We thank the members of the Y.D.S. laboratory. We would like to thank The Wohl Institute for Translational Medicine at the Hadassah Medical Center, Jerusalem, for providing the small animal imaging facility. This study was supported by Research Career Development Award from the Israel Cancer Research Fund.

All mouse experiments were carried out under the Hebrew University Institutional Animal Care and Use Committee-approved protocol MD-21-16429-5. In addition, the Hebrew University is certified by the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC).
1. Cell line maintenance
NOTE: The human breast cancer cell lines (MCF-7, MDA-MB-468, and MDA-MB-231) were used in this protocol.
<ol>
	<li>Culture all the breast cancer cell lines in Dulbecco&#39;s modified Eagle&#39;s medium (DMEM), supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin at 37 &#176;C in a humidified carbon dioxide (5% CO2) incubator. 
	&#8203;NOTE: Check the cell density regularly; split and expand for future usage when they reach 70% confluency.</li>
</ol>
2. Virus preparation
<ol>
	<li>Treat the HEK293T cells with 1 mL of trypsin until they detach.</li>
	<li>Add 10 mL of DMEM (10% FBS) to neutralize the trypsin activity, and transfer the cell suspension to a new 15 mL centrifuge tube.</li>
	<li>Centrifuge at 150 &#215; g for 5 min to sediment the cells. Discard the supernatant after the centrifugation and add 1 mL of fresh DMEM medium.</li>
	<li>Determine the cell concentration and seed 1.2 &#215; 106 cells/well in a six-well plate.</li>
	<li>On the following day, prewarm all the necessary reagents, including transfection reagent, serum-free DMEM, envelope plasmid (VSV-G), lentivirus packaging plasmid (&#916;VPR), and pLX304 Luciferase-V5 blast plasmid or FUW GFP plasmid.</li>
	<li>In a 1.5 mL autoclaved centrifuge tube, mix 50 &#181;L of serum-free DMEM with 0.3 &#181;g of VSV-G plasmid, 1 &#181;g of &#916;VPR, and 1.2 &#181;g of pLX304 Luciferase-V5 blast plasmid or FUW GFP plasmid.</li>
	<li>After thoroughly mixing these plasmids with the medium, add 5 &#181;L of the transfection reagent, mix gently, and incubate the mixture at room temperature for 15 min.</li>
	<li>Following incubation, add the mixture dropwise to the HEK293T cells.</li>
	<li>After 24 h, replace the growth medium with 2 mL of (30% FBS) DMEM. On the following day (48 h post-transfection), harvest the medium containing the viruses (&#34;pLX304 Luciferase-V5 or the FUW GFP viruses&#34;). 
	NOTE: The use of 30% FBS enhances the virus production efficiency.</li>
	<li>To avoid any HEK293T cell residues, pass the virus-containing medium through a 0.45 &#181;m syringe filter or centrifuge at 150 &#215; g for 5 min, and collect the supernatant. 
	NOTE: For long-term storage, keep the working aliquots of the virus at -80 &#176;C.</li>
</ol>
3. Establishing cells stably expressing GFP and luciferase (&#34;GFP&#160;&#160;+&#160;Luc+ cells&#34;)
<ol>
	<li>The day before infecting the cells, seed 8 &#215; 105 cells per well in a six-well plate.</li>
	<li>After overnight incubation, replace the growth medium with fresh medium containing 8 &#181;g/mL of polybrene. Add 200 &#181;L of FUW GFP viruses dropwise to the cells.</li>
	<li>Optional: To enhance the virus efficiency, centrifuge the plate at 560 &#215; g for 30 min (37 &#176;C) (spin infection).</li>
	<li>Incubate the cells for 48 h, and verify the GFP expression by fluorescence microscopy.</li>
	<li>Sort the GFP-expressing cells by fluorescence-activated cell sorting (FACS) (GFP+) (Figure 1A).</li>
	<li>Infect the GFP-sorted cells with the pLX304 Luciferase-V5 blast viruses as described in step 3.2.</li>
	<li>Treat the cells with blasticidin (10 &#181;g/mL) 30 h post-infection to enrich for pLX304 Luciferase-V5 blast-expressing cells (GFP+, Luc+ cells). Then, every two days, replace with fresh medium containing blasticidin. Additionally, as a control, treat na&#239;ve cells with the same blasticidin-containing medium. 
	NOTE: A clear difference between the infected and control cells should be observed after a few days of blasticidin treatment. This effect is cell line-dependent and usually takes ~8-10 days. A poor survival rate will indicate a low viral production yield. If so, produce a new batch of viruses as low efficiency may affect future experiments.</li>
</ol>
4. Validating in vitro luciferase activity
<ol>
	<li>Grow the MCF-7, MDA-MB-468, and MDA-MB-231 GFP+ Luc+ cells in a 15 cm plate to 80% confluency. Harvest the cells by trypsinization, as described in steps 2.1-2.2.</li>
	<li>Seed an increasing number of cells in each well (0.1, 0.5, 1, 2, 3, 4 &#215; 104) into a black 96-well plate. 
	NOTE: Black 96-well plates are more suited for measuring luciferase levels as white or transparent plates will produce autoluminescence signals. As a control, use phosphate-buffered saline (PBS) alone in one well to ensure there is no autoluminescence from PBS.</li>
	<li>Fill all the wells with 100 &#181;L of DMEM and incubate for 16-24 h.</li>
	<li>Prepare luciferin solution in PBS at a 1.5 mg/mL concentration from the stock of 30 mg/mL. Aliquot the stock of luciferin solution and store at -20 &#176;C.</li>
	<li>Wash the cells once with PBS gently, add 100 &#181;L of luciferin solution into each well, and wait for 2 min. Finally, measure the luciferase activity in all the breast cancer cells using bioluminescence. 
	NOTE: Examining in vitro GFP and luciferase expression prior to animal experiments is crucial. Additionally, blank wells are used to subtract the background.</li>
</ol>
5. Injecting mice with GFP+ Luc+ cells
<ol>
	<li>Transfer 5 &#215; 106 (MCF-7 and MDA-MB-468) or 2 &#215; 106 (MDA-MB-231) GFP+ Luc+ cells into 200 &#181;L or 100 &#181;L PBS, respectively.</li>
	<li>Before injection, clean the sterile biological hood with 5% disinfectant solution (see the Table of Materials). Then, anesthetize the mice with filtered (0.2 &#181;m) air containing 4% isoflurane at an airflow rate of 1 L/min for 2&#8722;3 min. 
	NOTE: It is essential to confirm proper anesthetization; pinch the mouse&#39;s toe and look for any response.</li>
	<li>Place a cone over the anesthetized mouse head in a supine position. Apply vet ointment to its eyes to prevent dryness while under anesthesia.</li>
	<li>Wipe the abdominal area of the mouse, above the mammary gland, with ethanol using a cotton swab and lift the 4th mammary gland with forceps.</li>
	<li>Insert the needle 27 G x 3/4 (0.4 x 19 mm) under the fat pad and slowly inject 100 &#181;L of the cell suspension. 
	NOTE: A round bulge will appear under the skin. In addition, an improper injection may lead to deviation in the tumor growth rate or absence of tumor in the same experimental group.</li>
	<li>After the injection procedure, take the mice out of the hood and transfer them to a new cage. Monitor the mice until they return to consciousness. 
	&#8203;NOTE: Ensure that all the used needles and syringes are discarded in the sharps box.</li>
</ol>
6. Measuring the luciferase levels in GFP+ Luc+ mice
<ol>
	<li>Before the bioluminescence detection, restrain the conscious mouse by holding its neck with the left hand. Then, tilt the hand to the left, resulting in the mouse face upward with the lower body in a supine position.</li>
	<li>Inject 100 &#181;L of luciferin (30 mg/mL) intraperitoneally (i.p.) into the abdominal surface of the mouse in the lower-left abdominal quadrant using a 1.0 mL syringe with needle size 27 G x 3/4 (0.4 x 19 mm). 
	NOTE: The tip of the needle should not be inserted more than 3-5 mm from the abdominal wall, as it might penetrate visceral organs. Additionally, it is recommended to perform i.p. injection without anesthesia as luciferin distribution in the body of anesthetized mice is slower than in conscious mice. Thus, monitoring luciferase levels in conscious mice is a faster procedure.</li>
	<li>Keep the mouse for 7 min without anesthesia followed by 3 min within the anesthesia chamber before measuring the tumor kinetics. 
	NOTE: The incubation time varies between the different experiments, cell lines, and species to species. Thus, it is recommended to calibrate the incubation time before starting the experiments.</li>
	<li>Anesthetize the mice as described in steps 5.2-5.3.</li>
	<li>Open the software (Table of Materials) during the incubation, initialize the imaging system, and click the Initialize button. 
	NOTE: Be aware that the camera will take ~10 min to cool down and reach -90 &#176;C. Additionally, as background control, measure the luciferase levels in na&#239;ve mice (i.e., GFP+ mice injected with cells that do not express the luciferase gene).</li>
	<li>Keep the setup in auto exposure using the following settings: exposure time auto, 60 s; Binning Medium, F/Stop 1; Excitation filter blocked; Emission filter open. When Initialization ends, select Imaging Wizard | Bioluminescence and then click Next | Open Filter | select Mouse in the image subject.</li>
	<li>In Field View, select stage C (10 cm) and Subject Height: 1.50 cm.</li>
	<li>Click Image Setup Stage to C, and before clicking the Acquire button, ensure that the mouse is placed on the stage in the proper supine position.</li>
	<li>Close the door, click the Acquire button, and wait for an image to appear on the screen. 
	NOTE: With the Auto-Exposure option, a strong signal takes 5-20 s depending on the signal; a weak signal will take around 60 s.</li>
	<li>Repeat this step for the other mice.</li>
	<li>To detect lung metastasis, cover the strong signal of the primary tumor using thick black cardboard paper and expose only the ventral side of the lungs towards the camera. Capture the image using the same parameters described above.</li>
</ol>
7. Acquiring ex vivo image using bioluminescence and fluorescence
<ol>
	<li>Euthanize the mice using carbon dioxide (CO2) inhalation in the desiccator and dissect the mice using autoclaved scissors and forceps.</li>
	<li>Perfuse the mice using 0.9% saline, harvest the organs, and rinse with 1x PBS to eliminate bloodstains from the organ.</li>
	<li>Transfer the rinsed organ to a Petri dish and place it into the stage of the bioluminescence machine. Apply the same bioluminescence setting as described in steps 6.2-6.6. 
	NOTE: Due to the decrease in luciferase signal, this step is time-limiting. Thus, after euthanizing mice, immediately visualize the organ by bioluminescence.</li>
	<li>For GFP images, apply the same setting as described in step 6.3, using Fluorescence GFP filter instead of Bioluminescence.</li>
	<li>Take lung images using a stereo microscope to examine the presence of GFP+ colonies.</li>
</ol>
8. Bioluminescence data analysis
<ol>
	<li>Double-click the software and select Open from the File menu.</li>
	<li>Open all the files and minimize them. Ensure all the units are Radiance (Photons). Additionally, click Apply to All to keep the same parameters for all the images.</li>
	<li>From the View menu, select the Tool Palette, which will open a new window.</li>
	<li>From the Tool Palette window, select the ROI Tools tab and in Type, choose the Average Bkg ROI.</li>
	<li>From the ROI tools, select Circle, and draw a small circle on the thoracic area of the mouse.</li>
	<li>Double-click on the circle, select the Use as BKG for future ROIs option from the Background ROI tab, and click Done.</li>
</ol>
9. Measuring the total flux
<ol>
	<li>From the Tool Palette window, select the ROI Tools tab and in Type, choose the Measurement of ROI.</li>
	<li>From the ROI tools, select Circle, and draw a big circle on the primary tumor of the mouse.</li>
	<li>Right-click Copy ROI and right-click Paste ROI into every individual file of each mouse.</li>
	<li>Click Measure ROIs from the ROI Tools tab, which will open a new window named ROI Measurements. From this tab, keep the Measurements Types as Radiance (Photons) and Image Attributes as All Populated Values.</li>
	<li>Export the file as Measurements File (*.txt) or Csv (*.csv) format.</li>
	<li>Open the exported data in a spreadsheet and take the Total Flux (p/s) and the values for the weeks. 
	NOTE: This step can be used to measure different groups. For example, mice treated with a vehicle vs. those treated with a drug.</li>
	<li>Generate an XY plot, where the Time is presented along the X-axis and Total Flux (p/s) along the Y-axis. For each week, take the Total Flux (p/s) parameter for each sample group and determine any significant differences using the non-parametric Student&#39;s t-test.</li>
</ol>

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P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Breast+cancer+treatment:+A+review.">Breast cancer treatment: A review.</a> JAMA. 321 (3), 288-300 (2019).</li><li>Jin, X., Mu, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+breast+cancer+metastasis.">Targeting breast cancer metastasis.</a> Breast Cancer: Basic and Clinical Research. 9, 23-34 (2015).</li><li>Saha, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+bioluminescence+imaging+of+tumor+hypoxia+dynamics+of+breast+cancer+brain+metastasis+in+a+mouse+model.">In vivo bioluminescence imaging of tumor hypoxia dynamics of breast cancer brain metastasis in a mouse model.</a> Journal of Visualized Experiments: JoVE. 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H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Orthotopic+injection+of+breast+cancer+cells+into+the+mammary+fat+pad+of+mice+to+study+tumor+growth.">Orthotopic injection of breast cancer cells into the mammary fat pad of mice to study tumor growth.</a> Journal of Visualized Experiments: JoVE. (96), e51967 (2015).</li><li>Baker, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+whole+picture.">The whole picture.</a> Nature. 463 (7283), 977-979 (2010).</li><li>Wang, Y., Tseng, J. -. C., Sun, Y., Beck, A. H., Kung, A. 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All authors have disclosed that they do not have any conflicts of interest.

Animal-based experiments are obligatory for cancer research7,8,9, and indeed many protocols have been developed3,6,10,11,12,13,14. However, most of these studies determined the biological effect onl...

Breast cancers are frequent types of cancer worldwide, with approximately 250,000 new cases diagnosed each year in the United States1. Despite its high incidence, a new set of anticancer drugs has significantly improved breast cancer patient outcomes2. However, these treatments are still inadequate, as many patients experience disease relapse and metastatic spread to vital organs2, which is the primary cause of patient morbidity and mortality. Therefore, one of the main challenges in breast cancer research is identifying the molecular mechanisms regulating the formation of distal metastases to develop new means to inhibit their development.
Cancer metastasis is a dynamic process in which cells detach from the primary tumor and invade neighboring tissues through the blood circulation. Thus, animal models in which the cells undergo a similar metastatic cascade can facilitate the identification of the mechanisms that govern this process3,4. Additionally, these in vivo models are essential for developing breast cancer therapeutic agents5,6. However, these orthotopic models cannot indicate the actual tumor growth kinetics as the effect is only determined upon termination. Therefore, we established a luciferase-based tool to detect tumor development and metastatic colonization in real time. Additionally, these cells express GFP to detect the metastatic colonies. This approach is relatively simple and does not involve any invasive procedures3. Thus, combining luciferase and fluorescence detection is a helpful strategy to advance the preclinical studies of breast cancer therapeutics and disease management.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1.7 mL eppendorf tubes</td>
			<td>Lifegene</td>
			<td>LMCT1.7B-500</td>
			<td></td>
		</tr>
		<tr>
			<td>10 &#181;L tips</td>
			<td>Lifegene</td>
			<td>LRT10</td>
			<td></td>
		</tr>
		<tr>
			<td>1000 &#181;L tips</td>
			<td>Lifegene</td>
			<td>LRT1000</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL tubes</td>
			<td>Lifegene</td>
			<td>LTB15-500</td>
			<td></td>
		</tr>
		<tr>
			<td>200 &#181;L tips</td>
			<td>Lifegene</td>
			<td>LRT200</td>
			<td></td>
		</tr>
		<tr>
			<td>6 well cell culture plate</td>
			<td>COSTAR</td>
			<td>3516</td>
			<td></td>
		</tr>
		<tr>
			<td>96 well Plates BLACK flat bottom</td>
			<td>Bar Naor</td>
			<td>BN30496</td>
			<td></td>
		</tr>
		<tr>
			<td>Automated Cell Counters</td>
			<td>Thermofisher</td>
			<td>A50298</td>
			<td></td>
		</tr>
		<tr>
			<td>BD FACSAria III sorter</td>
			<td>BD</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>BD Microlance 3 Needles 27 G (3/4&#39;&#39;)</td>
			<td>BD</td>
			<td>302200</td>
			<td></td>
		</tr>
		<tr>
			<td>BD Plastipak Syringes 1 mL x 120</td>
			<td>BD</td>
			<td>303172</td>
			<td></td>
		</tr>
		<tr>
			<td>Corning 100 mm x 20 mm Style Dish</td>
			<td>CORNING</td>
			<td>430167</td>
			<td></td>
		</tr>
		<tr>
			<td>Corning 150 mm x 20 mm Style Dish</td>
			<td>CORNING</td>
			<td>430599</td>
			<td></td>
		</tr>
		<tr>
			<td>Countess cell counting chamber slides</td>
			<td>Thermofisher</td>
			<td>C10228</td>
			<td></td>
		</tr>
		<tr>
			<td>Dulbecco&#39;s modified Eagle&#39;s medium (DMEM), high glucose, no glutamine</td>
			<td>Biological Industries</td>
			<td>01-055-1A</td>
			<td></td>
		</tr>
		<tr>
			<td>Eclipse 80i microscope</td>
			<td>Nikon</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>eppendorf Centrifuge 5810 R</td>
			<td>Sigma Aldrich</td>
			<td>EP5820740000</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>Biological Industries</td>
			<td>04-127-1A</td>
			<td></td>
		</tr>
		<tr>
			<td>FUW GFP</td>
			<td></td>
			<td></td>
			<td>Gifted from Dr. Yossi Buganim&#39;s lab (Hebrew University of Jerusalem)</td>
		</tr>
		<tr>
			<td>HEK293T</td>
			<td></td>
			<td></td>
			<td>Gifted from Dr. Lior Nissim&#39;s lab (Hebrew University of Jerusalem)</td>
		</tr>
		<tr>
			<td>Isoflurane, USP Terrell</td>
			<td>Piramal</td>
			<td>NDC 66794-01-25</td>
			<td></td>
		</tr>
		<tr>
			<td>IVIS Spectrum In Vivo Imaging System</td>
			<td>Perkin Elmer</td>
			<td>124262</td>
			<td></td>
		</tr>
		<tr>
			<td>L-Glutamine Solution</td>
			<td>Biological industries</td>
			<td>03-020-1A</td>
			<td></td>
		</tr>
		<tr>
			<td>Living Image Software</td>
			<td>PerkinElmer</td>
			<td></td>
			<td>bioluminescence measurement</td>
		</tr>
		<tr>
			<td>MCF-7</td>
			<td>ATCC</td>
			<td>ATCC HTB-22</td>
			<td></td>
		</tr>
		<tr>
			<td>MDA-MB-231</td>
			<td>ATCC</td>
			<td>ATCC HTB-26</td>
			<td></td>
		</tr>
		<tr>
			<td>MDA-MB-468</td>
			<td>ATCC</td>
			<td>ATCC HTB-132</td>
			<td></td>
		</tr>
		<tr>
			<td>Pasteur pipettes</td>
			<td>NORMAX</td>
			<td>2430-475</td>
			<td></td>
		</tr>
		<tr>
			<td>PBS</td>
			<td>Hylabs</td>
			<td>BP655/500D</td>
			<td></td>
		</tr>
		<tr>
			<td>pCMV-dR8.2-dvpr</td>
			<td>Addgene</td>
			<td>#8455</td>
			<td>Provided by David M. Sabatini&#8217;s lab (Whitehead institute, Boston, USA)</td>
		</tr>
		<tr>
			<td>pCMV-VSV-G</td>
			<td>Addgene</td>
			<td>#8454</td>
			<td>Provided by David M. Sabatini&#8217;s lab (Whitehead institute, Boston, USA)</td>
		</tr>
		<tr>
			<td>Penicillin-Streptomycin Solution</td>
			<td>Biological Industries</td>
			<td>03-031-1B</td>
			<td></td>
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		<tr>
			<td>Petri dish 90 mm (90x15)</td>
			<td>MINI PLAST</td>
			<td>820-090-01-017</td>
			<td></td>
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			<td>Pipettes 10ml</td>
			<td>Lifegene</td>
			<td>LG-GSP010010S</td>
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			<td>Pipettes 25ml</td>
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			<td>LG-GSP010050S</td>
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			<td>Pipettes 5ml</td>
			<td>Lifegene</td>
			<td>LG-GSP010005S</td>
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			<td>pLX304 Luciferase-V5 blast plasmid</td>
			<td>Addgene</td>
			<td>#98580</td>
			<td></td>
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			<td>Polybrene</td>
			<td>Sigma Aldrich</td>
			<td>#107689</td>
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			<td>Prism 9</td>
			<td>GraphPad</td>
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			<td></td>
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		<tr>
			<td>Reagent Reservoirs</td>
			<td>Bar Naor</td>
			<td>BN20621STR200TC</td>
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			<td>SMZ18 Stereo microscopes</td>
			<td>Nikon</td>
			<td></td>
			<td></td>
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			<td>Sodium Chloride</td>
			<td>Bio-Lab</td>
			<td>190359400</td>
			<td></td>
		</tr>
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			<td>Syringe filters</td>
			<td>Lifegene</td>
			<td>LG-FPV403030S</td>
			<td></td>
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		<tr>
			<td>Trypan Blue 0.5% solution</td>
			<td>Biological industries</td>
			<td>03-102-1B</td>
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		<tr>
			<td>Trypsin EDTA Solution B (0.25%), EDTA (0.05%)</td>
			<td>Biological Industries</td>
			<td>03-052-1a</td>
			<td></td>
		</tr>
		<tr>
			<td>Vacuum driven Filters</td>
			<td>SOFRA LIFE SCIENCE</td>
			<td>SPE-22-500</td>
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		<tr>
			<td>Virusolve</td>
			<td></td>
			<td>disinfectant</td>
			<td></td>
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		<tr>
			<td>VivoGlo Luciferin, In Vivo Grade</td>
			<td>Promega</td>
			<td>P1043</td>
			<td></td>
		</tr>
		<tr>
			<td>X-tremeGENE HP DNA Transfection Reagent</td>
			<td>Sigma Aldrich</td>
			<td>#6366236001</td>
			<td></td>
		</tr>
	</tbody>
</table>

monitoring breast cancer growth and metastatic colony formation in mice using bioluminescence

Breast cancer is a frequent heterogeneous malignancy and the second leading cause of mortality in women, mainly due to distant organ metastasis. Several animal models have been generated, including the widely used orthotopic mouse models, where cancer cells are injected into the mammary fat pad. However, these models cannot help monitor tumor growth kinetics and metastatic colonization. Cutting-edge tools to monitor cancer cells in real time in mice will significantly advance the understanding of tumor biology. 
Here, breast cancer cell lines stably expressing luciferase and green fluorescent protein (GFP) were established. Specifically, this technique contains two sequential steps initiated by measuring the luciferase activity in vitro and followed by the implantation of the cancer cells into mammary fat pads of nonobese diabetic-severe combined immunodeficiency (NOD-SCID) mice. After the injection, both the tumor growth and metastatic colonization are monitored in real time by the noninvasive bioluminescence imaging system. Then, the quantification of GFP-expressing metastases in the lungs will be examined by fluorescence microscopy to validate the observed bioluminescence results. This sophisticated system combining luciferase and fluorescence-based detection tools evaluates cancer metastasis in vivo, which has great potential for use in breast cancer therapeutics and disease management.

We generated breast cancer cell lines (MDA-MB-231, MCF-7, and MDA-MB-468) expressing GFP and luciferase vectors. Specifically, this was achieved by a sequential infection. First, the breast cancer cell lines were infected with a lentivirus vector expressing fluorescent GFP. The GFP-positive cells (GFP+) were sorted 2 days post-infection (Figure 1A,B) and infected with the pLX304 Luciferase-V5 vector. Then, blasticidin was used to select for luciferase to generate ...

Watch this Scientific Journal Video about Monitoring Breast Cancer Growth and Metastatic Colony Formation in Mice using Bioluminescence at JoVE.com

Monitoring Breast Cancer Growth and Metastatic Colony Formation in Mice using Bioluminescence

Here, we describe a noninvasive monitoring method involving luciferase and green fluorescent protein expression in various breast cancer cell lines. This protocol provides a technique to monitor tumor formation and metastatic colonization in real time in mice.

Breast cancer is a frequent heterogeneous malignancy and the second leading cause of mortality in women, mainly due to distant organ metastasis. Several ...

monitoring-breast-cancer-growth-metastatic-colony-formation-mice

Research

JoVE Journal

Cancer Research

2.9K Views.  The Hebrew University-Hadassah Medical School. Here, we describe a noninvasive monitoring method involving luciferase and green fluorescent protein expression in various breast cancer cell lines. This protocol provides a technique to monitor tumor formation and metastatic colonization in real time in mice.

Video: Monitoring Breast Cancer Growth and Metastatic Colony Formation in Mice using Bioluminescence

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 ...

Labeling of Breast Cancer Patient-derived Xenografts with Traceable Reporters for Tumor Growth and Metastasis Studies

The use of preclinical models to study tumor biology and response to treatment is central to cancer research. Long-established human cell lines, and many transgenic mouse models, often fail to recapitulate the key aspects of human malignancies. Thus, alternative models that better represent the heterogeneity of patients' tumors and their metastases are being developed. Patient-derived xenograft (PDX) models in which surgically resected tumor samples are engrafted into immunocompromised mice have become an attractive alternative as they can be transplanted through multiple generations,and more efficiently reflect tumor heterogeneity than xenografts derived from human cancer cell lines. A limitation to the use of PDXs is that they are difficult to transfect or transduce to introduce traceable reporters or to manipulate gene expression. The current protocol describes methods to transduce dissociated tumor cells from PDXs with high transduction efficiency, and the use of labeled PDXs for experimental models of breast cancer metastases. The protocol also demonstrates the use of labeled PDXs in experimental metastasis models to study the organ-colonization process of the metastatic cascade. Metastases to different organs can be easily visualized and quantified using bioluminescent imaging in live animals, or GFP expression during dissection and in excised organs. These methods provide a powerful tool to extend the use of multiple types of PDXs to metastasis research.

We describe a method for stable labeling of patient-derived xenografts (PDXs) with lentiviral particles expressing green-fluorescent protein and luciferase reporters. This method allows for tracking the growth of PDXs at the primary site, as well as detecting spontaneous and experimental metastases using in vivo imaging systems.

The use of preclinical models to study tumor biology and response to treatment is central to cancer research. Long-established human cell lines, and many ...

Practical Considerations in Studying Metastatic Lung Colonization in Osteosarcoma Using the Pulmonary Metastasis Assay

The pulmonary metastasis assay (PuMA) is an ex vivo lung explant and closed cell culture system that permits researchers to study the biology of lung colonization in osteosarcoma (OS) by fluorescence microscopy. This article provides a detailed description of the protocol, and discusses examples of obtaining image data on metastatic growth using widefield or confocal fluorescence microscopy platforms. The flexibility of the PuMA model permits researchers to study not only the growth of OS cells in the lung microenvironment, but also to assess the effects of anti-metastatic therapeutics over time. Confocal microscopy allows for unprecedented, high-resolution imaging of OS cell interactions with the lung parenchyma. Moreover, when the PuMA model is combined with fluorescent dyes or fluorescent protein genetic reporters, researchers can study the lung microenvironment, cellular and subcellular structures, gene function, and promoter activity in metastatic OS cells. The PuMA model provides a new tool for osteosarcoma researchers to discover new metastasis biology and assess the activity of novel anti-metastatic, targeted therapies.

The goal of this article is to provide a detailed description of the protocol for the pulmonary metastasis assay (PuMA). This model permits researchers to study metastatic osteosarcoma (OS) cell growth in lung tissue using a widefield fluorescence or confocal laser-scanning microscope.

The pulmonary metastasis assay (PuMA) is an ex vivo lung explant and closed cell culture system that permits researchers to study the biology of lung ...

Preclinical Assessment of the Bioactivity of the Anticancer Coumarin OT48 by Spheroids, Colony Formation Assays, and Zebrafish Xenografts

In vitro and in vivo pre-clinical screening of novel therapeutic agents are an essential tool in cancer drug discovery. Although human cancer cell lines respond to therapeutic compounds in 2D (dimensional) monolayer cell cultures, 3D culture systems were developed to understand the efficacy of drugs in more physiologically relevant models. In recent years, a paradigm shift was observed in pre-clinical research to validate the potency of new molecules in 3D culture systems, more precisely mimicking the tumor microenvironment. These systems characterize the disease state in a more physiologically relevant manner and help to gain better mechanistic insight and understanding of the pharmacological potency of a given molecule. Moreover, with the current trend in improving in vivo cancer models, zebrafish has emerged as an important vertebrate model to assess in vivo tumor formation and study the effect of therapeutic agents. Here, we investigated the therapeutic efficacy of hydroxycoumarin OT48 alone or in combination with BH3 mimetics in lung cancer cell line A549 by using three different 3D culture systems including colony formation assays (CFA), spheroid formation assay (SFA) and in vivo zebrafish xenografts.

Here, we present the preclinical screening of anticancer coumarins using 3D culture and zebrafish.

In vitro and in vivo pre-clinical screening of novel therapeutic agents are an essential tool in cancer drug discovery. Although human cancer cell lines ...

Orthotopic Injection of Breast Cancer Cells into the Mice Mammary Fat Pad

A proper animal model is crucial for a better understanding of diseases. Animal models established by different methods (subcutaneous injections, xenografts, genetic manipulation, chemical reagents induction, etc.) have various pathological characters and play important roles in investigating certain aspects of diseases. Although no single model can totally mimic the whole human disease progression, orthotopic organs disease models with a proper stromal environment play an irreplaceable role in understanding diseases and screening for potential drugs. In this article, we describe how to implant breast cancer cells into the mammary fat pad in a simple, less invasive, and easy-to-handle way, and follow the metastasis to distant organs. With the proper features of primary tumor growth, breast and nipple pathological changes, and a high occurrence of other organs&#39; metastasis, this model maximumly mimics human breast cancer progression. Primary tumor growth in situ, long-distant metastasis, and the tumor microenvironment of breast cancer can be investigated by using this model.

Here, we present a protocol to implant breast cancer cells into the mammary fat pad in a simple, less invasive, and easy-to-handle way, and this mouse orthotopic breast cancer model with a proper mammary fat pad environment can be used to investigate various aspects of cancer.

A proper animal model is crucial for a better understanding of diseases. Animal models established by different methods (subcutaneous injections, ...

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating investigators to analyze and interpret genes, samples and clinical data across different types of cancer. Herein, we describe a practical operation procedure, taking ID1 (Inhibitor of DNA binding proteins 1) as an example, to characterize the expression patterns of biomarker and survival predictors of breast cancer based on pooled clinical datasets derived from online accessible databases, including ONCOMINE, bcGenExMiner v4.0 (Breast cancer gene-expression miner v4.0), GOBO (Gene expression-based Outcome for Breast cancer Online), HPA (The human protein atlas), and Kaplan-Meier plotter. The analysis began with querying the expression pattern of the gene of interest (e.g., ID1) in cancerous samples vs. normal samples. Then, the correlation analysis between ID1 and clinicopathological characteristics in breast cancer was performed. Next, the expression profiles of ID1 was stratified according to different subgroups. Finally, the association between ID1 expression and survival outcome was analyzed. The operation procedure simplifies the concept to integrate multidimensional data types at the gene level from different databases and test hypotheses regarding recurrence and genomic context of gene alteration events in breast cancer. This method can improve the credibility and representativeness of the conclusions, thereby, present informative perspective on a gene of interest.

Here, we present a protocol to explore the biomarker and survival predictor of breast cancer based on the comprehensive analysis of pooled clinical datasets derived from a variety of publicly accessible databases, using the strategy of expression, correlation and survival analysis step by step.

In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating ...

In Vivo Inhibition of MicroRNA to Decrease Tumor Growth in Mice

MicroRNAs (miRNAs) are important regulators of gene expression through their ability to destabilize mRNA and inhibit translation of target mRNAs. An ever-increasing number of studies have identified miRNAs as potential biomarkers for cancer diagnosis and prognosis, and also as therapeutic targets, adding an extra dimension to cancer evaluation and treatment. In the context of thyroid cancer, tumorigenesis results not only from mutations in important genes, but also from the overexpression of many miRNAs. Accordingly, the role of miRNAs in the control of thyroid gene expression is evolving as an important mechanism in cancer. Herein, we present a protocol to examine the effects of miRNA-inhibitor delivery as a therapeutic modality in thyroid cancer using human tumor xenograft and orthotopic mouse models. After engineering stable thyroid tumoral cells expressing GFP and luciferase, cells are injected into nude mice to develop tumors, which can be followed by bioluminescence. The in vivo inhibition of a miRNA can reduce tumor growth and upregulate miRNA gene targets. This method can be used to assess the importance of a determined miRNA in vivo, in addition to identifying new therapeutic targets.

This protocol describes xenograft and orthotopic mouse models of human thyroid tumorigenesis as a platform to test microRNA-based inhibitor treatments. This approach is ideal to study the function of non-coding RNAs and their potential as new therapeutic targets.

MicroRNAs (miRNAs) are important regulators of gene expression through their ability to destabilize mRNA and inhibit translation of target mRNAs. An ...

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 ...

Combined Use of Tail Vein Metastasis Assays and Real-Time In Vivo Imaging to Quantify Breast Cancer Metastatic Colonization and Burden in the Lungs

Metastasis is the main cause of cancer-related deaths and there are limited therapeutic options for patients with metastatic disease. The identification and testing of novel therapeutic targets that will facilitate the development of better treatments for metastatic disease requires preclinical in vivo models. Demonstrated here is a syngeneic mouse model for assaying breast cancer metastatic colonization and subsequent growth. Metastatic cancer cells are stably transduced with viral vectors encoding firefly luciferase and ZsGreen proteins. Candidate genes are then stably manipulated in luciferase/ZsGreen-expressing cancer cells and then the cells are injected into mice via the lateral tail vein to assay metastatic colonization and growth. An in vivo imaging device is then used to measure the bioluminescence or fluorescence of the tumor cells in the living animals to quantify changes in metastatic burden over time. The expression of the fluorescent protein allows the number and size of metastases in the lungs to be quantified at the end of the experiment without the need for sectioning or histological staining. This approach offers a relatively quick and easy way to test the role of candidate genes in metastatic colonization and growth, and provides a great deal more information than traditional tail vein metastasis assays. Using this approach, we show that simultaneous knockdown of Yes associated protein (YAP) and transcriptional co-activator with a PDZ-binding motif (TAZ) in breast cancer cells leads to reduced metastatic burden in the lungs and that this reduced burden is the result of significantly impaired metastatic colonization and reduced growth of metastases.

The described approach combines experimental tail vein metastasis assays with in vivo live animal imaging to allow real-time monitoring of breast cancer metastasis formation and growth in addition to the quantification of metastasis number and size in the lungs.

Metastasis is the main cause of cancer-related deaths and there are limited therapeutic options for patients with metastatic disease. The identification ...

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. ...