Name: non-destructive evaluation of regional cell density within tumor aggregates following drug treatment
Uploaded: 2022-06-21T14:00:00
Description: Watch this Scientific Journal Video about Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment at JoVE.com

This study was supported by NIH R01 BRG CA207725 (MB/DTC) and NIH R01 CA233188 (MB). We would like to thank AMC Pharmacy for the Trastuzumab provided for these experiments.

AU565 (HER2+) and MDA-MB-231 breast cancer cell lines were used for the present study (see Table of Materials).
1. Preparing tumor aggregates
<ol>
	<li>Prepare AU565 (HER2+) breast cancer cell growth media using Roswell Park Memorial Institute (RPMI) 1640 basal medium (+) in L-glutamine supplemented with 10% (v/v) fetal bovine serum and 1% penicillin/streptomycin (see Table of Materials).</li>
	<li>Prepare MDA-MB-231 triple-negative breast c...

<ol>
	<li>Sutherland, R., JA, M., Inch, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+of+multicell+spheroids+in+tissue+culture+as+a+model+of+nodular+carcinomas.">Growth of multicell spheroids in tissue culture as a model of nodular carcinomas.</a> Journal of the National Cancer Institute. 46 (1), 113-120 (1971).</li><li>Sachs, N., 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+living+biobank+of+breast+cancer+organoids+captures+disease+heterogeneity.">A living biobank of breast cancer organoids captures disease heterogeneity.</a> Cell. 172 (1-2), 373-386 (2018).</li><li>Nagelkerke, A., Bussink, J., Sweep, F. C. G. J., Span, P. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Generation+of+multicellular+tumor+spheroids+of+breast+cancer+cells:+How+to+go+three-dimensional.">Generation of multicellular tumor spheroids of breast cancer cells: How to go three-dimensional.</a> Analytical Biochemistry. 437 (1), 17-19 (2013).</li><li>Kunz-Schughart, L. A., Freyer, J. P., Hofstaedter, F., Ebner, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+3-D+cultures+for+high-throughput+screening:+The+multicellular+spheroid+model.">The use of 3-D cultures for high-throughput screening: The multicellular spheroid model.</a> Journal of Biomolecular Screening. 9 (4), 273-285 (2004).</li><li>Hirschhaeuser, F., 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=Multicellular+tumor+spheroids:+An+underestimated+tool+is+catching+up+again.">Multicellular tumor spheroids: An underestimated tool is catching up again.</a> Journal of Biotechnology. 148 (1), 3-15 (2010).</li><li>Jiang, Y., Pjesivac-Grbovic, J., Cantrell, C., Freyer, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+multiscale+model+for+avascular+tumor+growth.">A multiscale model for avascular tumor growth.</a> Biophysical Journal. 89 (6), 3884-3894 (2005).</li><li>Freyei, J. P., Sutherland, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+growth+saturation+and+development+of+necrosisin+EMT6/R0+multicellular+spheroids+by+the+glucose+and+oxygen+supply.">Regulation of growth saturation and development of necrosisin EMT6/R0 multicellular spheroids by the glucose and oxygen supply.</a> Cancer Research. 46 (7), 3504-3512 (1986).</li><li>Desoize, B., Jardillier, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multicellular+resistance:+a+paradigm+for+clinical+resistance.">Multicellular resistance: a paradigm for clinical resistance.</a> Critical Reviews in Oncology Hematology. 36 (2-3), 193-207 (2000).</li><li>Mellor, H. R., Ferguson, D. J. P., Callaghan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+model+of+quiescent+tumour+microregions+for+evaluating+multicellular+resistance+to+chemotherapeutic+drugs.">A model of quiescent tumour microregions for evaluating multicellular resistance to chemotherapeutic drugs.</a> British Journal of Cancer. 93 (3), 302-309 (2005).</li><li>Roberge, C. L., 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=Non-destructive+tumor+aggregate+morphology+and+viability+quantification+at+cellular+resolution,+during+development+and+in+response+to+drug.">Non-destructive tumor aggregate morphology and viability quantification at cellular resolution, during development and in response to drug.</a> Acta Biomaterialia. 117, 322-334 (2020).</li><li>Piccinini, F., Tesei, A., Bevilacqua, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-image+based+methods+used+for+non-invasive+volume+estimation+of+cancer+spheroids+a+practical+assessing+approach+based+on+entry-level+equipment.">Single-image based methods used for non-invasive volume estimation of cancer spheroids a practical assessing approach based on entry-level equipment.</a> Computer Methods and Programs in Biomedicine. 135, 51-60 (2016).</li><li>Imamura, Y., 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=Comparison+of+2D-+and+3D-culture+models+as+drug-testing+platforms+in+breast+cancer.">Comparison of 2D- and 3D-culture models as drug-testing platforms in breast cancer.</a> Oncology Reports. 33 (4), 1837-1843 (2015).</li><li>Song, Y., 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=Patient-derived+multicellular+tumor+spheroids+towards+optimized+treatment+for+patients+with+hepatocellular+carcinoma.">Patient-derived multicellular tumor spheroids towards optimized treatment for patients with hepatocellular carcinoma.</a> Journal of Experimental &amp; Clinical Cancer Research. 37 (1), 1-13 (2018).</li><li>LaBarbera, D. V., Reid, B. G., Yoo, B. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+multicellular+tumor+spheroid+model+for+high-throughput+cancer+drug+discovery.">The multicellular tumor spheroid model for high-throughput cancer drug discovery.</a> Expert Opinion on Drug Discovery. 7 (9), 819-830 (2012).</li><li>Hakanson, M., Textor, M., Charnley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineered+3D+environments+to+elucidate+the+effect+of+environmental+parameters+on+drug+response+in+cancer.">Engineered 3D environments to elucidate the effect of environmental parameters on drug response in cancer.</a> Integrative Biology. 3 (1), 31-38 (2011).</li><li>Pickl, M., Ries, C. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+3D+and+2D+tumor+models+reveals+enhanced+HER2+activation+in+3D+associated+with+an+increased+response+to+trastuzumab.">Comparison of 3D and 2D tumor models reveals enhanced HER2 activation in 3D associated with an increased response to trastuzumab.</a> Oncogene. 28 (3), 461-468 (2009).</li><li>Huang, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optical+coherence+tomography+HHS+public+access.">Optical coherence tomography HHS public access.</a> Science. 254 (5035), 1178-1181 (1991).</li><li>Zhong, H. Q., 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=Enhancement+of+permeability+of+glycerol+with+ultrasound+in+human+normal+and+cancer+breast+tissues+in+vitro+using+optical+coherence+tomography.">Enhancement of permeability of glycerol with ultrasound in human normal and cancer breast tissues in vitro using optical coherence tomography.</a> Laser Physics Letters. 7 (5), 388-395 (2010).</li><li>Fujimoto, J., Swanson, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+development,+commercialization,+and+impact+of+optical+coherence+tomography.">The development, commercialization, and impact of optical coherence tomography.</a> Investigative Ophthalmology &amp; Visual Science. 57 (9), (2016).</li><li>Huang, Y., 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=Optical+coherence+tomography+detects+necrotic+regions+and+volumetrically+quantifies+multicellular+tumor+spheroids.">Optical coherence tomography detects necrotic regions and volumetrically quantifies multicellular tumor spheroids.</a> Cancer Research. 77 (21), 6011-6020 (2017).</li><li>Hari, N., Patel, P., Ross, J., Hicks, K., Vanholsbeeck, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optical+coherence+tomography+complements+confocal+microscopy+for+investigation+of+multicellular+tumour+spheroids.">Optical coherence tomography complements confocal microscopy for investigation of multicellular tumour spheroids.</a> Scientific Reports. 9 (1), 1-11 (2019).</li><li>El-Sadek, I. 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=Three-dimensional+dynamics+optical+coherence+tomography+for+tumor+spheroid+evaluation.">Three-dimensional dynamics optical coherence tomography for tumor spheroid evaluation.</a> Biomedical Optics Express. 12 (11), 6844 (2021).</li><li>Kingsley, D. 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=Laser-based+3D+bioprinting+for+spatial+and+size+control+of+tumor+spheroids+and+embryoid+bodies.">Laser-based 3D bioprinting for spatial and size control of tumor spheroids and embryoid bodies.</a> Acta Biomateralia. 95, 357-370 (2019).</li><li>Absher, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hemocytometer+counting.">Hemocytometer counting.</a> Tissue Culture. , 395-397 (1973).</li><li>Roberge, C. L., Rudkouskaya, A., Barroso, M., Corr, D. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Longitudinal,+label-free+assessment+of+cell+density+and+viability+in+multicellular+tumor+spheroids+via+optical+coherence+tomography.">Longitudinal, label-free assessment of cell density and viability in multicellular tumor spheroids via optical coherence tomography.</a> Summer Biomechanics, Bioengineering, and Biotransport Conference. , (2020).</li><li>Bellotti, C., Duchi, S., Bevilacqua, A., Lucarelli, E., Piccinini, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long+term+morphological+characterization+of+mesenchymal+stromal+cells+3D+spheroids+built+with+a+rapid+method+based+on+entry-level+equipment.">Long term morphological characterization of mesenchymal stromal cells 3D spheroids built with a rapid method based on entry-level equipment.</a> Cytotechnology. 68 (6), 2479-2490 (2016).</li><li>Noto, 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=Stearoyl-CoA+desaturase-1+is+a+key+factor+for+lung+cancer-initiating+cells.">Stearoyl-CoA desaturase-1 is a key factor for lung cancer-initiating cells.</a> Cell Death &amp; Disease. 4 (12), 947 (2013).</li><li>Riffle, S., Hegde, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+tumor+cell+adaptations+to+hypoxia+in+multicellular+tumor+spheroids.">Modeling tumor cell adaptations to hypoxia in multicellular tumor spheroids.</a> Journal of Experimental &amp; Clinical Cancer Research. 36, 102 (2017).</li><li>Wilson, W. R., Hay, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+hypoxia+in+cancer+therapy.">Targeting hypoxia in cancer therapy.</a> Nature Reviews Cancer. 11, 393-410 (2011).</li><li>Grimes, D. R., Kelly, C., Bloch, K., Partridge, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+estimating+the+oxygen+consumption+rate+in+multicellular+tumour+spheroids.">A method for estimating the oxygen consumption rate in multicellular tumour spheroids.</a> Journal of the Royal Society Interface. 11 (92), 20131124 (2014).</li><li>Nath, S., Devi, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+culture+systems+in+cancer+research:+Focus+on+tumor+spheroid+model.">Three-dimensional culture systems in cancer research: Focus on tumor spheroid model.</a> Pharmacology &amp; Therapeutics. 163, 94-108 (2016).</li><li>Pozzi, 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=Meet+me+halfway:+Are+in+vitro+3D+cancer+models+on+the+way+to+replace+in+vivo+models+for+nanomedicine+development.">Meet me halfway: Are in vitro 3D cancer models on the way to replace in vivo models for nanomedicine development.</a> Advanced Drug Delivery Reviews. 175, 113760 (2021).</li><li>. High throughput screening format identifies synthetic mimics of matrigel for tubulogenesis screening Available from: <a target="_blank" href="https://abstracts.biomaterials.org/data/papers/2015/abstracts/547.pdf">https://abstracts.biomaterials.org/data/papers/2015/abstracts/547.pdf</a> (2015)</li><li>Duchnowska, R., Szczylik, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Central+nervous+system+metastases+in+breast+cancer+patients+administered+trastuzumab.">Central nervous system metastases in breast cancer patients administered trastuzumab.</a> Cancer Treatment Reviews. 31 (4), 312-318 (2005).</li><li>Zazo, 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=Generation,+characterization,+and+maintenance+of+trastuzumab-resistant+HER2++breast+cancer+cell+lines.">Generation, characterization, and maintenance of trastuzumab-resistant HER2+ breast cancer cell lines.</a> American Journal of Cancer Research. 6 (11), 2661-2678 (2016).</li></ol>

Significance 
Multicellular tumor spheroids (MCTSs) are powerful 3D in vitro models for studying tumor progression and drug screening1,2,3. Advancing the utility of these relatively simple aggregate models relies heavily on the characterization of their key features, such as morphology and cell density, which are known to influence both tumor model progression and therapeutic response. However, the...

Researchers have largely turned to benchtop 3D culture in vitro systems to study some of the key features of tumor progression. Much of this research has been led by the re-emergence of multicellular tumor spheroids (MCTSs) and more complex organoids1,2. Although these models are avascular, they provide a powerful tool for recapitulating physiological and pathological processes that occur in vivo3,4,5. In particular, medium-sized models (300-500 &#181;m diameter) can mimic key tumor features such as 3D structure, pathophysiological gradients, and metastatic signaling due to hypoxia within the core. It is well documented that these models display the characteristic concentric layers seen in vascularized in vivo tumors, namely, an outer layer of proliferative cells, a transitional layer of senescent/quiescent cells, and cells experiencing hypoxia in the core3,6,7,8,9.&#160;Unique insight can be gained from these models by characterizing cell behavior within these layers, during development and in response to the drug. However, the requisite MCTS size, necessary to develop the gradients that make them such powerful in vitro models, drastically limits the tools used for non-destructive assessment. Indeed, one of the biggest challenges with non-destructive analysis of MTCSs is quantifying cell-scale details. Bright-field and phase-contrast microscopy are routinely utilized to assess 3D MCTSs growth and development non-destructively. However, these modalities are limited to 2D projections, lacking the capacity to visualize the crucial 3D structure of these models10,11,12,13. Information on cytotoxicity and cell proliferation is typically collected through fluorescent imaging (i.e., light-sheet microscopy, confocal microscopy) or ex vivo immunohistological staining14,15,16. While these approaches provide valuable, high-resolution information on tissue structure, cellular density, and cellular function, they often require sample preparation such as optical clearing, fixing/staining, or embedding that prevents longitudinal analyses.
Optical Coherence Tomography (OCT) is a non-destructive structural imaging modality that has the potential to overcome some of the challenges mentioned above. It boasts cellular resolution and a sufficiently wide field of view (up to 10 mm x 10 mm) capable of visualizing entire multicellular aggregates17,18,19. Importantly, due to the visible nature of the light used, this technique is completely non-destructive and label-free17. Also, samples can be imaged in situ without requiring sample preparation, such that samples can be taken straight from the incubator, quickly scanned with OCT (scan duration ~5-10 min), then returned to the incubator, enabling longitudinal characterization. Many studies seeking to use OCT to analyze tumor spheroid behavior have recently emerged. In one of the most exciting demonstrations, Huang et al. used OCT to non-destructively detect necrotic cores within large tumor spheroid models, noting that live and dead cell regions possess discernible differences in optical attenuation, which may be utilized for label-free viability monitoring20. Similarly, Hari et al. conducted refractive index (RI) measurements of human colon cancer (HCT116) spheroids imaged with OCT to study the presence of hypoxia within the samples21. Their measurements were not sufficient for direct inferences, though they did observe lower RI in locations that correlated with the site, though not size, of necrotic cores, later identified via confocal microscopy. Abd El-Sadek et al. used OCT to visualize and quantify regional tissue viability of breast cancer tumor models22. They reported two OCT-based methods for visualizing tissue dynamics and showed a moderate correlation between differences in these metrics and microscopy-identified regions of live/dead cells.
Our published work using OCT built upon this prior literature to establish a quantitative, non-destructive approach to measure the 3D morphology and cell count within MCTSs breast cancer models during development10,23. Using Imaris 3D rendering image analysis software to count the number of cell-sized objects (i.e., spots) imaged within the OCT volume scans, the cell counts were non-destructively measured in MCTSs that were statistically similar to those determined via hemocytometer upon aggregate dissociation. However, due to the structural nature of OCT, cell membranes still present after cell death by necrosis may be erroneously counted as live cells. Furthermore, this characterization was extended to non-destructively track cell viability within individual aggregates subjected to a drug regimen with promising success10. Importantly, it was noted that similar cell viability was reported from our OCT-Imaris approach with what was benchmarked within these samples upon dissociation. This non-destructive and label-free cell approach enables cells to be counted within 3D constructs and dense aggregates longitudinally without sacrificing the construct/aggregate structure.
The present work reports an improved approach to directly quantify regional cell density within dense aggregates by leveraging the ability of OCT-Imaris to measure both 3D aggregate morphology and cell number. This methodological advancement provides a more detailed picture of cells&#39; spatial distribution and proliferation within the characteristic concentric layers of MCTSs models. Rather than simply calculating an overall average aggregate cell density, such local density measurements can reveal cell density gradients, such as those associated with compaction. This regional assessment is also applied to aggregates treated with a chemotherapeutic to assess regional drug response, as measured by changes in local cell density. This combination of OCT and advanced imaging analysis methods provide quantification of regional cell viability, which may be used to explore drug penetration based on which regions experience decreases in cell density. This is the first report to non-destructively quantify regional cell density and viability in response to the drug within dense cellular tissues and measure it longitudinally. Such characterization of three-dimensional cell density and spatial distribution throughout entire MCTSs may help optimize drug delivery in cancer treatment and improve the understanding of cancer model progression.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>96 well plates</td>
			<td>Greiner Bio-One&#160;</td>
			<td>650970</td>
			<td>CellStar Cell-Repellent Surface, https://shop.gbo.com/en/usa/products/bioscience/cell-culture-products/cellstar-cell-repellent-surface/</td>
		</tr>
		<tr>
			<td>0.25% trypsin, 2.21 mM EDTA</td>
			<td>Corning</td>
			<td>25-053-CI</td>
			<td></td>
		</tr>
		<tr>
			<td>AU565 breast cancer cells</td>
			<td>ATCC</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Dulbecco&#39;s Modified Eagle&#39;s Medium</td>
			<td>Corning</td>
			<td>10-013-CV</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>ATCC</td>
			<td>30-2020</td>
			<td></td>
		</tr>
		<tr>
			<td>FIJI software</td>
			<td>open-source</td>
			<td>(Fiji Is Just) ImageJ v2.1/1.5.3j</td>
			<td>Downloaded from https://imagej.net/software/fiji/</td>
		</tr>
		<tr>
			<td>Hemocytometer</td>
			<td>Fisher Scientific</td>
			<td>0267151B</td>
			<td></td>
		</tr>
		<tr>
			<td>Imaris image analysis software</td>
			<td>Bitplane</td>
			<td></td>
			<td>Current version 9.8</td>
		</tr>
		<tr>
			<td>L-glutamine</td>
			<td>Lonza</td>
			<td>17-605E</td>
			<td></td>
		</tr>
		<tr>
			<td>Matrigel</td>
			<td>Corning</td>
			<td>354263</td>
			<td></td>
		</tr>
		<tr>
			<td>MDA-MB-231 breast cancer cells</td>
			<td>ATCC</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope</td>
			<td>Zeiss</td>
			<td>Z1 AxioVision</td>
			<td></td>
		</tr>
		<tr>
			<td>Penicilin streptomycin</td>
			<td>Corning</td>
			<td>30-0002CI</td>
			<td></td>
		</tr>
		<tr>
			<td>Plate centrifuge</td>
			<td>Eppendorf</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>RPMI medium 1640</td>
			<td>Gibco</td>
			<td>11875-085</td>
			<td></td>
		</tr>
		<tr>
			<td>Spectral Domain Optical Coherence Tomography</td>
			<td>ThorLabs</td>
			<td>TEL220C1</td>
			<td></td>
		</tr>
		<tr>
			<td>T75 cell culture flasks</td>
			<td>Greiner Bio-One&#160;</td>
			<td>658175</td>
			<td></td>
		</tr>
		<tr>
			<td>Trastuzumab</td>
			<td></td>
			<td></td>
			<td>Remnant clinical samples of Trastuzumab were used in this study, generously gifted by the Albany Medical College Pharmacy.&#160;</td>
		</tr>
	</tbody>
</table>

non-destructive evaluation of regional cell density within tumor aggregates following drug treatment

Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These relatively simple avascular constructs mimic key aspects of in vivo tumors, such as 3D structure and pathophysiological gradients. MCTSs models can provide insights into cancer cell behavior during spheroid development and in response to drugs; however, their requisite size drastically limits the tools used for non-destructive assessment. Optical Coherence Tomography structural imaging and Imaris 3D analysis software are explored for rapid, non-destructive, and label-free measurement of regional cell density within MCTSs. This approach is utilized to assess MCTSs over a 4-day maturation period and throughout an extended 5-day treatment with Trastuzumab, a clinically relevant anti-HER2 drug. Briefly, AU565 HER2+ breast cancer MCTSs were created via liquid overlay with or without the addition of Matrigel (a basement membrane matrix) to explore aggregates of different morphologies (thicker, disk-like 2.5D aggregates or flat 2D aggregates, respectively). Cell density within the outer region, transitional region, and inner core was characterized in matured MCTSs, revealing a cell-density gradient with higher cell densities in core regions compared to outer layers. The matrix addition redistributed cell density and enhanced this gradient, decreasing outer zone density and increasing cell compaction in the cores. Cell density was quantified following drug treatment (0 h, 24 h, 5 days) within progressively deeper 100 &#181;m zones to assess potential regional differences in drug response. By the final timepoint, nearly all cell death appeared to be constrained to the outer 200 &#181;m of each aggregate, while cells deeper in the aggregate appeared largely unaffected, illustrating regional differences in the drug response, possibly due to limitations in drug penetration. The current protocol provides a unique technique to non-destructively quantify regional cell density within dense cellular tissues and measure it longitudinally.

In a prior publication, a method was established for the non-destructive measurement of global cell density within cellular aggregates using OCT10. Herein, this technique is extended to assess the regional cell density of developing cell aggregates. Figure 1 shows a schematic of this extension, where cell density can be evaluated in concentric layers of a spheroid or more locally by looking instead at small (100 &#181;m diameter) spherical plugs, denoted by the yellow...

Watch this Scientific Journal Video about Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment at JoVE.com

Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment

The present protocol develops an image-based technique for rapid, non-destructive, and label-free regional cell density and viability measurement within 3D tumor aggregates. Findings revealed a cell-density gradient, with higher cell densities in core regions than outer layers in developing aggregates and predominantly peripheral cell death in HER2+ aggregates treated with Trastuzumab.

Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These ...

This protocol provides information on tumor model progression in a non-destructive manner. It also gives indications of therapeutic response through entire drug regimens within singular aggregates rather than relying on age match samples. Conventional methods for obtaining cell density and viability within aggregates require sample fixation and sectioning, while ours provides data non-destructively.So, changes can be tracked within a single aggregate over time. This technique is expected to improve our understanding of drug response within discreet regions of aggregate models, with implications on how well these models reflect in vivo responses and drug screening applications. To begin, prepare 70 to 90%confluence cell cultures of the desired cell lines in standard conditions.Detached cell monolayers from their culture flasks following the standard trypsinization method and add the cell suspension into a centrifuge tube. Add 10 microliters of the cell suspension to a hemocytometer and count via microscopy to determine the number of cells in the suspension. Pellet cells via centrifugation and resuspend cells in media at the desired concentration of 2.5 times 10 to the fifth cells per milliliter.For suspensions prepared with the basement membrane matrix, remove the matrix vial from minus 20 degree Celsius storage and placed in the refrigerator to thaw overnight. Prepare a container with growth media and refrigerate for 10 minutes to chill. Using a frozen pipette tip add the matrix to chilled media such that the final concentration of this solution is 5%Add 50 microliters of this media to each well of a round bottom, non-adherent 96-well plate such that the final concentration of matrix in these wells will be 2.5%following addition of cell suspension.For suspensions prepared without matrix, add 50 microliters of plain growth media to each well. Dispense 50 microliters of cell suspension into each well. Centrifuge the plates at 123 G for 10 minutes at room temperature immediately following seeding to ensure the collection of a cell pellet at the bottom of each well.Utilize an OCT system for structural imaging. Set the A scan rate to 5.5 kilohertz for high resolution image collection. Set the index of refraction to 1.33 for samples in a liquid medium.In the image parameters window on the right side of the screen, set the field of view by inputting X, Y, and Z values such that the sample is encompass within this region of interest. Click on 3D Acquisition Mode and then click on Record to collect the 3D volume scan of the sample. To create volume reconstruction, open Imaris and navigate to the converted TIF file within their arena.Go to edit, then click Image Properties and input the voxel size from the OCT image into the corresponding XYZ boxes. Next, click on OK.Click on Add New Surfaces above the objects tree. In the menu below the tree, click on Skip Automatic Creation and edit manually.Within the display adjustment window, manually slide the red and black arrows to enhance the contrast between the sample and the background and improve sample visualization. Adjust the slice position to the slice at one edge of the sample. Use the escape key to change the mouse from the navigation mode to the select mode and then click on Draw.Manually trace the outline of the region displaying the signal. Advance the slice position by entering the next position into the input box. This next position should be less than or equal to 100 slices further into the sample than the prior one.Manually trace the region displaying the signal. Repeat this step through the thickness of the sample until the opposite edge of the sample is reached. Then click on Create Surface and left menu to stitch these slices together.Finally, click on Edit, then click Mask Selection, then click OK to complete the volume reconstruction. To obtain the sample's total cell density, select Add New Spots. In the algorithm settings menu, deselect all boxes.Click on the blue arrow to move to the source channel screen. From the dropdown menu that appears, select the Masked Channel. Input the average cell diameter for the sample in the XY diameter box.Ensure that background subtraction is checked. Click on the blue arrow to move to the classify spot's screen. In the graph at the bottom of the menu, click and drag the left edge of the yellow threshold to the left edge of the graph such that all objects are included in the yellow shaded threshold.Then click on the green arrow to complete the spot creation. Obtain the number of objects identified by clicking on Statistics. Then click Overall and finally click Total Number of Spots.Click on the surface created and navigate to the surfaces style quality tab. Change selection to Center Point and change pixel width to less than equal to 20 for best visibility. Navigate to Statistics.Then click Detailed, followed by Position and record the location at the center spot. Select Add New Reference Frame from the menu above the object tree. Check the visible and fixed boxes next to the X, Y in the menu.Click and drag the center of the reference frame icon such that it is in line with the center spot. Deselect the XY visible and fix boxes and select them for XZ.Once again, click and drag the center of the reference frame icon such that it is in line with the center spot. Lastly, repeat this for the YZ plane, alternating between these three fixed planes until the reference frame perfectly aligns with the center spot.Double-click on the reference frame in the object tree and rename it center or similar. Click on the spots created and navigate to Statistics. Then click Detailed, followed by Position Reference Frame.Click on position X reference frame until it sorts from highest to lowest value. Record the highest value to obtain the aggregates'radius. Perform manual calculations to determine additional locations of interest.To do this, add 100 micrometers to the X center value and then use the Y and Z values of the center point to define the first location along the center axis. Select Add New Spots. Then select Skip Automatic Creation Edit Manually.Hold the shift button on the keyboard and click anywhere on the screen to place a new spot. Input the XYZ position values for the first location of interest. Then select Add New Reference Frame and align it over the spot.Add 100 micrometers to each sequential X location. Place the last reference frame less than equal to 50 micrometers away from the outer radius of the sample. Click on the spots created and navigate to Statistics.In the bottom right corner of the menu, click on Export All Statistics to File and save data into a spreadsheet. Open the spreadsheet. Navigate to the distance from origin reference frame tab.Use the mod function to numerically assign each distance to its corresponding reference frame. Filter the values in this column to work with the distances in each reference frame. For each of the reference frames, calculate the number of objects within 50 micrometers of the frame using the function COUNTIF.The resulting value corresponds to the number of cells in that regional plug. Divide this value by the volume of the 100 micrometer plug to obtain cell density. Student's T testing revealed significantly higher cell density in the spheroid core than in the transitional and outer layers for MDA-MB-231 spheroid models.The result indicates compaction in this spheroid core after four days. Within both AU565 and MDA-MB-231 aggregate models, the addition of the matrix does not appear to affect the volume or cell count, and thus seems to have negligible influence on cell proliferation. Rather, matrix addition appears to redistribute cell density promoting significant core compaction and decreasing cell density in the outer layers.These findings provide valuable insight into the physical mechanisms by which the matrix enables cell aggregation in different breast cancer cell lines. Looking next at AU565 tumors spheroid prepared with matrix, matured aggregates were treated with trastuzumab and regional cell density was evaluated through a five day drug regimen. Plugs were set every 100 micrometers throughout the thickness of the aggregates.Minor fluctuations in cell density were observed over time within the inner 500 micrometers of each aggregate indicating minimal cell death. The visualization of cell death as indicative drug response mostly in the outer layers of tumor spheroids is consistent with drug penetration issues of trastuzumab. We can now non-destructively measure cell viability in aggregates without sacrificing structure.This enables assessment of longitudinal drug response in singular tumor aggregates to identify temporal and penetration qualities of candidate anti-cancer drugs.

non-destructive-evaluation-regional-cell-density-within-tumor

Research

JoVE Journal

Cancer Research

Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice

Combination chemotherapy is frequently used in the clinic for cancer treatment; however, associated adverse effects to normal tissue may limit its therapeutic benefit. Nanoparticle-based drug combination has been shown to mitigate the problems encountered by free drug combination therapy. Our previous studies have shown that the combination of two anticancer drugs, doxorubicin (DOX) and mitomycin C (MMC), produced a synergistic effect against both murine and human breast cancer cells in vitro. DOX and MMC co-loaded polymer-lipid hybrid nanoparticles (DMPLN) bypassed various efflux transporter pumps that confer multidrug resistance and demonstrated enhanced efficacy in breast tumor models. Compared to conventional solution forms, such superior efficacy of DMPLN was attributed to the synchronized pharmacokinetics of DOX and MMC and increased intracellular drug bioavailability within tumor cells enabled by the nanocarrier PLN. 
To evaluate the pharmacokinetics and bio-distribution of co-administered DOX and MMC in both free solution and nanoparticle forms, a simple and efficient multi-drug analysis method using reverse-phase high performance liquid chromatography (HPLC) was developed. In contrast to previously reported methods that analyzed DOX or MMC individually in the plasma, this new HPLC method is able to simultaneously quantitate DOX, MMC and a major cardio-toxic DOX metabolite, doxorubicinol (DOXol), in various biological matrices (e.g., whole blood, breast tumor, and heart). A dual fluorescent and ultraviolet absorbent probe 4-methylumbelliferone (4-MU) was used as an internal standard (I.S.) for one-step detection of multiple drug analysis with different detection wavelengths. This method was successfully applied to determine the concentrations of DOX and MMC delivered by both nanoparticle and solution approaches in whole blood and various tissues in an orthotopic breast tumor murine model. The analytical method presented is a useful tool for pre-clinical analysis of nanoparticle-based delivery of drug combinations.

This protocol describes an efficient and convenient analytical process of sample extraction and simultaneous determination of multiple drugs, doxorubicin (DOX), mitomycin C (MMC) and a cardio-toxic DOX metabolite, doxorubicinol (DOXol), in the biological samples from a preclinical breast tumor model treated with nanoparticle formulations of synergistic drug combination.

Combination chemotherapy is frequently used in the clinic for cancer treatment; however, associated adverse effects to normal tissue may limit its ...

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is exposed to in vivo. Solid tumors grow not as a sheet attached to plastic, but instead as a collection of clonal cells in a three-dimensional (3D) space interacting with their neighbors, and with distinct spatial properties such as the disruption of normal cellular polarity. These interactions cause 3D-cultured cells to acquire morphological and cellular characteristics which are more relevant to in vivo tumors. Additionally, a tumor mass is in direct contact with other cell types such as stromal and immune cells, as well as the extracellular matrix from all other cell types. The matrix deposited is comprised of macromolecules such as collagen and fibronectin.
In an attempt to increase the translation of research findings in oncology from bench to bedside, many groups have started to investigate the use of 3D model systems in their drug development strategies. These systems are thought to be more physiologically relevant because they attempt to recapitulate the complex and heterogeneous environment of a tumor. These systems, however, can be quite complex, and, although amenable to growth in 96-well formats, and some now even in 384, they offer few choices for large-scale growth and screening. This observed gap has led to the development of the methods described here in detail to culture tumor spheroids in a high-throughput capacity in 1536-well plates. These methods represent a compromise to the highly complex matrix-based systems, which are difficult to screen, and conventional 2D assays. A variety of cancer cell lines harboring different genetic mutations are successfully screened, examining compound efficacy by using a curated library of compounds targeting the Mitogen-Activated Protein Kinase or MAPK pathway. The spheroid culture responses are then compared to the response of cells grown in 2D, and differential activities are reported. These methods provide a unique protocol for testing compound activity in a high-throughput 3D setting.

Across a wide variety of disease indications, more physiologically relevant models are being developed and implemented into drug discovery programs. The new model system described here demonstrates how three-dimensional tumor spheroids can be cultured and screened in a high-throughput 1536-well plate-based system to search for new oncology drugs.

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is ...

Evaluation of the Feasibility, Safety, and Accuracy of an Intraoperative High-intensity Focused Ultrasound Device for Treating Liver Metastases

Today, the only potentially curative option in patients with colorectal liver metastases is surgery. However, liver resection is feasible in less than 20% of patients. Surgery has been widely used in association with radiofrequency, cryotherapy, or microwaves to expand the number of treatments performed with a curative intent. Nevertheless, several limitations have been documented when using these techniques (i.e., a traumatic puncture of the parenchyma, a limited size of lesions, and an inability to monitor the treatment in real-time).High-intensity focused ultrasound (HIFU) technology can achieve precise ablations of biological tissues without incisions or radiation. Current HIFU devices are based on an extracorporeal approach with limited access to the liver. We have developed a HIFU device designed for intraoperative use. The use of a toroidal transducer enables an ablation rate (10 cm3&#183;min-1) higher than any other treatment and is independent of perfusion.
The feasibility, safety, and accuracy of intraoperative HIFU ablation were evaluated during an ablate-and-resect prospective study. This clinical phase I and IIa study was performed in patients undergoing hepatectomy for liver metastases. The HIFU treatment was performed on healthy tissue scheduled for resection.Liver metastases measuring less than 20 mm will be targeted during phase IIb (currently ongoing). This set-up allows the real-time evaluation of HIFU ablation while protecting participating patients from any adverse effects related to this new technique.
Fifteen patients were included in phase I&#8211;IIa and 30 HIFU ablations were safely created within 40 s and with a precision of 1&#8211;2 mm. The average dimensions of the HIFU ablations were 27.5 x 21.0 mm2, corresponding to a volume of approximately 7.5 cm3. The aim of the ongoing phase IIb is to ablate metastases of less than 20 mm in diameter with a 5 mm margin.

Here, we present an ablate-and-resect prospective study to evaluate the feasibility, safety, and accuracy of intraoperative high-intensity focused ultrasound ablation in patients undergoing hepatectomy for liver metastases.

Today, the only potentially curative option in patients with colorectal liver metastases is surgery. However, liver resection is feasible in less than 20% ...

Neutrophil Extracellular Traps Generated by Low Density Neutrophils Obtained from Peritoneal Lavage Fluid Mediate Tumor Cell Growth and Attachment

Activated neutrophils release neutrophil extracellular traps (NETs), which can capture and destroy microbes. Recent studies suggest that NETs are involved in various disease processes, such as autoimmune disease, thrombosis, and tumor metastases. Here, we show a detailed in vitro technique to detect NET activity during the trapping of free tumor cells, which grow after attachment to NETs. First, we collected low density neutrophils (LDN) from postoperative peritoneal lavage fluid from patients who underwent laparotomies. Short-term culturing of LDN resulted in massive NET formation that was visualized with green fluorescent nuclear and chromosome counterstain. After co-incubation of human gastric cancer cell lines MKN45, OCUM-1, and NUGC-4 with the NETs, many tumor cells were trapped by the NETs. Subsequently, the attachment was completely abrogated by the degradation of NETs with DNase I. Time-lapse video revealed that tumor cells trapped by the NETs did not die but instead grew vigorously in a continuous culture. These methods may be applied to the detection of adhesive interactions between NETs and various types of cells and materials.

Here, we present a method in which human low-density neutrophils (LDN), recovered from postoperative peritoneal lavage fluid, produce massive neutrophil extracellular traps (NETs) and efficiently trap free tumor cells that subsequently grow.

Activated neutrophils release neutrophil extracellular traps (NETs), which can capture and destroy microbes. Recent studies suggest that NETs are involved ...

Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo

Successful cancer immunotherapy has the potential to achieve long-term tumor control. Despite recent clinical successes, there remains an urgent need for safe and effective therapies tailored to individual tumor immune profiles. Oncolytic viruses enable the induction of anti-tumor immune responses as well as tumor-restricted gene expression. This protocol describes the generation and ex vivo analysis of immunomodulatory oncolytic vectors. Focusing on measles vaccine viruses encoding bispecific T cell engagers as an example, the general methodology can be adapted to other virus species and transgenes. The presented workflow includes the design, cloning, rescue, and propagation of recombinant viruses. Assays to analyze replication kinetics and lytic activity of the vector as well as functionality of the isolated immunomodulator ex vivo are included, thus facilitating the generation of novel agents for further development in preclinical models and ultimately clinical translation.

This protocol describes a detailed workflow for the generation and ex vivo characterization of oncolytic viruses for expression of immunomodulators, using measles viruses encoding bispecific T cell engagers as an example. Application and adaptation to other vector platforms and transgenes will accelerate the development of novel immunovirotherapeutics for clinical translation.

Successful cancer immunotherapy has the potential to achieve long-term tumor control. Despite recent clinical successes, there remains an urgent need for ...

Intramucosal Inoculation of Squamous Cell Carcinoma Cells in Mice for Tumor Immune Profiling and Treatment Response Assessment

Head and neck squamous cell carcinoma (HNSCC) is a debilitating and deadly disease with a high prevalence of recurrence and treatment failure. To develop better therapeutic strategies, understanding tumor microenvironmental factors that contribute to the treatment resistance is important. A major impediment to understanding disease mechanisms and improving therapy has been a lack of murine cell lines that resemble the aggressive and metastatic nature of human HNSCCs. Furthermore, a majority of murine models employ subcutaneous implantations of tumors which lack important physiological features of the head and neck region, including high vascular density, extensive lymphatic vasculature, and resident mucosal flora. The purpose of this study is to develop and characterize an orthotopic model of HNSCC. We employ two genetically distinct murine cell lines and established tumors in the buccal mucosa of mice. We optimize collagenase-based tumor digestion methods for the optimal recovery of single cells from established tumors. The data presented here show that mice develop highly vascularized tumors that metastasize to regional lymph nodes. Single-cell multiparametric mass cytometry analysis shows the presence of diverse immune populations with myeloid cells representing the majority of all immune cells. The model proposed in this study has applications in cancer biology, tumor immunology, and preclinical development of novel therapeutics. The resemblance of the orthotopic model to clinical features of human disease will provide a tool for enhanced translation and improved patient outcomes.

Here we present a reproducible method for developing an orthotopic murine model of head and neck squamous cell carcinoma. Tumors demonstrate clinically relevant histopathological features of the disease, including necrosis, poor differentiation, nodal metastases, and immune infiltration. Tumor-bearing mice develop clinically relevant symptoms including dysphagia, jaw displacement, and weight loss.

Head and neck squamous cell carcinoma (HNSCC) is a debilitating and deadly disease with a high prevalence of recurrence and treatment failure. To develop ...

In Vitro Tumor Cell Rechallenge For Predictive Evaluation of Chimeric Antigen Receptor T Cell Antitumor Function

The field of chimeric antigen receptor (CAR) T cell therapy is rapidly advancing with improvements in CAR design, gene-engineering approaches and manufacturing optimizations. One challenge for these development efforts, however, has been the establishment of in vitro assays that can robustly inform selection of the optimal CAR T cell products for in vivo therapeutic success. Standard in vitro tumor-lysis assays often fail to reflect the true antitumor potential of the CAR T cells due to the relatively short co-culture time and high T cell to tumor ratio. Here, we describe an in vitro co-culture method to evaluate CAR T cell recursive killing potential at high tumor cell loads. In this assay, long-term cytotoxic function and proliferative capacity of CAR T cells is examined in vitro over 7 days with additional tumor targets administered to the co-culture every other day. This assay can be coupled with profiling T cell activation, exhaustion and memory phenotypes. Using this assay, we have successfully distinguished the functional and phenotypic differences between CD4+ and CD8+ CAR T cells against glioblastoma (GBM) cells, reflecting their differential in vivo antitumor activity in orthotopic xenograft models. This method provides a facile approach to assess CAR T cell potency and to elucidate the functional variations across different CAR T cell products.

Here, we describe an in vitro co-culture method to recursively challenge tumor-targeted T cells, which allows for phenotypic and functional analysis of antitumor T cell activity.

The field of chimeric antigen receptor (CAR) T cell therapy is rapidly advancing with improvements in CAR design, gene-engineering approaches and ...

Drug Screening of Primary Patient Derived Tumor Xenografts in Zebrafish

Patient derived xenograft models are critical in defining how different cancers respond to drug treatment in an in vivo system. Mouse models are the standard in the field, but zebrafish have emerged as an alternative model with several advantages, including the ability for high-throughput and low-cost drug screening. Zebrafish also allow for in vivo drug screening with large replicate numbers that were previously only obtainable with in vitro systems. The ability to rapidly perform large scale drug screens may open up the possibility for personalized medicine with rapid translation of results back to clinic. Zebrafish xenograft models could also be used to rapidly screen for actionable mutations based on tumor response to targeted therapies or to identify new anti-cancer compounds from large libraries. The current major limitation in the field has been quantifying and automating the process so that drug screens can be done on a larger scale and be less labor-intensive. We have developed a workflow for xenografting primary patient samples into zebrafish larvae and performing large scale drug screens using a fluorescence microscope equipped imaging unit and automated sampler unit. This method allows for standardization and quantification of engrafted tumor area and response to drug treatment across large numbers of zebrafish larvae. Overall, this method is advantageous over traditional cell culture drug screening as it allows for growth of tumor cells in an in vivo environment throughout drug treatment, and is more practical and cost-effective than mice for large scale in vivo drug screens.

Zebrafish xenograft models allow for high-throughput drug screening and fluorescent imaging of human cancer cells in an in vivo microenvironment. We developed a workflow for large scale, automated drug screening on patient-derived leukemia samples in zebrafish using an automated fluorescence microscope equipped imaging unit.

Patient derived xenograft models are critical in defining how different cancers respond to drug treatment in an in vivo system. Mouse models are the ...

Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous metastasis models are available. Thus, the experimental metastasis model involving tail-vein injection of suitable cell lines is a mainstay of metastasis research. When cancer cells are injected into the lateral tail-vein, the lung is their preferred site of colonization. A potential limitation of this technique is the accurate quantification of the metastatic lung tumor burden. While some investigators count macrometastases of a pre-defined size and/or include micrometastases following sectioning of tissue, others determine the area of metastatic lesions relative to normal tissue area. Both of these quantification methods can be exceedingly difficult when the metastatic burden is high. Herein, we demonstrate an intravenous injection model of lung metastasis followed by an advanced method for quantifying metastatic tumor burden using image analysis software. This process allows for investigation of multiple end-point parameters, including average metastasis size, total number of metastases, and total metastasis area, to provide a comprehensive analysis. Furthermore, this method has been reviewed by a veterinary pathologist board-certified by the American College of Veterinary Pathologists (SEK) to ensure accuracy.

Intravenous injection of cancer cells is often used in metastasis research, but the metastatic tumor burden can be difficult to analyze. Herein, we demonstrate a tail-vein injection model of metastasis and include a novel approach to analyze the resulting metastatic lung tumor burden.

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous ...

Isolation and Functional Assessment of Human Breast Cancer Stem Cells from Cell and Tissue Samples

Breast cancer stem cells (BCSCs) are cancer cells with inherited or acquired stem cell-like characteristics. Despite their low frequency, they are major contributors to breast cancer initiation, relapse, metastasis and therapy resistance. It is imperative to understand the biology of breast cancer stem cells in order to identify novel therapeutic targets to treat breast cancer. Breast cancer stem cells are isolated and characterized based on expression of unique cell surface markers such as CD44, CD24 and enzymatic activity of aldehyde dehydrogenase (ALDH). These ALDHhighCD44+CD24- cells constitute the BCSC population and can be isolated by fluorescence-activated cell sorting (FACS) for downstream functional studies. Depending on the scientific question, different in vitro and in vivo methods can be used to assess the functional characteristics of BCSCs. Here, we provide a detailed experimental protocol for isolation of human BCSCs from both heterogenous populations of breast cancer cells as well as primary tumor tissue obtained from breast cancer patients. In addition, we highlight downstream in vitro and in vivo functional assays including colony forming assays, mammosphere assays, 3D culture models and tumor xenograft assays that can be used to assess BCSC function.

This experimental protocol describes the isolation of BCSCs from breast cancer cell and tissue samples as well as the in vitro and in vivo assays that can be used to assess BCSC phenotype and function.

Breast cancer stem cells (BCSCs) are cancer cells with inherited or acquired stem cell-like characteristics. Despite their low frequency, they are major ...