This work was conducted in the lab of Professor Kjetil Task&#233;n, and was supported by the Norwegian Cancer Society and Stiftelsen Kristian Gerhard Jebsen. Johannes Landskron and Marianne Enger are acknowledged for critical reading of the manuscript.

Blood samples were received following written informed consent from all donors. The study was approved by the Regional Committee for Medical and Health Research Ethics of South-East Norway and the research on human blood was carried out in accordance with the Declaration of Helsinki8.
NOTE: Steps 1-3 should be performed under sterile conditions in a tissue culture hood.
1. Isolation of Peripheral Blood Mononuclear Cells (PBMCs) from CLL Patient Blood Samples
CAUTION: Human blood should be handled according to regulations for Biosafety Level 2.
<ol>
	<li>Dilute the blood 1:1 with phosphate-buffered saline (PBS: 136.9 mM NaCl, 2.7 mM KCl, 10.1 mM Na2HPO4 x 2H2O, 1.8 mM KH2PO4, pH 7.4) and transfer to 50 mL tubes (30 mL/tube).</li>
	<li>Carefully layer 10 mL of a density gradient medium (e.g., Lymphoprep) to the bottom of the tube using a 10 mL pipette.</li>
	<li>Centrifuge at 800 x g for 20 min at 4 &#176;C. The PBMCs are now visible on top of the density gradient medium layer.</li>
	<li>Use a Pasteur pipette to transfer the cells into two new 50 mL tubes. Wash twice with PBS (fill up the tubes).</li>
	<li>Centrifuge at 350 x g for 15 min. Discard the supernatant and resuspend in 3 mL of PBS.</li>
	<li>Count the cells using a preferred method.</li>
	<li>Centrifuge the cells at 350 x g for 5 min. Discard the supernatant.&#160;NOTE:&#160;Steps 1.8 to 3.2 are optional. It is possible to proceed directly to step 3.3.</li>
	<li>Resuspend the cells in fetal bovine serum (FBS) supplemented with 10% dimethyl sulfoxide (DMSO) and freeze down in suitable aliquots using cryo tubes. 
	NOTE: DMSO is toxic to the cells. Work fast once the cells are mixed with FBS/DMSO. Cells can be stored long term in liquid nitrogen.</li>
</ol>
2. Thawing of Cells
<ol>
	<li>Quickly thaw the cells in a 37 &#176;C water bath. 
	NOTE: DMSO is toxic to the cells. Work fast to limit the exposure to DMSO.</li>
	<li>Wash the cells once with 10 mL of cold Roswell Park Memorial Institute medium (RPMI 1640 with supplemental GlutaMAX, see Table of Materials).</li>
	<li>Centrifuge at 300 x g for 5 min. Discard the supernatant.</li>
	<li>Resuspend the cells in RPMI 1640 medium supplemented with sodium pyruvate, MEM non-essential amino acids and penicillin/streptomycin (added at 1x dilution according to instructions) and 10% FBS. Transfer the cells to a small cell culture flask and leave in an incubator at 5% CO2, 37 &#176;C for 1 hour to allow the cells to calibrate.</li>
</ol>
3. Preparation of Cells
<ol>
	<li>Count the viable cells using a preferred method.</li>
	<li>Transfer the cells to a 50 mL tube and centrifuge at 300 x g for 5 min. Discard the supernatant.</li>
	<li>Resuspend the cells in RPMI 1640 medium (step 2.2) supplemented with 1% FBS to no more than 50 x 106 cells/mL.</li>
	<li>Transfer the required amount of cell suspension to wells in a 96 well V-bottom plate. 
	NOTE: Number of wells corresponds to the number of conditions to be tested. Samples for a stimulation time-course are drawn from a single well. Calculate 50 &#181;L sample per time-point + 50 &#181;L of dead volume. Save samples for compensation controls (one unstained sample + one sample per barcoding dye).</li>
	<li>Transfer the 96 well plate to a pre-heated 37 &#176;C water bath. Rest the cells for 10 min.</li>
</ol>
4. Stimulation and Fixation of Cells
NOTE: Perform steps 4-8 on the lab bench (i.e., not sterile).
CAUTION: The main ingredient of Fix Buffer I is paraformaldehyde, which is toxic (inhalation and skin contact). Handle with care.
<ol>
	<li>Prepare a 96 well V-bottom plate with 60 &#181;L of Fix Buffer I per well per sample. Leave in the 37 &#176;C water bath. 
	NOTE: Cells: Fix buffer should be 1:1. In order to allow for evaporation at 37 &#176;C, the Fix buffer is initially in abundance.</li>
	<li>Optionally, treat the cells with drugs before stimulation.</li>
	<li>Transfer a 50 &#181;L control sample to the fix plate. Mix by pipetting up and down.</li>
	<li>Optionally, start the stimulation time-course by adding 10 &#181;g/mL anti-IgM to the cells. Mix by pipetting up and down.</li>
	<li>Transfer a 50 &#181;L sample to the fix plate at each time-point. Mix by pipetting up and down. 
	NOTE: Anti-IgM induced signaling is usually initiated early (minutes).</li>
	<li>Leave the fix plate at 37 &#176;C for 10 min after the last sample has been added.</li>
</ol>
5. Fluorescent Cell Barcoding (FCB)
NOTE: See Table 1 for a list of barcoding reagents.
<ol>
	<li>Wash the fixed cells 3x with PBS (fill up the wells).</li>
	<li>Centrifuge at 500 x g for 5 min. Discard the supernatant.</li>
	<li>Prepare a 96 well V-bottom plate with barcoding reagents. Pipet 5 &#181;L of each barcoding reagent per well in the number of combinations required to stain all samples following the staining matrix, e.g., in Figure 1B. Each sample will have a unique combination of different barcoding concentrations.</li>
	<li>Resuspend the cells in 190 &#181;L of PBS and transfer to the barcoding plate. Mix thoroughly. 
	NOTE: Stain one compensation sample with the highest final concentration used for each barcoding reagent and save one unstained sample.</li>
	<li>Leave the cells for 20 min at room temperature, in the dark.</li>
	<li>Wash the stained cells 2x with flow wash (PBS, 1% FBS, 0.09% sodium azide) (fill up the wells).</li>
	<li>Centrifuge at 500 x g for 5 min. Discard the supernatant.</li>
	<li>Add 190 &#181;L of flow wash to the cells and combine the barcoded samples in one 15 mL tube. Transfer each compensation control to a separate 1.7 mL tube.</li>
	<li>Centrifuge at 500 x g for 5 min. Discard the supernatant.</li>
</ol>
6. Cell Permeabilization for Intracellular Antigen Staining
CAUTION: The main ingredient of Perm Buffer III is methanol which is toxic (inhalation and skin contact) and flammable. Handle with care.
<ol>
	<li>Transfer 2 mL of Perm Buffer III to a 15 mL tube. Leave at -20 &#176;C so it is ice-cold upon use. 
	NOTE: The Perm Buffer can be left at -20 &#176;C from the start of the experiment.</li>
	<li>Add 1.5 mL of ice-cold Perm Buffer to the barcoded cell population (in a 15 mL tube) and 100 &#181;L to each compensation control (in 1.7 mL tubes) drop-wise while vortexing to avoid that the cells clump together.</li>
	<li>Transfer the cells directly to -80 &#176;C. Leave for a minimum of 30 min. 
	NOTE: It is natural to pause the experiment at this point. Cells in Perm Buffer can be stored long term at -80 &#176;C.</li>
</ol>
7. Antibody Staining
NOTE: See Table of Materials for a list of reported phospho-specific antibodies.
<ol>
	<li>Transfer the cells from -80 &#176;C to a box of ice.</li>
	<li>Wash 3x with flow wash. 
	NOTE: It is important to add flow wash in excess to see the cell pellet, e.g., add 3 mL of flow wash to the barcoded cell population and 1 mL to each compensation control.</li>
	<li>Centrifuge at 500 x g for 5 min at 4 &#176;C. Discard the supernatant.</li>
	<li>Resuspend the barcoded cell population in a volume of flow wash, which allows 25 &#181;L of cell suspension per phospho-antibody stain. Resuspend the compensation controls in 200 &#181;L of flow wash.</li>
	<li>Prepare antibodies for staining in a 96 well V-bottom plate. The final volume will be 50 &#181;L/well. Per well, add phospho-specific antibody diluted in flow wash to a final volume of 10 &#181;L, surface marker diluted in flow wash to a final volume of 15 &#181;L, and 25 &#181;L of cell suspension. 
	NOTE: Antibody dilutions should be titrated prior to the experiment. Include isotype control.</li>
	<li>Leave the cells for 30 min at room temperature, in the dark.</li>
	<li>Wash the stained cells 2x with flow wash (fill up the wells).</li>
	<li>Centrifuge at 500 x g for 5 min. Discard the supernatant.</li>
	<li>Resuspend the cells in 150 &#181;L of flow wash.</li>
</ol>
8. Preparation of Compensation Controls
<ol>
	<li>Prepare compensation controls for the antibody-conjugated fluorochromes in parallel with the antibody staining. Use compensation beads according to the vendor&#8217;s instructions.</li>
</ol>
9. Flow Cytometry Analysis
NOTE: The experiment can be run on a flow cytometer with a High Throughput Sampler (HTS).
<ol>
	<li>Optimize the photomultiplier tube (PMT) voltage with the unstained control.</li>
	<li>Run compensation controls and calculate the compensation matrix.</li>
	<li>Run samples. The event rate should be in accordance with the instrument specifications.</li>
</ol>
10. Gating Strategy and Data Analysis
<ol>
	<li>Import the FCS files from the experiment to a flow cytometry analysis software like FlowJo or Cytobank (https://cellmass.cytobank.org).</li>
	<li>Gating strategy
	<ol>
		<li>Select lymphocytes by plotting SSC-A versus FSC-A in a density dot plot.</li>
		<li>Display the lymphocytes and select the singlets by plotting SSC-A versus FSC -W.</li>
		<li>Display the single cells and gate the cell type by plotting SSC-A versus the surface marker.</li>
		<li>Display the cell type population in a Pacific Blue versus SSC-A density plot and select the different FCB populations based on their Pacific Blue staining intensity (see Figure 1A).</li>
		<li>Plot the phospho antibody channel against the FCB channel, or as a heatmap (see Figure 1A) to display the phosphorylation events.</li>
	</ol>
	</li>
	<li>Calculate phospho-signals using the inverse hyperbolic sine (arcsinh) of the MFI (median fluorescent intensity) of phospho-signal versus isotype control (basal phosphorylation levels, see Figure 1D), or of stimulated versus unstimulated cell populations (see Figure 1E).</li>
</ol>

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The author has nothing to disclose.

Phospho flow cytometry is a powerful technique to measure protein phosphorylation levels in single cells. Since the method relies on staining with antibodies, phospho flow cytometry is limited by antibody availability. Furthermore, in order to obtain reliable results, all antibodies should be titrated and verified before use. A detailed protocol for titration of phospho-specific antibodies has been described elsewhere12. During panel design, consideration of the signal-to-noise ratio is critical. ...

Phospho flow cytometry is used to analyze protein phosphorylation levels at single-cell resolution. The overall goal of the method is to map cellular signaling patterns under specified conditions. By exploiting the multiparameter capacity of flow cytometry, several signaling pathways can be analyzed simultaneously in different subsets of a heterogeneous cell population such as peripheral blood. These traits offer advantages over other antibody-based technologies such as immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), protein array, and reverse phase protein array (RPPA)1. Phospho flow cytometry can be combined with fluorescent cell barcoding (FCB), which means that individual cell samples are labeled with unique signatures of fluorescent dyes so that they can be mixed together, stained and analyzed as a single sample2. This reduces the antibody consumption, increases the data robustness through the combination of control and treated samples, and enhances the speed of acquisition. The combined FCB population can then be divided into smaller samples and stained with up to 35 distinct phospho-specific antibodies, depending on the amount of starting material. Large profiling experiments can, thereby, be run with standard cytometer hardware. Phospho flow cytometry has been applied to profile signaling pathways in patient samples from several hematological cancers including chronic lymphocytic leukemia (CLL)3,4,5, acute myeloid leukemia (AML)6 and non-Hodgkin lymphomas7. Phospho flow cytometry is thus a powerful approach to characterize signaling aberrations, identify and validate biomarkers, and assess pharmacodynamics.
Here, the optimized protocol for analysis of CLL patient samples by phospho flow cytometry is provided (Figure 1A). Examples of basal signaling characterization, anti-IgM/B cell receptor stimulation and drug perturbation are shown. A detailed description of an FCB matrix is provided. The protocol can easily be adapted to other suspension cell types.

<table>
	<tbody>
		<tr>
			<td>RPMI 1640 GlutaMAX</td>
			<td>ThermoFisher Scientific</td>
			<td>61870-010</td>
			<td>Cell culture medium</td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>ThermoFisher Scientific</td>
			<td>10270169</td>
			<td>Additive to cell culture medium</td>
		</tr>
		<tr>
			<td>Sodium pyruvate</td>
			<td>ThermoFisher Scientific</td>
			<td>11360-039</td>
			<td>Additive to cell culture medium</td>
		</tr>
		<tr>
			<td>MEM non-essential amino acids</td>
			<td>ThermoFisher Scientific</td>
			<td>11140-035</td>
			<td>Additive to cell culture medium</td>
		</tr>
		<tr>
			<td>Lymphoprep</td>
			<td>Alere Technologies AS</td>
			<td>1114547</td>
			<td>Density gradient medium</td>
		</tr>
		<tr>
			<td>Anti-IgM</td>
			<td>Southern Biotech</td>
			<td>2022-01</td>
			<td>For stimulation of the B cell receptor</td>
		</tr>
		<tr>
			<td>BD Phosflow Fix Buffer I</td>
			<td>BD</td>
			<td>557870</td>
			<td>Fixation buffer</td>
		</tr>
		<tr>
			<td>BD Phosflow Perm Buffer III</td>
			<td>BD</td>
			<td>558050</td>
			<td>Permeabilization buffer</td>
		</tr>
		<tr>
			<td>Alexa Fluor 488 5-TFP</td>
			<td>ThermoFisher Scientific</td>
			<td>A30005</td>
			<td>Barcoding reagent</td>
		</tr>
		<tr>
			<td>Pacific Blue Succinimidyl Ester</td>
			<td>ThermoFisher Scientific</td>
			<td>P10163</td>
			<td>Barcoding reagent</td>
		</tr>
		<tr>
			<td>Pacific Orange Succinimidyl Ester, Triethylammonium Salt</td>
			<td>ThermoFisher Scientific</td>
			<td>P30253</td>
			<td>Barcoding reagent</td>
		</tr>
		<tr>
			<td>Compensation beads</td>
			<td>Defined by user</td>
			<td></td>
			<td>Correct species reactivity</td>
		</tr>
		<tr>
			<td>Falcon tubes</td>
			<td>Defined by user</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf tubes</td>
			<td>Defined by user</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>96 well V-bottom plates</td>
			<td>Defined by user</td>
			<td></td>
			<td>Compatible with the flow cytometer</td>
		</tr>
		<tr>
			<td>Centrifuges</td>
			<td>Defined by user</td>
			<td></td>
			<td>For Eppendorf tubes, Falcon tubes and plates</td>
		</tr>
		<tr>
			<td>Water bath</td>
			<td>Defined by user</td>
			<td></td>
			<td>Temperature regulated</td>
		</tr>
		<tr>
			<td>Flow cytometer</td>
			<td>Defined by user</td>
			<td></td>
			<td>With High Throughput Sampler (HTS)</td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Antigen</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>AKT (pS473)</td>
			<td>Cell Signaling Technologies</td>
			<td>4075</td>
			<td>Clone: D9E 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Parente-Ribes et al., 2016, Spleen tyrosine kinase inhibitors reduce&#8230;, Haematologica, 101(2):e59-62 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9</td>
		</tr>
		<tr>
			<td>ATF-2 (pT71)</td>
			<td>Santa Cruz Biotechnology</td>
			<td>sc-8398</td>
			<td>Clone: F-1 
			Reference: Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>BLNK (pY84)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558443</td>
			<td>Clone: J117-1278 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Parente-Ribes et al., 2016, Spleen tyrosine kinase inhibitors reduce&#8230;, Haematologica, 101(2):e59-62 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9 
			Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>Btk (pY223)/Itk (pY180)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>564846</td>
			<td>Clone: N35-86 
			Reference: Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>Btk (pY551)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558129</td>
			<td>Clone: 24a/BTK (Y551)&#160; 
			Reference: Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9</td>
		</tr>
		<tr>
			<td>Btk (pY551)/Itk (pY511)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558134</td>
			<td>Clone: 24a/BTK (Y551)&#160; 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Parente-Ribes et al., 2016, Spleen tyrosine kinase inhibitors reduce&#8230;, Haematologica, 101(2):e59-62</td>
		</tr>
		<tr>
			<td>CD3&#950; (pY142)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558489</td>
			<td>Clone: K25-407.69 
			Reference: Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410</td>
		</tr>
		<tr>
			<td>Histone H3 (pS10)</td>
			<td>Cell Signaling Technologies</td>
			<td>9716</td>
			<td>Clone: D2C8 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284</td>
		</tr>
		<tr>
			<td>I&#954;B&#945;</td>
			<td>Cell Signaling Technologies</td>
			<td>5743</td>
			<td>Clone: L35A5 
			Reference: Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>LAT (pY171)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558518</td>
			<td>Clone: I58-1169 
			Reference: Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410</td>
		</tr>
		<tr>
			<td>Lck (pY505)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558577</td>
			<td>Clone: 4/LCK-Y505&#160; 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284</td>
		</tr>
		<tr>
			<td>MEK1 (pS298)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>560043</td>
			<td>Clone: J114-64 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410</td>
		</tr>
		<tr>
			<td>NF-&#954;B p65 (pS529)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558422</td>
			<td>Clone: K10-895.12.50 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>NF-&#954;B p65 (pS536)</td>
			<td>Cell Signaling Technologies</td>
			<td>4887</td>
			<td>Clone: 93H1 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9</td>
		</tr>
		<tr>
			<td>p38 MAPK (pT180/Y182)</td>
			<td>Cell Signaling Technologies</td>
			<td>4552</td>
			<td>Clone: 28B10 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>p44/42 MAPK (pT202/Y204)</td>
			<td>Cell Signaling Technologies</td>
			<td>4375</td>
			<td>Clone: E10 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Parente-Ribes et al., 2016, Spleen tyrosine kinase inhibitors reduce&#8230;, Haematologica, 101(2):e59-62 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>p53 (pS15)</td>
			<td>Cell Signaling Technologies</td>
			<td>NN</td>
			<td>Clone: 16G8 
			Reference: Irish et al., 2007, Flt3 Y591 duplication and Bcl-2 overexpression&#8230;, Blood, 109(6):2589-96</td>
		</tr>
		<tr>
			<td>p53 (pS20)</td>
			<td>Cell Signaling Technologies</td>
			<td>NN</td>
			<td>Clone: Polyclonal 
			Reference: Irish et al., 2007, Flt3 Y591 duplication and Bcl-2 overexpression&#8230;, Blood, 109(6):2589-96</td>
		</tr>
		<tr>
			<td>p53 (pS37)</td>
			<td>Cell Signaling Technologies</td>
			<td>NN</td>
			<td>Clone: Polyclonal 
			Reference: Irish et al., 2007, Flt3 Y591 duplication and Bcl-2 overexpression&#8230;, Blood, 109(6):2589-96</td>
		</tr>
		<tr>
			<td>p53 (pS46)</td>
			<td>Cell Signaling Technologies</td>
			<td>NN</td>
			<td>Clone: Polyclonal 
			Reference: Irish et al., 2007, Flt3 Y591 duplication and Bcl-2 overexpression&#8230;, Blood, 109(6):2589-96</td>
		</tr>
		<tr>
			<td>p53 (pS392)</td>
			<td>Cell Signaling Technologies</td>
			<td>NN</td>
			<td>Clone: Polyclonal 
			Reference: Irish et al., 2007, Flt3 Y591 duplication and Bcl-2 overexpression&#8230;, Blood, 109(6):2589-96</td>
		</tr>
		<tr>
			<td>PLC&#947;2 (pY759)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558498</td>
			<td>Clone: K86-689.37 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>Rb (pS807/pS811)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558590</td>
			<td>Clone: J112-906 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>S6-Ribos. Prot. (pS235/236)</td>
			<td>Cell Signaling Technologies</td>
			<td>4851</td>
			<td>Clone: D57.2.2E 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284</td>
		</tr>
		<tr>
			<td>SAPK/JNK (pT183/Y185)</td>
			<td>Cell Signaling Technologies</td>
			<td>9257</td>
			<td>Clone: G9 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Pollheimer et al., 2013, Interleukin-33 drives a proinflammatory endothelial&#8230;, Arterioscler Thromb Vasc Biol, 33(2):e47-55</td>
		</tr>
		<tr>
			<td>SLP76 (pY128)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>558438</td>
			<td>Clone: J141-668.36.58&#160; 
			Reference: Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410</td>
		</tr>
		<tr>
			<td>STAT1 (pY701)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>612597</td>
			<td>Clone: 4a&#160; 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>STAT3 (pY705)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>557815</td>
			<td>Clone: 4/P-STAT3 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284</td>
		</tr>
		<tr>
			<td>STAT4 (pY693)</td>
			<td>Zymed/ThermoFisher Scientific</td>
			<td>71-7900</td>
			<td>Clone: Polyclonal 
			Reference: Uzel et al., 2001, Detection of intracellular phosphorylated STAT-4 by flow cytometry, Clin Immunol, 100(3): 270-6</td>
		</tr>
		<tr>
			<td>STAT5 (pY694)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>612599</td>
			<td>Clone: 47/Stat5(pY694) 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
		<tr>
			<td>STAT6 (pY641)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>612601</td>
			<td>Clone: 18/P-Stat6 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284</td>
		</tr>
		<tr>
			<td>SYK (pY525/Y526)</td>
			<td>Cell Signaling Technologies</td>
			<td>12081</td>
			<td>Clone: C87C1 
			Reference: Myhrvold et al., 2018, Single cell profiling of phospho-protein levels in.., Oncotarget, 9(10):9273-9284 
			Parente-Ribes et al., 2016, Spleen tyrosine kinase inhibitors reduce&#8230;, Haematologica, 101(2):e59-62</td>
		</tr>
		<tr>
			<td>ZAP70/SYK (pY319/Y352)</td>
			<td>Beckton Dickinson Pharmingen</td>
			<td>557817</td>
			<td>Clone: 17A/P-ZAP70 
			Reference: Sk&#229;nland et al., 2014, T-cell co-stimulation through the CD2 and CD28&#8230;, Biochem J, 460(3):399-410 
			Kalland et al., 2012, Modulation of proximal signaling in normal and transformed&#8230;, Exp Cell Res, 318(14):1611-9 
			Myklebust et al., 2017, Distinct patterns of B-cell receptor signaling in&#8230;, Blood, 129(6): 759-770</td>
		</tr>
	</tbody>
</table>

phospho flow cytometry with fluorescent cell barcoding for single cell signaling analysis and biomarker discovery

Aberrant cell signaling plays a central role in cancer development and progression. Most novel targeted therapies are indeed directed at proteins and protein functions, and cell signaling aberrations may therefore serve as biomarkers to indicate personalized treatment options. As opposed to DNA and RNA analyses, changes in protein activity can more efficiently evaluate the mechanisms underlying drug sensitivity and resistance. Phospho flow cytometry is a powerful technique that measures protein phosphorylation events at the cellular level, an important feature that distinguishes this method from other antibody-based approaches. The method allows for simultaneous analysis of multiple signaling proteins. In combination with fluorescent cell barcoding, larger medium- to high-throughput data-sets can be acquired by standard cytometer hardware in short time. Phospho flow cytometry has applications both in studies of basic biology and in clinical research, including signaling analysis, biomarker discovery and assessment of pharmacodynamics. Here, a detailed experimental protocol is provided for phospho flow analysis of purified peripheral blood mononuclear cells, using chronic lymphocytic leukemia cells as an example.

The main steps of the phospho flow cytometry protocol are illustrated in Figure 1A. In the presented example, CLL cells were stained with the barcoding reagent Pacific Blue at four dilutions. Three-dimensional barcoding can be performed by combining three barcoding dyes, as illustrated in Figure 1B. The individual samples are then deconvoluted by subsequent gating on each barcoding reagent versus SSC-A (<strong class="xf...

Watch this Scientific Journal Video about Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery at JoVE.com

Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery

Here, a protocol for medium- to high-throughput analysis of protein phosphorylation events at the cellular level is presented. Phospho flow cytometry is a powerful approach to characterize signaling aberrations, identify and validate biomarkers, and assess pharmacodynamics.

Aberrant cell signaling plays a central role in cancer development and progression. Most novel targeted therapies are indeed directed at proteins and ...

phospho-flow-cytometry-with-fluorescent-cell-barcoding-for-single

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21.1K Views.  University of Oslo. Here, a protocol for medium- to high-throughput analysis of protein phosphorylation events at the cellular level is presented. Phospho flow cytometry is a powerful approach to characterize signaling aberrations, identify and validate biomarkers, and assess pharmacodynamics.

Video: Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery

Target Cell Pre-enrichment and Whole Genome Amplification for Single Cell Downstream Characterization

Rare target cells can be isolated from a high background of non-target cells using antibodies specific for surface proteins of target cells. A recently developed method uses a medical wire functionalized with anti-epithelial cell adhesion molecule (EpCAM) antibodies for in vivo isolation of circulating tumor cells (CTCs)1. A patient-matched cohort in non-metastatic prostate cancer showed that the in vivo isolation technique resulted in a higher percentage of patients positive for CTCs as well as higher CTC counts as compared to the current gold standard in CTC enumeration. As cells cannot be recovered from current medical devices, a new functionalized wire (referred to as Device) was manufactured allowing capture and subsequent detachment of cells by enzymatic treatment. Cells are allowed to attach to the Device, visualized on a microscope and detached using enzymatic treatment. Recovered cells are cytocentrifuged onto membrane-coated slides and harvested individually by means of laser microdissection or micromanipulation. Single-cell samples are then subjected to single-cell whole genome amplification allowing multiple downstream analysis including screening and target-specific approaches. The procedure of isolation and recovery yields high quality DNA from single cells and does not impair subsequent whole genome amplification (WGA). A single cell&#39;s amplified DNA can be forwarded to screening and/or targeted analysis such as array comparative genome hybridization (array-CGH) or sequencing. The device allows ex vivo isolation from artificial rare cell samples (i.e. 500 target cells spiked into 5 mL of peripheral blood). Whereas detachment rates of cells are acceptable (50 - 90%), the recovery rate of detached cells onto slides spans a wide range dependent on the cell line used (&#60;10 - &#62;50%) and needs some further attention. This device is not cleared for the use in patients.

This protocol is to recover and prepare rare target cells from a mixture with non-target background cells for molecular genetic characterization at the single-cell level. DNA quality is equal to non-treated single cells and allows for single-cell application (both screening based and targeted analysis).

Rare target cells can be isolated from a high background of non-target cells using antibodies specific for surface proteins of target cells. A recently ...

Flow Cytometric Analysis of Mitochondrial Reactive Oxygen Species in Murine Hematopoietic Stem and Progenitor Cells and MLL-AF9 Driven Leukemia

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from healthy mice as well as mice with AML driven by MLL-AF9. Specifically, we describe a two-step cell staining process, whereby healthy or leukemia BM cells are first stained with a fluorogenic dye that detects mitochondrial superoxides, followed by staining with fluorochrome-linked monoclonal antibodies that are used to distinguish various healthy and malignant hematopoietic progenitor populations. We also provide a strategy for acquiring and analyzing the samples by flow cytometry. The entire protocol can be carried out in a timeframe as short as 3-4 h. We also highlight the key variables to consider as well as the advantages and limitations of monitoring ROS production in the mitochondrial compartment of live hematopoietic and leukemia stem and progenitor subpopulations using fluorogenic dyes by flow cytometry. Furthermore, we present data that mitochondrial ROS abundance varies among distinct healthy HSPC sub-populations and leukemia progenitors and discuss the possible applications of this technique in hematologic research.

We describe a method for using multiparameter flow cytometry to detect mitochondrial reactive oxygen species (ROS) in murine healthy hematopoietic stem and progenitor cells (HSPCs) and leukemia cells from a mouse model of acute myeloid leukemia (AML) driven by MLL-AF9.

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from ...

Characterize Disease-related Mutants of RAF Family Kinases by Using a Set of Practical and Feasible Methods

The rapidly accelerated fibrosarcoma (RAF) family kinases play a central role in cell biology and their dysfunction leads to cancers and developmental disorders. A characterization of disease-related RAF mutants will help us select appropriate therapeutic strategies for treating these diseases. Recent studies have shown that RAF family kinases have both catalytic and allosteric activities, which are tightly regulated by dimerization. Here, we constructed a set of practical and feasible methods to determine the catalytic and allosteric activities and the relative dimer affinity/stability of RAF family kinases and their mutants. Firstly, we amended the classical in vitro kinase assay by reducing the detergent concentration in buffers, utilizing a gentle quick wash procedure, and employing a glutathione S-transferase (GST) fusion to prevent RAF dimers from dissociating during purification. This enables us to measure the catalytic activity of constitutively active RAF mutants appropriately. Secondly, we developed a novel RAF co-activation assay to evaluate the allosteric activity of kinase-dead RAF mutants by using N-terminal truncated RAF proteins, eliminating the requirement of active Ras in current protocols and thereby achieving a higher sensitivity. Lastly, we generated a unique complementary split luciferase assay to quantitatively measure the relative dimer affinity/stability of various RAF mutants, which is more reliable and sensitive compared to the traditional co-immunoprecipitation assay. In summary, these methods have the following advantages: (1) user-friendly; (2) able to carry out effectively without advanced equipment; (3) cost-effective; (4) highly sensitive and reproducible.

In this article, we presented a set of practical and feasible methods for characterizing disease-related mutants of RAF family kinases, which include in vitro kinase assay, RAF co-activation assay, and complementary split luciferase assay.

The rapidly accelerated fibrosarcoma (RAF) family kinases play a central role in cell biology and their dysfunction leads to cancers and developmental ...

Cell Cycle-specific Measurement of &#947;H2AX and Apoptosis After Genotoxic Stress by Flow Cytometry

The presented method or slightly modified versions have been devised to study specific treatment responses and side effects of various anti-cancer treatments as used in clinical oncology. It enables a quantitative and longitudinal analysis of the DNA damage response after genotoxic stress, as induced by radiotherapy and a multitude of anti-cancer drugs. The method covers all stages of the DNA damage response, providing endpoints for induction and repair of DNA double-strand breaks (DSBs), cell cycle arrest and cell death by apoptosis in case of repair failure. Combining these measurements provides information about cell cycle-dependent treatment effects and thus allows an in-depth study of the interplay between cellular proliferation and coping mechanisms against DNA damage. As the effect of many cancer therapeutics including chemotherapeutic agents and ionizing radiation is limited to or strongly varies according to specific cell cycle phases, correlative analyses rely on a robust and feasible method to assess the treatment effects on the DNA in a cell cycle-specific manner. This is not possible with single-endpoint assays and an important advantage of the presented method. The method is not restricted to any particular cell line and has been thoroughly tested in a multitude of tumor and normal tissue cell lines. It can be widely applied as a comprehensive genotoxicity assay in many fields of oncology besides radio-oncology, including environmental risk factor assessment, drug screening and evaluation of genetic instability in tumor cells.

The presented method combines the quantitative analysis of DNA double-strand breaks (DSBs), cell cycle distribution and apoptosis to enable cell cycle-specific evaluation of DSB induction and repair as well as the consequences of repair failure.

The presented method or slightly modified versions have been devised to study specific treatment responses and side effects of various anti-cancer ...

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 ...

Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be involved in differentially regulating cancer metastatic cascade genes and gene products dependent on the cancer type, tissue, and individual patient characteristics. These represent potentially important targets for genetic therapeutics and personalized medicine approaches. The development of rapid screening platforms is essential for the identification of these genetic targets.
The chick chorioallantoic membrane (CAM) is a highly vascularized, collagen rich membrane located under the eggshell that allows for gas exchange in the developing embryo. Due to the location and vascularization of the CAM, we developed it as an intravital human cancer metastasis model that allows for robust human cancer cell xenografting and real-time imaging of cancer cell interactions with the collagen rich matrix and vasculature. 
Using this model, a quantitative screening platform was designed for the identification of novel drivers or suppressors of cancer metastasis. We transduced a pool of head and neck HEp3 cancer cells with a complete human genome shRNA gene library, then injected the cells, at low density, into the CAM vasculature. The cells proliferated and formed single-tumor cell colonies. Individual colonies that were unable to invade into the CAM tissue were visible as a compact colony phenotype and excised for identification of the transduced shRNA present in the cells. Images of individual colonies were evaluated for their invasiveness. Multiple rounds of selections were performed to decreases the rate of false positives. Individual, isolated cancer cell clones or newly engineered clones that express genes of interest were subjected to primary tumor formation assay or cancer cell vasculature co-option analysis. In summary we present a rapid screening platform that allows for anti-metastatic target identification and intravital analysis of a dynamic and complex cascade of events.

This is an effective method to screen for suppressors or drivers of cancer metastasis. Cells, transduced with an expression library, are injected into the chicken chorioallantoic membrane vasculature to form metastatic colonies. Colonies having decreased or increased invasiveness are excised, expanded, reinjected to confirm their phenotype, and finally, analyzed using high throughput sequencing.

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be ...

Exploring the Arginine Methylome by Nuclear Magnetic Resonance Spectroscopy

Protein-bound arginine is commonly methylated in many proteins and regulates their function by altering the physicochemical properties, their interaction with other molecules, including other proteins or nucleic acids. This work presents an easily implementable protocol for quantifying arginine and its derivatives, including asymmetric and symmetric dimethylarginine (ADMA and SDMA, respectively) and monomethyl arginine (MMA). Following protein isolation from biological body fluids, tissues, or cell lysates, a simple method for homogenization, precipitation of proteins, and protein hydrolysis is described. Since the hydrolysates contain many other components, such as other amino acids, lipids, and nucleic acids, a purification step using solid-phase extraction (SPE) is essential. SPE can either be performed manually using centrifuges or a pipetting robot. The sensitivity for ADMA using the current protocol is about 100 nmol/L. The upper limit of detection for arginine is 3 mmol/L due to SPE saturation. In summary, this protocol describes a robust method, which spans from biological sample preparation to NMR-based detection, providing valuable hints and pitfalls for successful work when studying the arginine methylome.

The present protocol describes the preparation and quantitative measurement of free and protein-bound arginine and methyl-arginines by 1H-NMR spectroscopy.

Protein-bound arginine is commonly methylated in many proteins and regulates their function by altering the physicochemical properties, their interaction ...

Simultaneous Imaging and Flow-Cytometry-based Detection of Multiple Fluorescent Senescence Markers in Therapy-Induced Senescent Cancer Cells

Chemotherapeutic drugs can induce irreparable DNA damage in cancer cells, leading to apoptosis or premature senescence. Unlike apoptotic cell death, senescence is a fundamentally different machinery restraining&#160;propagation of cancer cells. Decades of scientific studies have revealed the complex pathological effects of senescent cancer cells in tumors and microenvironments that modulate cancer cells and stromal cells. New evidence suggests that senescence is a potent prognostic factor during cancer treatment, and therefore rapid and accurate detection of senescent cells in cancer samples is essential. This paper presents a method to visualize and detect therapy-induced senescence (TIS) in cancer cells. Diffuse large B-cell lymphoma (DLBCL) cell lines were treated with mafosfamide (MAF) or daunorubicin (DN) and examined for the senescence marker, senescence-associated &#946;-galactosidase (SA-&#946;-gal), the DNA synthesis marker 5-ethynyl-2&#8242;-deoxyuridine (EdU), and the DNA damage marker gamma-H2AX (&#947;H2AX). Flow cytometer imaging can help generate high-resolution single-cell images in a short period of time to simultaneously visualize and quantify the three markers in cancer cells.

Here we present a flow cytometry-based method for visualization and quantification of multiple senescence-associated markers in single cells.

Chemotherapeutic drugs can induce irreparable DNA damage in cancer cells, leading to apoptosis or premature senescence. Unlike apoptotic cell death, ...

Far-Red Fluorescent Senescence-Associated &#946;-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry

Cellular senescence is a state of proliferative arrest induced by biological damage that normally accrues over years in aging cells but may also emerge rapidly in tumor cells as a response to damage induced by various cancer treatments. Tumor cell senescence is generally considered undesirable, as senescent cells become resistant to death and block tumor remission while exacerbating tumor malignancy and treatment resistance. Therefore, the identification of senescent tumor cells is of ongoing interest to the cancer research community. Various senescence assays exist, many based on the activity of the well-known senescence marker, senescence-associated beta-galactosidase (SA-&#946;-Gal). 
Typically, the SA-&#946;-Gal assay is performed using a chromogenic substrate (X-Gal) on fixed cells, with the slow and subjective enumeration of "blue" senescent cells by light microscopy. Improved assays using cell-permeant, fluorescent SA-&#946;-Gal substrates, including C12-FDG (green) and DDAO-Galactoside (DDAOG; far-red), have enabled the analysis of living cells and allowed the use of high-throughput fluorescent analysis platforms, including flow cytometers. C12-FDG is a well-documented probe for SA-&#946;-Gal, but its green fluorescent emission overlaps with intrinsic cellular autofluorescence (AF) that arises during senescence due to the accumulation of lipofuscin aggregates. By utilizing the far-red SA-&#946;-Gal probe DDAOG, green cellular autofluorescence can be used as a secondary parameter to confirm senescence, adding reliability to the assay. The remaining fluorescence channels can be used for cell viability staining or optional fluorescent immunolabeling.
Using flow cytometry, we demonstrate the use of DDAOG and lipofuscin autofluorescence as a dual-parameter assay for the identification of senescent tumor cells. Quantitation of the percentage of viable senescent cells is performed. If desired, an optional immunolabeling step may be included to evaluate cell surface antigens of interest. Identified senescent cells can also be flow cytometrically sorted and collected for downstream analysis. Collected senescent cells can be immediately lysed (e.g., for immunoassays or 'omics analysis) or further cultured.

A protocol for fluorescent, flow cytometric quantification of senescent cancer cells induced by chemotherapy drugs in cell culture or in murine tumor models is presented. Optional procedures include co-immunostaining, sample fixation to facilitate large batch or time point analysis, and the enrichment of viable senescent cells by flow cytometric sorting.

Cellular senescence is a state of proliferative arrest induced by biological damage that normally accrues over years in aging cells but may also emerge ...

A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer

A key challenge in developing an anticancer aptamer is to efficiently determine the selectivity and specificity of the developed aptamer to the target protein. Due to its several advantages over monoclonal antibodies, aptamer development has gained enormous popularity among cancer researchers. Systematic evolution of ligands by exponential enrichment (SELEX) is the most common method of developing aptamers specific for proteins of interest. Following SELEX, a quick and efficient binding assay accelerates the process of identification, confirming the selectivity and specificity of the aptamer. 
This paper explains a step-by-step flow cytometric-based binding assay of an aptamer specific for epithelial cellular adhesion molecule (EpCAM). The transmembrane glycoprotein EpCAM is overexpressed in most carcinomas and plays roles in cancer initiation, progression, and metastasis. Therefore, it is a valuable candidate for targeted drug delivery to tumors. To evaluate the selectivity and specificity of the aptamer to the membrane-bound EpCAM, EpCAM-positive and -negative cells are required. Additionally, a non-binding EpCAM aptamer with a similar length and 2-dimensional (2D) structure to the EpCAM-binding aptamer is required. The binding assay includes different buffers (blocking buffer, wash buffer, incubation buffer, and FACS buffer) and incubation steps. 
The aptamer is incubated with the cell lines. Following the incubation and washing steps, the cells will be evaluated using a sensitive flow cytometry assay. Analysis of the results shows the binding of the EpCAM-specific aptamer to EpCAM-positive cells and not the EpCAM-negative cells. In EpCAM-positive cells, this is depicted as a band shift in the binding of the EpCAM aptamer to the right compared to the non-binding aptamer control. In EpCAM-negative cells, the corresponding bands of EpCAM-binding and -non-binding aptamers overlap. This demonstrates the selectivity and specificity of the EpCAM aptamer. While this protocol is focused on the EpCAM aptamer, the protocol is applicable to other published aptamers.

A necessary step in anticancer aptamer development is to test its binding to the target. We demonstrate a flow cytometric-based assay to study this binding, emphasizing the importance of including a negative control aptamer and cancer cells that are positive or negative for that particular protein.&#160;

A key challenge in developing an anticancer aptamer is to efficiently determine the selectivity and specificity of the developed aptamer to the target ...

Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery

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