This work was funded by the Natural Science Foundation of China 81572599, 81773124, and 81972787; Natural Science Foundation of Tianjin City (China) 19JCYBJC27300; Tianjin People&#8217;s Hospital &#38;&#160;Nankai University Collaborative Research Grant 2016rmnk005; Fundamental Research Funds for the Central Universities, Nankai University 63191153.

1. Cell preparation
<ol>
	<li>Cell digestion and neutralization
	<ol>
		<li>Seed tumor cells (such as MDA-MB-231 cells) in a 6 well plate, and culture them in a 37 &#176;C incubator supplied with 5% CO2.</li>
		<li>Harvest cells when their density reaches about 90%. Aspirate the culture medium thoroughly and wash the cells 2x with 3 mL of phosphate buffered saline (PBS). 
		NOTE: To examine the effects of signaling pathway inhibitors (e.g., FRA1 inhibitor), or activators (e.g., STAT3 activator) on stemness features of tumor cells, tumor cells are seeded in a 6 well plate and pretreated with inhibitors or activators for a certain amount of time before harvest.</li>
		<li>Add 500 &#181;L of 0.25% trypsin-EDTA to each well of the 6 well plate, place the plate in an incubator at 37 &#176;C for 1&#8211;3 minutes (min), and gently tap the plate to detach the cells. 
		NOTE: Prolonged digestion will affect the SP profile due to changes in cell viability.</li>
		<li>Add 3 mL of PBS supplemented with 2% fetal bovine serum (FBS) to each well of the 6 well plate&#160;to terminate the digestion and gently pipette the cells up and down 3&#8211;5x to disperse the cell clumps.</li>
		<li>Add 0.5 mL of cell suspension to one well of a new 6 well plate and examine it under a microscope. If cell clumps are observed, pass the cell suspension through a 70 &#181;M cell strainer. 
		NOTE: This is an optional step.</li>
		<li>Transfer the cells to a 15 mL&#160;centrifuge tube. Centrifuge cells at 200 x g for 5 min to pellet cells. Remove the supernatant and resuspend them in 3 mL of PBS supplemented with 2% FBS. Pipette the cells up and down 3&#8211;5x to mix thoroughly.</li>
	</ol>
	</li>
	<li>Cell counts
	<ol>
		<li>Add 50 &#956;L of the cell suspension into a 1.5 mL microcentrifuge tube and mix it with 50 &#956;L trypan blue solution. Pipette 10 &#956;L of the mixture to count the number of living cells using a standard method, such as a hemocytometer.</li>
		<li>Dilute the cells in PBS supplemented with 2% FBS to a final concentration of 1 x 106 cells/mL. Add 1 mL of the cell suspension to a 5 mL polystyrene round bottom test tube and prepare two sample tubes.</li>
	</ol>
	</li>
</ol>
2. Cell staining with Hoechst 33342
<ol>
	<li>Add Hoechst 33342 to one tube to reach an appropriate final concentration. 
	NOTE: For example, the appropriate concentration of Hoechst 33342 is 3 &#181;g/mL for MDA-MB-231 cells.</li>
	<li>Add a blocker&#160;(e.g., Fumitremorgin C, Verapamil, or Reserpine) to another tube to an appropriate final concentration and incubate the tube at 37 &#176;C for 30 min before adding the same concentration of Hoechst 33342 as described in step 2.1. 
	NOTE: For MDA-MB-231 cells, the appropriate blocker is Reserpine (40 &#181;M). Reserpine is used as a blocking control to verify the absence of cells in the gated SP area.</li>
	<li>Prepare several tubes containing cells and add Hoechst 33342 to&#160;different concentration gradients. After a flow cytometry assay, choose the proper concentration according to the profile and proportion of SP. 
	NOTE: This is an optional step used to define the proper concentration of Hoechst 33342.</li>
	<li>Prepare several tubes containing cells, add the blocker to different concentration gradients, incubate the tubes at 37 &#176;C for 30 min, then add Hoechst 33342 to an appropriate concentration. After the flow cytometry assay, choose the proper concentration according to the absence of cells in the gated SP area. 
	NOTE: This is an optional step used to define the proper concentration of blocker.</li>
	<li>Place the tubes in a 37 &#176;C incubator and incubate them for 60 min, shaking the tubes every 10 min. 
	NOTE: Shaking tubes thoroughly is important for staining, because it ensures complete contact between the cells and the dye for better staining results.</li>
	<li>After the incubation, centrifuge the cells at 200 x g, 4 &#176;C for 5 min, and aspirate the supernatant carefully, because the cells form&#160;very loose and unstable pellets.</li>
	<li>Resuspend cells of each tube in 1 mL of ice-cold PBS supplemented with 2% FBS and pipette the cells up and down 3&#8211;5x to mix thoroughly. Add 1 &#956;L of 1 mg/mL propidium iodide (PI) to the suspension of each tube to identify dead cells. 
	NOTE: All procedures in this step should be performed at 4 &#176;C to inhibit the efflux of Hoechst 33342 from the tumor cells. The tubes should be protected from direct exposure to light.</li>
</ol>
3. Analysis by flow cytometry
NOTE: Instructions for use of the flow cytometer software (see Table of Materials) are described in this section and Supplementary Figures 1&#8211;10.
<ol>
	<li>In the flow cytometer software, click the FOLDER button. Click the Experiment button, then click New Experiment (Supplementary Figure 1A,B).</li>
	<li>Click the OK button. &#8220;Experiment_001&#8221; will show up under the FOLDER (Supplementary Figure 2A,B).</li>
	<li>Click the Experiment_001 button to change the folder name to a specific name (e.g., &#34;20191118-SP&#34;). Click Enter. The new name (&#34;20191118-SP&#34;) will show up under FOLDER (Supplementary Figure 3A,B).</li>
	<li>Click the New Specimen button to add a specimen to the new experiment folder (&#34;20191118-SP&#34;). Click the New Tube button to add a tube to the specimen. Click the Arrowhead button (Supplementary Figure 4A-C).</li>
	<li>Click the Parameters button and set up the parameters of the flow cytometer (Supplementary Figure 5).
	<ol>
		<li>Use a 610 nm dichroic mirror short-pass (DMSP) to separate the emission wavelengths. Use a 450/20 nm BP filter to collect the blue fluorescence and a 675 nm EFLP to collect the red fluorescence. 
		NOTE: Hoechst 33342 is excited with a UV laser at 355 nm and PI is excited at 488 nm.</li>
	</ol>
	</li>
	<li>Run the cell samples on the flow cytometer. 
	NOTE: SP cells can be sorted by fluorescence-activated cell sorting (FACS) under sterile conditions. A total of 100,000&#8211;500,000 cells should be collected for the follow-up experiments.
	<ol>
		<li>Run cells stained with Hoechst 33342 on the flow cytometer.
		<ol>
			<li>Place tubes containing cells stained with Hoechst 33342 on the cytometer.</li>
			<li>Click the Dot Plot button to display the dot plot, then click the X-axis and set it to &#8220;FSC-A&#8221;; click the Y-axis and set it to &#8220;PI-A&#8221;. Display the dot plot of forward scatter pulse area (FSC-A, X-axis set to linear mode) versus the PI fluorescence (Y-axis set to logarithmic scale). Adjust the voltages to show the living cells in the right side and the non-living cells, which are brightly&#160;stained with PI, in the upper left&#160;corner. Then, establish a polygon gate to exclude dead cells and cell debris (Figure 1A) by clicking the Polygon Gate button to gate the P1 subset, also known as FSC-A, PI-A subset (Supplementary Figure 6A,B).</li>
			<li>Click the Dot Plot button to display the dot plot, click the X-axis and set it to &#8220;FSC-A&#8221;; click the Y-axis and set it to &#8220;FSC-W&#8221;. Display the dot plot of FSC-A (X-axis) versus forward scatter pulse width (FSC-W, Y-axis). Right-click the dot plot, click the P1 button under the Show Populations button. Click the Rectangular Gate button to create a rectangular gate to gate the P2 subset (also known as FSC-A, FSC-W subset). This will exclude cells with large volumes (Supplementary Figure 7A-C and Figure 1A).</li>
			<li>Click the Dot Plot button to display the dot plot, click the X-axis and set it to &#8220;SSC-A&#8221;; click the Y-axis and set it to &#8220;SSC-W&#8221;. Display the dot plot of side scatter pulse area (SSC-A, X-axis) versus side scatter pulse width (SSC-W, Y-axis). Right-click the dot plot, and click the P2 button under Show Populations button. Then click the Rectangular Gate button to create a rectangular gate to gate the P3 subset (also known as SSC-A, SSC-W subset). This will obtain a cell population with uniform granularity (Supplementary Figure 8A-C and Figure 1A).</li>
			<li>Click the Dot Plot button to display the dot plot, click the X-axis and set it to &#8220;Hoechst Red-A&#8221;; click the Y-axis and set it to &#8220;Hoechst Blue-A&#8221;. Display the dot plot of Hoechst Red-A (X-axis) versus Hoechst Blue-A (Y-axis). Right-click the dot plot, click the P3 button under the Show Populations button. Click the Polygon Gate button to create a polygon gate to gate the P4 subset (also known as Hoechst Red-A, Hoechst Blue-A subset). Right-click the dot plot, click the Show Population Hierarchy button to show the population hierarchy. 
			NOTE: The dot plot will show three different populations: 1) a G0-G1 phase population near the center of the graph; 2) a S-G2/M phase population near the upper right corner; 3) the SP. The SP is then gated for further analysis (Supplementary Figure 9A-D and Figure 1A). If the dot plot of Hoechst Red-A versus Hoechst Blue-A does not show a&#160;SP profile similar to that shown in Figure 1A, the voltages should be adjusted until a similar profile is seen. Meanwhile, adjust all of above gates accordingly.</li>
			<li>After determining the gate region of the SP cells, click Acquire Data to collect 20,000&#8211;100,000 events from each sample to analyze the percentage of SP cells (Supplementary Figure 10).</li>
		</ol>
		</li>
		<li>Run the Hoechst 33342-stained cells treated with blocker on the flow cytometer.
		<ol>
			<li>Place tubes containing blocker on the cytometer and run cells using the same voltages and gates to further check whether the voltages and gates are selected appropriately. 
			NOTE: Compared with Hoechst 33342 staining alone, only&#160;a very small proportion of cells, if any, should appear in the gated area of the SP (Figure 1B).</li>
			<li>Collect 20,000&#8211;100,000 events from each sample to analyze the percentage of SP cells.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
4. Data analysis
NOTE: Instructions for the use of the flow cytometry analysis software (see Table of Materials) are described in this section and Supplementary Figures 11&#8211;16.
<ol>
	<li>Copy the files in fcs format to a computer, open the flow cytometry analysis software, and drag one sample file to the software (Supplementary Figure 11A,B).</li>
	<li>Gate cells and obtain the percentage of SP cells.
	<ol>
		<li>Double click this sample file, click the X-axis and set it to &#8220;FSC-A&#8221;; click the Y-axis and set it to &#8220;PI-A&#8221;. Then, create a polygon gate and click the OK button to obtain the FSC-A, PI-A subset (Supplementary Figure 12A-E).</li>
		<li>Double click the FSC-A, PI-A subset file, click the X-axis and set it to &#8220;FSC-A&#8221;; click the Y-axis and set it to &#8220;FSC-W&#8221;. Then, create a rectangular gate and click the OK button to obtain the FSC-A, FSC-W subset (Supplementary Figure 13A-E).</li>
		<li>Double click the FSC-A, FSC-W subset file, click the X-axis and set it to &#8220;SSC-A&#8221;; click the Y-axis and set it to &#8220;SSC-W&#8221;. Then, create a rectangular gate and click the OK button to obtain the SSC-A, SSC-W subset (Supplementary Figure 14A-E).</li>
		<li>Double click the SSC-A, SSC-W subset file, click the X-axis and set it to &#8220;Hoechst Red-A&#8221;; click the Y-axis and set it to &#8220;Hoechst Blue-A&#8221;. Then, create a polygon gate and click the OK button to obtain the Hoechst Red-A, Hoechst Blue-A subset (Supplementary Figure 15A-E).</li>
		<li>Open the Layout Editor by clicking the Open Layout Editor button. Drag the SSC-A, SSC-W subset file to Layout Editor, then click the Click to save layout window to file button to save the image results (Supplementary Figure 16A-C).</li>
	</ol>
	</li>
	<li>Save the workspace to keep the gating information when closing the software.</li>
	<li>Perform t-test analyses with statistical analysis software to compare the difference between two groups. A value of P &#60; 0.05 was defined as statistically significant.</li>
</ol>

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Y., Moon, J. Y., Unno, T., Cho, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Baicalein+Suppresses+Stem+Cell-Like+Characteristics+in+Radio-+and+Chemoresistant+MDA-MB-231+Human+Breast+Cancer+Cells+through+Up-Regulation+of+IFIT2.">Baicalein Suppresses Stem Cell-Like Characteristics in Radio- and Chemoresistant MDA-MB-231 Human Breast Cancer Cells through Up-Regulation of IFIT2.</a> Nutrients. 11 (3), 624 (2019).</li><li>Lee, H., Park, S., Kim, J. B., Kim, J., Kim, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Entrapped+doxorubicin+nanoparticles+for+the+treatment+of+metastatic+anoikis-resistant+cancer+cells.">Entrapped doxorubicin nanoparticles for the treatment of metastatic anoikis-resistant cancer cells.</a> Cancer Letters. 332 (1), 110-119 (2013).</li><li>Ota, 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=ADAM23+is+downregulated+in+side+population+and+suppresses+lung+metastasis+of+lung+carcinoma+cells.">ADAM23 is downregulated in side population and suppresses lung metastasis of lung carcinoma cells.</a> Cancer Science. 107 (4), 433-443 (2016).</li><li>Wei, H., 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=The+mechanisms+for+lung+cancer+risk+of+PM2.5+:+Induction+of+epithelial-mesenchymal+transition+and+cancer+stem+cell+properties+in+human+non-small+cell+lung+cancer+cells.">The mechanisms for lung cancer risk of PM2.5 : Induction of epithelial-mesenchymal transition and cancer stem cell properties in human non-small cell lung cancer cells.</a> Environmental Toxicology. 32 (11), 2341-2351 (2017).</li><li>Prasanphanich, A. F., White, D. E., Gran, M. A., Kemp, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetic+Modeling+of+ABCG2+Transporter+Heterogeneity:+A+Quantitative,+Single-Cell+Analysis+of+the+Side+Population+Assay.">Kinetic Modeling of ABCG2 Transporter Heterogeneity: A Quantitative, Single-Cell Analysis of the Side Population Assay.</a> PLoS Computational Biology. 12 (11), 1005188 (2016).</li><li>Han, H., 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=An+endogenous+inhibitor+of+angiogenesis+inversely+correlates+with+side+population+phenotype+and+function+in+human+lung+cancer+cells.">An endogenous inhibitor of angiogenesis inversely correlates with side population phenotype and function in human lung cancer cells.</a> Oncogene. 33 (9), 1198-1206 (2014).</li><li>Loebinger, M. R., Sage, E. K., Davies, D., Janes, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TRAIL-expressing+mesenchymal+stem+cells+kill+the+putative+cancer+stem+cell+population.">TRAIL-expressing mesenchymal stem cells kill the putative cancer stem cell population.</a> British Journal of Cancer. 103 (11), 1692-1697 (2010).</li><li>Chiba, T., 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=Side+population+purified+from+hepatocellular+carcinoma+cells+harbors+cancer+stem+cell-like+properties.">Side population purified from hepatocellular carcinoma cells harbors cancer stem cell-like properties.</a> Hepatology. 44 (1), 240-251 (2006).</li><li>Hirschmann-Jax, C., 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=A+distinct+"side+population"+of+cells+with+high+drug+efflux+capacity+in+human+tumor+cells.">A distinct "side population" of cells with high drug efflux capacity in human tumor cells.</a> Proceedings of the National Academy of Science of the United States of America. 101 (39), 14228-14233 (2004).</li><li>Chen, A. Y., Yu, C., Gatto, B., Liu, L. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+minor+groove-binding+ligands:+a+different+class+of+mammalian+DNA+topoisomerase+I+inhibitors.">DNA minor groove-binding ligands: a different class of mammalian DNA topoisomerase I inhibitors.</a> Proceedings of the National Academy of Science of the United States of America. 90 (17), 8131-8135 (1993).</li></ol>

The authors have nothing to disclose.

There are several key points to keep in mind for the SP assay. The first is the selection of a proper blocker, such as Verapamil or Reserpine, for each cell line, because the &#34;gate&#34; location of the SP cells is determined according to the position at which a large number of SP cells disappear after the addition of the blocker. For the MDA-MB-231 cell line, Reserpine works well. However, for other cell lines, different blockers might work better.
The second is the concentration of Hoechs...

Cancer stem cells (CSCs) are subsets of cells with self-renewal ability and multiple differentiation potential, which play a vital role in tumor growth, metastasis, and recurrence1,2. Currently, CSCs have been identified to exist in a variety of malignant tumors, including lung, brain, pancreas, prostate, breast, and liver cancers3,4,5,6,7,8,9. Identification of CSCs in these tumors is mainly based on the presence of surface marker proteins, such as high and/or low expression of CD44, CD24, CD133, and Sca-19,10, but a unique marker that can distinguish CSCs from non-CSCs has not been reported so far. Currently, several techniques are used to identify and purify CSCs in tumor tissue or tumor cell lines. These techniques are designed based on the specific properties of CSCs. Among them, assays and sorting of side population (SP) cells are two of the commonly used methods.
SP cells were originally discovered by Goodell et al.11, when they characterized hematopoietic stem cells in mouse bone marrow cells. When the mouse bone marrow cells were labeled with the fluorescent dye Hoechst 33342, a small group of Hoechst 33342 dimly-stained cells appeared in the two-dimensional dot plot of a flow cytometry assay. Hoechst 33342 is a DNA-binding dye and has at least two binding modes that lead to different spectral characteristics. When viewing fluorescence emission at two wavelengths at the same time, multiple populations can be revealed12. In their assay, the Hoechst 33342 was excited at 350 nm and the fluorescence was measured by using the 450/20 nm band-pass (BP) filter and 675 nm edge filter long-pass (EFLP)11. Compared with whole population of bone marrow cells, this group of cells was enriched with hematopoietic stem cells called SP cells11. SP cells are capable of rapidly expelling Hoechst 33342. The efflux of this dye is related to ATP-binding cassette (ABC) transporters13, which can be inhibited by some agents such as Fumitremorgin C14, Verapamil and Reserpine15,16. After that, different proportions of SP cells were detected in a variety of tissues, organs, tumor tissues, and tumor cell lines17,18,19. These SP cells have many characteristics of stem cells17,19.
This manuscript describes Hoechst 33342 labeling and staining of cultured tumor cells and the analysis of SP cells by flow cytometry. Moreover, optimization of the Hoechst 33342 concentration and the proper blocker selection for a specific tumor cell line using this approach are shown. Finally, the effects of stemness promotion or inhibition signals on the proportion of SP in tumor cells are demonstrated. The experimental examples demonstrate that analysis of SP can be used to explore the effects of various signals, such as gene expression, small inhibitors, activators, cytokines, and chemokines, on tumor stemness. Compared to other methods for isolation and purification of CSCs, such as sorting of CD44+/CD24&#8211; population, aldehyde dehydrogenase (ALDH) analysis, and tumor sphere formation assays, this method is easier for manipulation and is cost-effective.

<table>
	<tbody>
		<tr>
			<td>6 well cell culture plate</td>
			<td>CORNING</td>
			<td>3516</td>
			<td>9.5 cm2 (approx.)</td>
		</tr>
		<tr>
			<td>Colivelin</td>
			<td>MCE</td>
			<td>HY-P1061A</td>
			<td>Ser-Ala-Leu-Leu-Arg-Ser-Ile-Pro-Ala-Pro-Ala-Gly-Ala-Ser-Arg-Leu-Leu-Leu-Leu-Thr-Gly-Glu-Ile-Asp-Leu-Pro</td>
		</tr>
		<tr>
			<td>Fetal bovine serum (FBS)</td>
			<td>Biological Industries (BIOIND)</td>
			<td>04-001-1ACS</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cytometer</td>
			<td>BD Biosciences</td>
			<td>BD LSRFortessa</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cytometer software</td>
			<td>BD Biosciences</td>
			<td>FACSDiva</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cytometry analysis software</td>
			<td>BD Biosciences</td>
			<td>FlowJo</td>
			<td></td>
		</tr>
		<tr>
			<td>Hoechst33342</td>
			<td>Sigma-Aldrich</td>
			<td>B2261</td>
			<td>bisBenzimide H 33342 trihydrochloride</td>
		</tr>
		<tr>
			<td>Polystyrene round bottom test tube</td>
			<td>CORNING</td>
			<td>352054</td>
			<td>12 x 75 mm, 5mL</td>
		</tr>
		<tr>
			<td>Propidium iodide (PI)</td>
			<td>Sigma-Aldrich</td>
			<td>P4170</td>
			<td>3,8-Diamino-5-[3-(diethylmethylammonio)propyl]-6-phenylphenanthridinium diiodide</td>
		</tr>
		<tr>
			<td>Reserpine</td>
			<td>Sigma-Aldrich</td>
			<td>83580</td>
			<td>(3&#946;, 16&#946;, 17&#945;, 18&#946;, 20&#945;)-11,17-Dimethoxy-18-[(3,4,5-trimethoxybenzoyl)oxy]yohimban-16-carboxylic acid methyl ester</td>
		</tr>
		<tr>
			<td>SKLB816</td>
			<td>Provided by Dr. Shengyong Yang, Sichuan University</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin-EDTA (0.25%), phenol red</td>
			<td>Gibco</td>
			<td>25200072</td>
			<td></td>
		</tr>
		<tr>
			<td>Verapamil hydrochloride</td>
			<td>Sigma-Aldrich</td>
			<td>V4629</td>
			<td>5-[N-(3,4-Dimethoxyphenylethyl)methylamino]-2-(3,4-dimethoxyphenyl)-2-isopropylvaleronitrile hydrochloride</td>
		</tr>
	</tbody>
</table>

analysis of side population in solid tumor cell lines

Cancer stem cells (CSCs) are an important cause of tumor growth, metastasis, and recurrence. Isolation and identification of CSCs are of great significance for tumor research. Currently, several techniques are used for the identification and purification of CSCs from tumor tissues and tumor cell lines. Separation and analysis of side population (SP) cells are two of the commonly used methods. The methods rely on the ability of CSCs to rapidly expel fluorescent dyes, such as Hoechst 33342. The efflux of the dye is associated with the ATP-binding cassette (ABC) transporters and can be inhibited by ABC transporter inhibitors. Methods for staining cultured tumor cells with Hoechst 33342 and analyzing the proportion of their SP cells by flow cytometry are described. This assay is convenient, fast, and cost-effective. Data generated in this assay can contribute to a better understanding of the effect of genes or other extracellular and intracellular signals on the stemness properties of tumor cells.

Four experimental SP analyses were performed according to this method. In the first one, we detected the proportion of SP cells in MDA-MB-231, which is a triple negative human breast cancer cell line, under normal conditions. After cell counting, Hoechst 33342 was added into one tube containing 1 x 106 cells to a final concentration of 3 &#181;g/mL. Reserpine and Hoechst 33342 were added to another tube to&#160;final concentrations of 40 &#181;M and 3 &#181;g/mL, respectively. PI was added to both tubes. The d...

Watch this Scientific Journal Video about Analysis of Side Population in Solid Tumor Cell Lines at JoVE.com

Analysis of Side Population in Solid Tumor Cell Lines

A convenient, fast, and cost-effective method to measure the proportion of side population cells in solid tumor cell lines is presented.

Cancer stem cells (CSCs) are an important cause of tumor growth, metastasis, and recurrence. Isolation and identification of CSCs are of great ...

analysis-of-side-population-in-solid-tumor-cell-lines

Universidad de Cartagena UDEC

Research

JoVE Journal

Cancer Research

4.3K Views.  Nankai University. A convenient, fast, and cost-effective method to measure the proportion of side population cells in solid tumor cell lines is presented.

Video: Analysis of Side Population in Solid Tumor Cell Lines

Harnessing the DNA Dye-triggered Side Population Phenotype to Detect and Purify Cancer Stem Cells from Biological Samples

Cancer is a stem cell-driven disease and eradication of these cells has become a major therapeutic goal. Deciphering vulnerabilities of Cancer Stem Cells (CSCs) and identifying suitable molecular targets relies on methods that allow their specific discrimination in heterogeneous samples such as cell lines and ex vivo tumor tissue. Flow cytometry/FACS is a powerful technology to multi-parametrically dissect biological samples at the single cell level and is to date the method of choice to recover live cells for downstream analyses. Surface markers such as CD44 and CD133 as well as detection of aldehyde dehydrogenase enzymatic activity have often been used to define and sort out CSCs from tumor samples by FACS. A complementary approach, depicted here in methodological detail, makes use of functional dye extrusion by ABC drug transporters, which identifies a distinct population of fluorescence-dim cells commonly referred to as side population (SP). SP&#160;cancer cells exhibit canonical stem cell characteristics and can be abrogated and functionally confirmed using agents that inhibit the dye-extruding drug transporter (most frequently ABCB1/P-glycoprotein/MDR1/CD243 and ABCG2/Bcrp1/CD338). Moreover, the SP&#160;assay is compatible with other flow cytometric evaluations such as staining of surface antigens, aldehyde dehydrogenase detection and dead cell discrimination (e.g., with 7-AAD or propidium iodide (PI)). Thus, we describe a valuable and broadly applicable method for CSC identification, isolation and sub-characterization mechanistically based on a functional, rather than a phenotypic parameter. Although originally performed with Hoechst 33342 as triggering dye, we here focus on the more recent Violet dye-based SP phenotype that is resolvable on any flow cytometer equipped with a violet laser source.

Methods allowing the characterization and isolation of stem cell populations from biological samples are critical for the advance of stem cell-targeted treatments in cancer and beyond. Here, we provide a detailed protocol for cancer stem cell isolation using the dye-triggered side population phenotype.

Cancer is a stem cell-driven disease and eradication of these cells has become a major therapeutic goal. Deciphering vulnerabilities of Cancer Stem Cells ...

Conditional Knockdown of Gene Expression in Cancer Cell Lines to Study the Recruitment of Monocytes/Macrophages to the Tumor Microenvironment

siRNA and shRNA-mediated knock down (KD) methods of regulating gene expression are invaluable tools for understanding gene and protein function. However, in the case that the KD of the protein of interest has a lethal effect on cells or the anticipated effect of the KD is time-dependent, unconditional KD methods are not appropriate. Conditional systems are more suitable in these cases and have been the subject of much interest. These include Ecdysone-inducible overexpression systems, Cytochrome P-450 induction system1, and the tetracycline regulated gene expression systems. 
The tetracycline regulated gene expression system enables reversible control over protein expression by induction of shRNA expression in the presence of tetracycline. In this protocol, we present an experimental design using functional Tet-ON system in human cancer cell lines for conditional regulation of gene expression. We then demonstrate the use of this system in the study of tumor cell-monocyte interaction.

This protocol serves as a scheme for setting up a functional Tet-ON system in cancer cell lines and its subsequent use, in particular for studying the role of tumor cell-derived proteins in recruitment of monocytes/macrophages to the tumor microenvironment.

siRNA and shRNA-mediated knock down (KD) methods of regulating gene expression are invaluable tools for understanding gene and protein function. However, ...

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissues are widely used for genetic testing. However, FFPE DNA is generally damaged and fragmented during the fixation process with formalin. Therefore, FFPE DNA is sometimes not adequate for genetic testing because of low quality and quantity of DNA. Here we present a method of touch imprint cytology (TIC) to obtain genomic DNA from cancer cells, which can be observed under a microscope. Cell morphology and cancer cell numbers can be evaluated using TIC specimens. Furthermore, the extraction of genomic DNA from TIC samples can be completed within two days. The total amount and quality of TIC DNA obtained using this method was higher than that of FFPE DNA. This rapid and simple method allows researchers to obtain high-quality DNA for genetic testing (e.g., next generation sequencing analysis, digital PCR, and quantitative real time PCR) and to shorten the turnaround time for reporting results.

Obtaining high-quality genomic DNA from tumor tissues is an essential first step for analyzing genetic alterations using next generation sequencing. In this article, we present a simple and rapid method to enrich tumor cells and obtain intact DNA from touch imprint cytology specimens.

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. ...

Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as tumors. Because digital polymerase chain reactions (PCR) enable the precise quantification of DNA copy number variants, they are becoming an essential tool for detecting rare genetic variations, such as drug-resistant mutations. It is expected that molecular diagnoses using digital PCR (dPCR) will be available in clinical practice in the near future; thus, how to efficiently conduct dPCR with human genetic material is a hot topic. Here, we introduce a method to detect Adenomatous polyposis coli (APC) somatic mosaicism using dPCR with the chip-in-a-tube format, which allows eight dPCR reactions to be simultaneously conducted. Care should be taken when filling and sealing the reaction mixture on the chips. This article demonstrates how to avoid the over- and underestimation of positive partitions. Furthermore, we present a simple procedure for collecting the dPCR product from the partitions on the chips, which can then be used to confirm the specific amplification. We hope that this methods report will help promote the dPCR with the chip-in-a-tube method in genetic research.

Digital polymerase chain reaction (PCR) is a useful tool for the high-sensitivity detection of single nucleotide variants and DNA copy number variants. Here, we demonstrate key considerations for measuring rare variants in the human genome using digital PCR with the chip-in-a-tube format.

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as ...

Establishment of Gastric Cancer Patient-derived Xenograft Models and Primary Cell Lines

The use of preclinical models to advance our understanding of tumor biology and investigate the efficacy of therapeutic agents is key to cancer research. Although there are many established gastric cancer cell lines and many conventional transgenic mouse models for preclinical research, the disadvantages of these in vitro and in vivo models limit their applications. Because the characteristics of these models have changed in culture, they no longer model tumor heterogeneity, and their responses have not been able to predict responses in humans. Thus, alternative models that better represent tumor heterogeneity are being developed. Patient-derived xenograft (PDX) models preserve the histologic appearance of cancer cells, retain intratumoral heterogeneity, and better reflect the relevant human components of the tumor microenvironment. However, it usually takes 4-8 months to develop a PDX model, which is longer than the expected survival of many gastric patients. For this reason, establishing primary cancer cell lines may be an effective complementary method for drug response studies. The current protocol describes methods to establish PDX models and primary cancer cell lines from surgical gastric cancer samples. These methods provide a useful tool for drug development and cancer biology research.

The current protocol describes methods to establish patient-derived xenograft (PDX) models and primary cancer cell lines from surgical gastric cancer samples. The methods provide a useful tool for drug development and cancer biology research.

The use of preclinical models to advance our understanding of tumor biology and investigate the efficacy of therapeutic agents is key to cancer research. ...

Radiosensitivity of Cancer Stem Cells in Lung Cancer Cell Lines

The presence of cancer stem cells (CSCs) has been associated with relapse or poor outcomes after radiotherapy. Studying radioresistant CSCs may provide clues to overcoming radioresistance. Voltage-gated calcium channel &#945;2&#948;1 subunit isoform 5 has been reported as a marker for radioresistant CSCs in non-small cell lung cancer (NSCLC) cell lines. Using calcium channel &#945;2&#948;1 subunit as an example of a CSC marker, methods to study the radiosensitivity of CSCs in NSCLC cell lines are presented. CSCs are sorted with putative markers by flow cytometry, and the self-renewal capacity of sorted cells is evaluated by sphere formation assay. Colony formation assay, which determines how many cells lose the ability to generate descendants forming the colony after a certain dose of radiation, is then performed to assess the radiosensitivity of sorted cells. This manuscript provides initial steps for studying the radiosensitivity of CSCs, which establishes the basis for further understanding of the underlying mechanisms.

The presence of cancer stem cells have been associated with relapse or poor outcomes after radiotherapy. This manuscript describes the methods to study the radiosensitivity of cancer stem cells in lung cancer cell lines.

The presence of cancer stem cells (CSCs) has been associated with relapse or poor outcomes after radiotherapy. Studying radioresistant CSCs may provide ...

Evaluating Cell Death Using Cell-Free Supernatant of Probiotics in Three-Dimensional Spheroid Cultures of Colorectal Cancer Cells

This manuscript describes a protocol to evaluate cancer cell deaths in three dimensional (3D) spheroids of multicellular types of cancer cells using supernatants from Lactobacillus fermentum cell culture, considered as probiotics cultures. The use of 3D cultures to test Lactobacillus cell-free supernatant (LCFS) are a better option than testing in 2D monolayers, especially as L. fermentum can produce anti-cancer effects within the gut. L. fermentum supernatant was identified to possess increased anti-proliferative effects against several colorectal cancer (CRC) cells in 3D culture conditions. Interestingly, these effects were strongly related to the culture model, demonstrating the notable ability of L. fermentum to induce cancer cell death. Stable spheroids were generated from diverse CRCs (colorectal cancer cells) using the protocol presented below. This protocol of generating 3D spheroid is time saving and cost effective. This system was developed to easily investigate the anti-cancer effects of LCFS in multiple types of CRC spheroids. As expected, CRC spheroids treated with LCFS strongly induced cell death during the experiment and expressed specific apoptosis molecular markers as analyzed by qRT-PCR, western blotting, and FACS analysis. Therefore, this method is valuable for exploring cell viability and evaluating the efficacy of anti-cancer drugs.

Here methods are presented to understand anti-cancer effects of Lactobacillus cell-free supernatant (LCFS). Colorectal cancer cell lines show cell deaths when treated with LCFS in 3D cultures. The process of generating spheroids can be optimized depending on the scaffold and the analysis methods presented are useful for evaluating the involved signaling pathways.

This manuscript describes a protocol to evaluate cancer cell deaths in three dimensional (3D) spheroids of multicellular types of cancer cells using ...

Circulating Tumor Cell Lines: an Innovative Tool for Fundamental and Translational Research

Metastasis is a leading cause of cancer death. Despite improvements in treatment strategies, metastatic cancer has a poor prognosis. We thus face an urgent need to understand the mechanisms behind metastasis development, and thus to propose efficient treatments for advanced cancer. Metastatic cancers are hard to treat, as biopsies are invasive and inaccessible. Recently, there has been considerable interest in liquid biopsies including both cell-free circulating deoxyribonucleic acid (DNA) and circulating tumor cells from peripheral blood and we have established several circulating tumor cell lines from metastatic colorectal cancer patients to participate in their characterization. Indeed, to functionally characterize these rare and poorly described cells, the crucial step is to expand them. Once established, circulating tumor cell (CTC) lines can then be cultured in suspension or adherent conditions. At the molecular level, CTC lines can be further used to assess the expression of specific markers of interest (such as differentiation, epithelial or cancer stem cells) by immunofluorescence or cytometry analysis. In addition, CTC lines can be used to assess drug sensitivity to gold-standard chemotherapies as well as to targeted therapies. The ability of CTC lines to initiate tumors can also be tested by subcutaneous injection of CTCs in immunodeficient mice.
Finally, it is possible to test the role of specific genes of interest that might be involved in cancer dissemination by editing CTC genes, by short hairpin ribonucleic acid (shRNA) or Crispr/Cas9. Modified CTCs can thus be injected into immunodeficient mouse spleens, to experimentally mimic part of the metastatic development process in vivo.
In conclusion, CTC lines are a precious tool for future research and for personalized medicine, where they will allow prediction of treatment efficiency using the very cells that are originally responsible for metastasis.

Culturing CTCs allows a deeper functional characterization of cancer, through assaying specific marker expression, and assessing drug resistance and the ability to colonize the liver among other possibilities. Overall, CTC culture could be a promising clinical tool for personalized medicine to improve patient outcome.

Metastasis is a leading cause of cancer death. Despite improvements in treatment strategies, metastatic cancer has a poor prognosis. We thus face an ...

Analytical Determination of Mitochondrial Function of Excised Solid Tumor Homogenates

Mitochondria are essential to the onset and progression of cancer through energy production, reactive oxygen species regulation, and macromolecule synthesis. Genetic and functional adaptations of mitochondria to the tumor environment drive proliferative and metastatic potential. The advent of DNA and RNA sequencing removed critical barriers to the evaluation of genetic mediators of tumorigenesis. However, to date, methodological approaches to evaluate tumor mitochondrial function remain elusive and require technical proficiency limiting the feasibility, ultimately diminishing diagnostic and prognostic value in both experimental and clinical settings. Here, we&#160;outline a simple and rapid method to quantify rates of oxidative phosphorylation (OXPHOS) and electron transfer (ET) capacity in freshly excised solid tumor homogenates using high-resolution respirometry. The protocol can be reproducibly applied across species and tumor types as well as adapted to evaluate a diversity of mitochondrial ET pathways. Using this protocol, we demonstrate that mice bearing a luminal B mammary cancer exhibit defective nicotinamide adenine dinucleotide-linked respiration and reliance on succinate to generate adenosine triphosphate via OXPHOS.

We developed a practical protocol and analytical approach to evaluate mitochondrial oxidative phosphorylation and electron transfer capacity in fresh tumor homogenates. This protocol can be easily adapted to survey various mitochondrial functions that contribute to cancer initiation, progression, and treatment response.

Mitochondria are essential to the onset and progression of cancer through energy production, reactive oxygen species regulation, and macromolecule ...

Generation and Expansion of Primary, Malignant Pleural Mesothelioma Tumor Lines

Current methodologies for the expansion of primary tumor cell lines from rare tumor types are lacking. This protocol describes methods to expand primary tumor cells from surgically resected, malignant pleural mesothelioma (MPM) by providing a complete overview of the process from digestion to enrichment, expansion, cryopreservation, and phenotypic characterization. In addition, this protocol introduces concepts for tumor generation that may be useful for multiple tumor types such as differential trypsinization and the impact of dissociation methods on the detection of cell surface markers for phenotypic characterization. The major limitation of this study is the selection of tumor cells that will expand in a two-dimensional (2D) culture system. Variations to this protocol, including three-dimensional (3D) culture systems, media supplements, plate coating to improve adhesion, and alternate disaggregation methods, could improve this technique and the overall success rate of establishing a tumor line. Overall, this protocol provides a base method for establishing and characterizing tumor cells from this rare tumor.

The goal of this method paper is to demonstrate a robust and reproducible methodology for the enrichment, generation, and expansion of primary tumor cell lines from surgically resected pleural mesothelioma.

Current methodologies for the expansion of primary tumor cell lines from rare tumor types are lacking. This protocol describes methods to expand primary ...