This work was supported by The National Institutes of Health (R35GM133581 to JC) and the Cancer Center at Illinois Graduate Scholarship (awarded to SG). JC thanks the Camille and Henry Dreyfus Foundation for support. The authors thank Dr. Thomas E. Bearrood for his initial contribution to preparing stocks of AlDeSense and AlDeSense AM. We thank Mr. Oliver D. Pichardo Peguero and Mr. Joseph A. Forzano for their assistance with preparing various synthetic precursors. We thank Prof. Erik Nelson (Department of Molecular and Integrative Physiology, UIUC) for Caov-3, IGROV-1, and PEO4 cells. We thank Prof. Paul Hergenrother (Department of Chemistry, UIUC) for BG-1 cells. We thank the Core Facilities at the Carl R. Woese Institute for Genomic Biology for access to the Zeiss LSM 700 Confocal Microscope and corresponding software. We thank the Flow Cytometry Facility for access to BD LSR II CMtO Analyzer. We thank Dr. Sandra McMasters and the Cell Media Facility for assistance in preparing cell culture media.

1. Measure total ALDH1A1 activity in ovarian cancer cell homogenates via fluorimetry
<ol>
	<li>Thaw 1 &#215; 106 cells in a T25 cell culture flask in 5 mL of the following cell culture media:
	<ol>
		<li>IGROV-1 and PEO4: Roswell Park Memorial Institute (RPMI) 1640 medium with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S).</li>
		<li>BG-1 and Caov-3: Dulbecco&#39;s Modified Eagle&#39;s Medium (DMEM) with 10% FBS and 1% P/S.</li>
		<li>OVCAR-3: RPMI 1640 with 20% FBS, 1% P/S, and 0.01 mg/mL insulin.</li>
	</ol>
	</li>
	<li>Maintain the cells in an incubator at 37 &#176;C and 5% CO2 for two to three passages. Ensure the cells do not exceed 80%-90% confluency before passaging.</li>
	<li>Trypsinize the cells in 0.25% trypsin for 10 min, count them using an automated cell counter, and pellet 1 &#215; 107 cells via centrifugation (180 &#215; g) at 25 &#176;C for 5 min.</li>
	<li>Remove the supernatant carefully via aspiration, wash the pellet by resuspending the cells in 1 mL of 1x PBS, and re-pellet the cells via centrifugation under the same conditions as described in step 4.</li>
	<li>Resuspend the cells in a solution of 1x protease inhibitor in 1x PBS. Use 1 mL of this solution per 2.5 &#215; 106 cells.</li>
	<li>Sonicate the cell suspension on ice for 2 min (1 s pulse, 40% amplitude) with a cell homogenizer probe.</li>
	<li>Pellet insoluble/membrane fractions via centrifugation (3,200 &#215; g) at 25 &#176;C for 15 min. Remove and keep the supernatant, as this is the homogenate that will be used in subsequent steps. Separate the homogenates into three cuvettes to perform the experiment in triplicate.</li>
	<li>Add the probe to the homogenate to obtain a final probe concentration of 4 &#181;M. Pipette up and down three times to mix the solution well.</li>
	<li>Measure the fluorescent signal immediately after addition and after desired incubation times on a fluorimeter. The incubation time can be optimized to see the maximum fold turn-on (1 h in this experiment). The incubation time must be constant across all cell lines compared.
	<ol>
		<li>Set the excitation wavelength to 496 nm.</li>
		<li>Set the emission to 510-600 nm.</li>
		<li>Set the slit width to 0.5 mm.</li>
		<li>Pipette the solution into a 1 mL quartz cuvette, place into the fluorimeter, and hit scan.</li>
	</ol>
	</li>
	<li>Divide the final fluorescence intensity at 516 nm (maximum fluorescent wavelength) by the intensity at the same wavelength from the initial reading to determine the fold activation of the isoform-selective dye.</li>
</ol>
2. Use of fluorescence microscopy to image cells with high ALDH1A1 activity
<ol>
	<li>Thaw 1 &#215; 106 cells in a T25 cell culture flask in 5 mL of the appropriate cell culture media.</li>
	<li>Maintain the cells in an incubator at 37 &#176;C and 5% CO2 for two to three passages. Ensure the cells do not exceed 80%-90% confluency before passaging.</li>
	<li>The day prior to confocal imaging, plate 4 &#215; 105 cells in an 8-well chamber slide.
	<ol>
		<li>Coat the bottom of each well with poly-L-lysine (0.1 mg/mL, 100 &#181;L per well) for 10 min, subsequently aspirating.</li>
		<li>Wash each well 3x by adding cell culture grade water (100 &#181;L per well) and aspirating.</li>
		<li>Trypsinize the cells in 0.25% trypsin for 10 min, count them using an automated cell counter, and plate the cells at 4 &#215; 105 cells per well.</li>
		<li>Let the cells settle and attach overnight (12-16 h).</li>
	</ol>
	</li>
	<li>Aspirate the growth media and add serum-free media (500 &#181;L per well), supplemented with&#160;2 &#181;M of the probe or the&#160;control probe.</li>
	<li>Incubate with the probe at room temperature for 30 min and image the cells immediately.</li>
	<li>Turn on the confocal microscope and adjust for the sample.
	<ol>
		<li>Load the sample carefully at the lowest magnification; find the cells to ensure proper positioning.</li>
		<li>Ensure the objective lens is at 10x magnification and locate the cells.</li>
	</ol>
	</li>
	<li>For this experiment, the FITC channel (excitation: 488 nm laser; emission: 516-521 nm) and T-PMT (transmitted light) channel are required. Locate and focus on the cells using T-PMT to focus on the same z-plane for the entirety of the experiment to remove bias.</li>
	<li>Adjust the laser power and FITC gain to the appropriate setting, where the signal from the Ctrl-AlDeSense AM samples is minimally detectable, while still seeing signal in AlDeSense AM samples. Each parameter can be adjusted by sliding the corresponding bar. The settings may have to be adjusted a few times to identify the correct parameters. Once optimized, complete the rest of the experiment within that cell line using identical parameters.</li>
	<li>Snap three images per well for a total of three wells per treatment condition (nine images in total). Focus on the proper plane using T-PMT to avoid bias rather than using the fluorescence channel or merged image.</li>
	<li>Process the images to determine the percentage of ALDH1A1+ cells.
	<ol>
		<li>Using image processing software, split the czi file into different channels.</li>
		<li>Count the total number of cells and the total number of fluorescent cells.</li>
		<li>To determine the percentage of ALDH1A1+ cells, divide the number of fluorescent cells by the total number of cells in each image. It is imperative to count the same way for each image without manipulating the images, as, for instance, adjusting the brightness may add a confounding variable.</li>
	</ol>
	</li>
</ol>
3. Application of flow cytometry to identify cells with high ALDH1A1 activity
<ol>
	<li>Thaw 1 &#215; 106 cells in a T25 cell culture flask in 5 mL of the appropriate cell culture media.</li>
	<li>Maintain the cells in an incubator at 37 &#176;C and 5% CO2 for two to three passages. Ensure the cells do not exceed 80%-90% confluency before passaging.</li>
	<li>Trypsinize, count, and pellet the cells in a 15 mL centrifuge tube via centrifugation (180 &#215; g) at 25 &#176;C for 5 min.</li>
	<li>Resuspend the cells in 1 mL of 2 &#181;M probe/control probe solution in PBS. Rock the cells at room temperature for 60 min to ensure exposure to the dye is even.</li>
	<li>After the incubation period, pellet the cells via centrifugation (180 &#215; g) at 25 &#176;C for 5 min. Resuspend the cells in 0.5 mL of PBS. Run the cells through a cell strainer (35 &#181;m nylon mesh) to remove cell clumps that may clog the flow cytometer. Immediately place the cells on ice.</li>
	<li>Turn the instrument on and run the start-up protocol.</li>
	<li>Check for sheath fluid and empty waste.</li>
	<li>Run the lines with 10% bleach and water for 5 min each.</li>
	<li>Run quality control beads to ensure proper function.</li>
	<li>In the settings tab, select FSC (forward scatter), SSC (side scatter), and FITC (fluorescein isothiocyanate) for the fluorescence filter.</li>
	<li>Draw the following graphs to gate for viability, singlets, and fluorescence. Optimize the laser power (specific to user&#39;s instrument) so that the cell populations are within the given parameters for further analysis.
	<ol>
		<li>FSC-A versus SSC-A scatter plot: main cell population is near the center of the graph.</li>
		<li>FSC-A versus FSC-W scatter plot: narrow horizontal band indicative of singlets (rather than cell clumps).</li>
		<li>FITC-A versus FSC-A scatter plot: observe the distribution of cells sorted by the isoform-selective fluorogenic turn-on probe.</li>
		<li>FITC-A histogram: observe the shift in population based on FITC to determine the percentage of ALDH1A1+ cells.</li>
	</ol>
	</li>
	<li>To optimize the FITC laser power, run a sample with the probe so that the right tail of the histogram curve is near the maximum FITC-A signal. Subsequently, run a sample with the control probe. A population shift should be observable to reveal the maximum dynamic range. The laser power optimization step may have to be repeated multiple times, but the laser power should not be altered across samples once a setting has been designated for an experiment.</li>
	<li>Run each sample for 10,000 counts (done in triplicate).</li>
	<li>Repeat step 3.12 for each cell line, as there will be variability in uptake and ALDH1A1 activity.</li>
	<li>After completion of sample collection, run the lines with 10% bleach and water for 5 min each, then initiate shutdown of the instrument.</li>
	<li>Process the data using the flow cytometry software and gate the desired cell population. Set the gates so that all events fall into either the ALDH1A1- or ALDH1A1+ gate. Using the rectangle gate selection, set the ALDH1A1- gate so that &#62;99.5% of events in the control probe samples occur within this gate. The remaining cells will be considered ALDH1A1+. These same gates can then be applied to the probe sample to quantify the number of events considered ALDH1A1- and ALDH1A1+.</li>
</ol>

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J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bioluminescence+assay+for+aldehyde+dehydrogenase+activity.">A bioluminescence assay for aldehyde dehydrogenase activity.</a> Analytical Biochemistry. 434 (2), 226-232 (2013).</li><li>Minn, I., 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+red-shifted+fluorescent+substrate+for+aldehyde+dehydrogenase.">A red-shifted fluorescent substrate for aldehyde dehydrogenase.</a> Nature Communications. 5, 3662 (2014).</li><li>Doll&#233;, L., Boulter, L., Leclercq, I. A., van Grunsven, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next+generation+of+ALDH+substrates+and+their+potential+to+study+maturational+lineage+biology+in+stem+and+progenitor+cells.">Next generation of ALDH substrates and their potential to study maturational lineage biology in stem and progenitor cells.</a> American Journal of Physiology. Gastrointestinal and Liver Physiology. 308 (7), 573-578 (2015).</li><li>Yagishita, A., 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=Development+of+highly+selective+fluorescent+probe+enabling+flow-cytometric+isolation+of+ALDH3A1-positive+viable+cells.">Development of highly selective fluorescent probe enabling flow-cytometric isolation of ALDH3A1-positive viable cells.</a> Bioconjugate Chemistry. 28 (2), 302-306 (2017).</li><li>Maity, S., 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=Thiophene+bridged+aldehydes+(TBAs)+image+ALDH+activity+in+cells:+Via+modulation+of+intramolecular+charge+transfer.">Thiophene bridged aldehydes (TBAs) image ALDH activity in cells: Via modulation of intramolecular charge transfer.</a> Chemical Science. 8 (10), 7143-7151 (2017).</li><li>Koenders, S. T. A., 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=Development+of+a+retinal-based+probe+for+the+profiling+of+retinaldehyde+dehydrogenases+in+cancer+cells.">Development of a retinal-based probe for the profiling of retinaldehyde dehydrogenases in cancer cells.</a> ACS Central Science. 5 (12), 1965-1974 (2019).</li><li>Oe, 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=Deep-red/near-infrared+turn-on+fluorescence+probes+for+aldehyde+dehydrogenase+1A1+in+cancer+stem+cells.">Deep-red/near-infrared turn-on fluorescence probes for aldehyde dehydrogenase 1A1 in cancer stem cells.</a> ACS Sensors. 6 (9), 3320-3329 (2021).</li><li>Yagishita, A., Ueno, T., Tsuchihara, K., Urano, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Amino+BODIPY-based+blue+fluorescent+probes+for+aldehyde+dehydrogenase+1-expressing+cells.">Amino BODIPY-based blue fluorescent probes for aldehyde dehydrogenase 1-expressing cells.</a> Bioconjugate Chemistry. 32 (2), 234-238 (2021).</li><li>Okamoto, A., 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=Identification+of+breast+cancer+stem+cells+using+a+newly+developed+long-acting+fluorescence+probe,+C5S-A,+targeting+ALDH1A1.">Identification of breast cancer stem cells using a newly developed long-acting fluorescence probe, C5S-A, targeting ALDH1A1.</a> Anticancer Research. 42 (3), 1199-1205 (2022).</li></ol>

We disclose a pending patent (US20200199092A1) for the AlDeSense technology.

Pan-selectivity is a major limitation of many ALDH probes; however, several isoform-selective examples have recently been reported32,33,34,35,36,37,38,39,40,41. The isoform-selective fluo...

Cancer stem cells (CSCs) are a subpopulation of tumor cells that exhibit stem cell-like properties1. Similar to their non-cancerous counterparts, CSCs possess the extraordinary ability to self-renew and proliferate. Together with other built-in mechanisms, such as the upregulation of ATP-binding cassette transporters, CSCs are often spared from initial surgical debulking efforts, as well as subsequent adjuvant therapy2. Owing to their critical role in treatment resistance3, relapse4, and metastasis5, CSCs have become a priority in cancer research. Although there are a variety of cell surface antigens (e.g., CD133) that can be used to identify CSCs6, leveraging the enzymatic activity of aldehyde dehydrogenases (ALDHs) found in the cytoplasm has emerged as an attractive alternative7. ALDHs are a superfamily of 19 enzymes responsible for catalyzing the oxidation of reactive endogenous and xenobiotic aldehydes to the corresponding carboxylic acid products8.
In general, aldehyde detoxification is crucial in protecting cells from undesirable crosslinking events and oxidative stress that may damage stem cell integrity9. Moreover, the 1A1 isoform controls retinoic acid metabolism, which in turn influences stemness via retinaldehyde signaling10. AlDeSense11,12, a small-molecule activity-based sensing (ABS) probe to selectively detect ALDH1A1 activity, was recently developed. ABS designs achieve analyte detection through a chemical change rather than a binding event, allowing for high selectivity and decreased off-target responses13,14,15,16. The design principle of the isoform-selective fluorogenic probe relies on a donor-photoinduced electron transfer (d-PeT) quenching mechanism17, originating from the aldehyde functional group, which serves to suppress the fluorescent signature of the probe18. Upon ALDH1A1-mediated conversion to the carboxylic acid, radiative relaxation is unlocked to yield a highly fluorescent product. Because d-PeT quenching is never 100% efficient, the residual fluorescence that may lead to possible false positive results was considered when establishing this assay through the development of Ctrl-AlDeSense, a non-responsive reagent with matching photophysical characteristics (e.g., quantum yield) and an identical cytoplasmic staining pattern in cells. When used in tandem, this unique pairing can reliably distinguish cells with high ALDH1A1 activity from those that exhibit low levels via fluorimetry, molecular imaging, and flow cytometry. Several key advantages are associated with the use of isoform-selective activatable dyes over traditional immunohistochemical methods. For instance, CSCs are hypothesized to be buried deep within a tumor, and thus are more accessible to a small molecule relative to large antibodies19. Additionally, the turned-over fluorescent product does not covalently modify any cellular component, meaning it can be readily removed via wash cycles to leave a CSC in an unmodified state. Lastly, the turn-on response only identifies viable cells and functions, much like the MTT assay, owing to its reliance on the NAD+ cofactor.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64713/64713fig01.jpg" /> 
Figure 1: Schematic demonstrating fluorescent turn-on of AlDeSense. The isoform-selective dye is activated by ALDH1A1 and can be used to identify elevated ALDH1A1 activity in ovarian cancer cells via fluorimetry, molecular imaging, and flow cytometry. <a href="https://www.jove.com/files/ftp_upload/64713/64713fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In past work, the isoform-selective fluorogenic probe assay successfully stratified ALDH high (ALDH+) cells from ALDH low (ALDH-) cells in K562 human chronic leukemia cells, MDA-MB-231 human breast cancer cells, and B16F0 murine melanoma cells. This is important because, for many cancer types, high ALDH1A1 protein expression signifies a worse clinical prognosis20. This presumes that elevated levels of ALDH1A1 are indicative of CSCs which can evade treatment, develop resistance, and disseminate throughout the body. However, in the case of ovarian cancer, there are studies reporting the opposite finding (high ALDH1A1 expression is linked to improved patient survival)21,22,23,24. While this may appear contradictory at first glance, expression does not necessarily correlate to enzyme activity, which may be influenced by changes in the tumor microenvironment (e.g., pH flux, oxygen gradients), availability of the NAD+ cofactor or aldehyde substrates, levels of carboxylic acids (product inhibition), and post-translational modifications that can alter enzyme activity25. Additionally, ovarian cancer is divided into five main histological types (high-grade serous, low-grade serous, endometrioid, clear cell, and mucinous), which we hypothesize will feature variable levels of ALDH1A1 activity26. With the goal of investigating ALDH1A1 activity in ovarian tumors, an isoform-selective fluorogenic probe assay was employed to identify ALDH1A1+ populations in a panel of five ovarian cancer cell lines belonging to the different histological types mentioned above. The cell lines tested in this study include BG-1, Caov-3, IGROV-1, OVCAR-3, and PEO4 cells, covering clear cell and serous histotypes. Herein, the versatility and generalizability of the probe was highlighted to identify CSCs for the researchers that seek to perform similar studies in other immortalized cancer cell lines as well as patient samples. The use of AlDeSense will shed light on the biochemical pathways involved in CSC maintenance in complex tissue microenvironments and potentially serve as a clinical tool for determining prognosis and measuring cancer aggressiveness.

<table><tbody><tr><td>&amp;nbsp;0.25% Trypsin, 0.1% EDTA in HBSS w/o Calcium, Magnesium and Sodium Bicarbonate</td><td>Corning</td><td>&amp;nbsp;&amp;nbsp;25-050-CI</td><td></td></tr><tr><td>1x Phosphate Buffer Saline</td><td>Corning</td><td>21-040-CMX12</td><td></td></tr><tr><td>AccuSpin Micro 17R</td><td>Fisher Scientific</td><td>13-100-675</td><td></td></tr><tr><td>AlDeSense</td><td></td><td></td><td>Synthesized in-house</td></tr><tr><td>BG-1</td><td></td><td></td><td>A gift provided by the Prof. Paul Hergenrother Lab, University of Illinois Urbana-Champaign</td></tr><tr><td>BioLite 25cm&lt;sup&gt;2&lt;/sup&gt; Flask</td><td>Thermo Fisher Scientific&amp;nbsp;</td><td>130189</td><td></td></tr><tr><td>Biosafety Cabinet 1300 series A2</td><td>Thermo Fisher Scientific&amp;nbsp;</td><td></td><td></td></tr><tr><td>Caov-3</td><td></td><td></td><td>A gift provided by the Prof. Erik Nelson Lab, University of Illinois Urbana-Champaign</td></tr><tr><td>Cell homogenizer</td><td>Fisher Scientific</td><td></td><td></td></tr><tr><td>Centrifuge 5180R</td><td>Eppendorf</td><td>22627040</td><td></td></tr><tr><td>Contrl-AlDeSense</td><td></td><td></td><td>Synthesized in-house</td></tr><tr><td>DMEM, 10% FBS, 1% P/S</td><td></td><td></td><td>Prepared by UIUC cell media facility</td></tr><tr><td>Falcon Round-Bottom Polystyrene Test Tubes with Cell Strainer Snap Cap, 5mL</td><td>Corning</td><td>352003</td><td></td></tr><tr><td>FCS Express 6</td><td></td><td></td><td>Provided by UIUC CMtO</td></tr><tr><td>FL microscope</td><td>EVOS</td><td></td><td></td></tr><tr><td>Fluorometer</td><td>Photon Technology International</td><td></td><td></td></tr><tr><td>Forma Series II Water-Jacketed CO2&amp;nbsp;Incubator</td><td>Fisher Scientific</td><td>3110</td><td></td></tr><tr><td>IGROV-1</td><td></td><td></td><td>A gift provided by the Prof. Erik Nelson Lab, University of Illinois Urbana-Champaign</td></tr><tr><td>ImageJ</td><td>NIH</td><td></td><td></td></tr><tr><td>Innova 42R Incubated Shaker</td><td></td><td></td><td></td></tr><tr><td>LSM 700</td><td>Zeiss</td><td></td><td></td></tr><tr><td>LSR II</td><td>BD</td><td></td><td></td></tr><tr><td>Nunc Lab-Tek Chambered #1.0 Borosicilate Coverglass System</td><td>Thermo Fisher Scientific&amp;nbsp;</td><td>155383</td><td></td></tr><tr><td>OVCAR-3</td><td>ATCC</td><td>HTB-161</td><td></td></tr><tr><td>PEO4</td><td></td><td></td><td>A gift provided by the Prof. Erik Nelson Lab, University of Illinois Urbana-Champaign</td></tr><tr><td>Pierce Protease Inhibitor Tablets</td><td>Thermo Scientific</td><td>A32963</td><td></td></tr><tr><td>Poly-L-Lysine</td><td>Cultrex</td><td>3438-100-01</td><td></td></tr><tr><td>Rocker</td><td>VWR</td><td></td><td></td></tr><tr><td>RPMI, 10% FBS, 1% P/S</td><td></td><td></td><td>Prepared by UIUC cell media facility</td></tr><tr><td>RPMI, 20% FBS, 1% P/S, 0.01 mg/mL Insulin</td><td></td><td></td><td>Prepared by UIUC cell media facility</td></tr></tbody></table>

application of aldesense to stratify ovarian cancer cells based on aldehyde dehydrogenase 1a1 activity

Relapse after cancer treatment is often attributed to the persistence of a subpopulation of tumor cells known as cancer stem cells (CSCs), which are characterized by their remarkable tumor-initiating and self-renewal capacity. Depending on the origin of the tumor (e.g., ovaries), the CSC surface biomarker profile can vary dramatically, making the identification of such cells via immunohistochemical staining a challenging endeavor. On the contrary, aldehyde dehydrogenase 1A1 (ALDH1A1) has emerged as an excellent marker to identify CSCs, owing to its conserved expression profile in nearly all progenitor cells including CSCs. The ALDH1A1 isoform belongs to a superfamily of 19 enzymes that are responsible for the oxidation of various endogenous and xenobiotic aldehydes to the corresponding carboxylic acid products. Chan et al. recently developed AlDeSense, an isoform-selective "turn-on" probe for the detection of ALDH1A1 activity, as well as a non-reactive matching control reagent (Ctrl-AlDeSense) to account for off-target staining. This isoform-selective tool has already been demonstrated to be a versatile chemical tool through the detection of ALDH1A1 activity in K562 myelogenous leukemia cells, mammospheres, and melanoma-derived CSC xenografts. In this article, the utility of the probe was showcased through additional fluorimetry, confocal microscopy, and flow cytometry experiments where the relative ALDH1A1 activity was determined in a panel of five ovarian cancer cell lines.

Total ALDH1A1 activity of ovarian cancer cell homogenates 
The average fold turn-ons for each cell line obtained from this assay are: BG-1 (1.12 &#177; 0.01); IGROV-1 (1.30 &#177; 0.03); Caov-3 (1.72 &#177; 0.06); PEO4 (2.51 &#177; 0.29); and OVCAR-3 (10.25 &#177; 1.46) (Figure 2).
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64713/64713fig02.jpg" /> 
Figure 2<...

Watch this Scientific Journal Video about Application of AlDeSense to Stratify Ovarian Cancer Cells Based on Aldehyde Dehydrogenase 1A1 Activity at JoVE.com

Application of AlDeSense to Stratify Ovarian Cancer Cells Based on Aldehyde Dehydrogenase 1A1 Activity

Methods to measure ALDH1A1 activity in live cells are critical in cancer research due to its status as a biomarker of stemness. In this study, we employed an isoform-selective fluorogenic probe to determine the relative levels of ALDH1A1 activity in a panel of five ovarian cancer cell lines.

Relapse after cancer treatment is often attributed to the persistence of a subpopulation of tumor cells known as cancer stem cells (CSCs), which are ...

application-aldesense-to-stratify-ovarian-cancer-cells-based-on

Research

JoVE Journal

Cancer Research

1.0K Views.  University of Illinois Urbana-Champaign. Ons protocol stelt gebruikers in staat om ALDH1A1-activiteit te meten, een stamcelbiomarker met behulp van verschillende modaliteiten, variërend van flowcytometrie tot moleculaire beeldvorming van levende cellen. De grote voordelen van deze aanpak zijn dat sondeactivering de turnaround-respons omvat die wordt gekenmerkt door een hoge signaal-achtergrondverhouding, evenals selectieve ALDH1A1-isovormdetectie. Michael Lee, Sarah Gardner en Rodrigo Tapia Hernandez promovendi van mijn laboratoriu...

Video: Application of AlDeSense to Stratify Ovarian Cancer Cells Based on Aldehyde Dehydrogenase 1A1 Activity

In vitro Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis

Ovarian cancer is the fifth leading cause of cancer related deaths in the United States1. Despite a positive initial response to therapies, 70 to 90 percent of women with ovarian cancer develop new metastases, and the recurrence is often fatal2. It is, therefore, necessary to understand how secondary metastases arise in order to develop better treatments for intermediate and late stage ovarian cancer. Ovarian cancer metastasis occurs when malignant cells detach from the primary tumor site and disseminate throughout the peritoneal cavity. The disseminated cells can form multicellular clusters, or spheroids, that will either remain unattached, or implant onto organs within the peritoneal cavity3 (Figure 1, Movie 1). 
All of the organs within the peritoneal cavity are lined with a single, continuous, layer of mesothelial cells4-6 (Figure 2). However, mesothelial cells are absent from underneath peritoneal tumor masses, as revealed by electron micrograph studies of excised human tumor tissue sections3,5-7 (Figure 2). This suggests that mesothelial cells are excluded from underneath the tumor mass by an unknown process. 
Previous in vitro experiments demonstrated that primary ovarian cancer cells attach more efficiently to extracellular matrix than to mesothelial cells8, and more recent studies showed that primary peritoneal mesothelial cells actually provide a barrier to ovarian cancer cell adhesion and invasion (as compared to adhesion and invasion on substrates that were not covered with mesothelial cells)9,10. This would suggest that mesothelial cells act as a barrier against ovarian cancer metastasis. The cellular and molecular mechanisms by which ovarian cancer cells breach this barrier, and exclude the mesothelium have, until recently, remained unknown. 
Here we describe the methodology for an in vitro assay that models the interaction between ovarian cancer cell spheroids and mesothelial cells in vivo (Figure 3, Movie 2). Our protocol was adapted from previously described methods for analyzing ovarian tumor cell interactions with mesothelial monolayers8-16, and was first described in a report showing that ovarian tumor cells utilize an integrin &#x2013;dependent activation of myosin and traction force to promote the exclusion of the mesothelial cells from under a tumor spheroid17. This model takes advantage of time-lapse fluorescence microscopy to monitor the two cell populations in real time, providing spatial and temporal information on the interaction. The ovarian cancer cells express red fluorescent protein (RFP) while the mesothelial cells express green fluorescent protein (GFP). RFP-expressing ovarian cancer cell spheroids attach to the GFP-expressing mesothelial monolayer. The spheroids spread, invade, and force the mesothelial cells aside creating a hole in the monolayer. This hole is visualized as the negative space (black) in the GFP image. The area of the hole can then be measured to quantitatively analyze differences in clearance activity between control and experimental populations of ovarian cancer and/ or mesothelial cells. This assay requires only a small number of ovarian cancer cells (100 cells per spheroid X 20-30 spheroids per condition), so it is feasible to perform this assay using precious primary tumor cell samples. Furthermore, this assay can be easily adapted for high throughput screening.

In vitro Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis

The mesothelial clearance assay described here takes advantage of fluorescently labeled cells and time-lapse video microscopy to visualize and quantitatively measure the interactions of ovarian cancer multicellular spheroids and mesothelial cell monolayers. This assay models the early steps of ovarian cancer metastasis.

Ovarian cancer is the fifth leading cause of cancer related deaths in the United States1. Despite a positive initial response to therapies, 70 to 90 ...

Medicine

Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells

In this protocol, we outline the procedure for generation of tumor spheroids within 384-well hanging droplets to allow for high-throughput screening of anti-cancer therapeutics in a physiologically representative microenvironment. We outline the formation of patient derived cancer stem cell spheroids, as well as, the manipulation of these spheroids for thorough analysis following drug treatment. Specifically, we describe collection of spheroid morphology, proliferation, viability, drug toxicity, cell phenotype and cell localization data. This protocol focuses heavily on analysis techniques that are easily implemented using the 384-well hanging drop platform, making it ideal for high throughput drug screening. While we emphasize the importance of this model in ovarian cancer studies and cancer stem cell research, the 384-well platform is amenable to research of other cancer types and disease models, extending the utility of the platform to many fields. By improving the speed of personalized drug screening and the quality of screening results through easily implemented physiologically representative 3D cultures, this platform is predicted to aid in the development of new therapeutics and patient-specific treatment strategies, and thus have wide-reaching clinical impact.

This protocol describes generation of patient-derived spheroids, and downstream analysis including quantification of proliferation, cytotoxicity testing, flow cytometry, immunofluorescence staining and confocal imaging, in order to assess drug candidates&#8217; potential as anti-neoplastic therapeutics. This protocol supports precision medicine with identification of specific drugs for each patient and stage of disease.

In this protocol, we outline the procedure for generation of tumor spheroids within 384-well hanging droplets to allow for high-throughput screening of ...

Obtaining Cancer Stem Cell Spheres from Gynecological and Breast Cancer Tumors

Cancer stem cells (CSC) are a small population with self-renewal and plasticity which are responsible for tumorigenesis, resistance to treatment and recurrent disease. This population can be identified by surface markers, enzymatic activity and a functional profile. These approaches per se are limited, due to phenotypic heterogeneity and CSC plasticity. Here, we update the sphere-forming protocol to obtain CSC spheres from breast and gynecological cancers, assessing functional properties, CSC markers and protein expression. The spheres are obtained with single-cell seeding at low density in suspension culture, using a semi-solid methylcellulose medium to avoid migration and aggregates. This profitable protocol can be used in cancer cell lines but also in primary tumors. The tridimensional non-adherent suspension culture thought to mimic the tumor microenvironment, particularly the CSC-niche, is supplemented with epidermal growth factor and basic fibroblast growth factor to ensure CSC signaling. Aiming for robust identification of CSC, we propose a complementary approach, combining functional and phenotypic evaluation. Sphere-forming capacity, self-renewal and sphere projection area establish CSC functional properties. Additionally, characterization comprises flow cytometry evaluation of the markers, represented by CD44+/CD24- and CD133, and Western blot, considering ALDH. The presented protocol was also optimized for primary tumor samples, following a sample digestion procedure, useful for translational research.

The aim of this methodology is to identify cancer stem cells (CSC) in cancer cell lines and primary human tumor samples with the sphere-forming protocol, in a robust manner, using functional assays and phenotypic characterization with flow cytometry and Western blot.

Cancer stem cells (CSC) are a small population with self-renewal and plasticity which are responsible for tumorigenesis, resistance to treatment and ...

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic target analyses and drug response monitoring using patient derived xenografts (PDX). This strategy was validated using ovarian tumors as an example. The mate-pair next generation sequencing (MPseq) protocol was used to identify structural alterations and followed by analysis of potentially targetable alterations. Human tumors grown in immunocompromised mice were treated with drugs selected based on the genomic analyses. Results demonstrated a good correlation between the predicted and the observed responses in the PDX model. The presented approach can be used to test the efficacy of combination treatments and aid personalized treatment for patients with recurrent cancer, specifically in cases when standard therapy fails and there is a need to use drugs off label.

Here we present a protocol to test the efficacy of targeted therapies selected based on the genomic makeup of a tumor. The protocol describes identification and validation of structural DNA rearrangements, engraftment of patients&#8217; tumors into mice and testing responses to corresponding drugs.

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic ...

Generation of a Novel Dendritic-cell Vaccine Using Melanoma and Squamous Cancer Stem Cells

We identified cancer stem cell (CSC)-enriched populations from murine melanoma D5 syngeneic to C57BL/6 mice and the squamous cancer SCC7 syngeneic to C3H mice using ALDEFLUOR/ALDH as a marker, and tested their immunogenicity using the cell lysate as a source of antigens to pulse dendritic cells (DCs). DCs pulsed with ALDHhigh CSC lysates induced significantly higher protective antitumor immunity than DCs pulsed with the lysates of unsorted whole tumor cell lysates in both models and in a lung metastasis setting and a s.c.&#160;tumor growth setting, respectively. This phenomenon was due to CSC vaccine-induced humoral as well as cellular anti-CSC responses. In particular, splenocytes isolated from the host subjected to CSC-DC vaccine produced significantly higher amount of IFN&#947; and GM-CSF than splenocytes isolated from the host subjected to unsorted tumor cell lysate pulsed-DC vaccine. These results support the efforts to develop an autologous CSC-based therapeutic vaccine for clinical use in an adjuvant setting.

Evaluated in syngeneic immunocompetent hosts, cancer stem cell (CSC) based dendritic cell (DC) vaccine demonstrated significantly higher antitumor immunity than traditional DC vaccines pulsed with heterogeneous bulk tumor cells.

We identified cancer stem cell (CSC)-enriched populations from murine melanoma D5 syngeneic to C57BL/6 mice and the squamous cancer SCC7 syngeneic to C3H ...

Immunology and Infection

Assessment of Ovarian Cancer Spheroid Attachment and Invasion of Mesothelial Cells in Real Time

Ovarian cancers metastasize by shedding into the peritoneal fluid and dispersing to distal sites within the peritoneum. Monolayer cultures do not accurately model the behaviors of cancer cells within a nonadherent environment, as cancer cells inherently aggregate into multicellular structures which contribute to the metastatic process by attaching to and invading the peritoneal lining to form secondary tumors. To model this important stage of ovarian cancer metastasis, multicellular aggregates, or spheroids, can be generated from established ovarian cancer cell lines maintained under nonadherent conditions. To mimic the peritoneal microenvironment encountered by tumor cells in vivo, a spheroid-mesothelial co-culture model was established in which preformed spheroids are plated on top of a human mesothelial cell monolayer, formed over an extracellular matrix barrier. Methods were then developed using a real-time cell analyzer to conduct quantitative real time measurements of the invasive capacity of different ovarian cancer cell lines grown as spheroids. This approach allows for the continuous measurement of invasion over long periods of time, which has several advantages over traditional endpoint assays and more laborious real time microscopy image analyses. In short, this method enables a rapid, determination of factors which regulate the interactions between ovarian cancer spheroid cells invading through mesothelial and matrix barriers over time.

Ovarian cancer cell invasion into the mesothelial lining of the peritoneum is a dynamic process over time. Utilizing a real time analyzer, the invasive capacity of ovarian cancer cells in a spheroid-mesothelial cell co-culture model can be quantified over prolonged time periods, providing insights into factors regulating the metastatic process.

Ovarian cancers metastasize by shedding into the peritoneal fluid and dispersing to distal sites within the peritoneum. Monolayer cultures do not ...

Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments is crucial to advancing healthcare and improving patient outcomes. Organoids are in-vitro three-dimensional multicellular miniature organs. Patient-derived organoid (PDO) models of ovarian cancer may be optimal for drug screening because they more accurately recapitulate tissues of interest than two-dimensional cell culture models and are inexpensive compared to patient-derived xenografts. In addition, ovarian cancer PDOs mimic the variable tumor microenvironment and genetic background typically observed in ovarian cancer. Here, a method is described that can be used to test conventional and novel drugs on PDOs derived from ovarian cancer tissue and ascites. A luminescence-based adenosine triphosphate (ATP) assay is used to measure viability, growth rate, and drug sensitivity. Drug screens in PDOs can be completed in 7-10 days, depending on the rate of organoid formation and drug treatments.

We present a protocol that can be used to conduct therapeutic drug testing with patient-derived ovarian cancer organoids.

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments ...

Standardizing Ovarian Cancer Organoid Biobanking

Strategy for Biobanking of Ovarian Cancer Organoids: Addressing the Interpatient Heterogeneity across Histological Subtypes and Disease Stages

While the establishment of an ovarian cancer biobank from patient-derived organoids along with their clinical background information promises advances in research and patient care, standardization remains a challenge due to the heterogeneity of this lethal malignancy, combined with the inherent complexity of organoid technology. This adaptable protocol provides a systematic framework to realize the full potential of ovarian cancer organoids considering a patient-specific variability of progenitors. By implementing a structured experimental workflow to select optimal culture conditions and seeding methods, with parallel testing of direct 3D seeding versus a 2D/3D route, we obtain, in most cases, robust long-term expanding lines suitable for a broad range of downstream applications. 
Notably, the protocol has been tested and proven efficient in a great number of cases (N = 120) of highly heterogeneous starting material, including high-grade and low-grade ovarian cancer and stages of the disease with primary debulking, recurrent disease, and post-neoadjuvant surgical specimens. Within a low Wnt, high BMP exogenous signaling environment, we observed progenitors being differently susceptible to the activation of the Heregulin 1 &#223; (HER&#223;-1)-pathway, with HER&#223;-1 promoting organoid formation in some while inhibiting it in others. For a subset of the patient's samples, optimal organoid formation and long-term growth necessitate the addition of fibroblast growth factor 10 and R-Spondin 1 to the medium. 
Further, we highlight the critical steps of tissue digestion and progenitor isolation and point to examples where brief cultivation in 2D on plastic is beneficial for subsequent organoid formation in the Basement Membrane Extract type 2 matrix. Overall, optimal biobanking requires systematic testing of all main conditions in parallel to identify an adequate growth environment for individual lines. The protocol also describes the handling procedure for efficient embedding, sectioning, and staining to obtain high-resolution images of organoids, which is required for comprehensive phenotyping.

Author Spotlight: Advancing Personalized Medicine in Ovarian Cancer 

This protocol offers a systematic framework for the establishment of ovarian cancer organoids from different disease stages and addresses the challenges of patient-specific variability to increase yield and enable robust long-term expansion for subsequent applications. It includes detailed steps for tissue processing, seeding, adjusting media requirements, and immunofluorescence staining.

While the establishment of an ovarian cancer biobank from patient-derived organoids along with their clinical background information promises advances in ...

Evaluation of Stem Cell Properties in Human Ovarian Carcinoma Cells Using Multi and Single Cell-based Spheres Assays

Years of research indicates that ovarian cancers harbor a heterogeneous mixture of cells including a subpopulation of so-called &#8220;cancer stem cells&#8221; (CSCs) responsible for tumor initiation, maintenance and relapse following conventional chemotherapies. Identification of ovarian CSCs is therefore an important goal. A commonly used method to assess CSC potential in vitro is the spheres assay in which cells are plated under non-adherent culture conditions in serum-free medium supplemented with growth factors and sphere formation is scored after a few days. Here, we review currently available protocols for human ovarian cancer spheres assays and perform a side-by-side analysis between commonly used multi cell-based assays and a more accurate system based on single cell plating. Our results indicate that both multi cell-based as well as single cell-based spheres assays can be used to investigate sphere formation in vitro. The more laborious and expensive single cell-based assays are more suitable for functional assessment of individual cells and lead to overall more accurate results while multi cell-based assays can be strongly influenced by the density of plated cells and require titration experiments upfront. Methylcellulose supplementation to multi cell-based assays can be effectively used to reduce mechanical artifacts.

In vitro spheres assays are commonly used to identify cancer stem cells. Here we compare single with multi cell-based spheres assays. The more laborious single cell-based assays or methylcellulose supplementation give more accurate results while multi cell-based assays performed in liquid medium can be highly influenced by cell density.

Years of research indicates that ovarian cancers harbor a heterogeneous mixture of cells including a subpopulation of so-called &#8220;cancer stem ...

In vitro Enrichment of Ovarian Cancer Tumor-initiating Cells

Evidence suggests that small subpopulations of tumor cells maintain a unique self-renewing and differentiation capacity and may be responsible for tumor initiation and/or relapse. Clarifying the mechanisms by which these tumor-initiating cells (TICs) support tumor formation and progression could lead to the development of clinically favorable therapies. Ovarian cancer is a heterogeneous and highly recurrent disease. Recent studies suggest TICs may play an important role in disease biology. We have identified culture conditions that enrich for TICs from ovarian cancer cell lines. Growing either adherent cells or non-adherent &#8216;floater&#8217; cells in a low attachment plate with serum free media in the presence of growth factors supports the propagation of ovarian cancer TICs with stem cell markers (CD133 and ALDH activity) and increased tumorigenicity without the need to physically separate the TICs from other cell types within the culture. Although the presence of floater cells is not common for all cell lines, this population of cells with innate low adherence may have high tumorigenic potential.Compared to adherent cells grown in the presence of serum, TICs readily form spheres, are significantly more tumorigenic in mice, and express putative stem cell markers. The conditions are easy to establish in a timely manner and can be used to study signaling pathways important for maintaining stem characteristics, and to identify drugs or combinations of drugs targeting TICs. The culture conditions described herein are applicable for a variety of ovarian cancer cells of epithelial origin and will be critical in providing new information about the role of TICs in tumor initiation, progression, and relapse.

In vitro Enrichment of Ovarian Cancer Tumor-initiating Cells

Tumor-initiating cells (TICs) may represent a viable therapeutic target for the treatment of ovarian cancer, a highly recurrent and fatal disease. We present a protocol for culture conditions that enrich for this highly tumorigenic population of cells.

Evidence suggests that small subpopulations of tumor cells maintain a unique self-renewing and differentiation capacity and may be responsible for tumor ...

Application of AlDeSense to Stratify Ovarian Cancer Cells Based on Aldehyde Dehydrogenase 1A1 Activity

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