neutralize the trypsin following the detachment of the cells.</li>
		<li>Count the cells with a hemocytometer to determine the number of cell per unit volume.</li>
		<li>Add approximately 105 cells to each well based on the cell number per unit volume. After shaking it gently, put the plate back into the incubator to allow the cells to attach to the coverslips.</li>
	</ol>
	</li>
	<li>Expression of GFP-tagged &#945;-tubulin
	<ol>
		<li>To assay microtubule dynamics, transduce the cells with GFP-tagged &#945;-tubulin with the commercial GFP transduction control (e.g., BacMam) according to the manufacturer&#39;s protocol.</li>
		<li>Culture the cells in the well for 36 h in a 37 &#176;C cell culture incubator to allow complete adhesion and 60% confluence.</li>
		<li>Calculate the appropriate volume of GFP-tagged &#945;-tubulin to add to each well, according to the following equation: 
		<img alt="Equation" src="/files/ftp_upload/55027/55027eq1.jpg" /> 
		The number of cells is the estimated total number of cells in the well at the time of labeling and the desired PPC is the number of particles per cell. 
		&#8203;NOTE: Seeding the MCF-7 cells should have doubled the cell count from 105 to 2 x 105 with a desired PPC of 20, the volume needed for each coverslip is therefore 40 &#181;L. For different cells, the volume calculated based on the above formula may not be the best. The exact volume should be adjusted according to the actual expression level of GFP-tubulin.</li>
		<li>Mix the GFP-tagged &#945;-tubulin several times by inversion to ensure a homogenous solution. Do not vortex. 
		NOTE: For the control, the Null (control) reagent lacks any mammalian genetic elements and can be used to help determine potential baculovirus-mediated effects and background fluorescence. A non-targeted GFP transduction control may also be used, which will light up the entire cell.</li>
		<li>Replace the culture medium with fresh medium. Add 2 mL of the new medium and 40 &#181;L of GFP-tagged &#945;-tubulin to each well.</li>
		<li>Shake the plate gently to allow complete mixing of GFP-tagged &#945;-tubulin with the culture medium. Return the plate to the culture incubator and incubate for 24 h to allow the expression of GFP-tubulin.</li>
	</ol>
	</li>
	<li>Treat cells with docetaxel 
	NOTE: This experiment is to test the effect of docetaxel on microtubule dynamic instability. Thus, the cells are treated with the desired concentration of docetaxel.
	<ol>
		<li>Prepare a medium composed 90% of DMEM and 10% of FBS and supplemented with non-essential amino acids. Use DMEM without phenol red because phenol red may interfere with the fluorescence of GFP-tubulin. Add the desired concentration of docetaxel (ranging from 10 nM to 10 &#181;M). The stock solution of docetaxel is 10 mM in dimethyl sulfoxide (DMSO).</li>
		<li>Pre-warm the docetaxel-containing medium to 37 &#176;C in the tissue culture incubator.</li>
		<li>Replace the normal culture medium with the docetaxel-containing medium and incubate for 30 min in the tissue culture incubator. There should be at least 3 coverslips per well for each docetaxel concentration.</li>
	</ol>
	</li>
</ol>
2. Live Imaging to Examine Microtubule Dynamic Instability
<ol>
	<li>Setting up the system
	<ol>
		<li>Perform experiments in a chamber maintained at 37 &#176;C and 5% CO2. Acquire fluorescence images by time lapse with a microscopic system equipped with a 60X, 1.42 NA oil objective lens on an inverted fluorescence microscope and with a CCD camera.</li>
		<li>Set up the cells for live imaging. Pre-warm both the sample holder and the medium to 37 &#176;C. Choose a coverslip to examine. Mount the coverslip of interest on a sample holder and incubate it with 1 mL of the docetaxel-containing medium prepared in step 1.3.1.</li>
	</ol>
	</li>
	<li>Live imaging of microtubule dynamic instability
	<ol>
		<li>Identify the cells that will be used for imaging. They should be flat, have a high fluorescence intensity of expressed GFP-tubulin, and have clear microtubule structures.</li>
		<li>Choose one cell from the group of identified cells from step 2.2.1 to examine first. Focus on the peripheral area of the identified cell. Set up the program for exposure time and the frequency of image acquisition. As exposure time is usually 0.5 s, the images will be acquired every two s.</li>
		<li>Allow an additional 20 min for the steps from 1.33 to 2.2.3. Thus,exactly 50 min after the addition of docetaxel, as described in step 1.3.3, start imaging (this is for standardization).</li>
		<li>Record the microtubule dynamics for 2 min, taking a photo every 2 s. In total, acquire 60 images for the identified cell.</li>
		<li>Move to the next identified cell and repeat steps 2.2.2 to 2.2.4. Repeat the procedure until 5 cells have been imaged. It is imperative to do this before the time reaches 70 min after the addition of docetaxel, as described in step 1.3.3.</li>
		<li>For each treatment condition, repeat steps 2.2.1 to 2.2.5 for 3 different coverslips. In total, image 15 cells, which is enough data to measure microtubule dynamic instability.</li>
	</ol>
	</li>
</ol>
3. Image Processing and Data Analysis
<ol>
	<li>Deconvolution of images
	<ol>
		<li>Deconvolve the acquired images to achieve a high quality. Open the deconvolution program equipped with the microscope system.</li>
		<li>Click &#34;Process&#34; and select &#34;Deconvolve.&#34; Drag the image file to the &#34;Input&#34; window and click &#34;Do.&#34; The image file will be deconvolved, and the deconvolved file will be saved as a new file automatically.</li>
	</ol>
	</li>
	<li>Generation of videos
	<ol>
		<li>Click the deconvolved image file to open with equipped software.</li>
		<li>Click &#34;File&#34; and select &#34;Save as movie.&#34; Select the &#34;Movie format&#34; as &#34;AV&#34; and the &#34;Animation style&#34; as &#34;Forward.&#34; Set the &#34;Compression quality&#34; to &#34;100%&#34; and the &#34;Frame rate&#34; to &#34;5/second.&#34;</li>
		<li>Check the box of &#34;Animate through time&#34; and click &#34;Do it.&#34; The video will be generated.</li>
	</ol>
	</li>
	<li>Measurement of microtubule shortening and growth rate
	<ol>
		<li>Identify the microtubules that will be used for measurement. For each cell, only a few microtubules will be able to have their shortening or growth followed clearly and completely.</li>
		<li>Examine each frame of the video to identify the frame that shows the starting length of the microtubule and the frame with the most extended or shortened microtubule. Measure the change in length between the two microtubules and the time elapsed between the two frames.</li>
		<li>Calculate the rate of growth or shortening by dividing the change in length by time (the unit is &#181;m/s). For each treatment condition, follow at least 10 cells and measure at least 20 microtubules.</li>
		<li>Calculate the average and the standard error for each treatment condition. Analyze the statistical difference between the conditions using the Student test. Report the data in a table and/or in a chart.</li>
	</ol>
	</li>
</ol>

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The authors declare that they have no competing financial interests.

There are two major methods to measure microtubule dynamic instability: in vitro and in vivo. In the in vitro method, purified tubulin is used to measure microtubule dynamic instability with computer-enhanced time-lapse differential interference-contrast microscopy. In the in vivo method, microinjected fluorescent tubulin, or expressed GFP-tubulin, is incorporated into microtubules. The dynamics (growth and shortening) of the microtubules is then recorded by time-lapse using a sensitiv...

The leading cause of breast cancer mortality is through metastasis1,2. Taxanes, such as docetaxel and paclitaxel, are currently used as first-line regimens in the treatment of metastatic breast cancer2,3,4,5,6. They are part of a group of microtubule-targeting agents (MTAs) that disrupt microtubule dynamics. However, one of the greatest challenges to using taxanes in curative therapy is the development of taxane resistance in cancer cells, which leads to disease recurrence7. Drug resistance accounts for more than 90% of all deaths among patients with metastatic breast cancer7.
Microtubules are formed by the polymerization of &#945;- and &#946;-tubulin heterodimers8,9. The precise regulation of microtubule dynamics is important for many cellular functions, including cell polarization, cell cycle progression, intracellular transport, and cell signaling. Dysregulation of microtubules and their dynamics will disrupt cell function and result in cell death10,11. Depending on how they cause this dysregulation, MTA drugs can be classified as either microtubule stabilizing agents (i.e., taxanes) or microtubule-destabalizing agents (i.e., vinca alkaloids or colchicine-site binding agents)20. Despite their opposite effects on microtubule mass, at a sufficient dosage, both classes can kill cancer cells through their effects on microtubule dynamics21.
Taxanes function primarily by stabilizing the microtubule spindle12, leading to chromosomal misalignment. The subsequent perpetual activation of the spindle assembly checkpoint (SAC) arrests the cell in mitosis. Prolonged mitotic arrest then causes apoptosis13,14. Taxane interacts with microtubules through the taxane binding site on &#946;-tubulin8,15, which is only present in assembled tubulin16.
Multiple mechanisms for taxane resistance have been proposed9,17. These mechanisms include both general multidrug resistance due to the overexpression of drug-efflux proteins and taxane-specific resistance5,9,18,19. For example, taxane-resistant cancer cells may have altered expression and function of certain &#946;-tubulin isotypes5,9,19,20,21,22,23. By using an in vivo method to measure microtubule dynamic instability, we show that, when compared to non-resistant, parental MCF-7CC cells17, the microtubule dynamics of docetaxel-resistant MCF-7TXT cells are insensitive to docetaxel treatment.
To better understand the function of MTAs and the exact mechanism of taxane-resistance in cancerous cells, it is essential to measure microtubule dynamics. Here, we report an in vivo method of doing so. By using live imaging in combination with the expression of GFP-tagged tubulin in cells, we can measure the microtubule dynamics of MCF-7TXT and MCF-7CC cells with and without docetaxel treatment. The results can help us design more effective drugs that can overcome taxane resistance.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Dulbecco&#39;s Modified Eagle&#39;s Medium (DMEM)</td>
			<td>Sigma-Aldrich</td>
			<td>D5796</td>
			<td></td>
		</tr>
		<tr>
			<td>Non-essential amino acids</td>
			<td>Life Technologies, Invitrogen</td>
			<td>11140-050</td>
			<td></td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>Gibco, Invitrogen</td>
			<td>12483</td>
			<td></td>
		</tr>
		<tr>
			<td>Anti-Anti (100x)</td>
			<td>Life Technologies, Invitrogen</td>
			<td>15240-062</td>
			<td></td>
		</tr>
		<tr>
			<td>docetaxel</td>
			<td>Sigma-Aldrich</td>
			<td>01885-5mg-F</td>
			<td></td>
		</tr>
		<tr>
			<td>DMEM phenol red-free</td>
			<td>Gibco, Invitrogen</td>
			<td>21063</td>
			<td></td>
		</tr>
		<tr>
			<td>CellLight Reagent *BacMam 2.0* GFP-tubulin</td>
			<td>ThermoFisher Scientific</td>
			<td>C10613</td>
			<td>Key reagent for expressing GFP tubulin in cells</td>
		</tr>
		<tr>
			<td>CellLight Reagent *BacMam 2.0* GFP</td>
			<td>ThermoFisher Scientific</td>
			<td>B10383</td>
			<td>Control</td>
		</tr>
		<tr>
			<td>Dimethyl Sulfoxide (DMSO)</td>
			<td>Sigma-Aldrich+B9:AA9</td>
			<td>472301</td>
			<td>for dissoving decetaxel</td>
		</tr>
		<tr>
			<td>22-mm glass coveslip</td>
			<td>Fisher Scientifics</td>
			<td>12-545-101</td>
			<td></td>
		</tr>
		<tr>
			<td>6-well culture plate</td>
			<td>Greiner Bio-One International</td>
			<td>6 Well Celi Culture Plate</td>
			<td></td>
		</tr>
		<tr>
			<td>DeltaVision Microscopy Imaging Systems</td>
			<td>GE Health</td>
			<td></td>
			<td>This system is equipped with weather station for controlling temperature and CO2. It also equipped with Worx Software for deconvolution and time lapse control.</td>
		</tr>
		<tr>
			<td>Trypsin-EDTA (0.25%), phenol red</td>
			<td>ThermoFisher Scientific</td>
			<td>25200056</td>
			<td></td>
		</tr>
		<tr>
			<td>Bright-Line Hemacytometer Set, Hausser Scientific</td>
			<td>Hausser Scientific, Distributed by VWR</td>
			<td>Supplier No.: 1492 VWR No.:15170-172</td>
			<td></td>
		</tr>
	</tbody>
</table>

live imaging to study microtubule dynamic instability in taxane-resistant breast cancers

Taxanes such as docetaxel belong to a group of microtubule-targeting agents (MTAs) that are commonly relied upon to treat cancer. However, taxane resistance in cancerous cells drastically reduces the effectiveness of the drugs' long-term usage. Accumulated evidence suggests that the mechanisms underlying taxane resistance include both general mechanisms, such as the development of multidrug resistance due to the overexpression of drug-efflux proteins, and taxane-specific mechanisms, such as those that involve microtubule dynamics. 
Because taxanes target cell microtubules, measuring microtubule dynamic instability is an important step in determining the mechanisms of taxane resistance and provides insight into how to overcome this resistance. In the experiment, an in vivo method was used to measure microtubule dynamic instability. GFP-tagged &#945;-tubulin was expressed and incorporated into microtubules in MCF-7 cells, allowing for the recording of the microtubule dynamics by time lapse using a sensitive camera. The results showed that, as opposed to the non-resistant parental MCF-7CC cells, the microtubule dynamics of docetaxel-resistant MCF-7TXT cells are insensitive to docetaxel treatment, which causes the resistance to docetaxel-induced mitotic arrest and apoptosis. This paper will outline this in vivo method of measuring microtubule dynamic instability.

Using the protocol presented here, we studied the effects of docetaxel on the microtubule dynamics of normal (MCF-7CC) and docetaxel-resistant (MCF-7TXT) breast cancer cells. Two sets of images show the effects of docetaxel (0.5 &#181;M) on microtubule growth and shortening in MCF-7CC and MCF-7TXT cells (Figure 1A).
We also calculated the rate of microtubule growth or ...

Watch this Scientific Journal Video about Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers at JoVE.com

Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers

In this paper, we report a protocol describing an in vivo method to measure microtubule dynamic instability in docetaxel-resistant breast cancer cells (MCF-7TXT). In this method, a deconvolution microscopy imaging system is used to detect the expression of GFP-tubulin in target cells.

Taxanes such as docetaxel belong to a group of microtubule-targeting agents (MTAs) that are commonly relied upon to treat cancer. However, taxane ...

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7.5K Views.  University of Alberta. In this paper, we report a protocol describing an in vivo method to measure microtubule dynamic instability in docetaxel-resistant breast cancer cells (MCF-7TXT). In this method, a deconvolution microscopy imaging system is used to detect the expression of GFP-tubulin in target cells. 

Video: Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials.
Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Identifying novel drug targets that transition from pre-clinical testing to human trials is a scientific priority. To that end, here we describe a functional genomics approach for examining the impact of gene depletion on cancer cell line spheroids, which more appropriately model human cancers in vivo.

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery ...

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast cancer metastasis, and results in poor outcomes with median survival rates of only 4.8 - 15 months. Current rodent models of breast cancer metastasis, including primary tumor cell xenograft and spontaneous tumor models, rarely metastasize to the liver. Intracardiac and intrasplenic injection models do result in liver metastases, however these models can be confounded by concomitant secondary-site metastasis, or by compromised immunity due to removal of the spleen to avoid tumor growth at the injection site. To address the need for improved liver metastasis models, a murine portal vein injection method that delivers tumor cells firstly and directly to the liver was developed. This model delivers tumor cells to the liver without complications of concurrent metastases in other organs or removal of the spleen. The optimized portal vein protocol employs small injection volumes of 5 - 10 &#956;l, &#8805; 32 gauge needles, and hemostatic gauze at the injection site to control for blood loss. The portal vein injection approach in Balb/c female mice using three syngeneic mammary tumor lines of varying metastatic potential was tested; high-metastatic 4T1 cells, moderate-metastatic D2A1 cells, and low-metastatic D2.OR cells. Concentrations of &#8804; 10,000 cells/injection results in a latency of ~ 20 - 40 days for development of liver metastases with the higher metastatic 4T1 and D2A1 lines, and &#62; 55 days for the less aggressive D2.OR line. This model represents an important tool to study breast cancer metastasis to the liver, and may be applicable to other cancers that frequently metastasize to the liver including colorectal and pancreatic adenocarcinomas.

A surgical procedure was developed to deliver mammary tumor cells to the murine liver via portal vein injection. This model permits investigation of late stages of liver metastasis in a fully immune competent host, including tumor cell extravasation, seeding, survival, and metastatic outgrowth in the liver.

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast ...

Live-imaging of Breast Epithelial Cell Migration After the Transient Depletion of TIP60

The wound-healing assay is efficient and one of the most economical ways to study cell migration in vitro. Conventionally, images are taken at the beginning and end of an experiment using a phase-contrast microscope, and the migration abilities of cells are evaluated by the closure of wounds. However, cell movement is a dynamic phenomenon, and a conventional method does not allow for tracking single-cell movement. To improve current wound-healing assays, we use live-cell imaging techniques to monitor cell migration in real time. This method allows us to determine the cell migration rate based on a cell tracking system and provides a clearer distinction between cell migration and cell proliferation. Here, we demonstrate the use of live-cell imaging in wound-healing assays to study the different migration abilities of breast epithelial cells influenced by the presence of TIP60. As cell motility is highly dynamic, our method provides more insights into the processes of wound healing than a snapshot of wound closure taken with the traditional imaging techniques used for wound-healing assays.

Here, we present the real-time monitoring of cell migration in a wound-healing assay using TIP60-depleted MCF10A breast epithelial cells. The implementation of live-cell imaging techniques in our protocol allows us to analyze and visualize single-cell movement in real time and across time.

The wound-healing assay is efficient and one of the most economical ways to study cell migration in vitro. Conventionally, images are taken at the ...

Long-term Live-cell Imaging to Assess Cell Fate in Response to Paclitaxel

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over the past decade, new and innovative technologies have greatly enhanced the practicality of live-cell imaging. Cells can now be kept in focus and continuously imaged over several days while maintained under 37 &#176;C and 5% CO2 cell culture conditions. Moreover, multiple fields of view representing different experimental conditions can be acquired simultaneously, thus providing high-throughput experimental data. Live-cell imaging provides a significant advantage over fixed-cell imaging by allowing for the direct visualization and temporal quantitation of dynamic cellular events. Live-cell imaging can also identify variation in the behavior of single cells that would otherwise have been missed using population-based assays. Here, we describe live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel. We demonstrate methods to visualize whether mitotically arrested cells die directly from mitosis or slip back into interphase. We also describe how the fluorescent ubiquitination-based cell cycle indicator (FUCCI) system can be used to assess the fraction of interphase cells born from mitotic slippage that are capable of re-entering the cell cycle. Finally, we describe a live-cell imaging method to identify nuclear envelope rupture events.

Live-cell imaging provides a wealth of information on single cells or whole populations that is unattainable by fixed cell imaging alone. Here, live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel are described.

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over ...

Live-Cell Imaging Assays to Study Glioblastoma Brain Tumor Stem Cell Migration and Invasion

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include rapid proliferation and pervasive invasion into the normal brain. Recurrence is thought to result from the presence of radio- and chemo-resistant brain tumor stem cells (BTSCs) that invade away from the initial cancerous mass and, thus, evade surgical resection. Hence, therapies that target BTSCs and their invasive abilities may improve the otherwise poor prognosis of this disease. Our group and others have successfully established and characterized BTSC cultures from GBM patient samples. These BTSC cultures demonstrate fundamental cancer stem cell properties such as clonogenic self-renewal, multi-lineage differentiation, and tumor initiation in immune-deficient mice. In order to improve on the current therapeutic approaches for GBM, a better understanding of the mechanisms of BTSC migration and invasion is necessary. In GBM, the study of migration and invasion is restricted, in part, due to the limitations of existing techniques which do not fully account for the in vitro growth characteristics of BTSCs grown as neurospheres. Here, we describe rapid and quantitative live-cell imaging assays to study both the migration and invasion properties of BTSCs. The first method described is the BTSC migration assay which measures the migration toward a chemoattractant gradient. The second method described is the BTSC invasion assay which images and quantifies a cellular invasion from neurospheres into a matrix. The assays described here are used for the quantification of BTSC migration and invasion over time and under different treatment conditions.

Here, we describe live-cell imaging techniques to quantitatively measure the migration and invasion of glioblastoma brain tumor stem cells over time and under multiple treatment conditions.

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include ...

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 ...

Using the Chicken Chorioallantoic Membrane In Vivo Model to Study Gynecological and Urological Cancers

Mouse models are the benchmark tests for in vivo cancer studies. However, cost, time, and ethical considerations have led to calls for alternative in vivo cancer models. The chicken chorioallantoic membrane (CAM) model provides an inexpensive, rapid alternative that permits direct visualization of tumor development and is suitable for in vivo imaging. As such, we sought to develop an optimized protocol for engrafting gynecological and urological tumors into this model, which we present here. Approximately 7 days postfertilization, the air cell is moved to the vascularized side of the egg, where an opening is created in the shell. Tumors from murine and human cell lines and primary tissues can then be engrafted. These are typically seeded in a mixture of extracellular matrix and medium to avoid cellular dispersal and provide nutrient support until the cells recruit a vascular supply. Tumors may then grow for up to an additional 14 days prior to the eggs hatching. By implanting cells stably transduced with firefly luciferase, bioluminescence imaging can be used for the sensitive detection of tumor growth on the membrane and cancer cell spread throughout the embryo. This model can potentially be used to study tumorigenicity, invasion, metastasis, and therapeutic effectiveness. The chicken CAM model requires significantly less time and financial resources compared to traditional murine models. Because the eggs are immunocompromised and immune tolerant, tissues from any organism can potentially be implanted without costly transgenic animals (e.g., mice) required for implantation of human tissues. However, many of the advantages of this model could potentially also be limitations, including the short tumor generation time and immunocompromised/immune tolerant status. Additionally, although all tumor types presented here engraft in the chicken chorioallantoic membrane model, they do so with varying degrees of tumor growth.

We present the chicken chorioallantoic membrane model as an alternative, transplantable, in vivo model for the engraftment of gynecological and urological cancer cell lines and patient-derived tumors.

Mouse models are the benchmark tests for in vivo cancer studies. However, cost, time, and ethical considerations have led to calls for alternative in vivo ...

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. The leading cause of breast cancer related deaths is the metastatic burden. Therefore, preclinical models for breast cancer need to analyze metastatic burden to be clinically relevant. The 4T1 breast cancer model provides a spontaneously-metastasizing, quantifiable mouse model for stage IV human breast cancer. However, most 4T1 protocols quantify the metastatic burden by manually counting stained colonies on tissue culture plates. While this is sufficient for tissues with lower metastatic burden, human error in manual counting causes inconsistent and variable results when plates are confluent and difficult to count. This method offers a computer-based solution to human counting error. Here, we evaluate the protocol using the lung, a highly metastatic tissue in the 4T1 model. Images of methylene blue-stained plates are acquired and uploaded for analysis in Fiji-ImageJ. Fiji-ImageJ then determines the percentage of the selected area of the image that is blue, representing the percentage of the plate with metastatic burden. This computer-based approach offers more consistent and expeditious results than manual counting or histopathological evaluation for highly metastatic tissues. The consistency of Fiji-ImageJ results depends on the quality of the image. Slight variations in results between images can occur, thus it is recommended that multiple images are taken and results averaged. Despite its minimal limitations, this method is an improvement to quantifying metastatic burden in the lung by offering consistent and rapid results.

We describe a more consistent and expeditious method to quantify lung metastasis in the 4T1 breast cancer model by using Fiji-ImageJ.

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. ...

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System

Breast cancer (BC) remains a leading cause of death for women. Despite more than $700 million invested in BC research annually, 97% of candidate BC drugs fail clinical trials. Therefore, new models are needed to improve our understanding of the disease. The NIH Microphysiological Systems (MPS) program was developed to improve the clinical translation of basic science discoveries and promising new therapeutic strategies. Here we present a method for generating MPS for breast cancers (BC-MPS). This model adapts a previously described approach of culturing primary human white adipose tissue (WAT) by sandwiching WAT between adipose-derived stem cell sheets (ASC)s. Novel aspects of our BC-MPS include seeding BC cells into non-diseased human breast tissue (HBT) containing native extracellular matrix, mature adipocytes, resident fibroblasts, and immune cells; and sandwiching the BC-HBT admixture between HBT-derived ASC sheets. The resulting BC-MPS is stable in culture ex vivo for at least 14 days. This model system contains multiple elements of the microenvironment that influence BC including adipocytes, stromal cells, immune cells, and the extracellular matrix. Thus BC-MPS can be used to study the interactions between BC and its microenvironment. 
We demonstrate the advantages of our BC-MPS by studying two BC behaviors known to influence cancer progression and metastasis: 1) BC motility and 2) BC-HBT metabolic crosstalk. While BC motility has previously been demonstrated using intravital imaging, BC-MPS allows for high-resolution time-lapse imaging using fluorescence microscopy over several days. Furthermore, while metabolic crosstalk was previously demonstrated using BC cells and murine pre-adipocytes differentiated into immature adipocytes, our BC-MPS model is the first system to demonstrate this crosstalk between primary human mammary adipocytes and BC cells in vitro.

This protocol describes the construction of an in vitro microphysiological system for studying breast cancer using primary human breast tissue with off the shelf materials.

Breast cancer (BC) remains a leading cause of death for women. Despite more than $700 million invested in BC research annually, 97% of candidate BC drugs ...

A Murine Ommaya Xenograft Model to Study Direct-Targeted Therapy of Leptomeningeal Disease

Leptomeningeal disease (LMD) is an uncommon type of central nervous system (CNS) metastasis to the cerebral spinal fluid (CSF). The most common cancers that cause LMD are breast and lung cancers and melanoma. Patients diagnosed with LMD have a very poor prognosis and generally survive for only a few weeks or months. One possible reason for the lack of efficacy of systemic therapy against LMD is the failure to achieve therapeutically effective concentrations of drug in the CSF because of an intact and relatively impermeable blood-brain barrier (BBB) or blood-CSF barrier across the choroid plexus. Therefore, directly administering drugs intrathecally or intraventricularly may overcome these barriers. This group has developed a model that allows for the effective delivery of therapeutics (i.e., drugs, antibodies, and cellular therapies) chronically and the repeated sampling of CSF to determine drug concentrations and target modulation in the CSF (when the tumor microenvironment is targeted in mice). The model is the murine equivalent of a magnetic resonance imaging-compatible Ommaya reservoir, which is used clinically. This model, which is affixed to the skull, has been designated as the &#34;Murine Ommaya.&#34; As a therapeutic proof of concept, human epidermal growth factor receptor 2 antibodies (clone 7.16.4) were delivered into the CSF via the Murine Ommaya to treat mice with LMD from human epidermal growth factor receptor 2-positive breast cancer. The Murine Ommaya increases the efficiency of drug delivery using a miniature access port and prevents the wastage of excess drug; it does not interfere with CSF sampling for molecular and immunological studies. The Murine Ommaya is useful for testing novel therapeutics in experimental models of LMD.

Here, we describe a murine xenograft model that functionally resembles an Ommaya reservoir in patients. We developed the Murine Ommaya to study novel therapeutics for the universally fatal leptomeningeal disease.

Leptomeningeal disease (LMD) is an uncommon type of central nervous system (CNS) metastasis to the cerebral spinal fluid (CSF). The most common cancers ...