Name: using computer-based image analysis to improve quantification of lung metastasis in the 4t1 breast cancer model
Uploaded: 2020-10-02T15:00:00
Description: 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. ...

This work was supported by the Virginia-Maryland College of Veterinary Medicine (IA), the Virginia Tech Institute for Critical Technology and Applied Science Center for Engineered Health (IA), and National Institutes of Health R21EB028429 (IA).

All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Virginia Tech and in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. Performing this protocol requires permission from the appropriate institutions and adherence to all appropriate guidelines.
1. Cell Culture
<ol>
	<li>Make complete culture media (RPMI + 10% Fetal Bovine Serum +1% Pen Strep). Revive 4T1 cells according to ATCC Protoco...

<ol>
	<li>American Cancer Society. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer+Facts+&amp;+Figures.">Cancer Facts &amp; Figures.</a> American Cancer Society. , (2019).</li><li>Yousefi, M., 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=Organ-specific+metastasis+of+breast+cancer:+molecular+and+cellular+mechanisms+underlying+lung+metastasis.">Organ-specific metastasis of breast cancer: molecular and cellular mechanisms underlying lung metastasis.</a> Cellular Oncology. 41 (2), 123-140 (2018).</li><li>Pulaski, B. A., Ostrand-Rosenberg, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mouse+4T1+breast+tumor+model.">Mouse 4T1 breast tumor model.</a> Current Protocols in Immunology. , (2001).</li><li>Pulaski, B. A., Ostrand-Rosenberg, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reduction+of+established+spontaneous+mammary+carcinoma+metastases+following+immunotherapy+with+major+histocompatibility+complex+class+II+and+B7.1+cell-based+tumor+vaccines.">Reduction of established spontaneous mammary carcinoma metastases following immunotherapy with major histocompatibility complex class II and B7.1 cell-based tumor vaccines.</a> Cancer Research. 58 (7), 1486-1493 (1998).</li><li>Aslakson, C. J., Miller, F. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+events+in+the+metastatic+process+defined+by+analysis+of+the+sequential+dissemination+of+subpopulations+of+a+mouse+mammary+tumor.">Selective events in the metastatic process defined by analysis of the sequential dissemination of subpopulations of a mouse mammary tumor.</a> Cancer Research. 52 (6), 1399-1405 (1992).</li><li>Sikpa, 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=Automated+detection+and+quantification+of+breast+cancer+brain+metastases+in+an+animal+model+using+democratized+machine+learning+tools.">Automated detection and quantification of breast cancer brain metastases in an animal model using democratized machine learning tools.</a> Scientific Reports. 9 (1), 17333 (2019).</li><li>Valkonen, M., 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=Metastasis+detection+from+whole+slide+images+using+local+features+and+random+forests.">Metastasis detection from whole slide images using local features and random forests.</a> Cytometry A. 91 (6), 555-565 (2017).</li><li>Coutermarsh-Ott, S. L., Broadway, K. M., Scharf, B. E., Allen, I. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+Salmonella+enterica+serovar+Typhimurium+VNP20009+and+VNP20009+with+restored+chemotaxis+on+4T1+mouse+mammary+carcinoma+progression.">Effect of Salmonella enterica serovar Typhimurium VNP20009 and VNP20009 with restored chemotaxis on 4T1 mouse mammary carcinoma progression.</a> Oncotarget. 8 (20), 33601-33613 (2017).</li><li>Schindelin, J., 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=Fiji:+an+open-source+platform+for+biological-image+analysis.">Fiji: an open-source platform for biological-image analysis.</a> Nature Methods. 9 (7), 676-682 (2012).</li><li>ATCC. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A.T.C.C.+4T1+(ATCC+CRL2539)+Product+Sheet.">A.T.C.C. 4T1 (ATCC CRL2539) Product Sheet.</a> ATCC. , (2020).</li></ol>

As demonstrated, manually counting the metastatic colonies on each lung plate can be an inaccurate and imprecise method to quantify lung metastasis, demonstrating the need for a better means of quantification (Figure 2). Histopathological analysis differed slightly from both manual counting and Fiji-ImageJ analysis (Figure 2B and 4D), likely because the H&#38;E slides are not a representative sample of the entire organ. The protocol harvests an ...

One in eight women will be diagnosed with breast cancer in her lifetime, and yet despite multiple treatment options breast cancer is the second leading cause of cancer-related deaths in American women1. These women are not dying from the primary tumor in their breast. Instead, the metastatic burden is responsible for the mortality of this disease as it commonly spreads to the lung, bone, brain, liver, and lymph nodes2. Because of this, breast cancer models need to evaluate metastasis to contribute to curbing the mortality of this disease. The 4T1 murine breast cancer model is a superb protocol to accomplish this. The method described here offers an improvement to the 4T1 model by using Fiji-ImageJ to quantify lung metastasis, producing consistent and expeditious results.
The 4T1 model is well-established, with most labs using protocols such as those described by Pulaski and Ostrand-Rosenberg in 20013. The 4T1 cell line is 6-Thioguanine (6TG) resistant and representative of stage IV, triple negative breast cancer3,4,5. It is clinically relevant as it is an orthotopic model and spontaneously metastasizes to the same organs as in human breast cancer3,4. The 4T1 cells spontaneously metastasize at a predictable rate based on the quantity of cells injected3,4. Importantly, genetic differences between mice used here caused expected inter-individual variability in metastatic burden. To evaluate metastasis, tissues are harvested to collect and quantify cancer cells in distant sites using 6TG selection and methylene blue staining. The result is a collection of tissue culture plates with blue dots representing metastatic colonies. However, the Pulaski and Ostrand-Rosenberg protocol quantifies metastatic colonies by manually counting them, and therefore this has been the standard means of evaluating metastasis in this model. While this is easy for tissues with low metastatic burden, tissues like the lungs are often laden with metastases. As lung plates can be highly confluent, accurately and precisely quantifying metastatic colonies by manual counting is difficult and prone to human error. To better quantify metastatic burden, we describe using Fiji-ImageJ for a computer-based solution to human counting error. Histopathological analysis with hematoxylin and eosin (H&#38;E) staining is another means to quantify lung metastases, and interestingly has also been improved with Fiji-ImageJ software6,7. However, because histopathological analysis observes a single slice of the lung, it can be inaccurate and unrepresentative. This is because the 4T1 model causes several metastatic lesions throughout the organ that are not evenly distributed. While overall trends between histopathological analysis and manual counting can be similar8, individual values can differ and therefore histopathological analysis should not be used as the sole means of quantification. We demonstrate the benefit compared to histopathological analysis and the inconsistencies in manual counting between different counters, while also demonstrating the consistency of using Fiji-ImageJ. Additionally, we show that this method can reduce the incubation time from 10-14 days to 5 days, meaning researchers can analyze data from their study much sooner than when relying on manual counting.
This method is a collection of simple adjustments to the Pulaski and Ostrand-Rosenberg protocol3. Because the 4T1 model is widely used, and because lung metastasis is a critical parameter to measure in preclinical models, we believe this method can be widely used and is highly valuable to breast cancer researchers. The only additional supplies needed are a camera and access to a computer with Fiji-ImageJ, a free software used frequently in image analysis9. This method specifically focuses on lung metastasis, but it could be used for other tissues with significant metastatic burden.

<table>
	<tbody>
		<tr>
			<td>Anesthesia chamber</td>
			<td>See comments</td>
			<td>See comments</td>
			<td>Use approved materials in your institution&#39;s policies</td>
		</tr>
		<tr>
			<td>Anesthetic agent</td>
			<td>See comments</td>
			<td>See comments</td>
			<td>Use approved materials in your institution&#39;s policies</td>
		</tr>
		<tr>
			<td>BALB/c Female Mice</td>
			<td>The Jackson Laboratory</td>
			<td>651</td>
			<td></td>
		</tr>
		<tr>
			<td>Blunt scissors</td>
			<td>Roboz</td>
			<td>RS-6700</td>
			<td></td>
		</tr>
		<tr>
			<td>Calculator</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Camera</td>
			<td>Any</td>
			<td>Any</td>
			<td>Minimum of 8 megapixels</td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Any</td>
			<td>Any</td>
			<td>Needs to be capable of 125 x g and 300 x g</td>
		</tr>
		<tr>
			<td>CO2 euthanasia setup</td>
			<td>See comments</td>
			<td>See comments</td>
			<td>Use approved materials in your institution&#39;s policies</td>
		</tr>
		<tr>
			<td>Cold room, refrigerator, cold storage</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Computer with Fiji-ImageJ</td>
			<td>Any</td>
			<td>Any</td>
			<td>Needs to be capable of running Fiji-ImageJ</td>
		</tr>
		<tr>
			<td>Counting Chamber</td>
			<td>Fisher Scientific</td>
			<td>02-671-10</td>
			<td></td>
		</tr>
		<tr>
			<td>Curved scissors</td>
			<td>Roboz</td>
			<td>RS-5859</td>
			<td></td>
		</tr>
		<tr>
			<td>Distilled water</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Elastase</td>
			<td>MP Biomedicals</td>
			<td>100617</td>
			<td></td>
		</tr>
		<tr>
			<td>Electronic scale</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>R&#38;D Systems</td>
			<td>S11150</td>
			<td></td>
		</tr>
		<tr>
			<td>Forceps</td>
			<td>Roboz</td>
			<td>RS-8100</td>
			<td></td>
		</tr>
		<tr>
			<td>Ice</td>
			<td>N/A</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Incubator</td>
			<td>See comments</td>
			<td>See comments</td>
			<td>Needs to be capable of 5% CO2 and 37 &#176;C</td>
		</tr>
		<tr>
			<td>Methanol</td>
			<td>Fisher Scientific</td>
			<td>A412SK-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Methylene blue</td>
			<td>Sigma-Aldrich</td>
			<td>03978-250ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Penicillin Streptomycin</td>
			<td>ATCC</td>
			<td>30-2300</td>
			<td></td>
		</tr>
		<tr>
			<td>Pins or needles</td>
			<td>Any</td>
			<td>Any</td>
			<td>For pinning down mice during necropsy</td>
		</tr>
		<tr>
			<td>Plastic calipers</td>
			<td>VWR</td>
			<td>25729-670</td>
			<td></td>
		</tr>
		<tr>
			<td>RMPI-1640 Medium</td>
			<td>ATCC</td>
			<td>30-2001</td>
			<td></td>
		</tr>
		<tr>
			<td>Rocker or rotating wheel</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>Sharp scissors</td>
			<td>Roboz</td>
			<td>RS-6702</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile disposable filter with PES membrane</td>
			<td>ThermoFisher Scientific</td>
			<td>568-0010</td>
			<td></td>
		</tr>
		<tr>
			<td>T-150 Flasks</td>
			<td>Fisher Scientific</td>
			<td>08-772-48</td>
			<td></td>
		</tr>
		<tr>
			<td>T-25 Flasks</td>
			<td>Fisher Scientific</td>
			<td>10-126-10</td>
			<td></td>
		</tr>
		<tr>
			<td>T-75 Flasks</td>
			<td>Fisher Scientific</td>
			<td>13-680-65</td>
			<td></td>
		</tr>
		<tr>
			<td>Tri-cornered plastic beaker</td>
			<td>Fisher Scientific</td>
			<td>14-955-111F</td>
			<td>Used to weigh mice</td>
		</tr>
		<tr>
			<td>Trypan blue</td>
			<td>VWR</td>
			<td>97063-702</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin-EDTA</td>
			<td>ATCC</td>
			<td>30-2101</td>
			<td></td>
		</tr>
		<tr>
			<td>Type IV collagenase</td>
			<td>Sigma-Aldrich</td>
			<td>C5138</td>
			<td></td>
		</tr>
		<tr>
			<td>1 cm tissue culture plates</td>
			<td>Nunclon</td>
			<td>153066</td>
			<td></td>
		</tr>
		<tr>
			<td>1 mL syringe</td>
			<td>BD</td>
			<td>309659</td>
			<td></td>
		</tr>
		<tr>
			<td>1.7 mL microcentrifuge tubes</td>
			<td>VWR</td>
			<td>87003-294</td>
			<td></td>
		</tr>
		<tr>
			<td>10 cm tissue culture plates</td>
			<td>Fisher Scientific</td>
			<td>08-772-22</td>
			<td></td>
		</tr>
		<tr>
			<td>12 well plate</td>
			<td>Corning</td>
			<td>3512</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL centrifuge tube</td>
			<td>Fisher Scientific</td>
			<td>14-959-70C</td>
			<td></td>
		</tr>
		<tr>
			<td>1X Dulbecco&#39;s Phostphate Buffered Saline (DPBS)</td>
			<td>Fisher Scientific</td>
			<td>SH30028FS</td>
			<td></td>
		</tr>
		<tr>
			<td>1X Hank&#8217;s Balanced Saline Solution (HBSS)</td>
			<td>Thermo Scientific</td>
			<td>SH3026802</td>
			<td></td>
		</tr>
		<tr>
			<td>27 g 1/2 in needles</td>
			<td>Fisher Scientific</td>
			<td>14-826-48</td>
			<td></td>
		</tr>
		<tr>
			<td>4T1 (ATCC&#174; CRL&#173;2539&#8482;)</td>
			<td>ATCC</td>
			<td>CRL-2539</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL centrifuge tube</td>
			<td>Fisher Scientific</td>
			<td>14-959-49A</td>
			<td></td>
		</tr>
		<tr>
			<td>6-Thioguanine</td>
			<td>Sigma-Aldrich</td>
			<td>A4882</td>
			<td></td>
		</tr>
		<tr>
			<td>70 &#956;M cell strainer</td>
			<td>Fisher Scientific</td>
			<td>22-363-548</td>
			<td></td>
		</tr>
		<tr>
			<td>70% ethanol</td>
			<td>Sigma Aldrich</td>
			<td>E7023</td>
			<td>Dilute to 70% with DI water</td>
		</tr>
	</tbody>
</table>

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.

This method contains simple adjustments from the Pulaski and Ostrand-Rosenberg 4T1 protocol3 and can be visualized in Figure 1. When 3 separate researchers manually counted metastatic colonies for 12 lung plates (1:10 dilution), the results were very inconsistent between different counters (Figure 2A). All researchers were directed to &#8220;count the metastatic colonies that appear as blue dots&#8221;, yet the inconsistencies demonstrate...

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

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. ...

This protocol quantifies lung metastasis, which is an aggressive and common cause of breast cancer related death, with increased precision and efficiency in a preclinical breast cancer model. Compared to the original technique, this protocol gives researchers quicker, more consistent results. It alleviates human counting error through easy-to-use computer technology.This technique can absolutely be extended to preclinical research studying the effects of breast cancer therapies on lung metastasis by allowing researchers to demonstrate decreased metastatic burden following successful treatment. Begin by labeling a 15 milliliter conical tube for the tissue sample. Then add 2.5 milliliters of type four collagenase mixture and 30 units of elastase to the tube.Move the lung to a clean 1X HBSS well and swirl it with forceps to remove any remaining blood, then transfer it to an empty 3.5 centimeter tissue culture plate. Mince the lung with scissors, then rinse the plate with 2.5 milliliters of HBSS and transfer the HBSS with the lung pieces into a prepared 15 milliliter conical tube with the collagenase and elastase cocktail. Incubate the tube for 75 minutes at four degrees Celsius on a rocker or rotating wheel.Meanwhile, label one 50 milliliter centrifuge tube and one 10 centimeter tissue culture plate for each mouse. If doing a dilution, label enough tissue culture plates for the dilutions. Bring the volume of the tube up to 10 milliliters with 1X HBSS, then pour the contents over a 70 micrometer cell strainer into the 50 milliliter conical tube.Use the plunger of a one milliliter syringe to gently grind the sample through the strainer. Centrifuge the tube for five minutes at 350 times G and discard the supernatant, then wash the pellet twice with 10 milliliters of 1X HBSS. Resuspend the pellet in 10 milliliters of 60 micromolar 6-thioguanine complete culture media, and plate the samples in the 10 centimeter cell culture plates using a dilution scheme if desired.Incubate the plates at 37 degrees Celsius and 5%carbon dioxide for five days. Pour culture media off of the plates into the appropriate waste container. To fix the cells, add five milliliters of undiluted methanol to each plate and incubate for five minutes at room temperature, making sure to swirl the methanol so that it covers the entire plate.Pour the methanol off the plates into the appropriate waste container, then rinse each plate with five milliliters of distilled water. Add five milliliters of 0.03%methylene blue per plate and incubate it for five minutes at room temperature, making sure to swirl the methylene blue solution so that it covers the entire plate. Pour the methylene blue into the appropriate waste container and rinse each plate again with five milliliters of distilled water.Turn the plate upside down and blot it against a paper towel to remove excess liquid. Place the plate on its lid and let it air dry overnight. Metastatic colonies will be blue.Once the plates have dried, they can be stored at room temperature indefinitely. Remove the labeled lids from the plates, taking care to ensure clear identification of the samples. Line up all stained lung plates on a clean, light surface.Take a picture of the collection of plates in a well-lit area, making sure to minimize reflections. Reflections in the plates will influence image analysis and should be avoided. Pay close attention to the photographs taken, and take several pictures from several angles.After photographing the plates, crop the image to exclude the lids or anything in the background. Open the image in Fiji ImageJ and change it to black and white by clicking image, adjust, and color threshold. Then select default for thresholding method, black and white for threshold color, and lab for color space.Make sure that the dark background box is not selected. The image should now be black and white. Black represents the light background, and white represents the blue metastatic colonies.Use the circle tool to select the area to be analyzed. Draw one circle to use for all of the plates to ensure that each plate is analyzed for the same sized area. Choose a size that maximizes the analyzed area on the plates while minimizing the background noise that appears on the edge of the plates.The size appears in the toolbar as it is drawn. Analyze the selected circle to determine the percentage of area that is white. Click on analyze and analyze particles, then select zero to infinity for size, zero to one for circularity, and nothing for show.Check the summarized box and hit okay. Move the circle to the next plate in the picture by grabbing it center and repeat the analysis. Copy and paste the result into a spreadsheet.The percent area, which is the percentage of the selected area that is white, represents the metastatic burden. Once all plates and images have been analyzed, average the percent area results between different images for each plate to mitigate any inconsistencies between pictures. Fiji ImageJ analysis was compared to manual counting and histopathological analysis.When three separate researchers manually counted metastatic colonies, the results were inconsistent between counters. Fiji ImageJ results were consistent between counters for each of the three images. The results from the three images and the three counters were combined for each lung plate.The results were averaged for each plate to account for the variations between the images, which provided consistent results between counters. When ranking the plates from most to least metastatic, manual counting agreed on the most confluent plate but all following ranks were inconsistent. The ranks from the average Fiji ImageJ results were much more consistent between counters.To demonstrate the importance of avoiding reflections in the images, an image with the reflection of a hand and its subsequent Fiji ImageJ analysis is shown along with an image of the same plate without a reflection. Dark blemishes from a dirty background surface or a blood sample residue on the plates can also negatively impact Fiji ImageJ analysis. This blood plate only has two metastatic colonies but the dark residue caused Fiji ImageJ to consider it as 31.6%metastatic.When attempting this protocol, remember to carefully examine pictures for reflection, use the same size circle for each plate in the image, and average the results for each plate between at least three separate images.

Research

JoVE Journal

Cancer Research

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